Skip to main content
ARS Home » Southeast Area » Athens, Georgia » U.S. National Poultry Research Center » Quality and Safety Assessment Research Unit » Research » Research Project #430696

Research Project: Develop Rapid Optical Detection Methods for Food Hazards

Location: Quality and Safety Assessment Research Unit

2017 Annual Report


Objectives
The goal of the research is to develop and validate early, rapid, sensitive and/or high-throughput methods and techniques for detecting biological and physical hazards in poultry (food) products with optical sensing methods and instruments. Thus, the nature of the research is to combine chemistry and engineering disciplines (optical, agricultural, and food) with microbiological techniques to solve food safety detection problems in poultry (food). Specific objectives are: Objective 1: Develop high-speed imaging methods for rapid detection of pathogens in live poultry flocks, and foodborne hazards, including foreign materials, in processed poultry products. Sub-objective 1A: Develop Salmonella surveillance system for early detection of diseased birds. Sub-objective 1B: Develop high-speed hyperspectral imaging methods and system for foreign material detection. Objective 2: Develop rapid methods and protocols for early detection, identification, and quantification of pathogens in poultry products (foods) using imaging spectroscopy. Sub-objective 2A: Develop hyperspectral microscope imaging (HMI) methods and system for early detection and identification of pathogen at the cellular level. Sub-objective 2B: Develop fluorescence in-situ hybridization (FISH) imaging methods to identify pathogenic bacteria at the cellular level. Sub-objective 2C: Develop nanobiosensor for pathogen detection with surface enhanced Raman spectroscopy (SERS) at the cellular level. Sub-objective 2D: Develop methods for intervention carryover for Salmonella detection. Sub-objective 2E: Develop methods for plate detection with optimized agar media at the colony level. Objective 3: Develop methods to detect biofilms in poultry processing facilities with optical technologies. In developing the methods assess if any biomarkers can be identified to enhance or improve the detection sensitivity or specificity.


Approach
Ensuring poultry meat is safe to eat is of utmost importance to producers and consumers alike and rapid and early detection of foodborne pathogenic bacteria and foreign material in poultry products is needed. This research, which is divided into three objectives, primarily investigates optical sensors for rapid or improved detection of pathogenic bacteria with imaging and spectroscopic methods. Obj. 1A: an early-warning imaging surveillance system will be developed to detect bile in poultry droppings from laying hens in their cages. These higher levels of bile have been linked to birds with very high levels of Salmonella. Spectra will be collected to optimize key wavelengths and then a color-imaging system will be optimized for wireless real-time monitoring. Obj. 1B: Building on the success of a high speed hyperspectral imaging system developed within the unit, research will be expanded to detect foreign materials in various processed poultry products. Spectral libraries of normal meat features (muscle, fat, skin) and foreign material (rubber, metal, plastics, bone) will be used to develop algorithms suitable for high-speed use and then tested in real time. Obj. 2A: Hyperspectral microscope imaging (HMI) will be used to classify and quantify pathogens commonly found in poultry and other meats. The focus will be on identifying single bacteria cells from chicken rinsate by combining cell morphology and spectral profiles into an automated method for counting and classifying pathogenic bacteria. Additionally, markers will be used to enhance detection or means to separate and concentrate the bacteria will be implemented (immunomagnetic beads). Obj. 2B: Multiplex fluorescence in-situ hybridization (m-FISH) will be combined with HMI to further enhance detection with new protocols that will combine multiplexed probes and enhanced HMI detection resulting in broader, more robust methods of identification. Obj. 2C: Surface enhanced Raman spectroscopy (SERS), utilizing aptamers or antibodies and nano-enhanced surfaces, will be studied for Salmonella detection in broiler meat. Both labeled and label-free SERS will be evaluated. Obj. 2D: At FSIS’s request, research to neutralize sanitizers, frequently used to reduce pathogens while processing poultry meat, will be conducted to prevent interference of those sanitizers on bacterial analysis. Four potential neutralizing agents (quaternary ammonium, peroxyacetic acid, acidified sodium chlorite, acid solution, and dibromodimethylhydantoin sanitizers) will be screened for efficacy. Obj. 2E: Hyperspectral imaging (HI) systems will be used to classify pathogenic serovars growing in agar plates and collaborations will explore additional agar additives (both chromogenic and non-chromogenic) that will help differentiate serovars of E. coli O157:H7 and other shiga-toxin producing E. coli (STEC). Obj. 3: First in the lab, and then in processing plants, HI systems will be used and paired with spray-on markers to enhance the detection of biofilms on equipment surfaces. This research is potentially collaborative with ARS Beltsville and will help to discriminate biofilms from other organic material.


