Rapid and on-line instrumentation for food quality assurance

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Author: Ibtisam E. Tothill

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Rapid and on-line instrumentation for food quality assurance

Related titles from Woodhead’s food science, technology and nutrition list: Food authenticity and traceability: ISBN 1 85573 526 1 With recent problems such as the use of genetically-modified ingredients and BSE, the need to trace and authenticate the contents of food products has never been more urgent. The first part of this authoritative collection reviews the range of established and new techniques for food authentication. Part II explores how such techniques are applied in particular sectors, whilst Part III reviews the latest developments in traceability systems for differing food products. Texture in food, Volume 1: Semi-solid foods: ISBN 1 85573 673 X Understanding and controlling the texture of semi-solid foods such as yoghurt and ice cream is a complex process. With a distinguished international team of contributors, this important collection summarises some of the most significant research in this area. The first part of the book looks at the behaviour of gels and emulsions, how they can be measured and their textural properties improved. The second part of the collection discusses the control of texture in particular foods such as yoghurt, ice cream, spreads and sauces. Taints and off-flavours in foods: ISBN 1 85573 449 4 Taints and off-flavours are a major problem for the food industry. Part 1 of this important collection reviews the major causes of taints and off-flavours, from oxidative rancidity and microbiologically-derived off-flavours, to packaging materials as a source of taints. The second part of the book discusses the range of techniques for detecting taints and off-flavours, from sensory analysis to instrumental techniques, including the development of new rapid, on-line sensors. Details of these books and a complete list of Woodhead’s food science, technology and nutrition titles can be obtained by: • visiting our web site at www.woodhead-publishing.com • contacting Customer Services (email: [email protected]; fax: +44 (0) 1223 893694; tel.: +44 (0) 1223 891358 ext. 30; address: Woodhead Publishing Limited, Abington Hall, Abington, Cambridge CB1 6AH, England) Selected food science and technology titles are also available in electronic form. Visit our web site (www.woodhead-publishing.com) to find out more. If you would like to receive information on forthcoming titles in this area, please send your address details to: Francis Dodds (address, telephone and fax as above; e-mail: [email protected]). Please confirm which subject areas you are interested in.

Rapid and on-line instrumentation for food quality assurance Edited by Ibtisam E. Tothill

Published by Woodhead Publishing Limited Abington Hall, Abington Cambridge CB1 6AH England www.woodhead-publishing.com Published in North America by CRC Press LLC 2000 Corporate Blvd, NW Boca Raton FL 33431 USA First published 2003, Woodhead Publishing Limited and CRC Press LLC ß 2003, Woodhead Publishing Limited The authors have asserted their moral rights. This book contains information obtained from authentic and highly regarded sources. Reprinted material is quoted with permission, and sources are indicated. Reasonable efforts have been made to publish reliable data and information, but the authors and the publishers cannot assume responsibility for the validity of all materials. Neither the authors nor the publishers, nor anyone else associated with this publication, shall be liable for any loss, damage or liability directly or indirectly caused or alleged to be caused by this book. Neither this book nor any part may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, microfilming and recording, or by any information storage or retrieval system, without permission in writing from the publishers. The consent of Woodhead Publishing Limited and CRC Press LLC does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific permission must be obtained in writing from Woodhead Publishing Limited or CRC Press LLC for such copying. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation, without intent to infringe. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library. Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress. Woodhead Publishing Limited ISBN 1 85573 674 8 (book); 1 85573 710 8 (e-book) CRC Press ISBN 0-8493-1759-2 CRC Press order number: WP1759 Cover design by The ColourStudio Project managed by Macfarlane Production Services, Markyate, Hertfordshire (e-mail: [email protected]) Typeset by MHL Typesetting Limited, Coventry, Warwickshire Printed by TJ International Limited, Padstow, Cornwall, England

Contents

Contributor contact details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

xi

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

xv

Part I Product safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1

1

3

2

On-line detection of contaminants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R. Righelato, Ashbourne Biosciences, UK 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Process issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Detection of chemical contaminants . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 Detection of foreign bodies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6 Sources of further information and advice . . . . . . . . . . . . . . . . . . . 1.7 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . On-line immunochemical assays for contaminant analysis . . . . . . . I.E. Tothill, Cranfield University, UK 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Principles and applications of immunochemical assays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Immunoassays for food contaminant analysis . . . . . . . . . . . . . . . . 2.4 Immunochemical sensors (immunosensors) . . . . . . . . . . . . . . . . . . 2.5 On-line immunosensors in food processing . . . . . . . . . . . . . . . . . . 2.6 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3 5 6 7 10 12 12 14 14 15 20 21 25 30

vi

Contents 2.7 2.8 2.9

3

4

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sources of further information and advice . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Using bioassays in contaminant analysis . . . . . . . . . . . . . . . . . . . . . . . . . . L.A.P. Hoogenboom, State Institute for Quality Control of Agricultural Products (RIKILT), The Netherlands 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 The use of bioassays: the case of dioxins . . . . . . . . . . . . . . . . . . . . 3.3 The use of bioassays for other contaminants . . . . . . . . . . . . . . . . . 3.4 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The rapid detection of pesticides in food . . . . . . . . . . . . . . . . . . . . . . . . . R. Luxton and J. Hart, University of the West of England, UK 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Detecting pesticides: physicochemical methods . . . . . . . . . . . . . . 4.3 Detecting pesticides: biological methods . . . . . . . . . . . . . . . . . . . . . 4.4 The principles of biosensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Developing low-cost biosensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 Using biosensors: pesticide residues in grain, fruit and vegetables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.7 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 Sources of further information and advice . . . . . . . . . . . . . . . . . . . 4.9 Further reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

34 34 35 40

40 41 49 51 51 51 55 55 58 59 62 69 70 72 73 73

5 Detecting antimicrobial drug residues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A˚. Sternesjo¨, Swedish University of Agricultural Sciences 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Current screening methods for residue detection . . . . . . . . . . . . . 5.3 Developing biosensors: the use of surface plasmon resonance 5.4 Using biosensors to detect veterinary drug residues . . . . . . . . . . 5.5 Biosensor applications in the food industry . . . . . . . . . . . . . . . . . . 5.6 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7 Sources of further information and advice . . . . . . . . . . . . . . . . . . . 5.8 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

75 76 79 81 83 86 88 88

6

91

Detecting veterinary drug residues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . N. van Hoof, K. de Wasch, H. Noppe, S. Poelmans and H.F. de Brabender, University of Ghent, Belgium 6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Veterinary medicinal products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 Methods for detecting residues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 Validating detection methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

75

91 92 93 96

Contents 6.5 6.6 6.7 6.8 7

8

9

Rapid on-line confirmation of different veterinary residues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

The rapid detection of toxins in food: a case study . . . . . . . . . . . . . . G. Palleschi, D. Moscone and L. Micheli, University of Rome `Tor Vergata’, Italy 7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Immunosensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 Detecting toxins: domoic acid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4 Detecting toxins: okadaic acid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5 Detecting toxins: saxitoxin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.6 Developing on-line applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.8 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.9 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rapid detection methods for microbial contamination . . . . . . . . . . . I. E. Tothill and N. Magan, Cranfield University, UK 8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 Conventional methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 Specialised techniques: epifluorescence (DEFT), bioluminescence and particle counting . . . . . . . . . . . . . . . . . . . . . . . 8.4 Specialised techniques: flow cytometry, electron microscopy and immunoassay techniques . . . . . . . . . . . . . . . . . . . . 8.5 Cellular components detection: API, metabolising enzymes and nucleic acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.6 Electrochemical methods: impedimetry, conductivity and other methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.7 Immunosensors: amperometric, potentiometric, acoustic wave-based and optical sensors . . . . . . . . . . . . . . . . . . . . . 8.8 Detection of moulds using biochemical methods . . . . . . . . . . . . . 8.9 Electronic noses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.10 Conclusions: commercial products . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.11 Sources of further information and advice . . . . . . . . . . . . . . . . . . . 8.12 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rapid analysis of microbial contamination of water . . . . . . . . . . . . . L. Bonadonna, Istituto Superiore di Sanita` – Rome, Italy 9.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2 Current techniques and their limitations . . . . . . . . . . . . . . . . . . . . . 9.3 Identifying indicator organisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.4 The development of more rapid detection methods . . . . . . . . . .

vii

98 112 113 113 116

116 117 118 122 125 129 132 132 132 136 136 136 139 141 143 145 147 150 153 154 155 155 161 161 162 163 167

viii

Contents

9.5 9.6 9.7 9.8

Developing online monitors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sources of further information and advice . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

173 176 178 179

Part II Product quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

183

10

11

12

13

Rapid techniques for analysing food additives and micronutrients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C.J. Blake, Nestle´ Research Centre, Switzerland 10.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.2 The range of rapid methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.3 Chromatographic techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 X-ray fluorescence and other indirect methods . . . . . . . . . . . . . . . 10.5 PCR, immunoassays and biosensors . . . . . . . . . . . . . . . . . . . . . . . . . 10.6 Other rapid methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.7 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.8 Sources of further information and advice . . . . . . . . . . . . . . . . . . . 10.9 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Detecting genetically-modified ingredients . . . . . . . . . . . . . . . . . . . . . . M. Pla, T. Esteve and P. Puigdome`nech, Insitut de Biologia Molecular de Barcelona – CSIC, Spain 11.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 Principles of analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.3 Polymerase chain reaction (PCR) techniques . . . . . . . . . . . . . . . . . 11.4 Identifying genetically-modified ingredients in practice . . . . . . 11.5 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . In-line sensors for food process monitoring and control . . . . . . . . P.D. Patel and C. Beveridge, Leatherhead Food International Ltd, UK 12.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2 Principles of in-line sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.3 Current commercial sensor systems . . . . . . . . . . . . . . . . . . . . . . . . . . 12.4 Dealing with complex food matrices . . . . . . . . . . . . . . . . . . . . . . . . . 12.5 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 Sources of further information and advice . . . . . . . . . . . . . . . . . . . 12.7 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Measurement of added water in foodstuffs . . . . . . . . . . . . . . . . . . . . . M. Kent, Consultant, UK 13.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.2 Problems in measuring added water . . . . . . . . . . . . . . . . . . . . . . . . .

185 185 186 186 189 191 193 196 197 198 205

205 206 208 211 212 213 215 215 216 219 227 236 237 238 240 240 241

Contents 13.3 13.4 13.5 13.6 13.7 13.8 14

15

16

ix

Measuring the dielectric properties of water . . . . . . . . . . . . . . . . . Instrumentation for measuring dielectric properties . . . . . . . . . . Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sources of further information and advice . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

245 251 258 264 267 267

Spectroscopic techniques for analysing raw material quality . . R. Cubeddu, A. Pifferi, P. Taroni and A. Torricelli, INFM – Dipartimento di Fisica and Politecnico di Milano, Italy 14.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 Advantages of time-resolved optical methods . . . . . . . . . . . . . . . . 14.3 Principles of time-resolved reflectance . . . . . . . . . . . . . . . . . . . . . . . 14.4 Instrumentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.5 Data analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 Effect of skin and penetration depth . . . . . . . . . . . . . . . . . . . . . . . . . 14.7 Optical properties of fruits and vegetables . . . . . . . . . . . . . . . . . . . 14.8 Applications: analysing fruit maturity and quality defects . . . 14.9 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.10 Sources of further information and advice . . . . . . . . . . . . . . . . . . . 14.11 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

270

Using spectroscopic techniques to monitor food composition . . P. Grenier and V. Bellon-Maurel, Cemagref, France, R. Wilson, Institute of Food Research, UK and P. Niemela¨, VTT Biotechnology, Finland 15.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2 Spectroscopic techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.3 Instrument design for on-line applications . . . . . . . . . . . . . . . . . . . 15.4 Design or adaptation of MIR, optothermal and Raman spectrometers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.5 Applications: analysing the composition of cereal and dairy products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.6 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.7 Sources of further information and advice . . . . . . . . . . . . . . . . . . . 15.8 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.9 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Confocal scanning laser microscopy (CSLM) for monitoring food composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R.H. Tromp, Y. Nicolas, F. van de Velde and M. Paques, Wageningen Centre for Food Sciences, The Netherlands 16.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.2 The principles of CSLM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.3 Sample preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

270 271 272 274 277 278 280 285 287 288 289 291

291 292 296 298 300 302 303 304 305

306

306 308 310

x

Contents 16.4 16.5 16.6

17

18

19

Applications: food composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

313 319 321

Using electronic noses to assess food quality . . . . . . . . . . . . . . . . . . . . H. Zhang, University of Florida, USA 17.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.2 The theory of electronic noses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.3 Comparing sensor types of electronic nose . . . . . . . . . . . . . . . . . . . 17.4 Current commercial instruments and selection criteria . . . . . . . 17.5 Data analysis metods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.6 Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.7 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.8 Sources of further information and advice . . . . . . . . . . . . . . . . . . . 17.9 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

324

Rapid olfaction arrays for determining fish quality . . . . . . . . . . . . ´ lafsdo´ttir, Icelandic Fisheries Laboratories . . . . . . . . . . . . . . . . . . . . . G, O 18.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.2 Spoilage odours and product quality: the case of fish . . . . . . . . 18.3 Electronic noses: principles and applications . . . . . . . . . . . . . . . . . 18.4 Validation of the performance of the electronic nose . . . . . . . . 18.5 Developing rapid and on-line applications . . . . . . . . . . . . . . . . . . . 18.6 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.7 Sources of further information and advice . . . . . . . . . . . . . . . . . . . 18.8 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . On-line analysis and control of product quality . . . . . . . . . . . . . . . . G. Montague, E. Martin and J. Morris, University of Newcastle, UK 19.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.2 Process models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.3 Case study 1: quality assessment in breakfast cereal production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.4 Building models of breakfast cereal production . . . . . . . . . . . . . . 19.5 On-line implementation and performance . . . . . . . . . . . . . . . . . . . . 19.6 Case Study 2: improving process control in french-fry manufacture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.7 On-line application and performance . . . . . . . . . . . . . . . . . . . . . . . . . 19.8 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.9 Sources of further information and advice . . . . . . . . . . . . . . . . . . . 19.10 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.11 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

324 325 325 327 329 331 334 335 335 339 339 340 341 348 352 354 355 356 361 361 362 363 367 373 376 384 391 392 392 393 395

Contributor contact details

Chapter 1

Chapter 3

Professor Renton Righelato Ashbourne Biosciences 63 Hamilton Road Reading RG1 5RA UK

Dr Ron Hoogenboom Department of Food Safety and Health RIKILT – Institute of Food Safety PO Box 230 6700AE Wageningen The Netherlands

E-mail: [email protected]

Tel: +31 317 475623 Fax: +31 317 417717 E-mail: [email protected]

Chapter 2 Dr Ibtisam E. Tothill Institute of Bioscience and Technology Cranfield University Silsoe Bedfordshire MK45 4DT UK Tel: +44 (0) 1525 863531 Fax: +44 (0) 1525 863533 E-mail: [email protected]

Chapter 4 Dr R. Luxton and J. Hart Faculty of Applied Sciences University of the West of England Frenchay Campus Coldharbour Lane Bristol BS16 1QY UK E-mail: [email protected] [email protected]

xii


Chapter 5

Chapter 8

˚ se Sternesjo¨ Dr A Department of Food Science Swedish University of Agricultural Sciences PO Box 7051 S-750 07 Uppsala Sweden

Dr Ibtisam E. Tothill and Professor N. Magan Institute of Bioscience and Technology Cranfield University Silsoe Bedfordshire MK45 4DT UK

Tel: +46 18 67 20 37 Fax: +46 18 67 29 95 E-mail: [email protected]

E-mail: [email protected]

Chapter 9 Chapter 6 Dr Katia de Wasch Faculty of Veterinary Medicine University of Ghent Veterinary Food Inspection – Lab Chemical Analysis Salisburylaan 133 B-9820 Merelbeke Belgium E-mail: [email protected]

Chapter 7 Professor Giuseppe Palleschi Dipartimento di Scienze e Tecnologie Chimiche Universita` di Roma ‘Tor Vergata’ Via della Ricerca Scientifica 00133 Roma Italy E-mail: [email protected]

Dr Lucia Bonadonna Laboratorio di Igiene Ambientale Istituto Superiore di Sanita` Viale Regina Elena, 299 00161 Roma Italy E-mail: [email protected]

Chapter 10 Mr. Christopher J. Blake Manager, Micronutrients and Additives Group Quality and Safety Assurance Department Nestle´ Research Center Lausanne 1000 Switzerland E-mail: Christopher-john.blake@ rdls.nestle.com


Chapter 11

Chapter 14

Dr Pere Puigdome`nech, Teresa Esleve and Maria Pla Institut de Biologia Molecular de Barcelona CID-CSIC Jordi Girona 18 08034 Barcelona Spain

Professor Rinaldo Cubeddu Physics Department Politecnico di Milano Piazza L. da Vinci 32 20133 Milan Italy

Tel: +34 934006100 Fax: +34 932045904 E-mail: [email protected] E-mail: [email protected] E-mail: [email protected]

Chapter 12 P.D. Patel and C. Beveridge Leatherhead Food International Ltd Randalls Road Leatherhead Surrey KT22 7RY UK Tel: 01372 822200 Fax: 01372 386228 E-mail: [email protected]

Chapter 13 Dr M. Kent Kent & Partner The White House Greystone Carmyllie Angus DD11 2RJ UK Tel: +44 1241 860323 Fax: +44 1241 860323 E-mail: [email protected]

xiii

Tel: +39 0023 996110 Fax: +39 0223 996126 E-mail: [email protected]

Chapter 15 Dr Pierre Grenier Cemagref, BP 5095 34033 Montpellier Cedex 1 France Tel: +33 (0) 4670463 (21 or 15 or 86) Fax: +33 (0) 4 670463 06 E-mail: [email protected]

Chapter 16 Dr R. Hans Tromp NIZO Food Research PO Box 20 6710 BA Ede The Netherlands E-mail: [email protected]

xiv


Chapter 17 Dr Haoxian Zhang Agricultural and Biological Engineering Department University of Florida 1 Frazier Rogers Hall PO Box 110570 Gainesville FL 32611-0570 USA E-mail: [email protected]

Chapter 18 ´ lafsdo´ttir Ms Guoruń O Icelandic Fisheries Laboratories Sku´lagata 4 PO Box 1405 121 Reykjavik Iceland

Tel: (354) 562 0240 Fax: (354) 562 0740 E-mail: [email protected]

Chapter 19 Professor Julian Morris Head of School of Chemical Engineering and Advanced Materials Director Centre for Process Analytics and Control Technology (CPACT) Merz Court University of Newcastle Newcastle upon Tyne NE1 7RU UK Tel: +44 191 222 7342 (Direct) Fax: +44 191 222 5748 (CPACT Office) E-mail: [email protected]

Introduction

The terms ‘in-line’, ‘on-line’, ‘at-line’ and ‘off-line’ are used variously in discussions of rapid instrumentation. These terms may be distinguished as follows: • in-line measurements are performed directly on the process line • on-line measurements may be performed in a bypass loop from the main process line which may then return the material or product to the main process line after measurement • at-line measurements involve removing product from the production line and measuring it with suitable instrumentation in the production area • off-line measurements entail removing product and taking it to a quality control laboratory for analysis Off-line measurement typically involves delays measured in hours or longer. As an example, conventional microbiological assays, which still provide a standard of accuracy against which newer microbiological methods are judged, can take days to perform. At-line measurements may, in some cases, be made in a matter of minutes. In-line and on-line measurement may take a matter of seconds. The food industry has long relied on off-line measurement to ensure product safety and quality. However, a number of trends have accelerated the need both to make off-line measurement more rapid and to move to the ideal of continuous, real-time in-line or on-line measurement: • consumers demand higher and more consistent quality, leading to the need for more frequent measurements of process variables and product attributes • volumes and rates of production have increased, making it more difficult for traditional off-line measurement systems to cope with rising workloads

xvi

Introduction

• competitive pressures and consumer demands for longer shelf-life products have made it less acceptable to hold product in quarantine, whether during or after production, whilst waiting for the results of safety or quality checks • the trend towards continuous automated production in place of batch processing necessitates tight feedback loops based on rapid in-line and online monitoring techniques • quality assurance and safety management systems such as HACCP have shifted the emphasis from a reactive approach, based on final product testing, to a proactive and preventative approach based on effective real-time process control As well as increased speed, modern instrumentation must also take account of other criteria such as: • appropriate accuracy and sensitivity for the task • hygienic design and construction • non-destructive operation: the measurement should not disrupt the process or damage the quality of the product • sufficient robustness to withstand often hostile operating conditions during food processing • automatic operation or capacity for use by non-skilled operators • low maintenance requirements • total costs (capital, operating and maintenance costs) proportionate to the benefits gained The chapters in this book summarise some of the most important developments in the shift from slower and off-line traditional measurement to more rapid and on-line process and product control. Part 1 reviews the key area of product safety. Chapter 1 looks at the development of new on-line techniques in such areas as the detection of foreign bodies. This is followed by a group of chapters looking specifically at immunochemical assays which exploit the immune system’s ability to produce antibodies in response to invasion by a foreign organic molecule. Chapter 2 reviews general principles and the development of robust, low-cost and portable immunosensors capable of at-line or on-line use by non-specialist personnel. The following chapters then consider the application of these new immunosensors in the detection of environmental contaminants such as dioxins (Chapter 3), pesticides (chapter 4), veterinary residues (Chapters 5 and 6) and toxins (Chapter 7). The final two chapters in Part I then review the development of rapid detection methods in the critical area of pathogenic and spoilage microorganisms, and the specific application of these new methods to detect microbial contamination of water. Part II considers developments in the analysis of product quality. A number of chapters discuss rapid and on-line analysis of ingredients from additives and micronutrients (Chapter 10) to genetically-modified organisms (Chapter 11) and added water (Chapter 13). Chapter 12 addresses in-line applications of these techniques and, in particular, ways of analysing complex food matrices during

Introduction

xvii

processing. The following group of chapters look at the use of spectroscopic techniques (Chapters 14 and 15) and confocal laser microscopy (Chapter 16) to monitor food composition. Chapters 17 and 18 then discuss the important area of electronic noses to detect volatiles and their use to monitor qualities such as flavour and freshness. The final chapter in the book reviews how a wide range of measurements such as these can be used to monitor and improve process control.

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Part I Product safety


1 On-line detection of contaminants R. Righelato, Ashbourne Biosciences, UK

1.1

Introduction

One of the most common causes of customer complaints for many food producers is ‘foreign bodies’ in the product: nasty surprises like the slug in the lettuce or an insect, or, more typically, a piece of bone or plastic that should not be there. At a recent workshop, manufacturers quoted foreign bodies as constituting around a quarter to a third of customer complaints (Righelato, 2002). Plastic tops the list, with bone, extraneous vegetable matter and insects and mites as significant problems (Table 1.1). A large proportion (16–35%) of the unwanted bodies in food products were not foreign, but intrinsic – elements of the raw material that should have been removed in processing, such as bone,

Table 1.1

Typical causes of customer complaints

Foreign body type

% all foreign body complaints

Plastic Psocid mites Other infestations Fruit and vegetable matter Stones Glass Bone Metal Wood

15.5 9.2 9.2 7.8 7.8 7.2 6.0 6.0 2.1

Data refer to customer complaints received by RHM in 2001 and were kindly provided by Dr Bob Marsh, RHM Technology.

4


cartilage, shells and stalks, over-ripe/under-ripe fruit and vegetables. These items are discrete, generally occur infrequently and are often very similar to the food in composition. They therefore usually require monitoring approaches that can differentiate the unwanted material from the rest of the food on the basis of small physical differences, size and shape. Other contaminants such as residues, toxins and taints present different problems: they are usually present at very low concentrations (ppm or lower) and, in some cases, such as protein allergens or hormones, are structurally very similar to normal components of the food (Table 1.2). Most arise from the raw material and for the food manufacturer control generally relies on supplier assurances and periodic off-line testing. If not eliminated at the raw material stage, they become diluted and distributed throughout the food batch. For those contaminants that might arise from the process, however, such as coolants or cleaning agents, off-line testing is not a practical option. The speed of most manufacturing is such that contaminated material would be packed and distributed before laboratory results were available. Reliance is therefore on plant design and good manufacturing practice (GMP). Despite this, on rare occasions, incidents do occur, and if suitable on-line monitoring technology were available for some of the contaminants that might prejudice safety or quality, it would probably be adopted. Malicious contamination of foods in manufacture and distribution is a rare occurrence that may involve introduction of foreign bodies or dissolved contaminants. Its control relies on minimising opportunities for adulteration in manufacturing, security measures such as tamper-evident packaging, forensic investigation and prosecution of offenders. Because it is impractical to monitor on-line effectively for the huge range of potential malicious adulterants, their detection is not considered here. The primary assurance against product contamination is the preventative measures taken in manufacturing. The case for installing technology to detect foreign bodies and other contaminants that may have escaped these measures depends on the risk of them failing, the potential for causing real harm to Table 1.2

Some examples of food contaminants

Source

Contaminant

Sensitivity range (w/w)

Water

Benzene Chlorophenol taints Mycotoxins Pesticide residues Nut allergens Growth promoters Antibiotic residues Coolants e.g., ethylene glycol; cleaning fluids Plasticisers

10ÿ8–10ÿ9 10ÿ7–10ÿ9 10ÿ6–10ÿ8 10ÿ6–10ÿ8 10ÿ8–10ÿ10 10ÿ6 10ÿ8

Grains, nuts, fruit Meat Process plant Package

10ÿ5 10ÿ7 10ÿ7–10ÿ9

On-line detection of contaminants

5

consumers, the risk to brand reputation and the effectiveness of the detection/ segregation system. The financial costs of failure can be huge. A contamination incident perceived to affect the safety or quality of a product can result in product recalls costing many millions of dollars and, at worst, irrecoverable loss of customer confidence and collapse of the brand. For a global brand this can mean losses of billions of US$. The values of most food processing operations are lower and, in practice, equipment for detection and exclusion in excess of US$100,000 was considered unlikely to find significant application by a selection of food manufacturers in 2002.

1.2

Process issues

Supplier assurance and auditing and the application of GMP and HACCP through the chain are the main ways in which the product is protected. But these can fail, so technology to detect and remove the unwanted materials is needed. For materials such as stone or metal, where large density or electro-magnetic differences exist between the food and the contaminant body, adequate technology can usually be applied, such as magnetic metal detectors or X-ray inspection. Plastics and materials of biological origin are much more difficult to detect and require for new approaches. For dissolved trace contaminants there is little on-line monitoring technology available and reliance is usually placed on good practice and retrospective laboratory analysis. Monitoring technology must be non-invasive and match the speeds of raw material flows, up to millions of units per minute for grains, several m3 per minute of liquid flows and lines packaging 103–104 items per minute passing at several metres per second. These speed requirements, together with the need for robust, non-invasive hardware that can readily interface with computer control, favour electromagnetic measurement systems (e.g. light, X-ray, impedance, magnetic resonance). For on-line monitoring technology to be useful, it should: • provide for 100% inspection of the process material • be appropriately sensitive to the analyte and insensitive to other variations in the food • be stable in operation • be mechanically robust and engineered to meet the necessary hygiene standards; ideally the equipment should be non-invasive • be linked to ways in which the contaminated item or flow can be segregated from the sound product and preferably be cleaned and recovered. It is often the segregation and handling of the contaminated material that is the most complex and costly part of the equipment involved • have acceptable ‘false reject rates’ so that good product is not unnecessarily rejected.

