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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Environmental Microbial & Food Safety Laboratory » Research » Research Project #430631

Research Project: Sensing Technologies for the Detection and Characterization of Microbial, Chemical, and Biological Contaminants in Foods

Location: Environmental Microbial & Food Safety Laboratory

2017 Annual Report

1a. Objectives (from AD-416):
Objective 1: Advance development and validation of on-line automated whole-surface inspection systems for simultaneous safety and quality inspection of fresh produce in high-throughput commercial processing operations. Objective 2: Develop and validate user-friendly analytical sensing methods and technologies for targeted and non-targeted rapid screening of foods for microbial, chemical, and biological contaminants in laboratory, field, and/or industrial environments. Objective 3: Advance development of portable spectral imaging technologies to allow identification and detection of food contaminants, and develop sampling and inspection protocols for implementation of the developed technologies in industry and regulatory applications. Objective 4: Advance development, test and validate an automated system for detecting contaminants in produce fields, and investigate cost and sensitivity trade-offs of different potential system components and configurations with regard to production of a cost-effective commercial system.

1b. Approach (from AD-416):
Because cross-contamination may occur at many points throughout the production, processing, and distribution chains, our research targets reduction of food safety risks at multiple points, including both upstream (pre-harvest) processing and subsequent stages. The inspection point at single-layer processing is not intended to be a comprehensive inspection on its own but is key for some packaged fresh products. The ARS approach includes both pre- and post-harvest risk reduction measures that collectively can mitigate food safety concerns related to foodborne illnesses. The whole-surface sample presentation/imaging technologies developed in the previous project cycle along with the multitask imaging technology will be integrated on conveyor/processing systems to develop two automated whole-surface inspection platforms to simultaneously inspect produce for safety and quality attributes such as contaminants and defects. The two stand-alone commercial-grade prototype processing-inspection platforms will be transportable to produce processing facilities for testing and demonstration of the whole-surface inspection efficacies, with an ultimate goal of technology transfer. The proposed whole-surface fruit inspection will complement current industry sorting—based on quality attributes such as color and size—by the addition of safety inspection and will be used immediately after conventional color and size sorting. The proposed leafy green inspection will be used for inspection immediately prior to “value-added” processing, e.g., washing for packaged fresh-cut products.