Progress Report
Listeria innocua biofilms were produced as a model for pathogenic Listeria biofilms. A series of generally regarded as safe (GRAS) dyes, as well as non-GRAS dyes, were tested for their abilities to bind preferentially to specific components of the Extracellular Polymeric Matrix (EPM) formed by the biofilms. Results indicate that most of the dyes studied are not suitable for use as biofilm disclosing agents due to either 1) non-specificity, making discrimination of biofilm from other contaminants non-viable, or 2) low binding to any of the components of EPM, making observation of the dyed biofilm extremely difficult. One dye, Calcofluor White, exhibited promising results. The dye binds preferentially to the carbohydrate portion of the EPM, and under illumination with 365-nm radiation can disclose biofilms with high specificity compared to background contaminants also found in poultry processing environments. The challenge in implementing this dye as a tool to disclose biofilms in poultry processing environments is that it does not carry GRAS status, though material safety data sheet (MSDS) show no harmful effects. Label-free multiplex detection of foodborne pathogenic bacteria using surface plasmon resonance imaging (SPRi). Foodborne outbreaks caused by pathogenic bacteria are a serious public health concern. Traditionally such pathogens are detected individually which is time consuming. In order to improve the screening efficiency for common pathogens, it is desirable to detect multiplex pathogens in a single test to shorten the time and reduce the overall cost of food safety screening. ARS researchers at Athens, Georgia, have developed a method based on the SPRi technique to detect foodborne Salmonella cells on a sensor surface modified with anti-Salmonella antibody spots. Salmonella could be detected from chicken carcass rinse matrix without sample pre-treatment. This technique does not require expensive detection labels and is promising in multiplex screening of foodborne pathogens simultaneously, as the sensor chip can be modified with dozens of spots consisting of antibodies targeting different pathogenic species. Bacterial cell classification with hyperspectral microscopy. Hyperspectral microscope imaging (HMI) have shown potential as an early, rapid, and sensitive presumptive detection tool for identifying pathogenic bacteria on a cellular level. Classification accuracy of HMI was high at the serotype level of the same species of bacteria for Salmonella. However, to confirm HMI technology for pathogen detection, the consistency of spectral signatures from bacteria has to be validated. ARS researchers at Athens, Georgia, have investigated the impact of environmental growth stresses such as growth media, incubation temperature and pH on HMI cellular spectra. Testing the same Salmonella strain on a variety of environmental factors found that acidic pH values and high incubation temperatures influence the cellular spectra, most likely due to the outer membrane of the cell generating acid and heat response proteins. The bacteria’s growth media suggested that the cell’s spectra did alter slightly with media, while media with similar color indicators were spectrally similar. These results suggest that pathogens can be classified with a high accuracy if they are grown within a range of pH and temperature values which do not induce cellular stress. Visible/near-infrared (NIR) spectroscopy for detection of bile in poultry layer and broiler droppings. Bile is produced by the gallbladder and is a fluid with high salt content that aids in the digestion of lipids in the small intestine. When the gallbladder becomes infected, inflammation can result in excretion of large amounts of bile which changes the color of excreta from brown to green. Often extreme bile discoloration is an indicator of birds infected with Salmonella enteritidis. ARS researchers in Athens, Georgia, used visible and near infrared spectroscopy to identify the spectral characteristics of bile in droppings. This information can be used to monitor flock gut health with either a machine vision, multispectral imaging, or hyperspectral imaging systems which could result in a surveillance system for early identification of unhealthy birds. Advanced image processing techniques for detection of microbial colonies on agar plates. Although big data research in hyperspectral imaging is emerging in remote sensing and many tools and methods have been developed in many other applications such as bioinformatics, the tools and methods still need to be evaluated and adjusted in applications where conventional machine learning algorithms are still dominant. A preliminary study was conducted to find appropriate big data analytic tools and methods, with an emphasis on the state-of-art machine learning method known as deep learning. This deep learning method is being evaluated to identify foodborne pathogens on agar plates. Imaging modified MacConkey agar for Escherichia (E.) coli detection. Current methods of plating pathogenic E. coli result in ambiguity among the most concerning shiga-toxin producing E. coli (STEC), known as the “Big Six”, and other non-pathogenic background microflora. In recent years, an agar media was developed by ARS scientists at Clay Center, Nebraska, that has the potential to differentiate between the Big Six and background microflora. Currently, ARS scientists at Athens, Georgia, are collecting hyperspectral imaging data of the new agar growing the Big Six and the most concerning E. coli O157:H7. Data are also being collected on modified Rainbow agar to allow comparison to current methods. The results will be used in model development to screen agar plates for presumptive-positive colonies for further testing.