6

1.3


Detection of chemical contaminants

Although impedance monitoring can be used for some contaminants in dilute aqueous media (see Section 1.4.3), for the majority of dispersed contaminants, such as those exemplified in Table 1.2, robust on-line measuring systems are not available. The complexity of most food matrices, the need to examine the whole of a heterogeneous food and the high sensitivity requirement generally preclude conventional instrumental approaches such as spectrophotometry, NMR and MS. Approaches which overcome some of these problems include biosensors and electronic nose techniques. Both techniques have the potential to provide the requisite sensitivity, and volatiles detection techniques avoid problems of interference from the food components by sampling the gas phase only. As yet, however, neither has been widely adopted for on-line operation in a manufacturing environment.

1.3.1 Biosensors Biosensors and biomimetic devices have the advantage of high specificity and sensitivity. A wide range of antibody and enzyme-based sensors have been developed for detection and quantification of important food contaminants – pesticide residues, growth promoters, mycotoxins. Most are suitable only for laboratory or field use off-line (Schmidt and Bilitewski, 2001). Although biosensors and biological test kits have revolutionised analytical biological chemistry, there are serious drawbacks to their use on-line in manufacturing in clean environments: • they are invasive – contact with the analyte is required, which can present problems of hygienic operation and fouling • in heterogeneous food systems it is difficult to ensure effective contact between the sensor and all elements of the food • the biological component of the sensor, usually a protein, is not stable to repeated high temperatures and cleaning agents. Some of these problems can be overcome by constructing the binding sites of the sensor from more stable polymers (Piletsky et al., 2001). Biomimetic antibodies have been created with specificities and sensitivities close to those of their protein homologue.

1.3.2 Volatiles detection techniques Detection of volatile indicators of contamination has been developed extensively over the last decade. Where the contaminant itself is volatile or there is a volatile surrogate compound, this approach can overcome the problems presented by the opacity and heterogeneity of most foods. In essence air (or a carrier gas) is used to sample the whole food item or stream. The gas stream can then be presented to a detection system such as gas chromatography, ion mobility spectroscopy, or the so-called ‘electronic noses’ – sensing arrays of conducting polymers, metal


7

oxide semiconductor field effect transistors or piezo-electric quartz crystals. The sensitivity of these methods for some important food volatiles is often very high, of the same order as the human nose. Electronic noses have been developed largely for laboratory use in flavour recognition (Gardner and Bartlett, 1994), though more recently they have also been researched for the detection of food contaminants off-line and on-line. Detection of fungal contamination of potatoes (de Lacy Costello et al., 2000), staling of wheat (Brown et al., 2001) and the presence of mite infestation has been demonstrated successfully. In each of these cases complex sets of changes occur in the pattern of volatiles present. Early spoilage detection is potentially valuable for raw materials in storage and transit and does not require continuous on-line measurement for which current e-noses are unsuitable. Identification of individual volatiles by electronic noses based on sensor arrays depends on recognition of the pattern of differential absorption of the compound between the individual sensors in the array (Bartlett et al., 1997). Thus they inherently lack molecular specificity and are influenced by other volatiles present. They are therefore likely to be superseded by other detectors systems with better specificity, for example: • Ion mobility spectrometers have been developed by Graseby Limited as hand-held units for military and forensic uses, such as detection of nerve gases. They can have ppm sensitivity and have been used experimentally to monitor volatiles produced by low levels of bacterial cell growth through the volatiles emitted (Ogden and Strachan, 1998). • Tunable diode laser absorption spectroscopy (TDLAS) is used to identify and monitor trace (ppm) levels of volatile solvents and other gases (Fried, 2002) and may be applicable to some food contaminants. More speculatively, work by Pickett and colleagues on the exquisite specificity and sensitivity of the insect antenna (Coglan, 1999) may form the basis for novel biosensors for trace volatile compounds. Although attractive as a way of sampling complex food structures non-invasively, a major drawback to volatiles detection for on-line monitoring of manufacturing processes is speed of response. The timescale for diffusion of a volatile into the headspace, sampling and analysis of the gas is in the order of seconds rather than the milliseconds needed in most operations. Thus, whilst it has found limited uses on-line in manufacturing operations, the use of volatile markers is probably more applicable to field, storage and off-line use.

1.4

Detection of foreign bodies

Detection of foreign bodies presents quite different challenges to chemical contaminants – they are discrete, occur at low frequency and are often similar in composition to the food itself. Metal detection is standard in most food manufacturing and current X-ray inspection technology can be used for stone,

8


bone and glass in many situations. However, plastics and most of the foreign bodies of biological origin are more difficult to detect. A wide range of imaging technologies, many of them developed for clinical use, has been proposed for application to food manufacturing. Some of these non-invasive techniques are outlined below. In addition, for some types of unwanted body, other approaches may be possible, for instance detection of contaminating insects or spoilt raw materials through the volatiles they emit.

1.4.1 Light-based systems Light-based measurement systems can usually be designed to meet the speed, hygiene and robustness requirements of food processes. Whilst visible light transmission can be used for many drinks, most foods are opaque to visible wavelengths and reflectance methods are used, providing surface shape and colour information from which the presence of unwanted items must be inferred. In some cases, compositional information can be obtained and subsurface damage detected though penetration of the longer wavelengths permits the use of NIR for some applications. Image analysis allows rapid signal processing and machine vision systems have been developed to scan and sort millions of items per minute (Low et al., 2001). The main applications of vision systems are in the detection of foreign bodies and damaged food items. They may in certain circumstances be applied to detection of trace contaminants where the target compound is present at the surface of the food and has a strong characteristic signal, such as the fluorescence of aflatoxin (Pearson 1996; Pearson et al., 2001).

1.4.2 X-ray based systems X-ray imaging is well-established for the detection of bone and other X-ray opaque bodies in foods. Machine vision systems using single and dual energy imaging are used (Graves et al., 1994), though current equipment will not resolve many less dense items such as most vegetable matter and many plastic items. Conventional X-ray radiography relies on differences in absorption that result from differences in density, thickness and elemental composition. Whilst good contrast can be obtained for metal, glass and bone, the low absorption coefficient of most biological tissue limits the ability of X-ray absorption to discriminate many types of foreign body. Recent development of phase contrast X-ray imaging, which enhances edges of structures, may offer an approach that will provide the level of discrimination needed to detect foreign bodies such as insects, hair and extraneous vegetable matter (Wilkins et al., 1996; Kagoshima et al., 1999).

1.4.3 Impedance The dielectric properties of foods are a function of the composition of the aqueous and non-aqueous phases present in it and information on contaminants


9

can sometimes be obtained from their interrogation. Impedance is a function of the resistive and reactive elements of a circuit that vary with the applied current frequency. Thus by measuring conductance of a food over a range of frequencies, an impedance spectrum can be obtained, whose characteristics give limited information on the types and quantities of solutes and the presence of particulate matter with different dielectric properties from the continuous phase. Dowdeswell of Kaiku Limited has described using impedance monitoring on-line on aqueous liquid streams to detect the presence of glycol leakages across heat exchangers, cleaning fluids and plastic and metal particles (summarised in Righelato, 2002). Impedance tomography is being developed for imaging in some medical applications and may have potential for detecting some types of foreign body in foods (Bolton, 2002). Engineering impedance detectors into tanks or pipelines is relatively straightforward; for other applications, for example to discrete solid food items and packages, engineering the electrical coupling is more problematic. Whilst impedance sensors can be designed to meet the criteria for hygiene, robustness and speed of detection, the necessary sensitivity and specificity are unlikely to be achieved for most applications in contaminant and foreign body detection.

1.4.4 Microwave radar Surface penetrating, microwave radar is used in military applications such as mine detection, in remote sensing of environmental parameters such as soil moisture and is being developed experimentally for medical diagnostic imaging. Microwaves travel at different speeds and are subject to different levels of damping in media of different dielectric properties. Microwave radiation can penetrate solids but the long wavelengths limit size resolution. The halfwavelength limit can to some degree be overcome for smaller bodies where edges create diffraction patterns that can be detected by measurements at different frequencies and at different positions around the object of scrutiny (Barr et al., 2001). The potential for application of microwave radar to foreign body detection in foods has been studied by Barr et al., (2001). Whilst it offers the advantage of being a remote sensing method with good penetration of foods, it has limited size resolution and poor discrimination in aqueous media. The screening effect of metal precludes its use for foods in metallic packs or cans and for many process plant applications.

1.4.5 Ultrasonic imaging High frequency, low power ultrasonic interrogation of food has been widely explored and, with frequency-scanning, can provide a range of information on composition and structure (Coupland and Clements, 2000; Hackley and Texter, 1998). Depending on the materials characteristics, it can provide size resolution

10


in the order of one millimetre or less. It has been used for inspection of package integrity and is capable of detecting leakage paths down to c. 10 m in width (Ozguler et al., 1998). It is a well-established imaging technique, widely used in medicine, but, although less costly than most of the other imaging techniques described, it has not yet been developed commercially for foreign bodies in foods. Direct contact or acoustic coupling between the signal generator and microphone and the sample is required; this can be simplified by using a pulsed echo rather than transmission method. However, although coupling may be straightforward in pipeline applications it presents difficulties in many processing operations dealing with fast moving discrete food items or packages.

1.4.6 Magnetic resonance imaging (MRI) MRI has become a major tool for non-invasive medical diagnosis: it is capable of resolving soft tissues and many biochemical changes occurring in them with spatial resolution of a millimetre or less. It has been used experimentally to observe many aspects of food quality, processing conditions and food structure (e.g. Duce et al., 1995; Metzler et al., 1995; Miquel and Hall, 1998), and is a candidate for the imaging of foreign bodies. For on-line process monitoring, however, it suffers from some major drawbacks. The process line must be surrounded by large, expensive magnets that are supported by complex data acquisition and processing facilities. To obtain two- and three-dimensional images with adequate spatial resolution, data acquisition can take seconds, too slow for many processing and packaging operations. Over the next decade, MRI may become a practical tool in food processing, if these drawbacks are overcome with novel magnet technology and new approaches to image analysis.

1.5

Conclusions

The complexity of most foods, the need for 100% sampling and for non-invasive techniques, and the speeds of operation of most processing severely limit the technologies that might be applied to on-line detection of contaminants. Several of the non-invasive and remote sensing technologies developed for clinical and environmental monitoring are potential candidates for foreign body detection (Table 1.3). Development of image analysis software is crucial to enable machine vision systems to discriminate most of the commonest foreign bodies in heterogeneous food systems. Although the costs of many of these systems are currently prohibitive, most are at an early stage of technological development and costs will become more attractive with time. Electronic nose technology has had much academic attention over the last decade, but little commercial application. Although attractive as a way of sampling complex food structures non-invasively, a major drawback to volatiles detection for on-line monitoring of manufacturing processes is speed of

Table 1.3

Comparison of some potential on-line detection techniques for contaminants and foreign bodies

Interrogation technique

Application1

Targets; size resolution

Cost order3 £/unit

Comments

Visible light

Processing

Plastic, EVM,2 insects; 1mm

104

Poor discrimination likely in complex foods

E-nose 1 2 3

Storage and distribution

Moulds, pest infestations, taints

Match to speeds, hygiene and other requirements. EVM = extraneous vegetable matter. Approximate order of cost of a detection unit.

4

10

Limited to contaminants with a volatile component or surrogate.

12


response. This is likely to limit its use to storage and distribution of raw materials and certain finished products, rather than the processing and packaging operations. Because they lack specificity, sensor array e-noses are likely to be superseded by other detection systems with better specificity, such as mass spectroscopy and, in some applications, tunable diode lasers. The principles of HACCP and GMP are the first, and most important, line of defence against contaminants and foreign bodies entering foods and reaching consumers. Systems, however, do occasionally fail and were cost-effective technology available to detect and reject unwanted material, it would no doubt be used to augment current practice.

1.6

Some sources of further information and advice

Sensors for food manufacturing applications, including biosensors: E Kress-Rogers and C J B Brimelow, Instrumentation and Sensors for the Food Industry, 2nd edition, Cambridge, Woodhead. X-ray imaging: Spectral fusion technologies: www.spectralft.com X-ray technologies: www.xrt.com.au CSIRO: www.cmst.csiro.au/photonic/xrayimaging.htm MRI: Herschel Smith Laboratory of Medical Chemistry: www.hslmc.cam.ac.uk

1.7

References

and MERKEL H (2001), ‘Detection of foreign objects in foods – from need to prototype’, Proceedings Food factory of the future, 27–29 Gothenburg, SIK (document 144, ISSN-280–9737). BARTLETT P N, ELLIOTT J M and GARDNER J W (1997), ‘Electronic noses and their application within the food industry’, Food Technology, 51, 44–8. BOLTON G (2002), ‘Finding out what goes on inside a process plant – prospects for the application of electrical impedance tomography to the food industry’, Food Science and Technology, 16, 52–4. BROWN H, GUNSON H E, PATTON D, RATCLIFFE N M and SPENCER-PHILLIPS P T N (2001), ‘Causes and detection of malodours in wheat grain’, Abstracts: Bioactive Fungal Metabolites – Impact and Exploitation. Swansea, British Mycological Society. COGLAN A (1999), ‘Something rotten’, New Scientist ,161, 15. COUPLAND J N and CLEMENTS D J (2000), ‘Ultrasonic evaluation of food properties’ in Gunasekaran S, Non-destructive food evaluation: techniques to analyze properties and quality, Marcel Dekker, New York. DUCE S L, ABLETT S, DARKE A H, PICKLES J, HART C and HALL L D (1995), ‘Nuclear magnetic resonance imaging and spectroscopic studies of wheat flake biscuits during baking’, Cereal Chemistry, 72, 105–8. FRIED A (2002), ‘Diode laser applications in atmospheric sensing’. Proceedings of SPIE BARR U-K, REIMERS M


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Conference 4817 July 11 2002, Seattle. and BARTLETT P N (1994), A brief history of electronic noses, Sensors and Actuators, B18–19, 211–20. GRAVES M, BATCHELOR B G and PALMER S (1994) ‘3D X-ray inspection of food products’, Proc. SPIE Conf. on Applications of Digital Image Processing 17, 2298, 248–59. HACKLEY V A and TEXTER J (1998), ‘Conference Report: International workshop on ultrasonic and dielectric techniques for suspended particulates, Gaithersburg, MD’, Journal of Research of the National Institute of Standards and Technology, 103, 217–223. KAGOSHIMA Y, TSUSAKA Y, YOKOYAME K, TAKAI K, TAKEDA S and MATSUI J (1999) ‘Phase contrast X-ray imaging using both vertically and horizontally expanded synchotron radiation X-rays with asymmetric Bragg reflection’, Japanese Journal of Applied Physics, 38, 470–2. DE LACY COSTELLO B J P, EWEN, R J, GUNSON, H E, RATCLIFFE N M and SPENCER-PHILLIPS P T N (2000), ‘The development of a sensor system for the early detection of soft rot in stored potato tubers’, Measurement Science and Technology, 11, 1685–91. LOW J M, MAUGHAN W S, BEE S C and HONEYWOOD M J (2001), ‘Sorting by colour in the food industry’ in E Kress-Rogers and C J B Brimelow, Instrumentation and Sensors for the Food Industry, 2nd edition, Cambridge, Woodhead. GARDNER J W

METZLER A, IZQUIERDO M, ZIEGLER A, KOCKENBERGER W, KOMR E, VON KIENLIN M, HAASE A

and DECORPS M (1995) ‘Plant histochemistry by correlation peak imaging’, Proceedings of the National Academy of Sciences of the USA, 92, 11912–15. MIQUEL M E and HALL L D (1998), ‘A general survey of chocolate confectionery by magnetic resonance imaging’, Lebensmittel Wissenschaft und Technologie, 31, 93–9. OGDEN I and STRACHAN N J C (1998), ‘Applications of ion mobility spectroscopy for food analysis’, in Biosensors for Food Analysis, Royal Society of Chemistry, Cambridge, 162–9. OZGULER A, MORRIS S A and O’BRIEN JR. W (1998), ‘Ultrasonic imaging of micro-leaks and seal contamination in flexible food packages by the pulse-echo technique’, Journal of Food Science, 63, 673–8. PEARSON T (1996), ‘Machine vision system for automated detection of stained pistachio nuts’, Lebensmittel Wissenschaft und Technologie 29, 203–9. PEARSON TC, WICKLOW D T, MAGHIRANG E B, XIE F and DOWELL F E (2001), ‘Detecting aflatoxin in single corn kernels by transmittance and reflectance spectroscopy’, Transactions of the American Society of Agricultural Engineers, 44, 1247–54. PILETSKY S A, ALCOCK S and TURNER A P F (2001), ‘Molecular imprinting: at the edge of the third millennium’, Trends in Biotechnology, 19, 9–12. RIGHELATO R C (2002), ‘Sticks, stones, bones and moans’, in Food Link News, 39, 10–11, London, DEFRA. SCHMIDT A and BILITEWSKI U (2001), ‘Biosensors for process monitoring and quality assurance in the food industry’ in E Kress-Rogers and C J B Brimelow, Instrumentation and Sensors for the Food Industry, 2nd edition, Cambridge, Woodhead. WILKINS S W, GUREYEV T E, GAO D, POGANY A and STEVENSON A W (1996), ‘Phase contrast imaging using polychromatic hard X-rays’ Nature, 384, 335–8.

2 On-line immunochemical assays for contaminant analysis I. E. Tothill, Cranfield University, UK

2.1

Introduction

Food analysis to date has usually been carried out using off-site testing where the samples are transported to a laboratory for the analysis to take place. This method allows accurate quantification, high recovery rates and low detection limits due to the availability of a dedicated laboratory equipped with the required instrumentation and highly-skilled personnel. However, these analyses are often time consuming and costly and an on-site analysis is always more favourable. Using robust, low cost, portable and rapid technologies that can make a determination of target analyte at the sampling site will overcome the problems of off-site analysis. Such screening methods can save valuable time and resources especially in food processing. Food analysis methods have to be sensitive and accurate to comply with legislation. Increasing customer confidence in the food that they consume is also important by eliminating any contaminated products entering the food chain. Recent cases, such as BSE, the foot and mouth outbreak and GMO foods (geneticallymodified organism), have aroused public concern over the potential health hazards of chemical and biological contaminants. This has prompted more stringent legislation related to the accepted concentration of these compounds and maximum residue limits (MRL) measured in ppb for most food contaminants have been set. Contaminant analysis is vital in food quality assurance and consumers demand high-quality foods free from polluting chemical compounds and pathogenic microorganisms. To ensure optimum quality is delivered to the consumer rapid assessment using cost-effective on-line measurements is required in the food industry. Immunochemical assays are dominating the market today in contaminant diagnostics and their use has increased in food quality testing. The impact of

On-line immunochemical assays for contaminant analysis 15 immunoassays on contaminant analysis for environmental and food applications is evident in the extensive diversity of kits which are available. Assay kits for the sensing of trace contaminants, including pesticides and herbicides, industrial residues and their degradation products, PCBs, microbial toxins and pathogens are available. A range of enzyme-linked immunosorbent assay (ELISA) kits for contaminant analysis has been developed and these kits are used as screening tools where the results can demonstrate the presence or absence of a particular analyte. The use of these tests will reduce the number of samples to be sent for further analysis using off-site methods. Although these tests can be carried out on-site they still require experienced personnel and also entail a multi-stage procedure with results taking 2–3 hours to be available. The time taken to carry out the test is too long for food manufacturers and more rapid monitoring is needed to speed up the analysis. Therefore, the demand for high sensitivity, speed and accuracy of all the analytes requiring testing has stimulated the interest in on-line diagnostics tools based on immunotechniques. Bio- and affinity sensors have the potential to provide rapid and specific sensing for food quality assurance. Sensors can be divided into two categories: catalytic and affinity. Details on the catalytic approach are covered in Tothill and Turner (1997) and Tothill (2001). Affinity sensors use mainly antibody–antigen binding reactions, but other biological components such as cell receptors, singlestranded DNA, lectins and artificial receptors have also been applied. A range of transducers has been employed and include electrochemical, optical, calorimetric, piezoelectric and magnetic ones (Tothill and Turner, 2003). This chapter, however, will concentrate on the use of immunochemical assays and immunosensors for contaminant analysis in food. Emerging on-line methods based on immunochemical assays will also be covered. On-line monitoring is very important in enabling effective process control and also helps in preventing low-quality products from reaching the consumer. Any sample preparation that may be required can also be accommodated using on-line methods such as filtration and dilution.

2.2

Principles and applications of immunochemical assays

Immunochemical assays (immunoassays) are analytical tests based on the selective and sensitive antibody (Ab)–antigen (Ag) interaction. These tests exploit the immune system’s ability to produce antibodies in response to any invasion by foreign organic molecules. The immune system’s function is to protect animals from infectious organisms and their toxic products. Therefore, it has evolved a powerful range of mechanisms to locate foreign macromolecules (antigen) and neutralise them by producing proteins (antibodies) to locate and interact with them and eliminate their harmful effect. The produced antibodies specifically recognise and attach to the antigen to form a complex. The high specific nature of the antibody–antigen reaction (Fig. 2.1) makes them fundamental reagent components in immunochemical techniques and this

16


Fig. 2.1

A schematic of the antibody structure and its interaction with the antigen.

interaction forms the basis of all immunochemical tests. The interaction is highly specific and follows the basic thermodynamic principles of any reversible biomolecular interaction: Ab Ag Ab ÿ Ag The affinity constant KA = [Ab–Ag]/([Ab] + [Ag]), where [Ab] is the molar concentration of unoccupied Ab binding sites, [Ag] is the molar concentration of unoccupied Ag binding sites and [Ab–Ag] is the molar concentration of the AbAg complex. The region of an antigen that interacts with an antibody is defined as the ‘epitope’. Because antibodies can recognise relatively small regions of antigens, occasionally they can find similar epitopes on other molecules. This forms the molecular basis for cross-reaction. The binding of the Ab–Ag is entirely dependent on reversible non-covalent interactions such as Van der Waals forces, electrostatic bonds, hydrogen bonds and hydrophobic interactions. The resulting complex is in equilibrium with the free compounds. The immune complex is stabilised by the combination of the above weak interactions that depend on the precise alignment of the antigen and antibody. The stringent binding requirements between the Ab–Ag makes immunoassays very selective. Small changes in antigen structure can affect profoundly the strength of the interaction. Also changes in the epitope structure can prevent antigen recognition. Therefore, antibodies have been isolated that will differentiate between conformations of protein antigens, detect single amino acids substitution, or act as weak enzymes by stabilising transition forms (Tothill and Stephens, 2001). Most organic contaminants of current interest are small molecules and have a molecular weight (MW) of less than 1000 Daltons. These small chemicals

On-line immunochemical assays for contaminant analysis 17 can be used to raise antibodies, if they are coupled to larger protein molecules. The small compounds are known as ‘haptens’, while the proteins to which they are coupled are called ‘carriers’. Bovine serum albumin (BSA) and keyhole limpet hemacyanin (KLH) are both popular carriers. Great care must be taken during the conjugation process since the hapten-carrier design and purity has crucial influence on the sensitivity and cross-reactivity of the antibody produced. Other food contaminants such as microorganisms and other macromolecules which have MW > 5000 Daltons are generally good immunogens and can elicit antibody production without the need for protein conjugation (Despande, 1996). An antibody of the desired affinity and specificity is vital to the process of developing immunochemical techniques. Most of the antibodies used in immunoassays are polyclonal antibodies raised or induced by injection of a solution or suspension of the appropriate antigen into an animal. Following a series of inoculations, blood is taken from the animal and the serum is separated from it. The resulting liquid is termed antisera and is a complex mix of proteins and specific antibodies directed against the inoculated immunogen. Because of the multiplicity of antigenic sites on any single immunogen or of impurities in the immunogen inoculated, a heterogeneous mixture of different antibodies of varying specificity and affinity are produced, i.e. polyclonal antibodies (PAbs). Purification of immunogen helps to narrow the range of affinities and specificities of the induced PAbs. When antibodies of monospecificity are required, antibodies can be derived from single cell lines using hybridoma technology to produce monoclonal antibodies. Since monoclonal antibodies are produced from a single chosen clone they can have high affinity and specificity to a single molecular compound. This will reduce the test cross-reactivity with other similar compounds and increase the specificity of the test. However, hybridoma technology can be expensive and assay specificity using monoclonal antibodies can be too narrow for some screening tasks. Another route for antibody production is to use antibody engineering, where recombinant antibodies can be produced at a fraction of the cost of the production of poly- or monoclonal systems. Due to the difficulty in cloning, assembling and expression of antibody molecules, this task is complex. There are two main types of recombinant antibodies: those produced by a cloning system (using an existing monoclonal cell line) and those produced in vitro (by passing the animal entirely). Research in this area is expanding to design and produce antibodies with the required test properties cheaply and without the use of animals. A range of labels are used today in immunochemical techniques to monitor the antibody–antigen binding reaction, including: latex particles (blue latex); radioisotopes (I125, H3); metal and dye soles (colloidal gold, fluorescent chromophore); enzymes (horseradish peroxidase, alkaline phosphatase and -Dgalactosidase); substrates and cofactors. Although fluorescent and chemiluminescent labels have been gaining popularity in the last few years, enzyme labels are still the most popular in immunoassay kits used for

18


contaminant detection. Depending on the assay format, the label is incorporated into either the Abs (primary or secondary) or the analyte (antigen or hapten). Immunoassays can be classified into three major formats: competitive, noncompetitive (sandwich) and displacement assays. In these formats either the Abs or Ags are immobilised on a solid phase support. Competitive assays are usually used for small molecular weight compounds such as food contaminates and environmental pollution. Analytes of environmental importance are too small to allow binding of two Abs simultaneously, therefore competitive assays are usually used in the diagnosis of compounds such as pesticides, herbicides, toxins and drugs, etc. Sandwich immunoassay utilises two antibodies, which bind the antigen and so form the sandwich. This type of format is used to detect analytes with a molecular weight that can allow the binding of two Abs simultaneously. Such tests are used for microbial and macromolecule detection. Figure 2.2 illustrates the competitive and noncompetitive assay formats. The displacement assay format is similar to the competitive assay. At the start of the assay all of the available binding sites on the immobilised antibodies are occupied by labelled antigen. On the addition of unlabelled antigen there is a displacement of labelled material and under appropriate conditions the extent of this displacement will be dependent on the amount of analyte in the sample. For more detailed information on immunochemical methods the reader is referred to the literature (Hammock and Gee, 1995; Despande, 1996). Detection techniques in immunoassays can be divided into two groups: 1. 2.

Direct detection, the antigen-specific antibody is labelled and used to bind to the antigen. Indirect detection, the antigen-specific antibody is unlabelled and its binding to the antigen is detected by a secondary reagent, such as labelled anti-immunoglobulin antibodies.

