Food Biochemistry and Food Processing (2 edition)

BLBS102-c45 BLBS102-Simpson March 21, 2012 14:38 Trim: 276mm X 219mm Printer Name: Yet to Come

45 Biosensors for Sensitive Detection of Agricultural Contaminants, Pathogens and Food-Borne Toxins 859

by the farmer, and at a minimal cost (Mitchum et al. 1996).

As further examples, grain and nuts may be inspected for the

presence of fungal contamination, while bacterial spoilage may

be indicated by the presence of an uncharacteristically strong

odour, such as in coleslaw and milk. However, these tests are

not sufficient for providing confirmation to the consumer that

the product satisfies regulations with respect to acceptable max-

imum residue limits (MRLs). Furthermore, it is not possible to

provide accurate quantitative or qualitative analysis of individual

contaminants through these methodologies, including those that

cannot be seen by visual inspection (e.g. mycotoxins). Hence,

it is common practice for food samples to be removed and sent

to an external laboratory where comprehensive in situ analysis

may be performed (Giraudi and Baggiani 1994).

Instrumentation-Based Analysis

There is a selection of different methodologies available for

quality determination, and some of the more relevant exam-

ples are discussed in this section. Product firmness can be de-

termined through the implementation of the Magness-Taylor

test, namely a destructive method that assesses the maximum

force required to perforate the product in a specific way (Abbott

2004). This has been applied for the analysis of fruit, including

pears (Gomez et al. 2005). The non-destructive determination ́

of elasticity may also be permitted through the measurement

of acoustic responses, with the signal being interrogated using

fast Fourier transform-based analysis. Shmulevich et al. (2003)

demonstrated the efficacy of this approach for evaluating the

firmness of apples, and monitored product softening over time

in a controlled atmosphere environment. While these methods

are suitable for monitoring the structural properties of the prod-

uct in question, they do not permit rigorous quality evaluation.

More suitable analytical methods include near-infrared (IR)

spectroscopy, implemented by Berardo et al. (2005) for the de-

tection of mycotoxigenic fungi and associated toxic metabolites,

and scanning electron microscopy, applied for the inspection

of ultrastructural changes of the epicuticular layer of oranges

treated with fludioxonil, a pesticide used to control the growth of

twoPenicilliumspecies (Penicillium digitatumandPenicillium

italicum) (Schirra et al. 2005). Furthermore, gas chromatog-

raphy (GS) or mass spectrometry (MS) and high-performance

liquid chromatography (HPLC) are accurate and highly sen-

sitive methods for the detection of an array of contaminants,

including pesticide, herbicide and toxins residues. The latter

method may also be used to detect the presence of indicator

molecules that are representative of product freshness, including

flavonoids (MacLean et al. 2006), while liquid chromatography

coupled with mass spectrometry (LC-MS) can accurately mon-

itor product bitterness. This was demonstrated by Dourtoglou

et al. (2006) for the analysis of olives (Olea europaea). In spite

of the efficacy of these analytical platforms, the instrumentation

needed to perform this analysis is expensive and bulky and may

require extensive operator training. In addition, analysis times

may also be extensive, as many contaminants require lengthy

sample pre-treatment prior to assessment.

Here, we focus on the application of biosensor-based plat-

forms that are rapid, sensitive and reliable and are frequently

used for the detection of herbicide and pesticide residues, bacte-

rial and fungal pathogens and toxins (fungal and water-borne).

BIOSENSORS

A biosensor can be defined as an analytical device that incor-

porates a biological element for promoting biorecognition of

an analyte of interest (e.g. herbicide, bacterial cell or toxin).

A schematic representation of a biosensor, illustrating the three

main components of the system, namely a bioligand, a transducer

and a readout device, is shown in Figure 45.1. Biosensor-based

platforms can use a wide selection of different recognition el-

ements, including nucleic acid probes, lectins and antibodies

(Table 45.1). The focus in this chapter will be placed on the

use of antibodies for detection of contaminants that are of inter-

est to the food industry with examples of enzyme- and nucleic

acid-based detection also provided.

Analytical matrix

Transducer

Sensor surface

Antibody

Antigen

Computational data

Transducer analysisanalysis

Figure 45.1.General format of a biosensor. The biorecognition element is in contact with the transducer, which converts the signal to an

output shown on the computer. For illustrative purposes, an antibody-based platform is shown, with non-specific antigens represented by

squares and triangles, respectively.