3. Progress Report:
Significant progress has been made for all objectives during the second year of the project. For Objective 1, upgraded multitask imaging module including the two-view angle optics and illumination sources for the whole-surface round fruit inspection technology along with an automated software to generate whole-surface fruit images was developed. In addition, developed upgraded leafy green multitask imaging module, sample flipping module, and ejection module along with two-conveyor system. Integrated individual modules for development of the commercial prototype leafy-green wholes surface inspection platform. For Objective 2.1 concerning the determination and evaluation critical parameters for Raman chemical imaging systems for effective commodity- and contaminant-specific analysis, we conducted experiments using tapioca starch, milk powder, and wheat flour to determine the depth of laser penetration into the food powders, the power of the laser, and the spatial resolution needed for effective quantitative imaging-based detection of contaminant particles. Optimal parameters were then used to develop a Raman chemical imaging method for identification and quantification of multiple components present in complex food powder mixtures. The method was developed by analyzing ten samples of powdered non-dairy creamer that were prepared at ten different mixture concentrations with vanillin, melamine, and sugar (all three components added together in equal amounts by weight). Individual pixels corresponding to each of the three components could be detected in Raman chemical images of the thinly spread sample mixtures, and their numbers were found to be strongly correlated with the actual sample concentrations (correlation coefficient of 0.99 for all components), indicating that this method can be used for simultaneous identification of multiple components and estimation of their concentrations for food powder authentication or quantitative inspection purposes. Under Objective 2.2, a variety of food powders with chemical additives/residues were imaged using the refined line-scan high-throughput Raman imaging system and the images were analyzed using a simple thresholding method based on key "fingerprint" peaks of the chemicals of interest. The first investigation used milk powder mixed with melamine and urea contaminants and found that the method used could detect melamine and urea at concentrations as low as 50 ppm in milk powder, with high correlation between of the image-based pixel determinations to the actual sample concentrations. The second investigation found that benzoyl peroxide (flour bleaching agent) could be detected in wheat flour at concentrations as low as 50 ppm; this is on the same level as industry regulatory standards. The third investigation found that maleic anhydride could be detected in cornstarch at 100 ppm. Under Objective 2.3, a multipurpose line-scan Raman platform was developed for food safety and quality research. The platform was designed so that it can be configured for either (1) line-laser Raman chemical imaging mode for surface evaluation or (2) point-laser spatially offset Raman spectroscopy (SORS) mode for nondestructive subsurface evaluation. To validate and confirm the new SORS functionality, we conducted an investigation to develop a SORS method for subsurface sample analysis. The method successfully analyzed samples of urea, ibuprofen, and acetaminophen powders through up to eight layers of nested pharmaceutical gelatin capsules. The Gradient Temperature Raman Spectroscopy (GTRS) technique was expanded to elucidate conformation and phase transitions of natural Poly Unsaturated Fatty Acids (PUFA) from one to six double bonds. The techniques was used to discovered properties with an even number of double bond were similar and discretely different from those with an odd number of double bond. Further, comparison of GTRS results for two cell membrane phospholipids biochemically critical to brain function (1-stearoyl-2-docosahexaenoyl (DHA) phosphotidylcholine and 1-stearoyl-2-arachidonoly (AA) phosphotidylcholine) identified the specific (and different in each) elastic molecular site that could be responsible for their unique role in brain chemistry. For Objective 3, research on ARS portable imaging technologies for contamination and sanitation inspection applications was discussed with the USDA-FSIS Office of Policy and Program Development (OPPD), Risk, Innovations, and Management Staff (RIMS). Seeking suitable new measures with strong scientific basis to use in modernizing inspection and enforcement policies, OPPD/RIMS consulted EMFSL on the potential use of the handheld imaging device and challenges of in-plant testing and evaluation. Joint EMFSL-RIMS site visits were planned for preliminary prototype testing at meat processing plants, to provide greater insight on in-plant inspection needs and situational considerations of processing environments, and to solicit feedback from FSIS inspection staff who are the potential end-users of the device for development of user protocol. Preliminary testing was conducted during one site visit to a Ready-to-Eat (RTE) deli meat processor and another to a beef packing plant. Initial results suggest more effective use might be found in meat slaughtering operations compared to RTE meat processing, and highlighted ergonomic aspects of the device and consideration of methods to safely and objectively evaluate device performance for real-world residue detection without imposition upon commercial processing operations. In-house 3D printing has been used to improve and test device balance and shape; ongoing efforts are intended to improve these ergonomic properties as well as device ruggedness for practical in-plant use. A user-friendly touchscreen interface is under development for ease of use and for easy on/off detection modes to implement targeted spectral image processing algorithms. For Objective 4, a second self-propelled vehicle for mounting the hyperspectral imaging system was developed, tested, and shipped to Yuma, Arizona, for use in commercial produce fields. This unit uses larger wheels compared to the first unit, allowing the vehicle to traverse the relatively rough terrain in produce fields. The optics system is moved between the USDA laboratory in Beltsville, Maryland, and Yuma as needed. The optics mounting system allows the optics to be calibrated in the laboratory and then transferred to the vehicle. Mounting the optics on the vehicle takes about 1 hr.

4. Accomplishments
1. Sensing techniques for food ingredient authentication and food contaminant detection. ARS researchers in Beltsville, Maryland, have developed point-scan and line-scan Raman chemical imaging systems and analysis methods for non-destructive detection of chemical contaminants in powdered food materials. Without any special sample preparation, the newest system can analyze a 30-ml sample (two tablespoons) of dry powder within 10 minutes, more quickly and efficiently than conventional Raman instruments that might require 24 hours to analyze the same sample. The system can perform quantitative contaminant detection down to concentrations as low as 50 parts per million of benzoyl peroxide (used for bleaching) in wheat flour or melamine in milk powder, for example. Currently under patent review, this system will provide a useful screening tool to help detect contaminated food products and prevent their distribution and use, which is now a global concern due to the potential for widespread illnesses and even deaths, such as those that occurred with over 135 documented cases of melamine-adulterated skim milk powder between 1984 and 2012 worldwide.