The choice of the direct or indirect method depends on the required test. The use of directly-labelled antibodies in an immunoassay involves fewer steps, is less prone to background problems, but is less sensitive than indirect methods and requires a new labelling step for every analyte to be tested. In contrast, indirect methods offer the advantages of widely available labelled reagents, which can be used to detect a large range of antigens, and are available commercially. Since the primary antibody is not modified by the label the loss of activity is also avoided. A further major distinction between immunoassays is the way in which the test is carried out: • Homogeneous immunoassay: A homogeneous system does not require separation of free and bound antigen: the assay relies on the alteration of the properties or function of the label on formation of the antibody–antigen complex. For example the Ab–Ag interaction will either inhibit or enhance the enzyme label used in the assay or change the signal in the case of radioactive isotopes and fluorescent labels. The assays are simple and easy to automate, therefore are commonly used in the diagnostic industry.

On-line immunochemical assays for contaminant analysis 19

Fig. 2.2

Most commonly used configurations for immunoassays for food analysis.

• Heterogeneous immunoassay: In a heterogeneous system there is a separation step to remove the unbound reagents before the label (tracer) is determined. This assay format is a more sensitive approach, less prone to interference and is most commonly employed in test kits. Other types of immunoassay use magnetic separation as enzyme immunoassays with paramagnetic particles as the solid phase. In this case the antibody is immobilised on the magnetic particle surface. This allows the separation of the desired measurable immune complex from excess reagents and sample (Perez et al., 1998). A range of assay kits based on this principle are available for food and agriculture analysis, some of which are marketed by Strategic Diagnostics Inc. (Newark, USA).

20


Immunoassay test strips for use outside the laboratory based on flow devices such as the pregnancy strips developed by Unipath (ClearblueTM one step) have also been constructed for environmental contaminant detection. The tests are based on immunochromatography strips using coloured latex as the label. Recently equipment has also been developed to measure the intensity of the coloured line making the test more quantitative. However, immunoassay test kits are the most commonly available kits on the market for contaminant testing. Most immunoassays are used to measure one analyte per kit (e.g. the urea herbicide Isoproturon) or group specific assays that utilise heterogenecity of the polyclonal antibodies to analyse for a group of compounds that are similar in their chemical structure such as the group of urea herbicides (urons). Assays that can measure two or more analytes simultaneously have many advantages in enabling the detection of different analytes using the same sample. Development in this type of assay is thriving. An example of this is the development of immunosensor arrays and microspot arrays which use multispot arrays (50 M2) on the wells that are coated with different Abs. The microspot arrays require a detection system that can resolve the different signals associated with the different spots such as the use of dual channel confocal microscope.

2.3

Immunoassays for food contaminant analysis

A large number of ELISA tests have been developed for the determination of environmental contaminants (for example, for pesticides, such as atrazine, urea herbicides and phenoxyacids, etc). Immunoassays are also used to detect veterinary drugs, microtoxins and other chemical contaminants in agrofood matrices. These tests have also been adapted and used for food analysis. However, suitable extraction methods may be required to remove a sample for testing. Many of the methods developed for soil extraction are now adapted for food sample extraction. Methods based on solvent extraction, microwave-assisted solvent extraction, solid phase extraction and supercritical fluid extraction have been used for liquid and solid sample preparation. Immunoassay techniques are ideal for contaminant analysis due to their selectivity, sensitivity and rapid turnover time (2–3 h). The robustness of the methods can generate on-the-spot data that can be used to make quick decisions. Many of these tests have been correlated to conventional methods such as HPLC and GC-MS and have been accepted by regulatory bodies. But before these tests can be widely used in routine monitoring, issues such as stability and reproducibility need to be improved in order to compete with established conventional methods. Immunoassays today have gained greater acceptance and this is illustrated by the US Environmental Protection Agency’s (EPA) implementation of the EPA ‘400 Series’ of approved commercial ELISA test kits for pollution analysis. The field of immunoassay has shown enormous growth in the last decades. To date there are a range of automated immunoassay analysers available on the market for use in medical analysis (Wild, 2001), which can be modified for use in food testing. Companies

On-line immunochemical assays for contaminant analysis 21 such as SDI Europe Ltd (Hampshire, UK) and Guildhay Ltd. (Surrey, UK) market a range of immunoassay kits for environmental and food diagnostics. Immunoassay kits can be classified as on-site or off-site methods of analysis. In order to lower costs and speed up the testing programme, on-site and on-line analysis is becoming increasingly important. Therefore, biosensors based on the use of antibody as the receptor (immunosensors) exhibit the potential to complement laboratory-based analytical methods and can be used for on-line testing.

2.4

Immunochemical sensors (immunosensors)

Immunosensors are analytical devices incorporating an antibody-based biorecognition molecule utilised in conjunction with or integrated within a physicochemical transducer or transducing microsystems and yielding a digital electronic signal, which is proportional to the concentration of a specific analyte or group of analytes. Immunosensors are very attractive due to their high specificity and the signal achieved is related to a single analyte or small number of related compounds. This is usually dependent on the cross-reactivity of the antibody applied. The direct transfer of existing immunoassay techniques to sensor format can facilitate the development of these devices. Interest in the development and application of these sensing tools is growing rapidly due to: • advances in hybridoma technology • developments in transduction methodologies • increasing demands for simple sensitive and rapid analytical tools for decentralised analysis • stringent environmental legislation. The most attractive advantages of immunosensors over immunoassays are simplification of the analysis procedure (fewer stages), decrease of analysis time, miniaturisation of equipment and automation. The markets for these types of devices are variable and require very different products. The controlling influences are; instrumentation cost, accuracy required, sensitivity and speed and portability. The devices can fall into several categories depending on the analysis place and time, and can include large multi-analysers, portable bench-top instruments and one-shot disposable sensors. Miniaturisation and improved processing power of modern microelectronics have increased the analytical capability of bio- and immunosensors. Research on Lab-on-a chip is exploding and interest from multinational companies in this area is also increasing. The use of antibodies as receptors in sensor configuration combined with a suitable transducer can result in a sensitive and specific affinity sensor. Immunosensors can be divided into direct sensing devices detecting the recognition event and the complex produced between the antibody and the analyte and indirect devices relying on the use of label compounds (enzyme, florescence marker, etc.) to create the signal. Indirect devices rely on the same principle and format used in heterogeneous immunoassays. The majority of immunosensor research and

22


development to date for disposable one-shot sensors is concentrating on indirect detection using enzyme and fluorescent labels. This is due to the low cost of this type of device when compared to direct methods. A range of immunosensors for pesticides, herbicides, toxins, antibiotics, hormones, additives, endocrine disrupting chemicals and microorganisms has been developed for environmental and food analysis. Immunosensors have already established their ease of use and costeffectiveness, thus allowing non-trained operators to employ a relatively cheap assay. The devices have been adapted and used with flow injection analysis for online monitoring of pesticides in water samples. Immunochemical techniques and immunosensors for contaminant monitoring have been reviewed in the literature (Marco et al., 1995; Gizeli and Lowe, 1996; Wittmann and Schmid, 1997).

2.4.1 Optical immunosensors To date affinity sensors based on the use of optical transducers have received considerable attention and have been applied to food sensing. Advances in optical fibres and laser technology have contributed to the wide use of this type of transducer. However, the high cost of some of the equipment based on optical sensing has hindered the widespread use of these devices outside the laboratory. The ability to monitor binding events between the antigen and antibody directly is the main attractiveness of this technique. Optical sensors based on surface plasmon resonance (SPR) such as the BIAcoreTM range of equipment developed by Pharmacia (Uppsala, Sweden) and the IAsys using resonant mirror from Affinity Sensors Ltd (Cambridge, UK) symbolise a significant breakthrough in optical sensor technology (Tothill, 2001; Mello and Kubota, 2002). The instruments are mostly used for kinetic interaction analysis in biochemical research and not as a monitoring tool. But the systems are semiautomated and analysis can be carried out at a rapid rate. The BIAcore has been used to develop immunosensors for a range of analytes in water and soil extracted samples. Skla´dal et al. (1999) used the IAsys optical sensor system to develop an immunosensor to detect atrazine in soil extracts. A detection of 1g lÿ1 was achieved repeatedly with sensor regeneration for up to 120 assays. A total internal reflectance fibre-optic immunosensor against 2,4-D with Mabs was developed by Mosiello et al. (1997). This immunosensor achieved a detection limit of about 60 nM for 2,4-D. The approach of using fluorescent labels detected via evanescent wave interaction with an optical fibre has been applied successfully in immunosensor development. Examples of these devices are the Raptor developed by the US Navy Research Laboratory and the fluorescence-based EW immunosensor that incorporates the capillary fill device developed by Unilever (Bedfordshire, UK).

2.4.2 Electrochemical Immunosensors Electrochemical affinity sensors generally rely on the use of electroactive label, usually employing enzyme labelling and amplification techniques. Detection

On-line immunochemical assays for contaminant analysis 23 using electrochemical immunosensors can be inexpensive and may achieve low detection limits. Different types of electrochemical affinity sensors have been developed including potentiometric, capacitive, conductometric and amperometric. A range of amperometric electrochemical immunosensors has been developed for pesticide detection. Most are based on screen-printing electrodes for one-shot analysis. However these sensors can also be adapted for on-line monitoring. A screen-printing immunosensor for 2,4-D analysis in soil extract was developed by Kro¨ger et al. (1999). The sensor was based on an indirect competitive assay with the antigen conjugate adsorbed directly onto the working electrode surface. The disposable sensor enabled ppm concentrations of the herbicide to be analysed in soil extracts. Another sensor for 2,4-D was develop by Wilmer et al. (1997) using a competitive assay with sequential injection analysis techniques sensing through an immunosensor with the analyte immobilised on a glass capillary or to Eupergit packed in the capillary. This was conducted for automatic measurement of 2,4-D in drinking water and groundwater and can be applied for on-line monitoring. An immunosensor based on a competitive direct enzyme immunoassay (EIA) system coupled to amperometric transducer for the detection of microcystin-LR in water and seafood samples has been developed by Lotierzo et al. (2001). The sensor implements a membrane-bound configuration of the EIA system. Signal detection is by amperometric transduction of the HRP between the carbon working and Ag/AgCl reference electrode via a hydroquinone mediator with hydrogen peroxide as substrate. The detection limit for the electrochemical immunosensor is in the range of 10 g lÿ1 (Fig. 2.3). The sensor was also used in a flow injection analysis (FIA) system for on-line application for water testing. Amperometric detection is the most applied system in these devices. However, more research on the efficiency of coupling of the biological electron-generating steps to the electrode is needed to improve the sensitivity of these devices. Also the effect of interfering compounds can be a problem with samples containing ppb analyte concentrations. Potentiometric devices rely on the measurement of changes in potential that arise from reaction of an analyte with a specific receptor. A range of devices has been developed using this type of transducer where the antibody has been immobilised on ion-selective electrodes. Devices such as the ion-sensitive fieldeffective transducers (ISFETs), chemically sensitive field-effective transistor (CHEMFET) and the light-addressable potentiometric sensor (LAPS) have all been reported in the literature (Colapicchioni et al., 1991; Poghossian et al., 2001; Selvanayagam et al., 2002). Another device, which uses ion-channel switches (ICSs) that mimic biological sensory functions have also been reported (Cornell et al., 1997; Cornell, 2002). The ICS sensor uses a gold electrode to which is tethered a lipid membrane that incorporates gramicidin ion-channels linked to antibodies. These ion channels are mobile within the membrane, which encloses an ionic reservoir between the gold electrode and the membrane. In the presence of an applied potential, ions flow between the reservoir and the

24


Fig. 2.3

Electrochemical disposable immunosensor format (Lotierzo et al., 2001).

external solution. Ion flux stops when dimerisation of the mobile channels in the outer half of the membrane with those on the inner half is prevented by binding of the antibody to its analyte (Malan, 2001). The presence of the analytes of interest can be measured by the change in membrane conductance. The sensor instrument AMBRI SENSIDX System is marketed by the Australian Membrane and Biotechnology Research Institute (AMBRI, Sydney) and can be used for veterinary, food and environmental diagnostics. Food testing applications include detection of dangerous organisms such as salmonella, enterecoccusin and faecal coliform bacteria in the food processing industry.

2.4.3 Piezoelectric/acoustic immunosensors Piezoelectric/acoustic sensors such as the quartz crystal microbalance (QCM) and surface acoustic devices (SAW) can also be classified as direct immunosensors when immunoreagents are used as the receptor. Piezoelectric transducers have gained attention recently in affinity sensor development. A quartz crystal is used for sensor fabrication and is sandwiched between two electrodes, which are generally gold or silver, prepared by thermal evaporation. The region between the electrodes is piezoelectric active and the change in the resonant frequency will depend on the change in the mass of the crystal (Bunde et al., 1998). These devices are also called quartz crystal microbalance (QCM), due to the frequency with which the crystal oscillates and thus the resulting acoustic wave depends on the mass of the molecules attached to the crystsl. A review of piezoelectric immunosensors and their application for food analysis have been reported by Minunni et al. (1995). Devices such as the surface acoustic wave (SAW) sensor and the acoustic wave guide (AWG) have been developed.

On-line immunochemical assays for contaminant analysis 25 Piezoelectric sensors have been used for the detection of contaminants such as pesticides in the gas and also liquid phase. By immobilising the antibody for the target analytes on the crystal, immunosensors for parathion, atrazine and 2,4D have been developed. However, these type of sensors have been found to have low sensitivity for small compounds such as environmental contaminants, and detection limits in the range of ppm are usually reported in environmental and food extracted samples. Coupling the sensor with a flow system to concentrate the samples using solid phase extraction columns has increased the sensitivity of these devices. The use of a piezoelectric sensor combined with a flow system using a flow cell has been developed and used to provide real-time data on the binding events between the analyte and its receptor (Chianella et al., 2003).

2.5

On-line immuno sensors in food processing

Analytical systems for on-line monitoring in food processing should not introduce contamination and compromise the sterility of the products, and also allow accurate and rapid results. The high complexity of food samples makes this very challenging for on-line monitoring systems. However, opportunities exist for on-line monitoring during manufacture and in shelf-life monitoring during distribution and storage. A range of immunochemical methods can be adapted and applied for on-line monitoring. Flow injection analysis (FIA) is an analytical technique, which has broad acceptance for on-line monitoring and has also been proved to be highly versatile and allows high measurement frequency. The technique has been coupled to a range of detection principles including spectrophotometry, chemiluminescence, fluorimetry, mass spectrometry, atomic absorption, flame emission, refractive index measurement and various electrochemical techniques such as amprometry and potentiometry. However, applying immunotechniques for on-line monitoring in the food industry requires extracting and interfacing the sample with the detection system. Also, the sensor mechanism must be reversible so that it can be reused without loss of sensitivity. Regeneration of the sensor surface so that it can be re-used in situ for long periods of time can be very challenging when using food samples. Several methods have been used in the literature to generate the sensors for on-line monitoring (GonzalezMartinez et al., 1997; Zeravik and Skla´dal, 1999; Paek and Schramm, 1997; Blonder et al., 1997). Many have reported successful reuse of the sensors with 100 assay cycles being reported. However, most studies used water samples or spiked buffer samples. One of the on-line immunosensor systems developed in recent years and attracting much attention is the prototype FIA River ANALyser (RIANA system) which was developed under European Commission funding. The RIANA system incorporates a multiple analytes immunoanalysis based on total internal reflection fluorescence with 15 minutes for each analysis (Mallat et al., 1999, 2001a,b). The transducer consists of a quartz slide with spatially resolved surface modification for antigen immobilisation, along which a coupled laser

26


beam propagates by total internal reflection. The antibodies are labelled with Cy5.5 fluorescent dye and compete with the free analyte. The system has been applied for the detection of chlorotriazines, atrazine, simazine and isoproturon. Detection limit for isoproturon in river water was 0.14 g lÿ1. The system is currently being developed to be a fully automated on-line system capable of detecting a range of contaminants in river water. Instruments such as the RIANA system can be further developed for wine and milk testing. Immunosensors have also been applied to quasi-continuous flow through monitoring in a system similar to immunoaffinity chromatography where the capture antibodies immobilised are in a column (Vianello et al., 1998). The activity of the label was monitored continuously from the micro column using amperometric detection. Flow injection capillary chemiluminescent ELISA using an imprinted polymer instead of the antibody has also been developed (Surugiu et al., 2001).

2.5.1 Application of on-line monitoring in the food industry Liquid and gas chromatography and mass spectrometry usually form the basis for routine contaminant analysis in the food industry. These techniques are still being used regularly for food quality assurance. Contaminants such as ethyl carbamate, anthocyanin, phenolic antioxidants and 2,4,6-trichloroanisole in wine are analysed using the above methods. There are many companies advertising their services on the Internet for wine and fruit juices and dairies analysis using conventional methods. However, the use of immunochemical techniques and sensors for this application is gaining attention, although most are still research tools. Immunosensors for contaminant monitoring are largely dominated by research into piezoelectric and optical devices (SPR, fibre optics and evanescent wave). This is mainly due to the simplicity of the tests since these devices can enable multi-analyte analysis and assays carried out in a direct format. Also the tests can be easily automated and run on-line and on-site. Amperometric devices are more attractive for field analysis using one-shot disposable devices. A range of immunosensors has been developed in the literature which adapt immunoassay technology and these can be applied for food testing. Immunodiagnostics tests are used today for pollution detection in food and for on-farm screening of livestock diseases and also monitoring of livestock reproduction (milk progesterone) and quality control of foodstuffs such as authenticity and adulteration (Van Der Lende, 1994). Many of these tests can be further developed to immunosensors and immunoprobes and used for real-time and on-line analysis. Antibiotic and chemotherapeutic use in animal husbandry has also led to the occurrence of veterinary drug residues in food of animal origin. To be able to analyse and detect all of these contaminating compounds, more rapid tests such as immunosensor assays need to be developed and implemented to speed up the screening process. Monitoring in dairies and bakeries, fruit juices and wine mainly concentrate on pathogenic microbial contamination screening and their contaminating by-

On-line immunochemical assays for contaminant analysis 27 products. However, detection of a range of toxins produced by microorganisms, metal contaminants, drugs residues, pesticide and herbicide contents are also becoming of importance. This is in order to comply with legislation and also to reduce the harmful effects of these contaminants on human health, which has become more apparent in recent years, especially the chronic exposure to low levels of these contaminants. Examples of some of the developments in this area will be covered in this section. Optical biosensors based on SPR technology have been used to develop rapid diagnostics tests for food analysis. SPR-based immunosensor for sulfamethazine detection in milk has been reported by Sternesjo et al. (1995) with detection limit of 1ppb. BIAcore AB have also launched the BIAcoreQuantTM, a version of their SPR technology for the automated analysis of vitamins in food. The sensor chip used in these instruments is shown in Fig. 2.4. Similar principles have also been applied for the determination of drug residues in meat and milk products and also microorganisms such as E. coli O157 in food samples using BIAcore 2000. Homola et al. (2002) reported the development of SPR biosensor for the detection of Staphylococcal enterotoxin B in milk. The sensor was able to detect the toxins in buffer as low as 5 ng lÿ1. By applying a sandwich detection format the sensor sensitivity was enhanced to 0.5 ng lÿ1 in both buffer and milk samples. Optical sensors have been demonstrated for the detection of various foodborne pathogens and their toxins such as Salmonella typhimurium and Listeria monocytogenes. Progesterone immunosensors have been developed and applied for milk analysis using the same principle as the immunodiagnostics test kit used to analyse it. A rapid and automated immunosensor using BIAcoreTM surface plasmon resonance biosensor was developed for the detection of progesterone in milk with a limit of detection found to be 3.56 ng mlÿ1 (Gillis et al., 2002). BIAcoreTM has also been use to detect levamisole residues in milk with a detection limit of 0.5 ng mlÿ1 (Crooks et al., 2002). Polido-Tofinõ et al. (2000, 2001) developed an FIA fluoroimmunosensor for food analysis. The system was based on direct immunoassay with fluoroscein

Fig. 2.4

The sensor chip used in the BIAcoreTM range of instrumnts.

28


isothiocyanate labelled antigen. The antibody was immobilised on a controlled pore glass transducer. Foodstuffs such as wheat, barley, potatoes and peas were spiked with isoproturon and used for the analysis. Detection limit of 3.0 g lÿ1 was achieved which exceeded the EU Directive maximum levels of 0.05 mg kgÿ1 in agricultural foodstuffs. However, matrix effects were apparent in some of the samples especially potato samples. The developed sensor system can be regenerated with citric acid and be used for 1000 measurements. Winemaking and fruit juice production poses many qualities (appearance, taste) as well as safety (chemicals, metals and pathogens) hazards. Christaki and Tzia (2002) have reviewed winemaking covering quality and safety analysis of the process as well as the different hazards that can contaminate the wine. Most of wine and fruit juice analysis, however, is still carried out using conventional methods. Recently immunochemical techniques have been investigated and also on-line analysis has been reported. Most of these concern pesticide, mycotoxin and microorganism concentration and detection. Ochratoxin A occurs in a variety of food commodities of which cereals and cereal products, beer and wine are the most important sources. The occurrence of Ochratoxin A in wine has been reported in various studies dealing with European wine (Leitner, et al., 2002). Most of the current analytical methods for the determination of this toxin and for pesticides (Wu et al., 2002) use immunoaffinity columns as sample clean-up and concentration methods. However, analysis is usually carried out using HPLC-MS or LC-MS. Methods based on immunosensors are still under development, although are increasingly being reported in the literature (De Saeger et al., 2002). A flow injection analysis manifold with three channels, using a dialysis unit to eliminate sample matrix interference and to accomplish on-line dilution has been developed for the spectrophotometrical determination of tartaric acid in wine (Silva and Alvares-Ribeiro, 2002). This method of on-line analysis was found to be fast, accurate, simple, economic and does not require any sample pre-treatment. Recently, FIA has been used frequently in the literature for the development of new methods for wine analysis (Azevedo et al., 1999; De Campos Costa and Arau´jo, 2002). The availability of antibodies for the analysis of contaminants is increasing rapidly. Also the use of specifically-tailored and mass-produced alternatives to conventional antibodies is likely to alleviate the production of immunosensors and affinity sensor devices. An example is plantibodies produced in plants, recombinant antibodies, catalytic antibodies or abzymes (Breitling and Du¨bel, 1999; Motherwell et al., 2001), artificial receptors such as molecularly imprinted polymers, synthetic peptides and aptamers, which are artificial nucleic acid ligands (Chianella et al., 2002; O’Sullivan, 2002). Many companies and research organisations are developing one-shot disposable immunosensors or on-line immunosensors for food diagnostics. These devices will reach the market in the near future. However, more investment is needed to accomplish this goal. Table 2.1 gives examples of some immunosensors that can be applied or have been used for food analysis or water analysis.

Table 2.1

Examples of immunosensors developed for contaminant detection

Analyte

Type of sensor

2,4-D

Disposable amperometric multi-channel sensor based on screen-printing electrode with acetylcholinesterase as the label Nonseparation electrochemical enzyme binding/immunoassay using microporous gold electrodes Flow through column with glass as the solid support to immobilise the antibody Indirect competitive immunosensor using fibreoptic transduction with flow injection analysis Label-free immunosensor using reflectometric interference spectroscopy FIA fluoroimmunosensor for on-line monitoring system SPR detection coupled with identification using mass spectrometry SPR-based immunosensor Automated SPR-based immunosensor

Dioxin Carbaryl insecticide Okadaic acid toxin Isoproturon Diuron Staphylococcal enterotoxin B Sulfamethazine residues Insulin-like growth factor-1 (1GF-1)

Detection limit

Detection time Matrix

Reference

0.01 g lÿ1

30 minute

Kalab and Skla´dal (1997)

0.01 g lÿ1

–

water and sheep serum

Ducey et al. (1997)

0.029 g lÿ1

20 minute

water

0.1 g lÿ1

20 minute

0.7 g lÿ1

–

mussel homogenates water

0.02 g lÿ1

–

water

1 ng lÿ1

–

1 ppb

20 minute

milk and mushroom milk

1 g lÿ1

–

milk

GonzalezMartinez et al. (1997) Marquette et al. (1999) Haake et al. (2000) Kra¨mer et al. (1997) Nedelkov et al. (2000) Sternesjo et al. (1995) Guidi et al. (2002)

water

30

2.6


Future trends

Future development in diagnostics is already progressing and turning fiction into reality. Advances in microfluidics, genomics and proteomics are transforming biochemical analysis and creating breakthroughs in microarray systems capable of multianalyte analysis for high-throughput screening tests. The emergence of microarray technology (Lab-on-a-chip), and the development of new receptor systems will have a major impact on food analysis.

2.6.1 Microarrays The advances in nanotechnology and microfluidics have created new products and materials which have enabled countless applications based on new capabilities. Microspot assays or multianalyte microarray are developing rapidly in the diagnostics industry and represent a powerful new set of tools. All microarray assays contain five experimental steps including biological query, sample preparation, biochemical reaction, detection and data visualisation and modelling (Schena et al., 1998). Protein microarrays have emerged after the development of DNA microarrays. In this section the application of antibodies in this type of assay is covered. In protein microarray tests the capture antibody is located on the solid support and exposed to an analyte-containing sample. Occupancy of the antibody within the spot may be determined by its exposure to a second (labelled) developing antibody or antigen reactive with either occupied or unoccupied sites following the noncompetitive and competitive assay format used in conventional immunoassays (Self and Winger, 2001). Since the assays rely on measurement of the fractional occupancy of the sensor antibody, the immobilised antibody on the microarray is also labelled. The signal is then observed by the ratio of signal emitted by the immobilised antibody with either the signal emitted by the second labelled antibody (noncompetitive assay) or the labelled antigen (competitive assay) (Fig. 2.5). Fluorescent labels are used in this system since they possess very high specific activity and permit good microspot distribution on the surface of the chip to be optically scanned using a confocal microscope or CCD camera. Other labels are also used such as chemiluminescent labels, but these have lower assay sensitivities. Microspot assays can yield higher sensitivities than other immunoassay formats. The amount of antibody immobilised on the microspot approximates 0.01/K. The tests are reviewed by Schena et al. (1998) and Self and Winger (2001). Microarrays have the great advantages of sensitivity, shorter assay time and multianalyte assay when compared with conventional immunoassays. However, they require good instrumentation and greater attention to non-specific binding of the labelled reagents, the background signal of the microspots and reagent stability. The instrumentation needed to support and implement this technology can be very expensive, such as microarray chip manufacturing, scanning the chips using fully automated analysers with microfluidic systems and sample preparation process. However, the multianalyte sensing capability of these devices will revolutionise the diagnostic industry.


Fig. 2.5

Protein microarrays.

2.6.2 New emerging receptors Several state-of-the-art approaches are used today for the production of affinity receptor molecules for analytes and contaminant separation and detection. Biological molecules are usually very specific and sensitive for the target analytes and when applied to sensor format they can produce good sensor specification. Antibodies are widely applied today in a range of immunotechnique devices ranging from immunoassay kits to dipsticks and biosensors. Antibody fragments and molecularly-engineered antibodies are being developed for immunosensor application. By using direct and combinatorial mutagenesis the affinity and selectivity of recombinant antibodies are being enhanced and adapted to make them better suited for specific devices, although, for some applications, biomolecules with the required affinity are either not available or lack the properties necessary for a successful sensor, such as stability, which can hinder wider application and lack of commercialisation. Replacing natural biomolecules with artificial receptors or biomimics has therefore become an attractive area of research in recent years. Development of artificial receptors for contaminant detection is being favoured and the increase of research in the area of biomimetics is growing. This may also be due to the fact that approaches used in receptor synthesis obviate the need for animals, which is essential for antibody production. Also the stability problems facing antibodies in extreme environmental conditions (such as pH and organic solvents and high temperature) need to be overcome. Studies of mimicking natural receptors have been a challenge to many researchers (Andersson et al., 1996). A range of suitable sensing layers are being developed such as combinatorial synthesis of molecular receptors, combinatorial library of nucleic acids (aptamers) and imprinted polymers. These receptors can be specific for a chosen analyte or a whole class of target analytes.