Accomplishments
1. Neutralizing-buffered peptone water carcass wash. Broiler carcasses are tested for presence of human pathogens by a whole carcass rinse method using buffered peptone water (BPW). During the course of commercial broiler processing, carcasses are washed with various antimicrobial processing-aid chemicals to lower bacterial contamination. ARS researchers in Athens, Georgia, showed that enough of the antimicrobial chemical is carried with a broiler carcass into a carcass rinse sample to confound detection of Salmonella by continued antimicrobial action in the rinsate during simulated shipment to an offsite lab. The scientists developed a new medium, neutralizing – BPW (n-BPW) that was effective in counteracting four of the most common antimicrobial treatments currently used in broiler processing and allow detection of Salmonella. This is very important as it makes a false negative result far less likely. The new medium has been adopted by the Food Safety and Inspection Service for regulatory sampling of broiler carcasses.

2. Detection and characterization of Salmonella with immunomagnetic separation (IMS) and surface enhanced Raman spectroscopy (SERS). Current detection and characterization techniques for Salmonella are time consuming and rapid methods could benefit investigation and control of foodborne outbreaks. ARS researchers in Athens, Georgia, developed a method that combines the advantages of immunomagnetic separation (IMS) and surface enhanced Raman spectroscopy (SERS) techniques to detect and characterize Salmonella in 24 hours with high sensitivity and minimal sample preparation. After selectively capturing the pathogen from food using IMS and overnight culture, SERS spectra were collected and analyzed with multivariate statistical models. The detection and characterization accuracies were confirmed by traditional methods, and validated in mixture samples consisting of common foodborne bacteria. The specificity for detecting Salmonella from other species was higher than accuracies between individual Salmonella serotypes. Overall, the approach provides an inexpensive alternative to current methods, and with the expansion of spectral libraries, the serotyping specificity could be improved with more robust spectral analysis.


Review Publications
Chu, X., Wang, W., Yoon, S.C., Ni, X., Heitschmidt, G.W. 2017. Detection of aflatoxin B1 (AFB1) in individual maize kernels using short wave infrared (SWIR) hyperspectral imaging. Biosystems Engineering. 157:13-23.
Gamble, G.R., Berrang, M.E., Buhr, R.J., Hinton Jr, A., Bourassa, D.V., Johnston, J.J., Ingram, K.D., Adams, E.S., Feldner, P.W. 2017. Neutralization of bactericidal activity related to antimicrobial carry-over in broiler carcass rinse samples. Journal of Food Protection. 80(4):685-691. doi:10.4315/0362-028x. JFP-16-412.
Park, B., Seo, Y., Eady, M.B., Yoon, S.C., Hinton Jr, A., Lawrence, K.C., Gamble, G.R. 2017. Classification of Salmonella serotypes with hyperspectral microscope imagery. Annals of Clinical Pathology. 5(2):1108-1116.
Wang, B., Park, B., Xu, B., Kwon, Y. 2017. Label-free biosensing of Salmonella enterica serovars at single-cell level. Journal of Nanobiotechnology (Biomed Central Open Access). 15:40.
Chen, J., Park, B., Eady, M.B. 2017. Simultaneous detection and serotyping of Salmonellae by immunomagnetic separation and label-free surface enhanced Raman spectroscopy. Journal of Food Analytical Methods. 10:3181-3193.
Chen, J., Park, B., Huang, Y., Zhao, Y., Kwon, Y. 2017. Label-free SERS detection of Salmonella Typhimurium on DNA aptamer modified AgNR substrates. Journal of Food Measurement and Characterization. doi:10.1007/s11694-017-9558-6.
Eady, M.B., Park, B. 2016. Rapid identification of Salmonella serotypes through hyperspectral microscopy with different lighting sources. Journal of Spectral Imaging. 5(a4):1-10.