2. Rapid quantitative detection of benzoyl peroxide in wheat flour. Quality and safety of wheat flour is an important issue worldwide due to the routine use of wheat flour in many staple foods. Use of benzoyl peroxide (BPO), a flour bleaching agent, at levels exceeding regulatory standards can destroy nutrients in the flour and may cause health concerns for consumers. A line-scan high-throughput Raman chemical imaging method was used for direct non-destructive sample analysis to create images visualizing BPO particles that were mixed into samples of wheat flour. BPO was detectable at 50 parts per million, which is on the same level as regulatory standards for acceptable use. High correlation between BPO pixel concentrations in the detection images and BPO mass concentrations in the prepared flour samples suggests that the method can be used for quantitative detection. This Raman imaging inspection method can be used by regulatory agencies and food processors to inspect wheat flour and other food powders and ingredients for adulteration and authentication screening purposes.

3. Detection and quantification of adulterants in milk powder. Past incidents of melamine-contaminated milk have illustrated the grave public health threat posed by economically motivated adulteration of milk. ARS researchers in Beltsville, Maryland, developed a new method for authenticating milk powder, using line-scan Raman chemical imaging to visualize particle identification, spatial distribution, and morphological features of two chemical adulterants (melamine and urea) mixed into milk powder samples, effectively detecting adulterant concentrations as low as 50 parts per million, which is a much lower concentration than those reported in some real-life incidents of adulteration (e.g., thousands of parts per million). The high correlation between the percentages of adulterant pixels in the images and the mass concentrations of the adulterants in the prepared samples suggests that the method can be effectively used for quantitative detection of adulterants in milk powder. This non-destructive Raman method is faster than conventional Raman methods and can be used to help regulatory agencies and food processors authenticate milk powder and other powdered foods subject to economic adulteration or fraud.

4. Subsurface food inspection using line-scan spatially offset Raman spectroscopy technique. Non-destructive subsurface food inspection is challenging due to complex interactions between light and heterogeneous or layered sample materials. ARS researchers in Beltsville, Maryland, developed a new line-scan-based technique to perform spatially offset Raman spectroscopy (SORS) for food and agricultural products. Unlike conventional Raman spectroscopy that detects signals dominated by the material nearest to the sample surface at point of measurement, SORS laterally separates the point laser source and the detector on the sample surface, thereby retrieving subsurface signals in the light that has passed through a deeper region of the sample before reaching the detector. The new line-scan SORS technique is more flexible and efficient than the traditional optical fiber probe approach in that a single image exposure can collect a series of Raman spectra all at once across a broad offset range with a narrow spatial interval. The new technique can be used for rapid and nondestructive subsurface inspection applications such as authentication of food ingredients or detection of contaminants in heterogeneous mixtures and layers or through coatings, films, or plastic packaging, and evaluation of internal attributes of fruits and vegetables, to the benefit of food processors seeking to ensure the safety and quality of their food products as well as regulatory agencies (e.g., FDA and USDA FSIS) that develop and enforce standards of food safety and quality.

5. Fecal detection system for produce fields. A system to take high-resolution visible/near-infrared hyperspectral images in outdoor fields using either natural ambient lighting for reflectance images or a pulsed ultraviolet laser for fluorescence images was designed, built, and tested by ARS researchers in Beltsville, Maryland. Components of the system include a semi-autonomous cart, a gated-intensified camera, a spectral adapter, a frequency-triple Nd:YAG (Neodymium-doped Yttrium Aluminum Garnet) laser, and optics to convert the Gaussian laser beam into a line-illumination source. The laser and camera are mounted on a removable plate that allows for laboratory optics calibration followed by installation on the cart for field use. The front wheels of the cart are independently powered by stepper motors that support stepping or continuous motion. When stepping, a spreadsheet is used to program imaging parameters for each step such as setting acquisition delays, acquisition time, and laser attenuation, a functionality that allows for specialized imaging such as establishing parameters for measuring fluorescence decay-curve characteristics. The system was validated by acquiring images of fluorescence responses of spinach leaves and dairy manure. These developments can be incorporated into future field imaging systems to detect fecal contamination and prevent cross-contamination during harvest operations.