32


The use of organic polymers to specifically imprint the target molecule has been carried out and the production of a molecularly-imprinted polymer (MIP) as a synthetic receptor has been realised (Mosbach, 1994; Mosbach and Ramstrom, 1996). Artificial antibodies and receptors prepared by using molecular imprinting are conceptually attractive due to their ease of preparation, high thermal and chemical stability, and long shelf-life in ambient temperature and humidity (Andersson, 2000a,b). Molecular modelling is a powerful tool to implement conformational study of molecules such as drugs, proteins, macromolecules, etc., and it allows computational chemists to generate and refine molecular geometry (Chianella et al., 2002). Molecularly-imprinted polymer for the pesticide bentazone has been synthesised and used to sense the pollutant (Baggiani et al., 1999). Herbicide assay using an imprinted polymer-based system analogous to competitive fluoroimmunoassays has also been reported (Haupt et al., 1998). These new types of receptors were used not only in sensor conformations but also in column chromatography and solid phase extraction columns to concentrate contaminants before analysis. The use of molecularly-imprinted solid-phase extraction for the selective concentration of clenbuterol from calf urine and bovine liver has been reported by Berggren et al. (2000) and Crescenzi et al. (2001). On-line solid-phase extraction of the triazine herbicides using a molecularly-imprinted polymer for selective sample enrichment has been conducted (Bjarnason et al., 1999). Reports on on-line solid-phase extraction using MIP technology is increasingly being reported in the literature (Masque et al., 2000; Koeber et al., 2001). Recent work at Cranfield University (Chianella et al., 2002) used a computational approach for the design of a molecularly-imprinted polymer specific for Cyanobacterial toxin, microcystin-LR. This toxin is the most widespread hepatotoxin which has a tumour-promoting activity that can threaten human health by low-level chronic exposure to these toxins in contaminated drinking water and also from consuming contaminated seafood. By using molecular modelling software, a virtual library of functional monomers was designed and screened against the target toxin, which was employed as a template for MIP synthesis. The monomers giving the highest binding energy were selected and used in a molecular dynamics process to investigate their interaction with the toxin (Fig. 2.6). The stoichiometric ratio observed from the study was used in the artificial receptor synthesis for microcystin-LR. The synthesised polymer was used both as a material for solid-phase extraction (SPE) and as a sensing element in a piezoelectric sensor (Chianella et al., 2003). Using the combination of SPE concentration followed by piezoelectric sensor detection the minimum detection limit achieved was 0.35 nM for microcystin-LR. The combinatorial library technique (combinatorial chemistry) has been an expanding area of development for receptor discovery and lead compound optimisation and is widely used by the drug industry. Combinatorial libraries consist of a large array of diverse molecular entities, generated by the systematic and repetitive covalent connection of a set of different ‘building blocks’ of


Fig. 2.6 Microcystin-LR, in balls and sticks in the centre and its interaction with six molecules of urocanis acid ethyl ester (UAEE) and 1 molecule of 2-acrylamido-2-methyl-1 propanesulfonic acid (AMPSA) (Chianella et al., 2002).

varying structures. Effort has been devoted in the development of new strategies for peptide and non-peptide libraries. A large number of compounds can be generated using combinatorial library techniques. Molecular modelling is usually used as a combined approach to facilitate a more efficient receptor discovery process. Combinatorial chemistry has been used to generate affinity peptide ligands which can be applied as receptors in diagnostic devices such as biosensors (Chen et al., 1998). At Cranfield University, we are working on the development of peptide receptors for anabolically active illegal androgens used to boost animal performance, such as boldenone and stanozolol. The receptors will be designed based on a combined approach of molecular modelling and combinatorial chemistry. The developed receptors will then be implemented in a sensor format for the detection of these compounds in meat and foodstuff. This research is part of the (RADAR) project funded by the European Commission. Aptamers (derived from the latin aptus, meaning ‘to fit’) are artificial nucleic acid ligands selected from combinatorial libraries of synthetic nucleic acids by an iterative process of adsorption, recovery and reamplification (O’Sullivan, 2002). These can be generated against amino acids, drugs, proteins and other molecules and used as receptors for sensor and kit developments. Aptamers are attracting interest in the area of diagnostics and are being developed to be implemented in future devices. Research activity in the area of artificial receptor discovery and synthesis is an exciting and rapidly growing area in ligand discovery. It should be possible to overcome the stability problems inherent in natural receptors using these techniques.

34

2.7


Conclusions

Detection of contaminants in food and food processing plants is of increasing importance to consumers, the food industry and regulatory authorities. Significant effects on quality improvement and cost reduction in practical agriculture, horticulture and food processing are expected by the establishment of appropriate technologies to apply rapid sensing methods such as on-line immunotechniques and immunosensors. Current instrumentation developments centre around miniaturisation, improved signal processing and sensor array technology where multiple analytes can be detected simultaneously on the same sensor chip. The chemistry, biochemistry and molecular biology communities are working together to improve currently available receptors such as antibodies, and also to design and synthesise new and more stable receptors. Techniques such as reagent deposition assay format and sensor design and fabrication are being developed to enhance immunosensor capabilities. The emergence and widespread use of miniaturised multianalyte chip-based microarray methods for DNA analysis and immunodiagnostics have a significant impact on the diagnostics food market. Advances in pattern-recognition methods and the availability of the instruments is also revolutionising the diagnostic industry. However, all developed assays must be compatible with regulatory requirements across the globe, and must ensure that design control practices, such as the ISO 9000 and other regulatory guidance, are followed. The time and expense involved with the detection of contaminants such as sample acquisition, sample preparation, and laboratory analysis have placed limitations on the number of tests that can be carried out on- and off-site. However, with recent advances in biotechnology, microelectronics and fibre optics the classical definition of biosensor has emerged to include a variety of analytical devices based on bioaffinity sensing. For immunosensors to have a significant impact on this monitoring task, several challenges must be addressed especially in food processing. These include compound diversity and complexity; matrix diversity and complexity; screening and monitoring requirements and method approval. For liquid matrix it is easier to apply these types of methods such as for milk and wine testing, but for more solid and high viscosity matrix a more complex sample preparation may have to be implemented to introduce the sample to the sensing devices. The potential success of immunosensors in agriculture, food processing and veterinary diagnosis is being established since new tests and instrumentation are appearing on the market for these applications.

2.8

Source of further information and advice

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On-line immunochemical assays for contaminant analysis 35 and GEE, S.J. (1995). ‘Impact of emerging technologies on immunochemical method for environmental analysis’ ACS Symposium Series 586, Immunoanalysis of Agrochemicals. ACS Press. HARLOW, E. and LANE, D. (1999). Using Antibodies: A Laboratory Manual. Cold Spring Harbour Laboratory Press, Cold Spring Harbour, NY. KRESS-ROGERS, E. (ed.) (1998). Handbook of Biosensors and Electronic Noses. Boca Raton, FL: CRC Press. SCOTT, A.O. (ed.) (1998). Biosensors for Food Analysis, Cambridge, The Royal Society of Chemistry. HAMMOCK, B.D.

2.9

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microbalance as biosensor. A status report on its future, Anal. Letters, 28, 749–764. (1994). Molecular imprinting, Trends in Biochemical Science, 19, 9–14. MOSBACH, K. and RAMSTROM, O. (1996). The emerging technique of molecular imprinting and its future impact on biotechnology, Biotechnology, 14, 163–170. MOSIELLO, L., NENCINI, L., SEGRE, L. and SPANO, M. (1997). A fibre-optic immunosensor for 2,4–dichlorophenoxyacetic acid detection. Sensors and Actuators B – Chemical, 39 (1–3), 353–359. MOTHERWELL, W.B., BINGHAM, M. J. and SIX, Y. (2001). Recent progress in the design and synthesis of artificial enzymes, Tetrahedron, 57, 4663–4686. NEDELKOV, D., RASOOLY, A. and NELSON, R.W. (2000). Multitoxin biosensor-mass spectrometry analysis: a new approach for rapid, real-time, sensitive analysis of staphylococcal toxins in food, International J. of Food Microbiology, 60, 1–13. O’SULLIVAN, C.K. (2002). Aptasensors – the future of biosensors? Anal. Bioanal. Chem., 372, 44–48. PAEK, S.H. and SCHRAMM, W. (1997). Performance characteristics of a reversible immunosensor with a heterobifunctional enzyme conjugate as signal generator, Biotechnology and Bioengineering, 56, (2), 221–231. PEREZ, F.G., MASCINI, M., TOTHILL, I.E. and TURNER, A.P.F. (1998). Immunomagnetic separation with mediated FIA amperometric detection of viable E. coli O157. Anal. Chem., 70, 2380–2386. ¨ NING, M.J. (2001). ¨ TH, H. and SCHO POGHOSSIAN, A., YOSHINOBU, T., SIMONIS, A., ECKEN, H., LU Penicillin detection by means of field-effect based sensors: EnFET, capacitive EIS sensor or LAPS?, Sensors and Actuators B: Chemical, 78 (1–3), 237–242. ˜ O, P., BARRERO-MORENO, J.M. and PE´REZ-CONDE, M.C. (2000). Flow-through POLIDO-TOFIN fluoroimmunosensor for isoproturon determination in agricultural foodstuff: Evaluation of antibody immobilisation on solid support, Analytica Chimica Acta, 417, 85–94. ˜ O, P., BARRERO-MORENO, J.M. and PE´REZ-CONDE, M.C. (2001). Sol-gel glass POLIDO-TOFIN doped with isoproturon antibody as selective support for the development of a flow-through fluoroimmunosensor, Analytica Chimica Acta, 429, 337–345. SCHENA, M., HELLER, R.A., THERIAULT, T.P., KONRAD, K., LACHENMEIER, E. and DAVIS R. (1998). Micoarrays; biotechnology’s discovery platform for functional genomics, Trends Biotechnology, 16, 301–306. SELF, C.H. and WINGER, L.A. (2001). 2 Anti-complex and selective antibody immunometric assays for small molecules. In: The Immunoassay Handbook, 2nd edn (David Wild, ed.), Nature Publishing Group, pp. 229–239. SELVANAYAGAM, Z.E., NEUZIL, P., GOPALAKRISHNAKONE, P., SRIDHAR, U., SINGH, M. and HO, L.C. (2002). An ISFET-based immunosensor for the detection of -Bungarotoxin. Biosensors and Bioelectronics, 17, 821–826. SILVA, H., A.D.F.O. and ALVARES-RIBEIRO, L.M.B.C. (2002). Optimisation of a flow injection analysis system for tartaric acid determination in wines, Talanta, 58, 1311–1318. ´ DAL, P., DENG, A. and KOLA ´ Rˇ, V. (1999). Resonant mirror-based optical immunosensor: SKLA application for the measurement of atrazine in soil, Analytica Chimica Acta, 399, 29–36. ˚ ., MELLGREN, C. and BJORCK, L. (1995). Determination of sulfamethazine ¨, A STERNESJO residues in milk by a surface plasmon resonance-based biosensoassay, Anal. Biochem. 226, 175–181. SURUGIU, I., SVITEL, J., YE, L., HAUPT, K. and DANIELSSON, B. (2001). Flow injection capillary chemiluminescent ELISA using an imprinted polymer instead of the antibody, MOSBACH, K.

On-line immunochemical assays for contaminant analysis 39 Anal. Chem., 73, 4388–4392. (2001). Biosensors Developments and potential applications in the agricultural diagnosis sector, Computers and Electronics in Agriculture, 30, 205–218. TOTHILL, I.E. and TURNER, A.P.F. (1998). Biosensors: New developments and opportunities in the diagnosis of livestock diseases. Towards livestock disease diagnosis and control in the 21st century. International Atomic Energy Agency, 79–94. TOTHILL, I.E. and TURNER, A.P.F. (2003). Biosensors. In: Encyclopaedia of Food Sciences and Nutrition (2nd edn), Benjamin Caballero (Editor in Chief), Luiz Trugo and Paul Finglas (editors), Academic Press, ISBN: 0-12-227055-X. TOTHILL, I.E. and STEPHENS, S. (2001). Methods for environmental monitoring: biological methods. In: Analytical Methods for Environmental Monitoring, (Ahmad, R., Cartwright, C. and Taylor, F. eds), Prentice Hall, pp 224–258. VAN DER LENDE, T. (1994). Generation and applications of monoclonal antibodies for livestock production, Biotechnology Advance, 12, 71–87. TOTHILL, I.E.

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and RIGO, A. (1998). Continuous flow immunosensor for atrazine detection, Biosensors & Bioelectronics, 13 (1), 45–53. WILD, D. (2001). The Immunoassay Handbook, 2nd edn, Nature Publishing Group. WILMER, M., TRAU, D., RENNEBERG, R. and SPENER, F. (1997). Amperometric immunosensor for the detection of 2,4-dichlorophenoxyacetic acid in water. Anal. Lett., 30 (3), 515–525. WITTMANN, C. and SCHMID, R.D. (1997). Bioaffinity sensors for environmental monitoring. In: Handbook of Biosensors and Electronic Noses – Medicine, Food, and the Environment (E. Kress-Rogers, ed.) Boca Raton: CRC Press, pp. 333–349. WU, J., TRAGAS, C. LORD, H. and PAWLISZYN, J. (2002). Analysis of polar pesticides in water and wine samples by automated in-tube solid-phase microextraction coupled with high-performance liquid chromatography-mass spectrometry, Journal of Chromatography A, 975, 357–367. ´ DAL, P. (1999). Screen-printed amperometric immunosensor for ZERAVIK, J. and SKLA repeated use in the flow-through mode, Electroanalysis, 11 (12), 851–856.

3 Using bioassays in contaminant analysis L. A. P. Hoogenboom, State Institute for Quality Control of Agricultural Products (RIKILT), The Netherlands

3.1

Introduction

Since ancient history, humankind has relied on bioassays to determine the safety of food and environment. In medieval times, food tasters were employed to ensure that food was free of poisons. Miners used small birds to detect the possible presence of toxic gases in mining tunnels. With increasing knowledge about the responsible toxicants, improvements in analytical chemistry, combined with the need to reduce animal experiments, we now rely on chemical methods aimed at the detection of compounds by their physicochemical properties. The use of animal bioassays is more or less restricted to the testing of the safety of specific substances, thereby supported by in vitro models with mammalian and prokaryotic cells. However, even today, bioassays with mice and rats are still the only reliable way to detect paralytic and diuretic poisons in shellfish,1,2 and the neurotoxins produced by Clostridium botulinum.3 Fish assays are widely used for testing the quality of drinking water. However, despite the rapid improvements in analytical chemistry, at the same time we start to realize that these methods may no longer be sufficient to deal with the often very complex mixtures of chemicals or ever changing chemical structures of toxicants present as residues in our food chain. Furthermore, there is a strong need for rapid screening assays that can be used for extensive monitoring programmes. Bioassays with pro- or eukaryotic cells capable of detecting compounds based on their effects, offer a possible solution. For the detection of antibiotics in milk and meat, a number of different tests are used for the screening4,5 and in many cases, chemical identification of the responsible substances is no longer required. Recent advances in cell biology and in particular biotechnology have allowed the

Using bioassays in contaminant analysis 41 development of a new generation of bioassays, based on the possibilities to introduce specific properties and reporter genes into stable cellular systems. This chapter will describe this new generation of bioassays and demonstrate their advantages, especially when used in combination with sensitive analytical methods. This will be demonstrated by the experiences obtained with the socalled DR-CALUX assay, a bioassay used for the detection of dioxins. The inclusion of bioassays in modern test strategies will allow rapid screening and detection of new, possibly unknown, agonists and help to evaluate the possible health hazards involved with the presence of such compounds in the food chain.

3.2

The use of bioassays: the case of dioxins

3.2.1 Development of the DR-CALUX assay After the discovery of dioxins in the food chain, it became clear that it would be impossible to set up large monitoring programmes for this group of compounds. The major reason for this was the very expensive and laborious analytical procedure required to detect 17 different 2,3,7,8-chlorinated dibenzo-p-dioxins (PCDDs) or furans (PCDFs) at the pg/g level. This can only be achieved after extensive clean-up and by using a high resolution mass spectrometer. A set of socalled toxic equivalency factors (TEFs), ranging from 1 to 0.0001, has been developed in order to express the concentrations of each of the congeners into one figure, which represents the group as if it was only the most toxic congener 2,3,7,8-tetrachloro-dibenzo-p-dioxin (TCDD).6 Previously this was expressed as i-TEQ but during the last reevaluation of the TEFs in 1998 this was changed to WHO-TEQ or simply TEQ. Typical limits for food are the maximum residue limits of 0.75 to 3 pg TEQ/g fat set by the EU in 2002. Limits like these are required to ensure that consumers do not exceed the tolerable weekly intake (TWI) of 12 pg TEQ/kg body weight as set by the EU. It has become clear that many other substances like the planar non-ortho and mono-ortho PCBs and also some brominated polyaromatic hydrocarbons behave similar to dioxins and should be included in these limits. Actually dioxin-like PCBs are already included in the exposure limit (TWI), and will be included in the EU food limits in the near future. In response to the limited analytical capacity, bioassays with mammalian cells have been developed, initially based on the known effects of these compounds. Receptor assays have been developed based on the binding of dioxins to a specific receptor (Ah-receptor) in the cells. The so-called ERODassay measures the deethylation of ethoxy-resorufin by certain cytochrome P450 enzymes, following the binding of dioxins to the cytosolic Ah-receptor, the binding of the complex to specific sites (DREs) in the DNA and the increased transcription of the gene encoding for the enzyme. Assays based on this principle are used for determining the levels of dioxin-like compounds in environmental samples like sewage sludge7 and sediments.8 A major drawback of this system is the possible inhibition of the enzyme by many different compounds, including natural occurring substances. The specificity of the test

42


Fig. 3.1 Principle behind the CALUX bioassay for Ah-receptor agonists. Following binding of the agonist to the Ah-receptor, the complex will be transported to the nucleus and bind to a so-called dioxin responsive element, resulting in the increased transcription of the luciferase gene and production of luciferase. Following incubation this enzyme can subsequently be measured in cell lysates by a light producing reaction.

was therefore tremendously increased by the development of a cell-line which contains the reporter gene luciferase under control of a murine DRE.9, 10, 11 In response to dioxins, this H4IIE rat hepatoma cell-line will synthesize luciferase in a dose-dependent way, which can subsequently be quantified by an enzymatic light producing reaction (Fig. 3.1). Figure 3.2 presents a typical dose-response curve, showing an increased luciferase production at concentrations as low as 0.5 pM. Since the test can be performed in 96 well-plates, a response is obtained with less than 50 fg TCDD. In principle, the amount of dioxins can be quantified by comparison of the response in the test with the calibration curve for TCDD. Several other dioxin and PCB congeners have been tested and were shown to give a response that reflects the differences in the TEF values (Fig. 3.3). However, congeners with a low TEF value showed a relatively low response in the test. This is similary true for 1,2,3,7,8-PeCDD which TEF value was recently adjusted from 0.5 to 1, and which is often a relatively important contributor to the total dioxin content. As a result the test may underestimate the total TEQ content, if calculations were based on the calibration curve for TCDD. However, in general it is evident that the bioassay obeys the TEQ principle and that the result will reflect the total TEQ content of the sample.

3.2.2 Validation for milk fat Following the succesful development of the cells, a rapid clean-up procedure for fat samples was developed, based on the use of an acid silica column. Using

Using bioassays in contaminant analysis 43

Fig. 3.2 Dose-response curve for 2,3,7,8-tetrachloro-p-dibenzodioxin (TCDD) in the CALUX bioassay. The concentration (expressed as TCDD) can subsequently be determined by comparing the response obtained with a sample extract with the calibration curve.

Fig. 3.3 Comparison of the relative response of a number of dioxins and non-ortho (#126, 169) and mono-ortho (#105, 118 and 156) PCBs in the CALUX bioassay and the TEF values established by the WHO.6 Compounds were selected based on their relative importance (contribution to total TEQ levels) in food samples. A major difference between the WHO-TEF values and the i-TEF values used in previous studies is the increase of the TEF for 1,2,3,7,8-penta-PCDD from 0.5 to 1, which is not supported by the CALUX assay.

44


Table 3.1 Reproducibility of the CALUX assay with milk fat samples. Spiked samples were tested singly in three independent test series (adapted from 12) Sample number

1 2 3 4 5 6

GC/MS CALUX determined dioxin content* determined (pg/g) level series 1 series 2 series 3 Mean (pg i±SD TEQ/g)

CV (%)

(%)

1 3 6 9 12 15

97 4 54 10 27 11

80 110 75 83 78 87

0.0 3.5 6.9 7.1 12.3 14.6

1.0 3.2 4.6 7.2 8.1 11.8

1.3 3.2 2.1 8.3 7.8 12.8

0.8±0.7 3.3±0.2 4.5±2.4 7.5±0.7 9.4±2.5 13.1±1.4

Recovery

* CALUX determined levels were corrected for the blank sample being respectively 6.3, 2.0 and 3.5 pg/g fat for series 1, 2 and 3 respectively. In addition values were corrected for the difference between relative responses in the CALUX assay and i-TEF values.

dimethylsulphoxide as intermediate, the extracted dioxins are transfered to the tissue culture medium and subsequently added to the cells. After exposure for 24 hours the luciferase concentration in the cells is determined. The test was validated for milk fat using a number of samples spiked at 1 to 15 pg i-TEQ/g fat (1.2–17.5 pg WHO-TEQ/g) with a mix containing the 17 congeners at equal amounts.12 Table 3.1 shows the reproducibility obtained in three independent tests with these samples. Concentrations were calculated based on the TCDD calibration curve, and subsequently corrected for the 15% difference between CALUX and i-TEF values. The calculated limit of detection was around 1 pg iTEQ/g fat, explaining the high variation obtained with the lowest sample. When calculated in i-TEFs, the recovery varied between 70% and 103%. These results demonstrate the suitability of the test to screen milk fat samples. Another important conclusion from these studies was the need to include reference samples with levels around 0 and the residue limit, in order to control for possible impurities introduced with the chemicals, recovery losses and differences in TEF values. Based on this approach, dioxin-like compounds were measured in oil obtained from a large number of different fish and shellfish products. Levels up to 100 pg i-TEQ were detected but based on general agreements these should be corrected for the sometimes very low oil levels in, for example, shellfish. As shown in Fig. 3.4, a good correlation was obtained with the combined dioxin and non-ortho PCB contents in these oils, although in a few cases relatively large differences were observed. Although this might be caused by high levels of mono-ortho PCBs (not included in GC/MS measurements), it cannot be excluded that other compounds are responsible for this effect.

Using bioassays in contaminant analysis 45

Fig. 3.4 Comparison of CALUX determined dioxin levels and combined GC/MS determined levels of dioxins and non-ortho PCBs (77, 126 and 169) in fish and shellfish oil. Since oil levels vary widely in these samples, dioxin levels are normally expressed on a pg/g product base.

3.2.3 Citrus pulp incident Following the succesful validation of the test for milk fat, the bioassay was first used in the food and feed area during the Brazilian citrus pulp incident. Increasing milk levels in German cows were traced back to the use of citrus pulp that had been mixed with contaminated lime. Pulp samples of 5 g were extracted and cleaned by the same procedure as used for the milk fat. A rapid comparison between CALUX and GC/MS data showed that the assay was capable of selecting the highly contaminated samples, using a cut-off value of 5000 pg iTEQ/kg. Most samples contained levels higher than this limit and required GC/ MS confirmation. At the end of the crisis the limit was officially set at 500 pg iTEQ/kg, based on the detection limit of the GC/MS method. The test procedure was subsequently optimized and validated. Based on the consideration that an increased response is not necessarily caused by dioxins or dioxin-like PCBs, and that samples with an increased response would still have to be confirmed by GC/ MS, it was decided to switch to a screening approach. This approach is based on the comparison of the response obtained with test sample with that of a reference sample, containing 400 pg i-TEQ/kg. Table 3.2 shows the results obtained with 71 citrus pulp samples containing GC/MS determined levels between 50% >20–50% >10–20% 0.991), was obtained for all the assays performed in the linear range between 4 and 125 ng/mL of OA. Figure 7.5 reports results typical of such assays. The repeated measurement of each OA standard was somewhat hampered by the time necessary to measure each electrode. This could be overcome by using a multi-electrode potentiostat, which can limit the errors involved with each point. Another important aspect of these OA-SPEs was the detection limit. This parameter was again determined by several measurements and yielded a value between 1 and 4 ng/mL OA. This was in the range of nanomolar quantities of OA (1.24 109 mol/L) and when compared to fluorimetric assays showed more sensitive results with no need for prior derivatisation.36 The recoveries of OA from spiked mussel samples were studied using the OA immunosensor. Once the calibration curves had been determined, dilutions of organic solvent from the extraction procedure containing the toxins were prepared in such a manner that they would fall within the range of the calibration curve. Blank extracts were also prepared where zero toxin concentration should be present. These blanks would be indicative of the matrix effect resulting from the mussel tissue as well as fats also in the organic solvent used for the extraction. The recovery percentage using screen-printed electrodes for real samples yielded values generally ±10 per cent of the true value. Assays were generally completed in 60 minutes and measurements within five minutes. The incubation period could also be shortened to approximately 30 minutes, thus making the overall procedure no longer than 35 minutes.

The rapid detection of toxins in food: the case study

Fig. 7.5

7.5

125

Typical competitive immunoassay for okadaic acid using SPEs with amperometric detection at + 300 mV vs Ag/AgCl.

Detecting toxins: saxitoxin

Saxitoxin is one of the most lethal non-protein toxins known (LD50 9 g/kg37) and is one of the paralytic shellfish poisons (PSP) produced by several marine dinoflagellates and freshwater algae. Contamination of shellfish with saxitoxin has been associated with harmful algal blooms throughout the world. In humans, paralytic shellfish poisoning causes dose-dependent perioral numbness or tingling sensations and progressive muscular paralysis, which may result in death through respiratory arrest.38 The Food and Drug Administration has determined a maximum acceptable level for paralytic poison in fresh, frozen or tinned shellfish of up to 400 mouse units (MU) or about 40–80 g/100 g edible portion.13 This value is equivalent to twice the minimum detection level of the mouse bioassay, the first and still most common PSP toxin testing method, which is also the official AOAC method.39

7.5.1 Analytical methods The Mouse Bioassay (MBA) is the official method for the determination of PSP in seafood, but this is neither specific nor sensitive; it requires a continuous supply of mice and results are affected by test conditions such as animal strain and sample extract preparation. Other methods include fluorimetric assay40 and liquid chromatography.41,42 The latter requires expensive equipment for pre41 or

126


post column42 analyte oxidation. Additionally, samples must be analysed one at a time, and so the method is unsuitable for routine on-site testing. Immunochemical methods have advantages in terms of both sensitivity and speed, and are therefore of increasing importance in food control as rapid screening tests. Because of the highly specific antigen–antibody interaction, several laboratories have attempted to develop an immunoassay for PSP.43,44 In the following section the optimisation and comparison of spectrophotometric and electrochemical competitive ELISA formats (direct and indirect) for the detection of saxitoxin (STX) are reported. Spectrophotometric study The tests were performed in a 96-well microplate using toxin-specific polyclonal antibodies produced in our laboratory.45 The antibodies were obtained from rabbits immunised with saxitoxin-keyhole limpet hemocyanin (STX-KLH). In indirect ELISA format saxitoxin, conjugated to bovine serum albumin (BSASTX), was coated onto the microtitre plate and incubated with standard toxin and anti-STX antibody. A goat anti-rabbit IgG peroxidase conjugate (IgG-HRP) was used to enable the detection. In the direct ELISA format, STX standard, STX conjugate to horseradish peroxidase (STX-HRP) and the enzyme substrate/ chromogen solutions were sequentially added to the microplate after antibody coating. The operative range was calculated using equation (7.1). The detection limit was 3 and 10 g/mL for direct and indirect ELISA formats, respectively (Figs 7.6 and 7.7). In both tests, the linear regression showed a range of 5 10ÿ3 to 4 10ÿ1 ng/mL (top right insert, Figs 7.6 and 7.7).

