ABSTRACT
A study in 2011 estimated that in the United States between the years 2000 and 2008, 9.4 million episodes of food-borne illness were caused by 31 major pathogens resulting in 55,961 hospitalizations and 1,351 deaths (Scallan et al. 2011). Similarly, in the European Union (EU), a total of 5,648 food-borne outbreaks were reported in 2011 resulting in 69,553 human cases, 7,125 hospitalizations, and 93 deaths (EFSA [European Food Safety Authority] 2013). This report also showed that in 2011 campylobacteriosis caused by the pathogen Campylobacter was the highest reported food-borne-related disease in humans (220,209 conrmed cases), followed by salmonellosis (95,548 conrmed cases), verotoxigenic Escherichia coli (VTEC) infection (9,485), and yersiniosis (7,017 conrmed cases). Listeria was seldom detected above the legal safety limit from ready-to-eat foods, resulting in only 1476 reported cases of listeriosis. Such statistics highlight the widespread prevalence of food-borne illness despite strict regulations governing food both at legislative and industrial levels. To protect public health, the monitoring for the presence of food-borne pathogens is critical, and EU commission regulation (EC) No. 2073/2005 sets maximum levels for certain contaminants in food, as summarized in Table 9.1
The contamination of food by pathogenic organisms can have serious economic consequences and presents a considerable risk to human health even at low concentrations (≈10-100 cells). To ensure the safety of the food we eat, it is imperative that these food-borne pathogens are detected at all stages of the food chain and that detection methods can meet the challenge of detection at such low concentrations. Due to the low numbers of pathogens that may be present in a sample, detection is difcult without highly sensitive detection systems. Culture methods remain the gold standard for detection, and they are the primary methods cited in the legislation for the determination of food-borne pathogens. While culturebased methods are relatively cost-effective, have good sensitivity, and ultimately provide the end user with useful qualitative and quantitative information, they are severely restricted by analysis time. For example, colony count estimation can range from 24 h for E. coli to 7 days for Listeria monocytogenes,
9.1 Introduction: Background and Driving Forces .............................................................................161 9.2 Optical Detection ..........................................................................................................................162