6. Identification of parasite membrane vulnerability for chemical water treatments. Bleach is a commonly used disinfectant but can be ineffective in killing the infectious parasite Cryptosportium parva, which sickened ten school children in Litchfield, Minnesota, in May 2016. This parasite can cause typically mild yet treatable illness as well as severe and even fatal illness in people with weakened immune systems, and can easily be spread by contaminated drinking water or recreational aquatic environments. Raman mapping of the parasite’s protective membrane layer in its environmentally durable oocyst life stage found significant concentrations of calcium ions and magnesium ions on the oocyst’s spherical surface and at the edges of opened / broken surfaces. This suggests chemical mechanisms to be investigated for effective water treatment to protect against and prevent future outbreaks.

7. Fluorescence imaging for detecting fecal contamination of soil and assessing compost maturity. Serious outbreaks of food-borne illness can result from consumption of fresh produce contaminated by pathogens such as E. coli and salmonella that originate from animal or human fecal matter, particularly if the produce is mishandled at temperatures that encourage pathogen growth. Sources/pathways of contamination can include the excrement of wildlife or livestock, immature manure composts used as soil amendments, contaminated irrigation water or field tools, and poor health or hygiene of field workers. Although food safety standards exist regarding use of mature manure composts and prevention of fecal contamination in produce fields, verification in field production environments remains challenging since neither compost maturity nor fecal traces are easily identified by eye. ARS researchers investigated hyperspectral fluorescence imaging techniques to determine spectral characteristics of fecal samples from four species (dairy cows, pigs, chickens, and sheep) to test detection of animal feces and identification of species origin in soil-feces mixtures, and to evaluate use for assessing maturity of manure-based composts and results found fluorescence features that could be used to detect feces on soil and showed that identifying animal species origin is feasible. Furthermore, the fluorescence features could be used via simpler single-waveband imaging techniques, instead of more complex and costly full-spectrum hyperspectral imaging methods, for assessing compost maturity. These findings can be incorporated into field-use tools to help prevent contamination or harvesting of contaminated produce.

Review Publications
Qin, J., Kim, M.S., Chao, K., Schmidt, W.F., Cho, B., Delwiche, S.R. 2017. Line-scan Raman imaging and spectroscopy platform for surface and subsurface evaluation of food safety and quality. Journal of Food Engineering. 198:17-27.

Chao, K., Dhakal, S., Qin, J., Schmidt, W.F., Kim, M.S., Chan, D.E. 2017. A spatially offset Raman spectroscopy method for non-destructive detection of gelatin-encapsulated powders. Sensors. 17(3):618.

Dhakal, S., Chao, K., Qin, J., Kim, M.S., Chan, D.E. 2017. Identification and evaluation of composition in food powder using point-scan Raman spectral imaging. Applied Sciences. 7(1):1.

Dhakal, S., Qin, J., Kim, M.S., Chao, K. 2017. Raman spectroscopy. In: Franca, A.S., Nollet, L.M.L., editors. Spectroscopic Methods in Food Analysis. Boca Raton, FL: CRC Press. p. 111-142.

Chen, Z., Peng, Y., Li, Y., Chao, K. 2017. Extraction and identification of mixed pesticides’ Raman signal and establishment of their prediction models. Raman Spectroscopy. 48(3):494-500.

Schmidt, W.F., Hapeman, C.J., McConnell, L., Mookherji, S., Rice, C., Nguyen, J.K., Qin, J., Chao, K., Kim, M.S., Broadhurst, C.L., Shelton, D.R. 2017. Using torsional forces to explain the gradient temperature Raman spectra of endosulfan isomers and its irreversible isomerization. Journal of Molecular Spectroscopy. 1139:43-51.

Broadhurst, L., Schmidt, W.F., Kim, M.S., Nguyen, J.K., Qin, J., Chao, K., Bauchan, G.R., Shelton, D.R. 2016. Continuous gradient temperature Raman spectroscopy of n-6 DPA and DHA from -100 C to 20°C. Chemistry and Physics of Lipids. 200:1-10.