Fig. 7.6 Direct competitive ELISA for saxitoxin. Antibody against saxitoxin (10 g/ mL) was coated on the ELISA plate and STX-HRP (1:30) was used as competitor.


127

Fig. 7.7 Indirect competitive ELISA for saxitoxin. BSA-STX (3 g/mL) was coated on the ELISA plate.

The stability of the coating reagents was evaluated using microplates coated with conjugated antigen or antibody, blocked and then stored at 4ºC. Assays were performed periodically using assessed protocols. Results showed that the plates coated with the antibodies (direct test) could be used up to three weeks after the coating step, while the antigen immobilised on the wells was stable for only 24 h (indirect test). The superior results obtained from the direct format could therefore be due to this higher antibody stability. The suitability of the assay for saxitoxin quantification in mussels was also studied. Sample extraction was carried out according to the AOAC method.13 Samples were spiked with saxitoxin before and after sample treatment to study the extraction efficiency and the matrix effect, respectively. After treatment, samples were analysed at 1:1000 v/v dilution in PBS to minimise the matrix effect and to detect the established limit of 40 g of saxitoxin in 100 g of mussels. The saxitoxin extraction efficiency was from 72 to 102 per cent (see equation 7.2). Repeatability and accuracy of ELISA assays were evaluated by means of six replicates of tissue. Blank controls fortified with saxitoxin at a concentration equal to twice (0.8 /g), half (0.2 g/g) and regulatory limit (0.4 g/g), were prepared and extracted on three days for each concentration (n 18). The precision was calculated by the relative standard deviation (RSD%) for the replicate measurements and the accuracy (relative error, RE%) was calculated by assessing the agreement between measured and nominal concentrations of the fortified samples. Results were confirmed by the analysis of the same extracts using a previously validated LC method.42 Values reported

128


Table 7.1 Precision (RSD) and accuracy (RE%) for saxitoxin in mussel, determined by ELISA and LC (n 18) (a) Results with ELISA method STX added g/g

STX found g/g

RSD

0.20 0.40 0.80

0.19 0.43 0.83

4 1 3

RE% 3 7 4

(b) Results with LC method STX added g/g

STX found g/g

RSD

RE%

0.20 0.40 0.80

0.18 0.42 0.88

4 5 5

ÿ10 5 8

(c) Comparison of ELISA and LC methods STX added g/g

Direct ELISA/LC RE (%)

0.20 0.40 0.80

6 2 ÿ6

in Table 7.1, together with the accuracy of the spectrophotometric ELISA versus LC, showed a good agreement. In conclusion, ELISA assays were shown to be suitable screening tools for routine analysis of saxitoxin in mussels. In fact, compared to the LC method, spectrophotometric direct ELISA showed similar precision but better accuracy and speed, and at a lower cost. Additionally, this method does not require sample purification. SPE immunoassay The electrochemical enzyme immunoassay for STX has been performed using the carbon working electrode of the disposable sensors as solid phase for reagent immobilisation and as signal transducer. In a first phase, the spectrophotometric ELISA protocols were applied, but the results were unsatisfactory. In order to obtain the best signal-to-noise ratio and the highest sensitivity, several trials were performed for each test to optimise the analytical parameters, and all tests were repeated several times in order to confirm the data obtained. This immunosensor was employed in a direct competitive assay involving STX labelled with antibody. The enzyme substrate used was 3,30 ,5,50 -tetra-


129

Fig. 7.8 Competitive curve with direct test for saxitoxin using SPEs.

methylbenzidine (TMB) plus hydrogen peroxide and the product of the reaction was detected by chronoamperometry at ÿ100 mV for 60 s. The calibration curve for STX was measured in the concentration range 0–103 ng/mL and the results showed a sensitivity in the range 1–103 ng/mL of the toxin (Fig. 7.8). STX levels determined by the proposed electrochemical immunoassay compared favourably with a spectrophotometric method.

7.6

Developing on-line applications

Miniaturisation is a growing trend in the field of analytical chemistry. Electrochemistry is particularly attractive for microscale analysis as its instrumentation can be miniaturised and multiplexed without compromising its capabilities. The portable nature and low power demands of electrochemical analysers46 satisfy many of the requirements for on-site and in-situ measurements. Modern microfabrication technologies allow us to replace the traditional electrodes and cumbersome cells with easy-to-use miniaturised electrochemical systems. A small portable and easy to use instrument (calculator size, microprocessor controlled with LCD display) was constructed for toxin measurement with disposable strips. This system was provided with one site for disposable strip connection. A battery applies a selected potential to the electrodes screen printed onto the strip, and the current due to the reaction occurring on the strip is recorded and displayed as the concentration of toxin measured. The instrument will be provided with a self-calibration to make it easy to use for unskilled personnel. This small instrument is able to perform DPV and chronoampero-

130


Fig. 7.9

(a) DPV peaks obtained with the portable instrument prototype.; (b) DPV peaks obtained with AUTOLAB instrument equipped with GPES software

metric measurements in an interval range between ÿ1000–1000 mV, useful for the determination of 1–naphthol, as example, of enzymatic products, which is the product of the reaction of AP with 1–naphthyl phosphate. A calibration curve was obtained for 1-naphtol at different concentrations (0– 1 mM). The peaks obtained for each concentration were compared with the results attained with AUTOLAB and AMEL instruments (Fig. 7.9). An excellent agreement was observed among all results (the difference in current observed with the AMEL instrument is due to its software, which multiplies ten times the current when compared to the other instruments). Indirect competitive tests have been performed using the SPE’s working electrode also as solid phase for the immobilisation of the reagents. The same experiments were also carried out using the AUTOLAB instrument and the results obtained with the two instruments were comparable (Fig. 7.10).


131

Fig. 7.9 (c) DPV peaks obtained with AMEL instrument (mod. 433). This instrument multiplied the current values by 10 automatically.

Fig. 7.10 Competitive curve for DA with indirect test using SPE; DPV detection between 0–600 mV; portable prototype (•) and AUTOLAB (▲) instruments; AP as label.

132


7.7

Conclusions

This chapter reports the development of novel procedures based on cost effective electrochemical instrumentation for the detection of selected seafood toxins by the use of monoclonal and polyclonal antibodies, electrode strips and a portable instrument. The work has been carried out with a selection of the most common seafood toxins and the production of specific polyclonal and monoclonal antibodies. Biosensor development has been initiated and carried on in parallel with the setting up and comparison of ELISA procedures with spectrophotometric and then finally with electrochemical detection. The development of a procedure for measuring toxins with disposable strips was carried out first using bench electrochemical instrumentation, then a portable prototype constructed by the industrial partner. Validation of disposable strips using established reference procedures and the portable electrochemical instrument has been carried out. This research has successfully achieved the primary objective: detection of seafood toxins by use of disposable strips.

7.8

Acknowledgements

This work was supported by the EC project CT 96 FAIR 1092 and by the European Concerted Action QLK3-200-01311 ‘Evaluation/Valuation of Novel Biosensors in Real Environmental and Food Samples’.

7.9 1.

References PALLESCHI G,

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and SCHMITZ F J, ‘Okadaic acid, a cytotoxin polyether from two marine sponges of the genus Halichondria’, J Am Chem Soc, 1981 103 2469–2471. SHIBATA S, ISHIDA Y, KITANO H, OHIZUMI Y, HABON J, TSUKITANI Y and KIKUCHI H, ‘Contractile effects of okadaic acid, a novel ionophore-like substance from black sponge, on isolated muscles under the condition of Ca deficiency’, J Pharmacol Exp Ther, 1982 223 135–143. COHEN P, HOLMES C F B and TSUKITANI Y, ‘Okadaic acid: a new probe for the study of cellular regulation’, TIS, 1990 15 98–102. SAKAI A and FUJIKI H, ‘Promotion of BALB/3T3 cell transformation by the okadaic acid class of tumor promoters, okadaic and dinophysistoxin-1’, Jpn J Cancer Res, 1991 82 518–523. GOPICHAND Y

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and KELLY S S, ‘Isolation of a new okadaic acid analogue from phytoplankton implicated in diarrhetic shellfish poisoning’, J Chromatogr A, 1998 798(1/2) 137– 145. BROWER D J, HART R J, MATTHEWS P A and HOWDEN M E H, ‘Non protein neurotoxins’, Clin Toxicol, 1981 18 813–865. USLEBER E, SHNEIDER E, TERPLAAN G and LAYCOCK M V, ‘Two formats of enzyme immunoassay for the detection of saxitoxin and other paralytic shellfish poisoning toxins’, Food Addit Contam, 1995 12(3) 405–413. GAZZETTA UFFICIALE DELLA REPUBBLICA ITALIANA (8–9–1990), serie generale no. 218. BATES HA and RAPOPORT H, ‘A chemical assay for saxitoxin, the paralytical shellfish poison’, J Agr Food Chem, 1975 23(2) 237–239. LAWRENCE J F and MENARD C, ‘Liquid chromatographic determination of paralytic shellfish poisons in shellfish after prechromatographic oxidation’, J Assoc Off Anal Chem, 1991 74(6) 1006–1012. OSHIMA Y, ‘Postcolumn derivatisation liquid chromatographic method for paralytic shellfish toxins’, J AOAC Int, 1995 78(2) 528–532. CHU F S and FAN T L, ‘Indirect enzyme-linked immunosorbent assay for saxitoxin in shellfish’, J Assoc Off Anal Chem, 1985 68(1) 13–16. M

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8 Rapid detection methods for microbial contamination I. E. Tothill and N. Magan, Cranfield University, UK

8.1

Introduction

Today, quality assurance systems (QA) based on Hazard Analysis Critical Control Point (HACCP) principles are preferred to quality control systems (QC) which require careful monitoring and the withholding of contaminated material from the market place. Thus the rapid detection of spoilage microorganisms in the food production and processing chain is critical regardless of the system being used or implemented. There are however, different levels of detection, which may be required from a simple yes/no to quantitative data to meet legislative requirements. Thus there is a need for commercial instrumentation which is rapid but relatively inexpensive for the detection of microbial contaminants of food products. A range of methods has been developed relying on the biochemical and physical properties of micoorganisms. Conventional methods of microbial detection used in the food industry have a number of drawbacks including being labour intensive, time-consuming and sometimes expensive. Furthermore, within a HACCP framework corrective actions require real-time analyses. Figure 8.1 compares the time required for carrying out a range of tests and the time required obtaining a result. This shows clearly the difference between techniques, which can have a significant impact on the responsiveness within a QA system. This chapter will describe the range of conventional and new and novel technologies available and being developed for assessing microbial quality of food.

8.2

Conventional methods

Classical microbiological methods are usually based on several steps: isolation; identification and then if necessary colony forming unit counting and rely

Rapid detection methods for microbial contamination

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Fig. 8.1 Comparison of the time required to carry out and the time to obtain a result for different types of tests. Arrow indicates the time for a test and time for a result which is needed today.

mainly on specific microbiological and biochemical markers. These methods take a long time to complete and need a skilled operator to interpret the results, but they are sensitive and inexpensive and give both qualitative and quantitative information. Since the occurrence of pathogens in food is usually at very low numbers, an initial enrichment step is needed to detect the contaminating microorganisms. The simple method used for biomass estimation is the dry weight method. Dry weight is widely used for the assessment of biomass in fermentation culture samples. By removing the required volume, the cells are washed free of the media components and dried to constant weight by heating in an oven at 105ºC, cooled and weighted. This method can only be applied to liquid samples that do not contain suspended solid. Other methods such as the viable count method (motility test) are used to estimate microbial populations. This method relies on the growth of the cells in either liquid culture medium, on an agar media or on membrane filters. Serial dilution of the sample is usually carried out before spreading the sample on the plate or filtering through the membrane. The method requires the plates or cultures to be incubated at an appropriate growth temperature for between 12–72 hours depending on the type of microorganisms being analysed. The number of colonies is counted and this calculated as a colony-forming unit (cfu mlÿ1) obtained in the original sample. The disadvantages of this method is the long incubation time required before the results can be achieved, which is hazardous in food testing since the foods may have already been displayed to the consumer. Standard methods such as the NF EN ISO 11290-1 for Listeria monocytogenes

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Fig. 8.2

(a) The HYCONÕ Dip Slide and (b) the HYCONÕ Contact Slides (Courtesy of Biotest Diagnostics Corporation, USA).

detection may require 7 days for visible colonies to be identified (Artault et al., 2001). Several products are on the market such as the HYCONÕ Dip Slides and the Contact Slides (Fig. 8.2) marketed by Biotest (New Jersey, USA). The HYCONÕ dip slides are used to monitor microbial contamination in liquid samples and contain different microbiological media on each side. This can either be dipped in the sample or streaked. The contact slides, which also contain selective growth media, are used for the detection of contamination on surfaces by bacteria, yeast and moulds. These tests require an incubation time between 2– 3 days. The use of highly porous cellulose acetate membrane filters (0.45 m) has also been implemented in microbial detection. Membranes that allow the passage of large volume of liquid sample but prevent the passage of bacteria or fungi have been used. Microorganisms retained on the membrane are incubated on a specific agar medium and the appropriate room temperature. The number of colonies is subsequently counted on the filter. The main advantage of this method is the large sample volume that can be applied on these types of filters. Turbidity is also widely used for the estimation of cells in suspensions by using a spectrophotometer. The ability of microbial cells to scatter lights and hence appear turbid in a solution is utilised in this technique to measure the concentration of the cells. The scattered light of a microbial suspension is proportional to the number of cells present. Measurements are usually carried out at 600 nm of bacterial analysis using a spectrophotometer. A standard calibration curve of log Io/I against either the total count or the dry weight is used (Singh et al., 1994). The calibration curve applies only to a particular microorganism grown under a particular set of growth conditions. But this


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technique is unable to differentiate between viable and non-viable cells. Park and co-workers (1995) used spectrofluorometric assay to detect total and faecal Coliforms in water samples. Microscopy is also an important technique in the diagnosis of microorganisms, since it allows the view of the cells under the microscope. The most important stain procedure in microbiology is the Gram stain. Using this method bacterial cell morphology and Gram reaction may be examined via the use of Gram stain microscopy, which provide the information of whether the organism is a gram negative or gram positive based on the differences in bacterial cell walls. Gram staining is a rapid procedure that can be performed in minutes. Further details on the methods are given in Dart (1996).

8.3 Specialised techniques: epifluorescence (DEFT), bioluminescence and particle counting 8.3.1 Epifluorescence technique Fluorescent microscopy is a very rapid method for microbial enumeration and it does not require an incubation step. The direct epifluorescence filter method (DEFT) has been developed for microbial contamination detection in milk and other dairy products (Pettifer et al., 1980). The principle of the method is similar to membrane filtration and takes about 25 min to complete. The method involves the re-treatment of the sample with the enzyme trypsin and detergent (Triton X100) to break down the somatic cells and fat globule content of the milk, enabling it to be filtered through a polycarbonate membrane, retaining the bacteria present in the sample. The fluorochrome (acridine orange or diamidino2-phenylindole) is added to the filtered sample for a contact time of a few minutes and then filtered through a polycarbonate membrane. The membrane is rinsed with the same sample volume of distilled water and the microorganisms are counted using epifluorescence microscopy. Under UV light, acridine orange stains deoxyribonucleic acid (DNA) green and ribonucleic acid (RNA) orange. This method can distinguish between active from inactive microorganisms based on their higher RNA content (Allen, 1990). Systems such as the Bactoscan Automated Microbiology System (Foss Electric, Hillerød, Denmark) has been developed for the detection of bacteria in food and drink samples. This device is rapid, with an estimated 60 to 70 samples undertaken every hour. The MicroFoss is a user-friendly instrument and has been used especially in dairy and meat segments and gives rapid microbiological analysis based on microorganisms growth, pH change and dye indication. The products also include ready-to-use vials for enumeration of Total Viable Count, Enterobacteriaceae, Coliform, generic E. coli, and Yeast. The MicroFoss showed the ability to detect counts as low as 0.5 cfu mlÿ1 in milk. The use of the fluorescent indicators can discriminate between viable from non-viable cells (Matsunaga et al., 1995). Antibodies conjugated to fluorochrome such as fluorescein iosthiocyanate has been used for microbial detection. By applying tagged antibody for the

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target microorganism to the sample, the micoorganism will fluoresce due to the complex forming with its complementary tagged antibody. The number of fluorescing cells is then counted using an epifluorescence microscope. This method has had wider applications in the field of on-line estimation of fermenter biomass (Armiger et al., 1984). Nakamura et al. (1993) coupled E. coli separation using magnetic particles with detection by flourescein isothiocianate.

8.3.2 Bioluminescence Bioluminescence test based on adenosine 5’ triphosphate (ATP) is a rapid and sensitive method used for microbial detection. ATP is the energy molecule for all living cells (animal, vegetable, bacteria, yeast and mould cells). The measurement is based on the use of the firefly enzyme luciferase: Luciferase

Luciferin ATP O2 ÿÿÿÿ! Oxyluciferin AMP CO2 PPi Photon Light is produced depending on the concentration of ATP in the sample, which can be interpreted to the microbial content. Several instruments have been developed based on this principle for the estimation of microbial biomass and also as cleanliness and hygiene testing. The Clean-TraceTM products such as the Biotrace Uni-LiteÕ and Uni-LiteÕ XCEL instruments (Biotrace Ltd., Bridgend, UK) are instruments using the above principle. Other companies such as Celsis International plc (Suffolk, UK) and Biotest (New Jersey, USA) also market instruments based on this technology. ATP Instruments can usually detect low levels of contamination (103 cells mlÿ1) and are used for testing in food production plants and dairies. When testing milk samples, the samples need to be pre-treated to remove non-bacterial ATP present in somatic cells before the analysis can be carried out for microbial contamination in milk. Tests may take between 10ÿ20 minutes depending on the procedure to be implemented in the tests. Stanley (1992) has reviewed commercially available luminometers.

8.3.3 Particle counting Coulter counters are also used for microorganisms counting mainly algae and yeast. The principle of the technique is based on passing a suspension of cells through a small aperture separating two electrodes between which an electric current flows (sensing zone). The pulse generated by each cell is amplified and recorded electronically, giving a count of the number of cells flowing through the aperture. The Coulter method of sizing and counting particles is based on measurable changes in electrical impedance produced by nonconductive particles suspended in an electrolyte. In this case cells can be counted in the medium in which they are growing. A range of products are commercially available such as the COULTER COUNTERÕ Z1 Series, (Coulter International Corporation, Miami USA ), and MultisizerTM 3 Coulter CounterÕ (Beckman Coulter, UK). CellFacts I, developed and manufactured by CellFacts Instruments Ltd, UK, also uses electrical flow-impedance determination to


Fig. 8.3

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CellFacts I (Courtesy of CellFacts Instruments Ltd, UK).

count and size particles in a sample (Gentelet et al., 2001). The analysing principle of CellFacts I is it counts and sizes every particle in a sample introduced to the instrument and provides detailed information on the microbiological status of that sample with applications in microbiological research and the food, biotechnology, water, cosmetics, and pharmaceutical industries. Its most powerful applications are in on-line monitoring of fermentation processes and cell cultures (Fig. 8.3). Devices based on acoustic resonance densitometry have been reported by Clarke et al. (1985), which could provide effective real-time and in situ determination of biomass in fermentation and downstream processes. The technique is based on the change in the acoustic resonance of a fixed volume of fermenter culture during the fermentation period due to the microbial growth.

8.4 Specialised techniques: flow cytometry, electron microscopy and immunoassay techniques 8.4.1 Flow cytometry Flow cytometry is a powerful technique that allows the user to measure several parameters in a sample and it is one of the most reviewed methods for bacterial detection (Jepras et al., 1995, Attfield et al., 1999). Parameters such as physical characteristics as cell size, shape and internal complexity can be examined. The principle behind the technique is that a thin stream of fluid containing the cells of interest is passed through a laser beam. Biomass is analysed by light scattering methods and by staining of chemical components such as DNA. The light energy is converted into an electrical signal by the use of photomultiplier tubes (Okada et al., 2000). Gunasekera et al. (2000, 2002), used flow cytometry for analysing the microbiological states of milk and dairy products.

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8.4.2 Electron microscopy The use of a scanning electron microscope for counting bacteria on membrane filters has been reported (Borsheim et al., 1990). However, this technique suffers from the high cost of the instrumentation and operator skills required.

8.4.3 Immunoassay techniques Immunodetection with antibodies has been successfully employed for the detection of microbial cells, viruses and spores (Iqbal et al., 2000) Antibodies can be easily produced for a range of microorganisms. Immunoassay techniques have been developed for microbial detection using different labels to generate the signal. Radioisotopes were the first to be used, but enzymes became more attractive due to cost and environmental issues. Lateral flow immunoassay tests such as the RapidChekTM for E. coli O157 marketed by SDI (Strategic Diagnostics Inc. Hampshire, UK) can detect one cell in 25 grams and has been approved by the AOAC RI for applications in ground beef, boneless beef, and apple cider (Fig. 8.4). The test has also been validated on carcass swabs and poultry and is available for an 8 hour enrichment time and 10 min test time. A RapidChekTM for Salmonella is also marketed by the SDI, with 24 hour enrichment time (10 min test time). ClearviewTM and REVEALÕ are a range of products marketed by Oxoid (Basingstoke, UK) and Adgen Ltd. (Ayr, UK) respectively for the detection of E. coli O157, Salmonella and also Listeria based on the same principle used by SDI. Tests for Campylobacter are also available on the market. Most of these tests are based on isolation and enumeration of the bacteria before detection. The reason being that concentration of these bacteria in food (raw vegetables, milk, soft cheese and ready prepared food) are usually very low to be detected directly by the common

Fig. 8.4

RapidChekTM (Courtesy of Strategic Diagnostics Inc. Hampshire, UK).


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plating techniques and it needs to be isolated and allowed to multiply to the detectable level (Scott, 1998). Enzyme-linked immunosorbent assay (ELISA) tests have been used for the detection of microbial infections in veterinary diseases, with detection limit in the range of 103 cells mlÿ1. ELISA tests for microbial detection in food samples are also marketed by several companies (e.g. Syva laboratories, S.A.; SDI; BioMe´rieux’s; Adgen). A range of test formats has also been developed such as the immobilisation of the antibody on a bead solid support. The beads are paramagnetic and can be separated from the food sample easily in a magnetic field. This separation step will remove the target contaminated microorganism for the food sample. The beads can be washed and either used to detect the microorganism following the Elisa procedure (Bennett et al., 1996) which takes 2 hours for the test or re-suspended and transferred to a selective agar plate, streaked and cultured, if the concentration is low for ELISA detection. Results in this case can be obtained in 24–48 h. The use of the paramagnetic beads have been applied for the detection of Salmonella (Cudjoe et al., 1995), E. coli 0157 (Cubbon et al., 1996) and Listeria in food samples. Immunoassay tests can take up to 2 hours to achieve the results, therefore it is not a ‘real-time’ procedure. However, complete assay automation can be carried out using the range of equipment available on the market for this application. Also the advances in recombinant antibodies and the emergence of phage-displayed peptide receptors (Goldman et al., 2000; Benhar et al., 2001; Goodridge and Griffiths, 2002) and their application in pathogens detection offer increasing possibility for rapid methods development.

8.5 Cellular components detection: API, metabolising enzymes and nucleic acids Methods of biomass estimation by measuring the concentration of a biochemical component of the target microorgansm are reported in the literature. However, the presence of these compounds needs to be detected with the appropriate precision if they are to be used for microbial estimation. A range of compounds such as lipids and their derivatives (Singh et al., 1994), cell carbon/phosphate (Galnous and Kapoulos, 1966) and total nitrogen/proteins (Garg and Neelkantan, 1982) have all been used for microbial quantitation. Some of these methods are dependent on the physiology of the cells and therefore their validity may be questionable. In this section the more applied methods will be covered in detail.

8.5.1 API The API test kits are the best known biochemical tests for microbial identification. API tests marketed by BioMerieux Inc (France) usually contain about 20 miniature biochemical tests, which may detect all bacterial groups and 550 species. The procedure involves the inoculation of each of the 20 mini test

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tubes with a saline suspension of a pure culture. The samples are then incubated for 18–24 hours before the colour change is read. An API system based on enzyme detection (Rapidec) is also marketed by BioMerieux Inc. The test is followed either by a colour change directly or following the addition of appropriate reagents (Batchelor, 1995).

8.5.2 Metabolising enzymes Specific enzymes have been used as indicator for the presence of specific microorganisms. For example total coliforms and E. coli contain the enzyme aˆgalactosidase which can be used as an indicator to their presence. E. coli also contain the enzyme glucuronidase, which is used to indicate the presence of E. coli in the samples. Different companies have implemented the analysis of these two enzymes to develop products for microbial detection. Palintest Ltd. (Tyne and Wear, UK) has produced the Colilert test, which is a colorimetric test based on the detection of these enzymes through their interaction with the substrate. The tests are capable of detecting 1 CFU 100 mlÿ1 in 24 hours of incubation (Hobson et al., 1996). The enzymes catalase and oxidase have also been used to analyse for bacterial contamination.

8.5.3 Nucleic acids The building blocks (nucleic acids) of DNA and RNA are present in all living cells and may be used as a general indicator of microbial biomass. The principle of the tests is based on the hybridisation of a characterised nucleic acid probe to a specific nucleic acid sequence in a test sample followed by the detection of the paired hybrid. The use of the polymerase chain reaction (PCR) has been frequently applied for microbial detection to enhance the sensitivity of nucleic acid-based method (Baker et al., 2003; Cook, 2003). The technique has been used for qualitative analysis, but quantitative measurements are important in food analysis and methods have been developed to make the test quantitative. The use of fluorometry for PCR product analysis has been implemented for rapid and sensitive tests. Quantitative PCR methods are shown to be very sensitive with a detection limit of 10 cells mlÿ1 and an analysis time of approximately 3 h has been reported (Paton et al., 1993). PCR methods have been used to detect viruses (Traore et al., 1998), bacteria (Fach and Popoff, 1997) and protozoa (Stinear et al., 1996) in food and water samples. However, these methods can be expensive, time consuming, require skilled workers and sometimes complicated. The GEN-PROBE hybridisation protection assay (HPA) technique uses a specific DNA probe, labelled with an acridinium ester detector molecule that emits a chemiluminescent signal. Two methods which have used this technology successfully are the AccuProbeÕ and the FlashTrak (Gen-Probe Incorporated, San Diego, USA). In these systems the DNA probe is targeted against the ribosomal RNA of the target organism. The nucleic acids are then hybridised to


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form a stable molecule. The chemiluminescence is then measured by the genprobe luminometer (Thomson, 2001). This method has been developed for Fungi and bacterial detection and takes 5 hours to achieve the results with 92– 100% sensitivity and specificity. Molecular Devices Corporation (Sunnyvale, USA), have developed products for total DNA assay which can be applied for microbial detection. DNA array marketed by Affymetrix (Santa Clara, USA), such as the GeneChip E. coli Antisense Genome Array is used for examining expression of all known E. coli genes. The GeneChip Yeast Genome S98 Array contains probe sets for approximately 6,400 S. cerevisiae (S288C strain) genes identified in the Saccharomyces Genome Database. The GeneChip technology can be used mainly for the broad spectrum of nucleic acid analysis applications including sequence analysis, genotyping and gene expression monitoring. Other companies such as MediGenomix GmbH (Germany) is also expanding into DNA-analysis for veterinary and food testing.

8.6 Electrochemical methods: impedimetry, conductivity and other methods Electrochemical methods have been developed for microbial detection (Paddle, 1996). The most reported techniques for food analysis will only be covered in this section.

8.6.1 Impedimetry and conductivity Changes to the ionic conductivity of the culture medium due to microbial growth have been used to measure microbial content (Richards et al., 1978; Colquhoun et al., 1995). Impedance measurements have been utilised in the development of microbial devices. The Bactometer marketed by BioMe´rieux (BioMerieux Inc., Marcy-’Etoile, France) (Fig. 8.5) is one of these instruments based on proven impedance technology. It provides a rapid and cost effective system for the detection of spoiled raw materials. It offers quantitative and qualitative tests including total counts of enterobacteriaceae, coliforms, yeast and mould. The Malthus system (Malthus Instruments Ltd, Bury, UK), is also based on the detection of microorganisms by measuring the changes in the flow of an electric current passing through a medium. This system can detect a range of microorganisms such as Coliforms, Salmonella, Yeast and Mould in foods.

8.6.2 Fuel cell technology The technology is based on the direct conversion of chemical to electrical energy (Hobson, 1996). The fuel cell device uses an anode, a cathode and a supporting electrolyte medium to connect the two electrodes, and an external circuit to utilise the electricity. The use of microorganisms for the generation of electric

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Fig. 8.5

BactometerÕ (Courtesy of BioMe´rieux INDUSTRY, Missouri, USA).

currents has been reported to be enhanced by the incorporation of traces of potassium ferricyanide or benzoquinone in the solution (Davis, 1963). Devices based on the use of mediated systems (Benjamin et al., 1979) and non-mediated systems (Matsunaga et al., 1980) have been used for monitoring microbial growth. The analytical sensitivity of the fuel cell method has been increased by the use of the mediator phenosine ethosulphate for the detection of E. coli (detection limit of 4 106 cells mlÿ1) in 30 minutes assay time (Turner et al., 1983).

8.6.3 Amperometry Amperometric techniques have also been applied to the measurement of microbial biomass and the detection system is based upon the measurement of the current flowing through the working electrode of an electrical cell. Several devices based on amperometry have been applied for microbial sensing. Redox mediators (such as Potassium hexacyanoferrate (III), benzoquinone and 2,6dichlorophenolindophenol) have been used which are reduced by the micoorganisms as a consequence of substrate metabolism. Kala´b and Skla´dal (1994) have evaluated the use of different mediators for the development of amperometric microbial bioelectrodes. The reduced mediators diffuse to the working electrode where it is subsequently re-oxidized. The current flow measured has been shown to be proportional to the reduced mediator concentration and hence the microbial concentration. This device can detect 5 104 cells mlÿ1 E. coli in 15 minutes (Hobson, 1996). Several devices have been developed based on this principle and commercial instruments were also marketed, but were then withdrawn due to poor reproducibility when testing a range of microorganisms. Hitchens et al., (1993) measured bacterial activity using mediated amperometry in a flow injection system. The Medeci analyser (Medeci Developments Ltd, Harpenden, UK) is under development for medical application. The device is based on the use of screen-printed three-electrode


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configuration incorporated into a novel wall-jet flow-cell design, with electrochemical measurement of bacterial concentration by hydrodynamic coulometry. This process is similar to amperometry in that it measures current, but instead of current at a point in time it measures current over a period of time, hence total charge passed (Thomson, 2001). Devices based on the use of the Clark oxygen electrode have also been developed for microbial detection.

8.6.4 Cyclic and square wave voltammetry A three electrode system using working electrode, reference electrode (SCE or Ag/AgCl) and counter electrode (platinum) have been developed using cyclic voltammetry (CV) for the detection of yeast and bacteria. The application of dyes for bacterial detection using square wave voltammetry (SWV) has also been applied (Lafis, 1992). Dyes such as carbocyanine, 3,30 -dihexyloxacarbocyanine and safranin O have been investigated (Carino et al., 1991) with concentrations in the range of 104 ÿ 108 cells mlÿ1 being detected (Lafis, 1992).

8.7 Immunosensors: amperometric, potentiometric, acoustic wave-based and optical sensors Microbial detection using immuno- and affinity sensor configuration has been used for a range of microorganisms. Different types of transducers have also been applied in the development of these sensors for microbial detection.

8.7.1 Amperometric sensors Detection of microorganisms using the amperometric transducer is widely used and it involves the measurement of the current produced through an oxidation/ reduction mechanism catalysed by microbial enzymes. Amperometric transducers have also been applied in affinity sensors format to detect micoorganisms where the antibody marker produces an electrochemical signal. Devices based on a flow through, immunofiltration and enzyme immunoassay in conjunction with an amperometric sensor were used for the detection of E. coli (Abdel-Hamid et al., 1999; Ivnitski et al., 1999). An amperometric enzymechannelling immunosensor has been developed and was able to detect S. aureus cells in pure culture at concentrations of 1000 cells mlÿ1 (Rishpon and Ivnitski, 1997). Ivnitski et al. (2000) developed an amperometric immunosensor based on supporting planar lipid bilayer for the detection of Campylobactor. Sensors for E coli O157 using the paramagnetic beads have been developed coupled with electrochemical detection (P’erez, 1998). The system was based on flow injection analysis (FIA) detection of viable bacteria. Using a solution containing E. coli O157, the electrochemical response with different mediators (potassium hexacyanoferrate (III) and 2,6-dichlorophenolin-dophenol) was evaluated first in

148


Fig. 8.6 Schematic model of E. coli detection method performed in three separate steps: (A) the selective capture of the bacteria, (B) the reaction of the bacteria with a mediator and (C) the electrochemical measurement of the reduced mediator using an amperometric method. (Pe´rez et al., 1998).

the FIA system. Antibody derivatized Dynabeads were used to selectively separate E. coli from the matrix. The immunomagnetic separation was then used in conjunction with electrochemical detection to measure the concentration of viable bacteria (Fig. 8.6). A calibration curve of colony-forming units (cfu) against the electrochemical response was obtained and a detection limit of 105 cfu mlÿ1 in 2 h assay time was achieved (Pe´rez et al., 1998). Coupling flow injection analysis with immunosensor configuration is very attractive for on-line detection system development and many researchers have used this system for food sensing (Bouvrette and Luong, 1995).

8.7.2 Potentiometric sensors A light addressable potentiometric sensor (LAPS) based on a field effect transistor (FET) has been used for the detection of microorganisms (Invitski et al., 1999; Leonard et al., 2003). The sensor is based on a silicon semiconductor


Fig. 8.7

149

The ThresholdÕ Immunoassay detection system.

and uses antibody as the receptor. A commercially available LAPS (ThresholdÕ Immunoassay System) marketed by Molecular Devices (USA) uses silicon semiconductor and an enzyme generates potentiometric signal (urease) as the enzyme marker. This system (Fig. 8.7) has been used by several researchers for microbial cells detection (Dill et al., 1997; 1999). A cell concentration of 2.5 104 cells mlÿ1 of E. coli O157:H7 was detected using this system (Gehring et al., 1998).

8.7.3 Aucoustic wave-based sensors Acoustic wave based devices have been applied for microbial detection. The mass sensitive detectors operate on the basis of an oscillating crystal that resonates at a fundamental frequency. Antibodies or receptor molecules are usually immobilised on the crystal surface and the sensor is then exposed to the sample containing the microorganism of interest. A change in the resonant frequency of the crystal surface related to the mass change is quantifiable and depends on the microbial concentration in the sample (Fig. 8.8). These type of sensors offer label free and on-line analysis of miccroorganisms (Bunde et al., 1998, Babacan et al., 2000). Mass balance acoustic wave transducers can be classified into: (a) bulk wave (BW) devices and (b) surface acoustic wave (SAW) devices. Piezoelectric crystal immunosensors for the detection of enterobacteria in drinking water have been reported by Plomer et al. (1992). A piezoelectric biosensor for the detection of Salmonella (Pathirana et al., 2000), Helicobacter pylori (Su and Li, 2001), Listeria monocytogenes (Vaughan et al., 2001), Legionella and E. coli (Howe and Harding, 2000) have also been developed using antibodies as the receptor.

8.7.4 Optical sensors Optical transducers are usually very attractive as they allow real-time and direct ‘label-free’ detection of microorganisms. Optical sensors based on surface

150


Fig. 8.8

Piezoelectric microbial immunosensor.

plasmon resonance (SPR) detection and evanescent wave (EW) have shown promise in microbial detection (Haines et al., 1995; Watts et al., 1994). The BIAcoreTM (BIAcore AB, Uppsala, Sweden) has been applied for E coli sensing and also for Salmonella and Listeria detection (Haines et al., 1995). A large number of instruments are marketed today by BIAcore AB offering varying degrees of automation and cost and these include BIAcore 1000, 2000, 3000 and BIAliteTM, BIAcore XTM, BIAQuadratTM, BIAcore S51 and BIAcore J. In these devices binding events are monitored between two molecules, such as an antibody and its antigen (in this case it is the microbial cell) using SPR technology. Direct microbial detection using the BIAcoreTM achieved a detection limit for E.coli O157:H7 of 5 107 CFU mlÿ1 (Fratamico, 1998). The IAsysÕ systems (Affinity Sensors, Cambridge, UK), which is also an optical biosensor based on a resonant mirror has also been used for microbial detection by immobilising the antibody on the chip surface. The company markets several products today and these include IASys plusTM and IASys Auto + AdvantageTM. Optical devices as the ones listed above tend to use small samples and the presence of microorganisms in complex food matrices are problematic. Therefore, pre-enrichment (as in ISO 11290-1) and immunoseparation or a concentration step is needed to enhance the detection limit of the sensors for pathogen detection (Kaclikova et al., 2001, Quinn and O’Kennedy, 2001). Watts et al., (1994) reviewed optical biosensors for microbial cells monitoring. A new range of devices has emerged recently based on resonant mirror configuration and SPR and these are reviewed by Leonard et al., (2003).

8.8

Detection of moulds using biochemical methods

A wide variety of methods has been used to quantify the fungal activity in raw materials such as grain and processed food. Chitin, ergosterol, adenine triphosphate, immunofluorescence, immunoassays and DNA probes have all been developed (Magan, 1993; Fleurat-Lessard 2002). Since ergosterol is the predominant sterol in most spoilage fungi (ascomycetes and deuteromycetes) and not found in insect pests it has been utilised extensively as an indicator of


151

whether deterioration has occurred in the food chain. The method was first described by Seitz et al. (1977) and can now be performed relatively quickly and routinely using simple extraction and HPLC. It has thus been used extensively for the in vitro quantification of biomass of spoilage fungi which demonstrated that this does change with culture age (Marfleet, et al. 1991). Cahagnier et al. (1991) suggested that the ergosterol content in storage fungi was not significantly affected by environmental factors such as aw. They thus suggested that ergosterol could be used as an ‘index’ of the level of fungal biomass and the length of storage of food raw materials. Tothill et al. (1993) determined the relationship between ergosterol content, CFUs and microscopic and visible moulding in both inoculated and natural grain under different aw and temperature regimes. These studies showed that there was a significant positive correlation between ergosterol content and total CFUs at 0.95 aw, while in drier grain of 0.85 aw there was no significant correlation. Grain inoculated with individual species (Alternaria alternata, Eurotium amstelodami, Penicillium aurantiogriseum) at 0.95/0.85 aw and 25ºC showed a significant correlation between CFUs and ergosterol although the content for an individual species varied considerably. Table 8.1 compares some of the available information on ergosterol levels in a raw material such as grain used for the bakery product industry with that when microscopic growth has occurred, with those suggested by Cahagnier et al. (1991) as a threshold for fungal spoilage. They suggested levels of < 5–6 g gÿ1 fresh wheat grain, with grain having microscopic growth about 7.5–12 g gÿ1. This correlated with a threshold of 105 CFUs gÿ1 grain as a spoilage threshold indicator. Fleurat-Lessard (2002) has suggested that perhaps modelling of ergosterol production rates under different environmental conditions using sigmoid curves similar to those used for insect population dynamics may enable the use of an ergosterol index in the future when correlation models become available. It may also be possible to use both ergosterol and the production of mycotoxins in predicting potential environmental factors over which spoilage/ Table 8.1 Comparison of ergosterol levels in dried, recently harvested grain (A) with concentrations at which microscopic fungal growth (B) was observed Grain type

Ergosterol (g gÿ1) A B

Reference

Wheat Maize Sorghum Wheat Barley Maize Wheat (Avalon) Wheat (Rendevous) Barley

0.7–3.5 0.2–2.0 0.2–4.0 3–4 4.0 0.5 4–5 5–6 3–7

Seitz et al. (1977) Seitz et al. (1977) Seitz et al. (1977) Cahagnier et al. (1991) Cahagnier et al. (1991) Cahagnier et al. (1991) Tothill et al. (1993) Tothill et al. (1993) Olsen and Schnurer (2002)

ND ND ND 10–12 10–12 5–8 8–9 10.13 > 10

152


mycotoxins may be produced. Two-dimensional models for growth and fumonisin production have already been developed (Marin et al., 1999) and such information may be useful in further development of predictive models for risk assessment of spoilage and toxin contamination of food. Perhaps, modelling of cumulative ergosterol production by spoilage fungi and associated mycotoxins in relation to aw, temperature, time, gas composition (modified atmosphere storage) and time may allow more effective and precise risk assessment of mould contamination and mycotoxin occurrence to the consumer.

8.8.1 Enzyme changes as an indicator of deterioration of food by moulds Changes in food enzyme concentrations, e.g. amylases, due to fungal deterioration are important as they have an impact on processing and bread making quality of flour and dough. However, studies which examined amylase, -amylase and total amylases of wheat and tried to correlate these with the time to microscopic and visible moulding were found to be an inaccurate measure of mould activity in grain (Magan, 1993). Fleurat-Lessard (2002) has suggested that for a range of cereal raw materials enzyme changes are too small and occur too late as functions of storage conditions and duration, especially as a rapid indicator of spoilage. However, there is a quite large body of work which suggests the contrary. Fungi colonising the rich food raw materials such as grain under conducive environmental conditions produce a battery of hydrolytic enzymes for degrading food. Both Flannigan and Bana (1980) and Magan (1993) showed that aw and temperature affect the production of enzymes by fungi during grain colonisation, including cellulases, polygacturonase, pectin methyl esterase, 1-4- -glucanase, -glucosidase, -xylosidase and lipases. Jain et al. (1991) were the first to demonstrate that by using chromogenic 4-nitrophenol substrates in an ELISA well format, rapid quantification could be carried out for a range of hydrolytic enzymes, provided that substrates were available for them. They demonstrated that in both barley and wheat grain at different aw levels (0.85, 0.90, 0.95) significant increases in N-acetyl- -D-glucosaminidase were produced when compared to non-moulded dry harvested grain. Grain inoculated with the xerophile Eurotium amstelodami also showed marked increases in -Dgalactosidase. Magan (1993) extended this and examined stored dry grain with that at different aw levels and temperatures of incubation. This showed that significant change in the production of some enzymes was evident at times of microscopic and visible moulding. Of seven enzymes examined significant changes in -Dglucoaminidase, -D-glactosidase and -D-glucosidase were observed by the time microscopic growth had occurred. Work with maize-based food matrices under different temperature and aw regimes inoculated with fumonisinproducing Fusaria (F. verticillioides, F. proliferatum) demonstrated that both total and specific enzyme activity for -D-galactosidase, -D-glucosidase and N-acetyl- -D-glucosaminidase changed significantly (Martin et al., 1998).


153

Changes could be monitored within 72 hrs of storage. They also suggested that these enzymes could be used as an early indicator of infection of food by such mould species and that these enzymes were important in enabling rapid colonisation over a wide range of environmental factors. Recent work by Keshri and Magan (1998) and Keshri et al. (2002) have also suggested similar hydrolytic enzymes are an early indicator of fungal activity in vitro on wheat flour-based media and in bread substrates. Thus potential does now exist for the use of such relatively simple enzyme assay formats to be used as a possible tool for early detection of fungal activity in food substrates.

8.9

Electronic noses

In recent years the rapid development of sensor technology has enabled the production of different sensor array formats which can interact with different volatile molecules. The resistance of the material is changed providing a signal which can be utilised effectively as a fingerprint of the volatiles produced. Metal oxide, conducting polymer and discotic crystals have all been utilised in different array formats to try and qualitatively and semi-quantitatively obtain information on, and differentiate between volatile production patterns produced by spoilage microorganisms in food matrices. However, it is important that the results are combined with multivariate data analysis systems to enable rapid intepretation of volatile patterns and for user-friendly answers to be obtained. Although most electronic nose systems are qualitative for QA, the level of detail required determines the use of the instrument. If a simple yes/no answer is needed then it can be very appropriate. Recent studies have demonstrated that real-time evaluation of food raw materials can be made in approx. 10 mins per sample for discrimination of mouldy from good grain (Magan and Evans, 2000; Evans et al., 2000). Recent studies have also demonstrated that discrimination between mould contaminated and non-contaminated bread was possible within 24–30 hrs after inoculation, prior to any visible growth and more sensitive than enzyme assays or CFU population measurements (see Fig. 8.9; Keshri et al., 2002). Studies have also suggested that since the biochemical pathways for mycotoxin producing strains of a species may differ from non-producing strains, the volatiles produced may also differ (Olssen et al., 2002). Keshri and Magan (2000) demonstrated that mycotoxigenic and nonmycotoxigenic strains of Fusarium species could be discriminated using volatile production patterns with an electronic nose using conducting polymer sensor array. Recent studies have also suggested that changes in bacterial populations in milk and water can be detected at between 103ÿ104 CFUs per ml (Magan et al., 2001; Canhoto and Magan, 2003). Indeed, detection of medically important aerobic and anaerobic bacteria has also been successful (Pavlou et al., 2002). The take up of this technology had been slow because of problems with consistency and the price of the technology. However, as the development of sensor arrays becomes cheaper the potential for exploitation of this technology should improve rapidly.

154


Fig. 8.9 Dendrogram which shows discrimination between bread inoculated with different mould species and the control (Keshri et al., 2002). Example of differentiation between spoilage moulds using electronic nose technology.

8.10

Conclusions: commercial products

Due to the increased need for detecting micoorganisms in food and other applications many devises have been developed and marketed. The success of any instrument is based on the level of detection and cost. Table 8.2 lists some of the products on the market today. Most of the instruments developed for laboratory analysis are large with detection limits of 103ÿ105 cells mlÿ1 with analysis time ranging from 10 min to 8 hours. Smaller instruments are in demand especially for on site testing. On-line methods of microbial testing have been Table 8.2

Examples of commercial instruments available for microbial detection.

Detection method

Detection limit (cells mlÿ1 )

Time of analysis

Bioluminescence

103

10–20 min

Electronic particle analysis Coulter counter Enzymes

105

20 min

5104 1 cfu 100mlÿ1

30 min 24 h

Surface plasmon resonance (SPR) Epifluorescence Impedance

105

1–2 h

0.5 cfu 105

10–20 min 2.5–8 h

Electronic nose

103ÿ104

1 hr

Commercial instrument Clean-TraceTM (Biotrace Ltd., Bridgend, UK) Ramus 265 (Orbec Ltd., Surrey, UK) Coulter Counter Inc., Canada Colilert (Palin test Ltd., Gateshead, UK) BIAcore (Pharmacia, Uppsala, Sweden) FOSS Electric, Hillerød, Denmark Bactometer (BioMerieux Inc., Marcy-’Etoile, France) AlphaMoss, France


155

developed by many researchers (Ashley, 1991; Chunxiang et al., 1993; Silley, 1994). For food samples, which are usually coloured and contain particulate matter, sample preparation is important to reduce interferences. Ideal methods of analysis should be capable of real time and in situ analysis. Microbial contamination detection and analysis is a very important area in food safety. Classical methods usually have a long time of analysis but give good sensitivity. The other more recently developed methods may give faster results but usually suffer from low sensitivity. However, no single method, to date, has been completely satisfactory in the determination of microbial contents. Drawbacks encountered by the various detection techniques include long response time, lack of sensitivity and high cost of the instruments. Lack of discrimination between viable and non-viable biomass can result in errors. A range of contract laboratories provide a complete microbial testing with testing regimes for physico-chemical characterisation of ingredients and their application in food and drink products from bench to pilot plant to factory sites.

8.11

Sources of further information and advice

http://www.sdix.com/ http://www.oxoid.com/uk/index.asp http://www.ciberis.com/syva/ http://www.leatherheadfood.com/lfi/index.htm http://www.mcsdiagnostics.com/doc-e/e-cf1-1.htm http://www.mcsdiagnostics.com/index.htm http://www.microcheck.com/ http://www.rocheuk.com/html/products/default.asp http://www.biomerieux-usa.com/clinical/immunoassay/index.htm http://www.foss.dk/c/p/default.asp?width=1024 http://www.adgen.co.uk/ http://www.gen-probe.com http://www.affymetrix.com/index.affx http://www.biacore.com http://www.affinity-sensors.com

8.12

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9 Rapid analysis of microbial contamination of water L. Bonadonna, Istituto Superiore di Sanita` – Rome, Italy

9.1

Introduction

The presence of enteric pathogens in drinking and recreational waters is of great public concern. As a result of the risk to public health due to the presence of pathogens, it is extremely important to determine the microbiological safety of these waters. The ideal manner for doing this would be to analyse the waters for the presence of specific pathogens of concern. However, hundreds of different micro-organisms have been shown to be involved in waterborne disease outbreaks; thus, it would be impractical to look for every pathogen potentially present in water. In addition, traditional methods used routinely in the control for enteric pathogens are often time-consuming and scarcely selective. Thus, indicator organisms of faecal contamination are used globally as a warning of possible contamination. They are considered as an index of theoretical risk for public health and of water quality deterioration. Heavy reliance has been placed on the coliform and enterococci groups of bacteria to determine the safety of drinking water, recreational water and shellfishharvesting water. However, the presence of the indicators is not an absolute indication of the presence of pathogens and, on the other hand, their absence is not a guarantee that other, more resistant microbial forms are not present. Furthermore, their presence has no diagnostic value for biological agents deliberately introduced in water. Ideally, microbial indicators should provide a measure of health risk associated with the exposition to contaminated water (ingestion or contact). Nevertheless, these groups of micro-organisms have many limitations as predictors of risk of waterborne disease. In fact, the bacterial indicators tend to be poor models for enteric protozoa and viruses because of their shorter survival

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times in water and their greater susceptibility to water treatment processes. Moreover, there are non-faecal sources for these indicator organisms, and in contrast to most enteric pathogens, coliforms may multiply in aquatic environments with sufficient nutrients and optimal temperatures. Such characteristics may result in false-positive reports of water contamination. One of the requirements of choice of an ideal indicator of faecal contamination is to be easy to identify, isolate and enumerate. Thus the monitoring and the statutory assessment of the hygienic quality of drinking water are based on the determination of bacterial indicators of faecal contamination.

9.2

Current techniques and their limitations

Classically and routinely, the detection and the enumeration of indicator microorganisms of faecal pollution is based on cultural methods. In these methods, the micro-organism is grown on either a solid (agar) or liquid (broth) medium, which supplies the nutritional requirements of the organism. Once a microorganism has been grown and isolated as a pure culture, the identification is generally based on biochemical characteristics of the isolate; sometimes immunological (serological) and genetic characteristics are also determined. In many instances, specific and selective compounds are incorporated into the primary media, which allow for selection and differentiation of the target organisms and, contemporaneously, inhibit the growth of background bacterial flora (non-target organisms). This detection system can be based on fermentation of specific sugars, enzymatic degradation of specific substrates, mobility, reduction of hydrogen acceptors, etc. and will usually result in recognisable colour changes, gas production, etc. Cultivation of micro-organism needs the growth/multiplication of micro-organisms. However, the viability of a micro-organism may affect detection and for a long time the failure of some bacteria to grow on solid media has been recognised. Conventional methods for detecting indicators and pathogenic bacteria in water may indeed underestimate the actual microbial population due to sublethal environmental injury, inability of the target organisms to take up nutrients and other physiological factors which reduce bacterial culturability. In fact, it is recognised that only a small proportion, possibly less than 1%, of the number of viable bacteria may be enumerated in water (McFeters, 1990). A requirement for reproductive ability is for the cell to be metabolically active and possess intact cell membrane and cellular components. An intact, metabolically active cell may not necessarily grow, however, due to non-lethal injury. The concepts of bacterial injury (McFeters, 1990) and ‘viable but non-culturable’ cells (VBNC) (Roszak and Colwell, 1987; Desmonts et al., 1990, 1992) have been demonstrated by molecular techniques. Besides, stressed micro-organisms, even able to multiply, can lose the ability to express some metabolic characteristics. For example, it is the case of stressed

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Escherichia coli strains: non-gas producing strains of E. coli have been reported to approach 10% of the E. coli population in water (Dufour et al., 1981). Appropriate sampling procedure is the first step at obtaining good analytical results from an analysis. The sample should be representative of the water to be analysed. Additionally, the amount of elapsed time allowed between sample collection and analysis should not exceed 24 hours for most micro-organisms and less than 18 hours for some pathogens. All microbiological methods are designed to detect and/or enumerate particular types of micro-organisms, the target-organisms. Thus the detection of specific groups (e.g., coliforms) or species (e.g., Escherichia coli) of microorganisms should be carried out using selective media. Interfering flora that may be present in the sample should go undetected and should not interfere with the analytical process. The often harsh conditions needed to suppress the non-target groups may however reduce the recovery of the target population as well. Besides, non-target organisms will not always be totally eliminated and the characteristic appearance of the target colonies may not be unequivocally distinct. Consequently, methods/media are not completely selective for the specific micro-organisms to be determined and few selective methods can be trusted to function so well that further confirmation of the primary colonies is unnecessary in all sample types. Moreover different methods will recover different proportion of the bacterial population. It is also important to outline that because the growth medium and the conditions of incubation, as well as the nature and age of the water sample, can influence the species isolated and the count, microbiological examinations may have variable accuracy. This means that the standardisation of methods and of laboratory procedures is of great importance if criteria for microbiological quality of water are to be uniform in different laboratories and internationally.