Mo, C., Kim, M.S., Kim, G., Lim, J., Delwiche, S.R., Chao, K., Lee, H., Cho, B. 2017. Spatial assessment of soluble solid contents on apple slices using hyperspectral imaging. Biosystems Engineering. 159:10-21.

Cho, H., Lee, H., Kim, S., Kim, D., Park, H., Lefcourt, A.M., Chan, D.E., Kim, M.S. 2016. Hyperspectral fluorescence imaging of animal feces and soil: potential use of fluorescence imaging for assessment of soil fecal contamination and compost maturity. Applied Sciences. 6:246.

Everard, C., Kim, M.S., O'Donnell, C. 2016. Distinguishing bovine fecal matter on spinach leaves using field spectroscopy. Applied Sciences. 6:246-254.

Mo, C., Kim, K., Kim, M.S., Lim, J., Lee, K., Lee, W., Cho, B. 2017. On-line fresh-cut lettuce quality measurement system using hyperspectral imaging. Biosystems Engineering. 156:38-50.

Mo, C., Kim, G., Kim, M.S., Lim, J., Lee, S.H., Lee, H., Kang, J., Cho, B. 2017. Discrimination methods of biological contamination on fresh-cut lettuce based on VNIR and NIR hyperspectral imaging. Infrared Physics and Technology. 85:1-12.

Mo, C., Kim, G., Kim, M.S., Lim, J., Cho, H., Barnaby, J.Y., Cho, B. 2017. Fluorescence hyperspectral imaging technique for the foreign substance detection on fresh-cut lettuce. Journal of the Science of Food and Agriculture. 97(12):3985-3993.

Qin, J., Chao, K., Schmidt, W.F., Dhakal, S., Cho, B., Peng, Y., Huang, M., Lee, H., Kim, M.S. 2017. Subsurface inspection of food safety and quality using line-scan spatially offset Raman spectroscopy technique. Food Control. 75:246-254.

Qin, J., Kim, M.S., Chao, K., Chan, D.E., Delwiche, S.R., Cho, B. 2017. Line-scan hyperspectral imaging techniques for food and agricultural applications. Applied Sciences. 7(20):125.

Qin, J., Kim, M.S., Chao, K., Dhakal, S., Lee, H., Cho, B. 2017. Detection and quantification of adulterants in milk powder using high-throughput Raman chemical imaging technique. Food Additives & Contaminants. 34(2):152-161.

Lohumi, S., Joshi, R., Kandpal, L.M., Kim, M.S., Cho, H., Mo, C., Seo, Y., Rahman, A., Cho, B. 2017. Quantitative analysis of Sudan dye adulteration in paprika powder using FTIR spectroscopy. Journal of Food Additives & Contaminants. 34(5):678-686.

Scholl, P., Bergana, M., Yakes, B., Zbylut, S., Downey, G., Mossoba, M., Jablonski, J., Margaletta, R., Holroyd, S.E., Buehler, M., Qin, J., Xie, Z., Hurst, W., Laponte, J.H., Roberts, D., Zrybko, C., Mackey, A., Holton, J.D., Israelson, G.A., Payne, A., Kim, M.S., Chao, K., Moore, J. 2017. Effects of the adulteration technique on the near-infrared detection of melamine in milk powder. Journal of Agricultural and Food Chemistry. 65:5799-5809.

Lefcourt, A.M., Kistler, R., Gadsden, A., Kim, M.S. 2016. Automated cart with VIS/NIR hyperspectral reflectance and fluorescence imaging capabilities. Applied Sciences. 7(1):3.

Qin, J., Kim, M.S., Chao, K., Cho, B. 2017. Raman chemical imaging technology for food and agricultural applications. Journal of Biosystems Engineering. 42(3):170-189.

Lohumi, S., Kim, M.S., Qin, J., Cho, B. 2017. Raman imaging from microscopy to macroscopy: Quality and safety control of biological materials. Trends in Analytical Chemistry. 93:183-198.