9.3

Identifying indicator organisms

The following paragraphs give a brief overview of the most common methods used for detection of bacteria in water. In liquid enrichment methods, a test portion is inoculated into a growth medium that has been formulated to stimulate growth of the target organisms and to suppress growth of the background flora. The selective nature of the enrichment medium is enhanced by choosing an appropriate incubation temperature and time. If the target organism is present in the test portion, this will usually result in a positive signal, irrespective of the original number. In its simplest form, a liquid enrichment method therefore gives a Presence/Absence type of information. In order to obtain (semi-) quantitative information, a series of different volumes (e.g., 100, 10, 1 and 0.1 ml) may be examined to produce an end-point type of result. If a series of different volumes is examined in replicate, e.g. three- or five-fold, it is possible to use a method known as the Most Probable

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Number (MPN) technique to estimate the original concentration of the target organism. MPN analysis is a statistical method based on the random (Poisson) dispersion of micro-organisms in a given sample. The results are expressed in terms of the MPN of micro-organisms detected per volume of sample. Classically, this assay has been performed as a multiple-tube fermentation test. The precision of this estimate is low (e.g., the 95% confidence interval of a fivefold MPN estimate is roughly between one-third and three times the analytical results) (Lightfoot and Maier, 1998). However, if the number of parallel test portions is increased to 100 or more, the MPN technique will surpass the conventional plating technique in precision. In fact, precision of single-dilution or multi-dilution MPN estimates is inversely related to the square root of the number of parallel tubes. A convenient way to increase precision is to use the miniaturised enzymatic MPN method at multi-well (Section 9.4). The classic MPN technique is also time-consuming: to perform the presumptive, confirmed, and sometimes completed steps, 48–72 hours or more are necessary. Besides, only little volumes of the sample can be analysed. However, it still remains a good technique for the analysis of samples characterised by high turbidity and for the analysis of environmental solid matrixes (sediments, sands, sludge, compost). The other traditional method is the colony count technique. A test portion is inoculated onto the surface of a selective or not selective growth medium that has been solidified by addition of agar-agar (spread-plate method). Each individual cell of the target organism will multiply into a colony visible to the naked eye. If several cells of the target organism are physically connected or laid upon, this will result in one colony. The result of the plate count technique are therefore expressed as the (number) concentration of Colony-Forming Units (CFU) per unit volume. Each CFU represents one or more cells of the target organism in the original sample. Variations are the pour-plate method where the test portion is mixed with the liquefied agar medium, poured into Petri dishes and incubated after solidification. The more commonly used colony count procedure for the detection of indicator organisms is the membrane filtration method where the test portion is filtered through a membrane filter (usually of 0.45 m pore size) and the filter is placed on the growth agarised medium. Results of analyses performed by the membrane filtration method are generally obtained in primary isolation after 24–48 hours; if a confirmation or biochemical tests have to be carried out final results can be reached also after 96 hours. A procedure of resuscitation, necessary to revive micro-organisms before placing them on the selective growth medium, may be an integral part of the test method and usually involves incubation in a less selective medium and/or at a less restrictive temperature. The use of membrane filtration methods can exhibit some issues due to inhibition of growth on filter grid-lines, abnormal spreading of colonies, hydrophobic areas, poor colony sheen, decreased recovery and wrinkling


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(Brenner and Rankin, 1990). Different brands of membrane filters also produce discrepancies in the enumeration of micro-organisms from water (Presswood and Brown, 1973; Sladek et al., 1975; Brenner and Rankin, 1990). Turbidity in water samples may preclude the use of filtration as high sediment concentration on the membrane surface may interfere with colony growth. Besides, bacterial colonies on plates or membrane filters may influence each other and in general there will be a tendency to lower test results if more colonies are found on the same plate. To some extent these so-called ‘crowding effects’ will influence the final test result. Furthermore, the linearity of the method can be affected by the ability of the analyst to distinguish ‘typical’ from ‘atypical’ colonies. Experience has shown that misinterpretation and differences between several analysts are more likely to occur at higher colony densities, particularly with methods that require subjective interpretation of colours or dimensions of colonies. Advantages of the current methods have outweighed the limitations for decades. The low cost per sample and low complexity of the procedure makes the techniques universally applicable to laboratories. The selectivity of the media commonly used and the time for obtaining confirmed results remain major limitations.

9.3.1 Microbiological detection methods A broad variety of micro-organisms can be found in aquatic environments. Since the pathogen micro-organisms appear intermittently in natural waters at low concentrations, and the techniques available for their selective recovery and enumeration are, generally, complex, the use of surrogate (indicator) bacteria has been standard practice in water quality monitoring. Historically the heterotrophic plate count (HPC), the coliform group, the enterococci have been the bacterial indicators of choice. The former parameter is generally used as indicator of the effectiveness of the water treatment processes and as a measure of numbers of regrowth organisms that may or may not have sanitary significance. The latter two indicator bacteria are excreted in high numbers by healthy humans and animals, and thus their presence in environmental samples is indicative of faecal contamination. By contrast, specific enteric pathogens are voided only by infected individuals, and their numbers in aquatic environments depend on the excretion level of each particular pathogen and on the number of infected individuals in the community. The great diversity of micro-organisms in water, and associated variety of required growth conditions, hamper attempts to isolate, identify, and enumerate most organisms’ members of this microcosm. Thus the presence of indicator organisms will likely continue to be used as a criterion of water quality that will be of value if attention is given to the development and use of optimal and more rapid methods for the recovery of these micro-organisms. The commonly used indicator organisms belong to the groups of coliforms and streptococci/enterococci. The traditional definition of the coliform group of bacteria (family of Enterobacteriaceae) specifies that they are aerobic and

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facultatively anaerobic, gram-negative, non spore-forming, rod-shaped bacteria, able to ferment lactose with gas and acid production in 24 to 48 h at 35–37ºC (total coliforms) or at 44–44.5ºC (faecal or thermotolerant, or more correctly thermotrophic coliforms). However, the more recent advent of enzyme-specific media and tests has allowed the application of cytochrome oxidase (negative) and -galactosidase (positive) as additional criteria for their characterisation. Adoption of DNA-DNA hybridisation has also recently allowed a substantially improved grouping of Enterobacteriaceae in general and of coliforms in particular. The coliform group, now defined as ONPG+ Enterobacteriaceae (ortho-nitrophenyl- -D-galactosidase-positive), is distributed among 19 genera and 80 species. Among the coliform group, Escherichia coli deserves further discussion. In particular, E. coli has been demonstrated to be a more specific indicator for the presence of faecal contamination than the other coliform bacteria. In addition, E. coli conforms to taxonomic as well as functional identification criteria and is enzymatically distinguished by the presence of -Dglucuronidase, while possession of the gene coding for the -galactosidase enzyme is the most fundamental characteristic of the coliforms. Moreover, these enzymes form the basis for recently developed differential methods that will be discussed later in this section. The coliform bacteria have been for a long time the primary standards for drinking water in Europe and North America. Now, among the microbiological parameters for the control of water for human consumption, the European Directive 98/83 (European Directive, 1998) indicates, in substitution to faecal coliforms, Escherichia coli as specific indicator of faecal contamination. The group of the faecal streptococci/enterococci, gram-positive bacteria, is useful as indicator of microbiological water quality since these micro-organisms are common inhabitants of the intestinal tracts of humans and lower animals. Some of these organisms have persistence patterns that are similar to those of a range of potential waterborne pathogenic bacteria. As to the coliform group, recent molecular approaches have markedly changed traditional classification of the group. Two genera, Streptococcus and Enterococcus, have been recognised, and the different species have been reassigned to them. Whether testing for indicator organisms or directly for pathogens, there is a common need for rapid analyses. Typically, the drinking water treatment process is a continuous process and water is consumed within a few hours after treatment. Real-time analysis would be ideal for the management and control of microbial water quality and the safeguard of public health. At the present, with the use of conventional cultural methods, the assessment of the hygienic quality of drinking water is only available after a minimum of 18 to 24 hours. If results have to be confirmed, another one to two days may be required. The detection of bacterial pathogens in water can take even longer. Analytical procedures have often low selectivity and are complex and time-


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consuming. Testing water for the presence of specific viruses or Giardia and Cryptosporidium might even take as long as a few weeks for a complete determination (Keswick et al., 1984; Gerba et al., 1989; Girones et al., 1993; Fricker, 2002). Consequently, information on the microbiological quality of the water supplied to consumers is often available long after the water has been utilised. Nevertheless different causes could change water quality: sudden failure of drinking water treatment plants, contamination of distribution networks or disruption of water supply services, water contamination by natural disasters or by intentional introduction of microbial pathogens, regrowth phenomena. That could constitute a risk to consumer health. So water treatment facilities should have the capability of detecting water quality changes rapidly in order to adjust the treatment process. In all these cases there is an urgent need for rapid and reliable information on the microbiological quality of drinking water.

9.4

The development of more rapid detection methods

A variety of analytical approaches have been proposed for the rapid detection of bacteria in water, although most are limited by sensitivity with respect to analysis of water of good microbiological quality. An essential requirement for rapid methods should be the availability of data in the shortest time possible, that means that these methods should be faster than the standard methods currently used. For bacterial indicators, the ideal for rapid methods should therefore be to have results within the same working day. Rapid methods should ideally have sensitivity and specificity at least equal to those of the standard methods used regularly. Until now, sensitivity remains a major drawback for many of the rapid methods in development. Moreover, these techniques should have the ability to distinguish between viable and dead microorganisms and results should be robust, repeatable and reproducible. In order for the development of rapid detection methods to be used on a routine basis, other logistical and economic factors should also be considered. Thus attention should be given to the cost and availability of reagents, the need for special handling of samples, the need for dedicated and expensive apparatus, the ease of performance and interpretation of results, and the training needs of the analyst. A great variety of methods, based on different principles, are available for recovery and characterisation of micro-organisms in water. Some of them, however, have a more meaningful application and are more suitable for pathogens detection rather than indicator micro-organisms. In fact, the costsbenefits ratio is still unfavourable for some methods because of their low sensitivity and specificity, interference problems, need of skilled personnel, high cost of instruments and reagents. Therefore, some rapid methods for the indicators detection in water are described with consideration to their current and wider actual application.

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Among these methods, some techniques are referred to as rapid methods although they may not be faster than some of the membrane filtration methods using selective media. Nevertheless, as the results are available within 18 to 24 hours, they are faster than those of the standard methods where confirmation of the results is required, which take 48 to 72 hours. Methods for the detection of micro-organisms in water can be roughly divided into two principal categories: cultivation techniques and techniques in which the micro-organisms are detected directly without first culturing them. Within these two big categories, methods, sometimes combined, can be arranged at different levels: qualitative or semi-quantitative methods, quantitative methods and methods for identification and characterisation of micro-organisms.

9.4.1 Methods based on specific enzyme activities Over the last twenty years, new membrane filtration and MPN techniques, and Presence-Absence tests, using the metabolic activity of cellular enzymes for the detection of total coliforms, E. coli and enterococci have been developed and now currently applied (Edberg et al., 1988; Manafi and Kneifel, 1989; Hernandez et al., 1991; Budnick et al., 1996). The tests rely on the detection of specific enzyme activities ( -Dgalactosidase, -D-glucuronidase, -D-glucosidase) associated with the targeted indicator organism and no further confirmation tests are needed (Manafi et al., 1991; Frampton and Restaino, 1993). The specific substrates allow the expression of these enzymes and their hydrolysis by the specific enzymes releases fluorophores or chromophores, providing a signal for detection. However, these assays can be affected by the incidence of enzymes positive interfering organisms (e.g., Flavobacterium spp., Aeromonas, some Shigella strains) and E. coli strains (E. coli O157:H7) that do not express the specific enzyme. For use in membrane filtration procedures, with the aim to obtain faster results compared to those of traditional media, many new selective media based on enzymatic activity have been proposed for the recovery of indicator organisms, particularly E. coli. Nevertheless, over the last ten years, enzyme substrates used in semi-quantitative methods have received more concern. Among these techniques, based on the MPN procedure, ColilertÕ QuantyTrayTM and Enterolert Quanty-TrayTM (IDEXX, Westbrook, Maine) are the recommended methods for drinking water analysis in the United States and for recreational water analysis in Australia and New Zealand. Moreover ColilertÕ Quanty-TrayTM is approved by USEPA and by UBA, the Agency for the environment, as an alternative method in Germany to the ISO 9308-1 reference method for drinking water analysis. The ColilertÕ Quanty-Tray, developed by Edberg et al. (1988), enables simultaneous detection and enumeration of total coliforms and E. coli within 18–24 hours. Sample preparation is minimal, requiring direct addition of the sample to the powdered medium containing ortho-nitrophenyl- -Dgalactosidase (ONPG) and 4-methylumbelliferyl- -D-glucuronidase (MUG). A


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yellow colour is considered a positive reaction for total coliforms, whereas a blue-fluorescent colour under UV (ultraviolet) light is considered a confirmation of E. coli presence. A European trial among twenty laboratories belonging to thirteen European countries, held in 1999–2000, showed the ColilertÕ to be at least equivalent to the ISO standard reference method 9308-1 for the detection of E. coli and coliforms (Fricker et al., 2000). The EnterolertÕ Quanty-TrayTM uses the same principle of the former method. Its powdered medium contains as a substrate the 4-methylumbelliferyl- -D-glucoside (MUD) for the detection and enumeration of enterococci in 24 hours. All these methods require little skill to perform and interpretation of the results is easier and less prone to error, especially for high colony concentrations, than from a membrane filter plate. Miniaturised enzymatic MPN methods for E. coli (MU/EC) and for enterococci (MUD/EN) are based on the same criteria of the previous mentioned methods: positive wells in a 96 wells microtitre plate result fluorescent under UV light. During two European Projects both the methods were compared to selected and representative analytical methods used in different laboratories in Europe. Even if they give results in 36–72 hours, no confirmation has to be done and a higher specificity was found compared to the membrane filtration methods (Hernandez et al., 1995). Both the methods have recently been recommended by the ISO (International Organisation for Standardisation). The revised Bathing Water Directive, at the present time under discussion at the European Parliament, include them as reference methods for bathing water analysis. Among the Presence/Absence tests, ColifastÕ (Norway) has proposed the ColifastÕ Analyser for the detection of total and thermotolerant coliforms, E. coli, faecal streptococci, Pseudomonas aeruginosa and TVO (Total Viable Organisms) in water samples. It is a semi-automated instrument with customised software and ColifastÕ reagents and media incorporating enzyme substrates. The method is automated after sample concentration and registration, and contemporaneously allows the analysis of 80 samples. Fluorescence is detected by the ColifastÕ Analyser providing Presence/Absence results. Semiquantitative information can be obtained by determining the Time To Detect (Samset et al., 2000). The speed of detection depends upon the level of contamination within the sample. In raw water samples detection times ranged from 1 hour with >1000 CFU to generally under 8 hours for one thermotolerant coliform and 9.5–13 hours for one total coliform (Eckner et al., 1999). The ColifastÕ Analyser has been applied as an early warning operational tool (Tryland et al., 2000), in MPN format (Samset, 2000), Presence/Absence format (Samset et al., 2000) and direct addition or membrane filtration (Angles d’Auriac et al., 2000). Another application is an on-line, auto-sampling/auto-reporting instrument (CALM) for routine assessment of the quality of incoming raw water being used for drinking water production. At the present time, the performance of the ColifastÕ method is evaluated into a European Project (Section 9.6).

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9.4.2 Biosensors Among techniques used for the detection of active micro-organisms in water, biosensors can be included (Hobson et al., 1996). They provide an indication of the level of active micro-organisms in the sample and are, therefore, of only limited use in controlling the microbiological quality of water. Biosensors are analytical devices which yield a measurable signal proportional to the concentration of micro-organisms in the sample. Biosensors can provide direct detection of a biological reaction by measuring physical changes in pH, potential difference, oxygen consumption, ion concentrations, current, resistance or optical properties occurring as a direct result of the analyte-receptor complex formation on surfaces of a physical or chemical transducer. Biosensors are of use as screening tools and give a rapid indication of poor water quality in hours. There is a wide range of biosensors available on the market, some of them are portable (e.g., the GeneChip); others require substantial power inputs and software appliances. Among the electrometric biosensors, the impedimetric methods, widely known for a long time, measure the electrical resistance (impedance) to a flow of alternating current through a conducting medium where the microbial growth results in electrochemical changes, increasing the conductivity of the medium. The number of micro-organisms present in the inoculum can be estimated from the rate of change of the impedance. The success of impedimetric methods depends entirely on the selective properties of the growth medium. The first uses of impedimetry were to replace general parameters, such as total plate counts, sterility testing, yeasts and moulds. Over the last years, systems such as the Malthus (IDG, UK), the Bactometer (BioMe´rieux, France) and the RABIT (Don Whitley Scientific Ltd, UK), with selective media, have been developed for detection of microbial groups such as coliforms and enterococci.

9.4.3 Direct detection techniques In recent years, technological advancements have developed a variety of direct detection techniques for recovery of micro-organisms in water. Moreover, with the rapid development of molecular methods, several techniques with high specificity have been developed for the direct micro-organisms characterisation. In order to utilise the major advantages of both groups of techniques, combinations have been developed. Immunoassays may be competitive or non-competitive, based on the principle of antibody presence (Ekins, 1997). Commonest techniques for the labelling of antibodies include the conjugation of an immuno-fluorescent dye (IF), immuno-magnetic bead (IMS), secondary enzyme-linked antibody (ELISA), increasing the signal for detection of fluorescence, magnetism or enzyme activity. Polyclonal and monoclonal antibodies can be used, and these latter, more specific, produce a more reproducible and standardised immunoassay response. Nevertheless, the sensitivity and specificity required


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for water quality determination and the abundance of non-specific substances and interfering organisms producing false-positive results hamper the routine application of immunoassay to water analysis. The application for the detection of coliforms, E. coli and enterococci is further limited by the lack of commercially available antibodies specific for the required target. Cells to which the antibodies attach can be detected by epifluorescent microscopy, flow cytometry, optical density or by the ChemScanÕ RDI (Chemunex, France). In fact, epifluorescent microscopy is widely used for the detection and enumeration, by operator, of auto-fluorescent or labelled by fluorescent compounds organisms. Alternative detection techniques, such as flow cytometry involve counting blind to the operator. Flow cytometry measures the physical (size and length) and biochemical (DNA, photosynthetic pigments and proteins) characteristics of individual cells as they pass through a sharply focused, high intensity light beam derived from an arc lamp or laser (Shapiro, 1990). Cells can be detected by the effect of their physical status upon light scatter, or by auto-fluorescence or other fluorescent compounds conjugated to cell markers. The instrument detects cell presence when the signal strength exceeds a threshold set by the operator, which triggers a measurement. A constant, known flow rate enables the user to obtain an absolute count of cell number per unit volume injected. This is achieved by a constant sheath flow rate, maintained by pressure or pumps (Shapiro, 1995). Although it is assumed that measurements result from the detection of single cells, an underestimation of the real cells number has been obtained whether cellular aggregation occurs or not. Flow cytometry relies upon the strength of the signal for detection; therefore most target bacterial cells are labelled with fluorescent stains, antibodies or nucleic probes. Stains can be used to identify cell viability and taxonomic identification to some extent, although antibody labelling and nucleic probe and in situ hybridisation provide a more specific identification method. The application of flow cytometry for the detection and enumeration of indicator bacteria is limited (Porter et al., 1993; Davey and Kell, 2000) because of the high microbial density required (102–103 cells for optimal detection), the need for skilled operators, the high cost of the instrument. A portable, battery operated flow cytometer is the Microcyte (Optoflow, Norway) that has the advantage to reduce interference from auto-fluorescence of non-target organisms and particles. Flow cytometric analysis is completed in under 10 seconds at a fixed flow rate, therefore absolute cell numbers per unit volume are obtained (Davey and Kell, 2000). The detection limit is approximately 101–102 cells/ml, although 104–106 cells are required for optimal signal detection. The instrument requires little training for successful utilisation and provides the opportunity to screen biological from non-biological particles using fluorescent dyes. The simplicity, low cost and portability of the instrument are definite advantages when compared to the large-scale flow cytometers. Applications include the analysis of micro-organisms in environmental samples (river and

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drinking water, soil) and clinical specimens. The instrument has been extensively evaluated, particularly for the application to biowarfare. The ChemScanÕ RDI instrument (Chemunex, France) is a laser-scanning instrument designed for the detection and enumeration of fluorescently labelled micro-organisms. The instrument has been developed specifically for the detection of Cryptosporidium, Giardia, coliforms or E. coli. A three and a halfhour assay is required for the induction and labelling of target cells prior to laser scanning. Organisms are captured by membrane filtration, labelled and the filter subsequently scanned with a laser. The laser scanner detects and locates the position of all fluorescent organisms within three minutes. During the analysis, fluorescent events, including labelled organisms are detected by a series of detection units. Finally the signals generated undergo a sequence of computer analyses which distinguish between labelled organisms and fluorescent debris. A visual validation of all results can be made by transferring the membrane to an epifluorescence microscope which is fitted to a motorised stage. This stage, which is controlled by the ChemScan RDI, can be driven to the location of each fluorescent event for a rapid confirmation of all results.

9.4.4 Molecular techniques Hybridisation techniques using various types of probes have been used for the detection of specific pathogenic bacteria, viruses and parasites in water (Abbaszadegan et al., 1991; Dubrou et al., 1991; Knight et al., 1991). Because of their low sensitivity, these techniques have been used mainly for the identification of micro-organisms in polluted water and have to a great extent been replaced by PCR-based techniques. In situ hybridisation has been used for the direct detection of bacteria in water samples. Only active bacteria should be detected because the oligonucleotide probe is directed at the rRNA of the bacterium. After hybridisation, the organisms can be detected with a microscope or flow cytometer (Manz et al., 1993; Manz et al., 1995). The polymerase chain reaction (PCR) technique has recently received most of the attention in the development of rapid detection methods. This is due mainly to the excellent specificity, improved sensitivity, applicability to any group of micro-organisms and ease of detection of results. It is used mostly for the detection of pathogens in water but can also be used for indicator bacteria (Alvarez et al., 1993). PCR can be used as a screening, quantitative or characterisation technique. By using the PCR, a selected gene sequence specific to a group of organisms or a single species can be selectively amplified, increasing the chance of detection of low numbers of organisms within a complex mixture of micro-organisms and particulate. The replication process involves purification and extraction of cellular DNA, followed by melting of the DNA to break down double stranded DNA to single strands. Oligonucleotide primers (commonly Taq) hybridise to regions of the DNA flanking the target sequence using DNA polymerase enzyme in the presence of free deoxynucleotide triphosphates, resulting in duplication of the


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target sequence (Steffan and Atlas, 1991). This procedure is repeated over a number of cycles to exponentially increase the quantity of target DNA. High temperature cycles, to melt the DNA, are alternated with cool cycles, which provide the optimal temperature for hybridisation. PCR amplification time is limited by the length of time required for heating and cooling cycles. The more recent PCR instruments utilise rapid heating and cooling to reduce PCR cycling times. Successively the amplified sequence can easily be detected by means of techniques such as electrophoresis, hybridisation, high performance liquid chromatography or ELISA. PCR has been used for the direct detection of bacteria, protozoan parasites and viruses in water (Bej et al., 1991; Mahbubani et al., 1991; Toranzos and Alvarez, 1992; Abbaszadegan et al., 1993; Graff et al.,1993; Mayer and Palmer, 1996). The main concern with the use of PCR-based techniques for the direct detection of all types of micro-organisms in water is about infectivity and viability. In particular, no PCR method has been proved reliable for the detection, enumeration and examination of viable cells, because nucleic acid fragments from cells which may have been alive or dead, metabolically active or inactive, or even from previously lysed cells, may be amplified. Nevertheless, recent studies have suggested that methods to detect mRNA represent a promising approach for distinguishing bacterial viability (Sheridan et al., 1998). Furthermore, the use of reverse transcriptase PCR (rt PCR) can be used for the detection of viable organisms (Kaucner and Stinear, 1998). The technique also needs to be combined with concentration steps. Another problem with PCR-based techniques is that they only supply presence-absence data. Nevertheless, at present, different methods for the quantification of PCR products have been developed by adding known quantities of competitive DNA or by Most Probable Number PCR or by utilising fluorescence to quantify amplified DNA products.

9.5

Developing online monitors

Historically, physical, chemical, and biological parameters associated with producing drinking water have been monitored using routine grab sampling in source waters, treatment plants, and distribution systems, followed by analysis in the laboratory and manual or computer-assisted data handling. This approach collected only a relatively small data set to describe the sample variance. Automation has increased the amount of data produced and the ease of data handling and analysis. Online monitor development has included automation of sampling, analysis, and reporting functions. The online monitoring can be defined as unattended (except for routine maintenance) sampling, analysis, and reporting of a parameter; it produces data at a greater frequency with respect to the traditional grab-sample monitoring. It also allows real-time feedback for water quality characterisation for operational

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and regulatory decisions. Online monitoring may also be used as a screening or warning tool rather than a replacement for grab sampling of health-related parameters. In France, Germany, Italy, the Netherlands, Spain, and the United Kingdom, a relatively small number of large water companies supply a large portion of the population on a National or international basis. These companies perform online monitoring throughout the entire water cycle (from source to distribution) because facilities are operated remotely or because certain analytes require frequent data collection in order to ensure adequate treatment. Nevertheless online monitors are not available for measuring all parameters for which a critical demand exists in the drinking water sector. In fact, while automated, online measurement technologies have been developed for various physico-chemical parameters such as turbidity, particles, etc., automated online or in situ microbiological testing remains largely unrealised. On the biological point of view, two kinds of monitors can be distinguished: monitors that use biological species as sentinels for in water presence of contaminants of concern, such as toxic chemicals, and monitors that screen for the presence of specific biological species, such as pathogenic protozoa (Giardia and Cryptosporidium) and bacterial indicators. At the present time, generally speaking, automated online monitors for microbiological testing are indeed not in widespread use and most are still in development. In fact, until now there are still difficulties for setting up methods with an online capability for continuous monitoring. The biggest issues to be resolved include detection sensitivity and specificity, analysis time, data storage and transfer, and system cost. In this group of online monitors some biosensors (Section 9.4) could be included. In fact, an ideal biosensor would enable in situ, real-time detection of viable target micro-organisms, at concentrations as low as 1-10 cells/100 ml, by relatively untrained staff. However, biosensors are not currently the best choice for the microbiological evaluation of water samples containing low and moderate contamination, such as those characterising water for human consumption. Nevertheless industrial developments in this field have prospects of success. Now, an online instrument is utilised and its performance is evaluated for the detection of indicator organisms in the course of a European project (Sections 9.4 and 9.6). These technologies could have high operating relevance for the indicator bacteria because their presence, detected through a continuous monitoring, could be an early warning of failure or cross-connection with sewerage lines in drinking water distribution systems.

9.5.1 Automated devices for the detection of Giardia and Cryptosporidium Currently, automated devices for the detection of Giardia and Cryptosporidium are in a quite advanced development. In fact, the importance of automated methods being developed to detect and quantify these protozoans in waters is


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related to two orders of problems: these protozoans are known as human pathogens and are resistant to conventional treatment practices. As such, their presence can justify an immediate operational response. The two protozoan parasites are ubiquitous in the aquatic environment worldwide and have been implicated as the causative agents of outbreaks of waterborne enteric disease in humans. Their transmissive stages, oocysts and cysts, are voided by infected persons or animals and enter surface water through direct input, discharges of treated or untreated sewage, run-off or discharges of manure from agricultural lands and in pristine waters. The persistence of (oo)cysts in the aquatic environment, their infectivity and resistance to chemical disinfectants make the (oo)cysts of the parasites critical pathogens for drinking water production from surface water source and for recreational water (LeChevallier et al., 1991; Rose et al., 1991; De Abramovich et al., 1996; Graczyk et al., 1997; Fricker, 2002; Bonadonna et al., 2002). Recently, several systems have been described that may be appropriate for online measurement of Giardia and Cryptosporidium. These systems are still under development. The online innovations are mainly linked with new detection technologies. The systems described in the following paragraphs can be operated automatically and are claimed to be specific enough to eliminate the need for human verification. Multiangle, multiwavelength particle characterisation The multiangle, multiwavelength approach uses UV-visible light absorption and scattering at several observation angles. The absorption spectrum is used to estimate particle concentration, density, and chemical composition. The scattering data are used to measure particle size and molecular weight distributions. These spectral characteristics allow the identification and quantification of particles having a size range of 10 nm to 20 m, including Cryptosporidium oocysts (4 to 6 m) and Giardia cysts (8 to 15 10 m). Some technical limitations are yet to be resolved, especially those associated with the interpretation of spectral characteristics. In fact, some changes in diffusion and absorption characteristics have been observed in relation to quantity and chemical nature of the interfering particles. These spectral changes can result in a high number of false-negative or positive results. The spectral characteristics of Cryptosporidium and Giardia, for instance, are speciesspecific, and flow cytometry studies have shown that the light diffusion characteristics of Cryptosporidium oocysts change with the stage age (Compagnon et al., 1997). Multiangle light scattering (MALS) The Multiangle light scattering (MALS) technique has been used to detect various types of microscopic particles, including but not limited to E. coli, phytoplankton, and algae. This technique’s ability to detect Cryptosporidium parvum has been successfully tested in selected waters in a laboratory environment (Gregg, 2000). MALS relies on simultaneous measurement of

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various scattered light angles. The light source is a solid-state laser that provides a coherent monochromatic light source, typically using red wavelength (e.g., 632.8 nm). Water flows freely through the sensing device and particles pass through the laser beam and generate unique light-scattering fingerprints. They automatically and electronically are compared to an existing library of optical fingerprints. Identification is essentially instantaneous, and about 1 L of water can be completely scanned in 1 hour. Currently, the studies focus on the sensitivity and accuracy of the MALS technique in various water types and its ability to detect morphological changes of Cryptosporidium parvum oocysts. These approaches remain interesting but require further progress before onsite application can be considered.

9.6

Future trends

The industrial market for microbiology quality testing in environmental, food, beverage and pharmaceutical sectors, comprises approximately 800 million tests world-wide, only considering the ‘indicator’ tests and it is growing due to public health concerns and increased attention to food and water safety, increasing regulatory controls, economic pressures on producers to reduce delivery times, stock levels and wastage as well as protecting brand values. The European water industry produces some 900 000 000 tonnes of water per hour for domestic and industrial use. Fifty to sixty organisations are supplying water in the European Union and all have central and local laboratories where routine analyses are performed. It is estimated that there are some 1100 waterworks in Europe where large numbers of samples are tested for microbial contamination. About 1.2–1.5 million compliance tests are carried out in the European Union each year. This shows how appropriate water quality controls are important for this sector, and not only for the safeguard of public health but even for the economical perspectives. All the commonest methods for the microbiological examination of water are retrospective. There have been considerable efforts to try to develop new methods for the rapid detection of micro-organisms in water but most are complex and require specialised equipment and highly trained laboratory staff. At present the ideal of real-time analysis cannot be achieved, but developments during the last ten years have made it possible to detect many indicator organisms and pathogens in water within the same day. Sensitivity is still a major concern, especially when monitoring drinking water. To improve sensitivity, attention should be given not only to culture and direct detection techniques, but also to concentration and separation methods. The methods described in this chapter are by no means inclusive of all technologies in this area; in Table 9.1 some characteristics of the described technologies are reported. Most of them are still in the research and development phase or have only very recently been made available publicly, and questions remain about their utility and feasibility for early warning purposes.


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Table 9.1 Some features of technologies currently available for the detection and the enumeration of micro-organisms in environmental samples Technology

Speed of detection

Limit of detection

Screening Enzyme assay Bioluminescence Biosensors

< 1–12 hours 1 min–48 hours < 1 min–30 min

1 organism/sample 103–104 organisms 104–109 organisms

Quantitative methods Plate culture Enzyme activity (MF) Enzyme activity (MPN) Impedance

24–72 hours 18–24 hours 18–24 hours 6–48 hours

1 organism/sample 1 organism/sample 1 organism/sample 105–106 organisms

2–4 hours

–

15–30 min 10 min–1 hour+

– –

depending upon stain few min (flow injection) 2–3 hours (solid phase) < 1 hour depending upon probe

organism/sample 104–105 organisms

3–10 min 3 min depends on the operator

10–102 organisms 1 organism/sample 1 organism/sample

< 1 min

102–104 organisms

Pre-enrichment methods Plate culture Immuno-magnetic Separation (IMS) PCR Labelling technologies Staining Immunoassay Nucleic probe Detection Instruments Flow cytometry Laser scanning Epifluorescence microscope Luminometer

104–105 organisms

There are currently two commercially available products that may be applied to monitoring water quality, the ColifastÕ Analyzer and the ColilertÕ 3000. Both methods convey the drawbacks of enzymatic assays involving non-specific organism expression of enzymes and non-expression by certain E. coli strains, and the growth rate of organisms limits the time to detection. In this context the ‘Demonstration of a rapid microbial monitor for operations and quality monitoring in the water industries’ project was proposed to the European Commission and at the present time it is in progress. Its main global objective is to demonstrate in water industries that a sensitive and rapid micro-organisms atline monitor or laboratory system, the ColifastÕ Analyzer, is comparable to the relevant reference methods, and enables ‘Early Warning’ of various indicators and semi-automation of the methods. Among non-cultura1 methods for the detection of micro-organisms, some molecular methods could revolutionise water testing. The DNA microchip array is

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currently under development, and holds promise for the rapid, sensitive detection of micro-organisms in water. This method is a new technology that allows for the detection and identification of multiple organisms within four hours. Up to 400,000 oligonucleotides are synthesised in situ on a miniaturised glass substrate. DNA fragments that are labelled with a fluorescent marker are then floated across the chip array. A positive hybridisation result is detected by an intense fluorescence reaction. Because the oligonucleotide sequence for each position on the chip is known, micro-organisms in the water sample can be identified. Despite the numerous shortcomings of traditional growth-dependent methods, they still remain the cornerstone of microbiological quality assessment in most applied fields. Nevertheless, using image analysis, robotics, biosensors and molecular technologies, the possibility of rapid, automated monitoring for specific micro-organisms may be possible in the foreseeable future.

9.7

Sources of further information and advice

To ensure the full protection of drinking water, a technology-based early warning monitoring system should be the first component of a comprehensive programme to protect public health. Technological advancements are gathering speed to produce the ultimate rapid microbiological analysis system. The ideal technique for the enumeration of faecal indicators from water should be portable, flexible, speed, economic and ease to use. Its performance should be at least as accurate and precise as reference methods and it should provide cost benefits through time and labour savings. The current market for rapid analysis technologies provides a number of techniques which may fit into one or more of these categories and some of these may have an important application for the automation in aquatic microbiology in the future. However, it has to be outlined that the development and the choice of a new technology need the method performance to be evaluated with specially designed experiments. In this context, validation programmes must be prepared and acceptance criteria established. The new method, which is found acceptable after the validation steps have been completed, should then be tested against the reference method. This, as a final step before the routine use, should then demonstrate that there are no major differences between the two methods. Here some references are reported that can help in the application of the procedures for validation and comparison of methods: COMMISSION OF THE EUROPEAN COMMUNITIES, COMMUNITY BUREAU OF REFERENCE. MOOIJMAN KA, IN’T VELD PH, KOEKSTRA JA, HEISTERKAMP SH, HAVELAAR AH, NOTERMANS SHW, ROBERTS D, GRIEPINK B AND MAIER E,

Development of microbiological reference materials., Report EUR 14375 EN, 1992, ISSN 10185593. DRINKING WATER INSPECTORATE FOR ENGLAND AND WALES. Comparison of microbiological methods of analysis, organisation and supervision of performance tests. DWI Contract 70/2/128, 2001.


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DRINKING WATER INSPECTORATE,

Ashdown House, 123 Victoria Street, London, SW1E 6DE Comparison of Methods for Drinking Water Bacteriology – Cultural Techniques. www.dwi.detr.gov.uk/regs/infolett/2000/info500.htm. ISO CD 17994. Water Quality – Criteria for the establishment of equivalence between microbiological methods. Committee draft 2001-06-15. LIGHTFOOT NF and MAIER EA (1998), Microbiological Analysis of Food and Water: Guidelines for Quality Assurance, Amsterdam, Elsevier Science. LIGHTFOOT NF, TILLETT HE, BOYD P. and EATON S (1994), ‘Duplicate split samples for internal quality control in routine water microbiology’, Lett Appl Microbiol, 19, 321–4. ¨ SI (2001), ‘Comparison of methods NIEMI RM, HEIKKILA MP, LAHTI K, KALSO S and NIEMELA for determining the numbers and species distribution of coliform bacteria in well water samples’, J Appl Microbiol, 90, 850–8. STEERMAN, R L (1955), ‘Statistical concepts in microbiology’, Bacteriol Rev, 19, 160–215. WATER QUALITY – GUIDANCE ON VALIDATION OF MICROBIOLOGICAL METHODS, TECHNICAL REPORT ISO TR 13843:2000 INTERNATIONAL STANDARDS ORGANISATION, GENEVA.

9.8

References

and ROSE JB (1991), ‘Detection of Giardia cysts with a cDNA probe and applications to water samples’, Appl Environ Microbiol, 57, 927– 931. ABBASZADEGAN M, HUBER MS, GERBA CP and PEPPER IL (1993), ’Detection of Enteroviruses in groundwater with the polymerase chain reaction’, Appl Environ Microbiol, 59, 1318–1324. ALVAREZ AJ, HERNANDEZ-DELGADO EA and TORANZOS GA (1993), ‘Advantages and disadvantages of traditional and molecular techniques applied to the detection of pathogens in water’, Wat Sci Tech, 27, 253–256. ANGLES D’AURIAC MB, ROBERTS H, SHAW T, SIREVAG R, HERMANSEN LF and BERG JD (2000), ‘Field evaluation of a semi-automated method for rapid and simple analysis of recreational water microbiological quality’, Appl Environ Microbiol, 66, 4401– 4408. BEJ AK, MAHBUBANI MH, DICESARE JL and ATLAS RM (1991), ‘Polymerase chain reactiongene probe detection of microorganisms by using filter-concentrated samples’, Appl Environ Microbiol, 57, 3529–3530. BONADONNA L, BRIANCESCO R, OTTAVIANI M and VESCHETTI E (2002), ‘Occurrence of Cryptosporidium oocysts in sewage effluents and correlation with microbial, chemical and physical water variables’, Environ Monit Assess, 75, 241–252. BRENNER KP and RANKIN CC (1990), ‘New screening test to determine the acceptability of 0.45 lm membrane filters for analysis of water’, Appl Environ Microbiol, 26, 332– 336. BUDNICK GE, HOWARD RT and MAYO DR (1996), ‘Evaluation of Enterolert for enumeration of enterococci in recreational waters’, Appl Environ Microbiol, 62, 3881–3884. COMPAGNON B, ROBERT C, MENNECART V, DE ROUBIN MR, CERVANTES P and JORET JC (1997), ‘Improved detection of Giardia cysts and Cryptosporidium oocysts in water by flow cytometry’, in Proceedings of the AWWA Water Quality Technology Conference, Denver, Co, Am Water Work Ass. ABBASZADEGAN M, GERBA CP

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Part II Product quality


10 Rapid techniques for analysing food additives and micronutrients C. J. Blake, Nestle´ Research Centre, Switzerland

10.1

Introduction

Today more than 2500 different additives are added to food products. Branen and Haggerty (2000) have classified these additives into six major categories: preservatives, nutritional additives, flavouring agents, colouring agents, texturising agents and miscellaneous additives. Several lists of additives are available. In Europe and other parts of the world the E system developed by the European Union provides a comprehensive list. Nutrients are not included in the E system. An alternative international numbering system (INS) has been developed by the Codex Alimentarius Commission. Micronutrients are also added to food products and may in some cases also be classified as additives. In the food industry analytical methods for these compounds can be divided into reference methods and rapid methods. However the borderline between these classes of methods is often indistinct. The ‘reference methods’ are often used to calibrate or to check the performance characteristics of rapid methods. Blake (2002) has recently reviewed reference methods for food additives while analyses of vitamins by HPLC, microbiological assay and other techniques are described by De Leenheer et al. (2000), Ball (2000) and Song et al. (2000). Many of the reference methods have been issued by international organisations such as the Association of Official Analytical Chemists International (AOAC International), Commission European Normalisation (CEN), International Dairy Federation (IDF) and the International Standardisation Organisation (ISO) and have been validated through collaborative studies. This type of method is of great importance as analytical laboratories are seeking accreditation via ISO, EN or related systems where the use of official or well-validated methods is mandatory.

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Rapid (or alternative) methods provide faster analyses that can be performed at or near the food production line. Thus more rapid action can be taken to correct for incorrect addition of micronutrients or additives or to check nutrient premixes before use. The ideal situation would be to develop on-line measurement techniques but this is still a long-term aim for the future. However, a range of near-line techniques are available. Rapid methods are not always simple or cheap, but the aim is that they can be performed either by an unskilled line-operator or, if this is not possible, by a trained technician in a line-laboratory. For the latter case, this may involve relatively sophisticated techniques like high performance liquid chromatography (HPLC), gas chromatography (GC), inductively coupled plasma atomic emission spectrometry (ICP-AES), near infrared (NIR) or X-ray fluorescence (XRF) techniques, but may also involve simpler test-kit or sensor/biosensor procedures.

10.2

The range of rapid methods

As mentioned above the methods fall into several categories: • chromatographic methods which are normally off-line, demanding skilled technicians • indirect methods like NIR, Fourier Transform Infrared (FTIR), energy dispersive–X-ray fluorescence (ED-XRF) or wavelength dispersive–X-ray fluorescence (WD-XRF) which are usually near-line, but which can be operated by less-skilled personnel once calibrated • sensors/biosensors which can be used off-line or near-line with some potential to be used on-line in the future • various enzymatic, test-kit or simple colorimetric procedures which need to be performed in a line laboratory • ICP-AES or F-AAS (flame atomic absorption spectrophotometry) techniques for mineral analyses which also need to be performed in a line-laboratory.

10.3

Chromatographic techniques

HPLC is the most useful and widely applied chromatographic method for analysis of additives and certain vitamins in food products. Its theory and application is described in numerous publications but Nollet (2000a) focuses on food analysis by HPLC. In recent years the technology of HPLC columns has markedly improved enabling more reproducible and robust separations. The range of detectors has also been improved with developments in diode-array detection, post-column reaction with fluorescence detection, evaporative light scattering detection and mass spectrometry, improving the selectivity and specificity of analysis.

Rapid techniques for analysing food additives and micronutrients

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Blake (2002) thoroughly reviewed HPLC methods for additives including: colours, sweeteners, sugars, antioxidants, preservatives, emulsifiers and stabilisers and the reader will find much useful information. Direct methods of analysis of food samples by HPLC were reviewed by Bovanova and Brandsteterova (2000). Key steps are off-line and on-line solid-phase extraction (SPE) and on-line dialysis methods to speed up sample preparation. HPLC is generally accepted as the reference method for the individual analysis of the fat-soluble vitamins A, E, D3, and K1 as well as tocopherols. Internationally accepted methods have been published by the AOAC International, CEN and other organisations. This technique generally involves the following steps: • saponification followed by solvent extraction or direct solvent extraction • HPLC analysis using UV or fluorescence detection. Efforts have been made to reduce the time-consuming sample preparation steps. One approach involves direct solvent extraction avoiding saponification (Ye et al., 1998, 2001), for vitamin E in margarine and reduced fat products and for total vitamin E and -carotene in reduced-fat mayonnaise. A similar approach was also reported for extraction of all-trans-retinyl palmitate, -carotene and vitamin E in fortified foods (Ye et al., 2000). A recent advance is in the use of an on-line supercritical fluid extraction (Turner et al., 2001) with immobilised lipase hydrolysis for the extraction of vitamin A and E esters in dairy and meat products prior to HPLC analysis. This procedure was recently collaboratively studied for vitamins A, E and -carotene (Mathiasson et al., 2002) for a wide variety of food matrices. It was reported that sample throughput was at least 12 per day, about double that of the conventional HPLC methods. Since the classical saponification/extraction methods are similar for the vitamins A, D and E, it would be advantageous to determine several vitamins in one chromatographic run. Multi-analyte methods for fat-soluble vitamins were reviewed by Eitenmiller and Landen (1999). A novel approach was described by Gomis et al. (2000) in which fat-soluble vitamins (A, D2, D3, E, K1, retinyl acetate, retinyl palmitate, tocopherol acetate) and provitamins D2 and D3 in milk were separated simultaneously by reversed-phase fused-silica microcolumn chromatography with UV detection. Recoveries of each vitamin spike were in the range 89–107 per cent; however, this method needs further validation. HPLC methods have also been reported for analysis of water-soluble vitamins in certain matrices (see Table 10.1). Some of these methods are in the process of approval by the CEN. These HPLC methods are often complex, requiring pre- or post-column reactions to improve the specificity of detection and often using fluorescence detection. A multi-method for several B-vitamins was reported by Albala-Hurtado et al. (1997). However, it needs a more complete validation. Related micronutrients like 50 -mononucleotides, added to dietetic and clinical nutrition products, can be analysed by HPLC-UV (Perrin et al., 2001).

188


Table 10.1

Examples of HPLC methods for analysis of water-soluble vitamins

Vitamin C Biotin Folic acid Niacin Pantothenate Thiamine and riboflavin Vitamin B6

Furusawa (2001) Lahe´ly et al. (1999) Ndaw et al. (2001) LaCroix et al. (1999), Rose-Sallin et al. (2001) Woollard et al. (2000) Arella et al. (1996) Bergaentzle´ et al. (1995), Reitzer-Bergaentzle´ et al. (1993)

Since different extraction methods are used for each water-soluble vitamin, multi-vitamin sample preparation methods are needed. Some progress is being made by the group of Professor Hasselmann (Ndaw et al., 2000) using enzymatic hydrolyses to extract several vitamins (B 1 , B 2 and B 6 ) simultaneously. More work is needed in this area. Some attempts have been made to automate sample preparation and HPLC extraction using robotics. Russell et al. (1998) described a robotic system for automated determination of riboflavin in foods while Gamiz-Gracia et al. (1999) described an automated analysis of vitamins A and E. Liquid chromatography-mass spectrometry (LC-MS) and tandem LC-MS/MS is a promising multi-analyte technique for the future. Several papers describe the analysis of individual vitamins: folic acid (Stokes and Webb, 1999), tocopherols and carotenoids (Rentel et al., 1998) and vitamin E (Stoeggl et al., 2001). A multi-analyte approach would be more useful and cost effective. Ion chromatography is another useful and robust separation technique involving separation of anions or cations on an ion-exchange column (Henshall, 1997). The column packings for ion chromatography consist of ion-exchange resins bonded to inert polymeric particles (typically 10 m diameter). Detection is usually made by conductimetry or electrochemistry and occasionally by UV. Suppressors reduce eluent background conductivity to facilitate optimum conductivity detection. Some applications are given in Table 10.2. Another traditional but still useful technique is thin-layer chromatography (TLC), which is particularly useful for separation of natural and synthetic food colours (Hirokado et al., 1999). Sherma (2000) reviewed the use of TLC in food and agricultural analysis. Capillary electrophoresis (CE) is a fairly recent analytical technique that allows the rapid and efficient separation of sample components based on differences in their electrophoretic mobilities as they migrate or move through narrow bore capillary tubes (Frazier et al., 2000a). In spite of considerable developments CE still suffers from problems of poor peak shape, lack of sensitivity and poor robustness. It has not yet been accepted in the food industry due to the absence of well-validated analytical procedures applicable to a broad range of food products. Some recent examples of applications include: eight colorants in milk beverages (Huang et al., 2002) and the simultaneous analysis of artificial sweeteners, preservatives and colours in soft drinks (Frazier et al.,

Rapid techniques for analysing food additives and micronutrients Table 10.2

189

Examples of ion-chromatographic methods for analysis of food additives

Aspartame Carrageenans and agars containing 3,6-anhydrogalactose Choline Inositol Nitrates and nitrites Polyphosphates Sugars Sugar alcohols Sucralose Sulfites Synthetic food colours Artificial sweeteners, preservatives, caffeine, theobromine and theophylline

Qu et al. (1999) Jol et al. (1999) Laikhtman and Rohrer (1999) Tagliaferri et al. (2000) Siu and Henshall (1998); Kaufman et al. (2000) Sekiguchi et al. (2000); Kaufman et al. (2000) Cataldi et al. (2000) Corradini et al. (1997) Ito (1999) Wygant et al. (1997) Chen et al. (1998) Chen and Wang (2001)

2000b). Sa´decka´ and Polonsky´ (2000) reviewed electrophoretic methods in the analysis of beverages. The principles of gas chromatography (GC) applied to food analysis are well covered in numerous publications (Cscerha´ti and Forgaćs, 1999). Capillary GC or GC-MS are widely used for flavour analysis. However, few additives are sufficiently volatile for direct analysis by GC without prior derivatisation. Thus the application of GC for food additives is much less widespread than that of HPLC. Some recent examples of applications are given. Gonza´lez et al. (1999) described a GC method for the preconcentration and simultaneous determination of antioxidant and preservative additives in fatty foods. Ochiai et al. (2002) described the use of stir-bar sorptive extraction for the simultaneous and quantitative determination of several preservatives in soft drinks, wines, vinegar, soy sauce and quasi-drug drinks with thermal desorption GC-MS.

10.4

X-ray fluorescence and other indirect methods

10.4.1 X-ray fluorescence This non-destructive technique is very useful for rapid in-line analysis of inorganic additives in food products (Price and Major, 1990; Anon, 1995). It includes a family of related techniques, WD-XRF or ED-XRF. The principles of this technique related to food analysis are described by Pomeranz and Meloan (1994). The main components of a laboratory ED-XRF are the X-ray source (normally an X-ray tube) and the detector e.g. liquid nitrogen or Peltier cooled Si(Li) detectors. Some benchtop instruments have proportional counters, or newer Peltier cooled PIN diode detectors. The most recent and fastest growing detector technology is the Peltier cooled silicon drift detector (SDD). Another important component is the X-ray tube filter whose function is to absorb and transmit some energies in order to reduce the background counts in the region of

190


interest while producing a peak that is well suited to exciting the elements of interest. Secondary targets are an alternative to filters. A secondary target material is excited by the primary X-rays from the X-ray tube, and then emits secondary X-rays that are characteristic of the elemental composition of the target. One specialised form of secondary target is the polarising target which provides high quality measurements. The second major technique is WD-XRF which also uses an X-ray tube source to directly excite the sample. Because the overall efficiency of the WDXRF system is low, X-ray tubes in larger systems are normally rated at 1–4 kilowatts. There are some specialised low power systems that operate at 50 to 200 watts. A diffraction device, usually a crystal or multi-layer, is positioned to diffract X-rays from the sample toward the detector at a specific angle. Collimators are normally used to limit the angular spread of X-rays, to further improve the effective resolution of the WDX system. Because the detector is not relied on for the system’s resolution it can be a simple proportional counter or other low-resolution counter. A simultaneous WD-XRF analyser will have a number of fixed single channels for individual elements usually formed in a circle around the sample with the X-ray tube facing upward in the middle. Other sequential WD-XRF analysers use a goniometer to allow the angle to be changed, so that one element after another may be measured in sequence. There are also combined sequential/simultaneous instruments. XRF is a comparative measurement technique, thus a calibration needs to be established involving the intensity measurements for each element against the concentration of the element. The key step is to establish a calibration covering the elemental concentration ranges to be met in practice and using a set of samples of the same matrix as those to be analysed routinely. The ‘reference set of samples’ must be analysed by a reliable method like ICP-AES or F-AAS. Once the instrument is calibrated with a set of ‘reference products’, and the calibration validated with a second set of similar products, it can be readily used by non-skilled operators. Dry materials like powders can be pressed into a pellet or simply poured into a sample cup. Semi-liquid or wet products can also be placed in the sample cups. Calibrations can be stored by the instrument software and restandardised on a daily basis with reference materials. Some typical applications include: determination of salt content in snack foods via analysis of chloride, and analysis of fortified minerals like iron and calcium in infant formula or petfoods and calcium in fortified fruit juices. Another application is the determination of the food colour titanium dioxide in bakery products and confectionery. Because no reagents or chemicals are involved, it can be used for in-line quality control and its main advantages lie in its simplicity of use and speed of analysis, typically 5–10 minutes per sample. One of the main difficulties is to apply the technique to broad classes of food products, and often individual calibrations are required per food product. Another disadvantage is the high cost of XRF equipment.

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191

10.4.2 Near infrared and Fourier Transform infrared spectroscopy Applications of NIR and FTIR techniques for food and agricultural analysis have been reviewed recently by Reh (2001) and Williams and Norris (2001). Very few applications have been described for analysis of additives or vitamins in food products. One interesting application is for controlling vitamin premixes used for fortification of food products by attenuated total reflectance (ATR) accessory with FTIR. Four vitamins were analysed – B1, B2, B6 and niacin (nicotinic acid) – in about ten minutes (Wojciechowski et al., 1998). The partial least squares technique was used for calibration. The precision of measurements was in the range 4–8%, similar to those obtained for the four vitamins by the reference HPLC method. Another publication (Shi et al., 2000) described the quantitative determination of vitamin E by NIR. Coupled FIA-FTIR has been used to determine caffeine in soft drinks (Daghbouche et al., 1997). The sample was passed through a C18 SPE cartridge and extracted with chloroform prior to FTIR analysis. A more direct determination of caffeine content in soft drinks by FTIR-ATR spectroscopy was reported by Paradkar and Irudayaraj (2002). The spectral region between 2800 and 3000 cmÿ1 was used with a correlation coefficient (R2) between 0.97 and 0.99 for different drinks. The method could predict caffeine content in about five minutes.

10.4.3 Conductimetry Conductimetry-based analysers are often used for rapid salt determination. The digital salt analysers need periodic checking against a reference method for chloride e.g. potentiometry (AOAC Int., 2000).

10.5

PCR, immunoassays and biosensors

A new method of analysis for specific additives involves the polymerase chain reaction (PCR) for rapid amplification of specific DNA fragments which can then be analysed (Schwagele, 1999). The advantage is that DNA is present in every cell of the subject, unlike specific proteins. PCR for food analysis is limited by the lack of reference materials, and by bioactive substances in foods. A recent example was published by Meyer et al. (2001). A polymerase chain reaction (PCR) was developed to differentiate the thickening agents locust bean gum (LBG) and the cheaper guar gum in finished food products. The presence of

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