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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Environmental Microbial & Food Safety Laboratory » Research » Research Project #421312

Research Project: DEVELOPMENT OF SENSING AND INSTRUMENTATION TECHNOLOGIES FOR FOOD SAFETY AND SANITATION INSPECTION IN FRESH FRUIT AND VEGETABLE PROCESSING

Location: Environmental Microbial & Food Safety Laboratory

2016 Annual Report


1a. Objectives (from AD-416):
The first objective is to develop and validate multitask in-line real-time inspection technologies for small to large processors that simultaneously detect contaminants and defects of fruits and vegetables. 1a) Evaluate visible/near-infrared reflectance and fluorescence imaging techniques for whole-surface detection of fecal material, damage, defects, and spoilage artifacts on fruits and vegetables. 1b) Identify multispectral wavebands and develop detection algorithms and image segmentation procedures for whole-surface inspection of produce that can be utilized for multitask screening for safety and quality concerns. Integrate and test methods for use in in-line multitask inspection systems. 1c) Develop and evaluate methods to facilitate whole-surface line-scan imaging of fruits and vegetables for in-line inspection. 1d) Develop and evaluate two prototype multitask inspection systems, one for fruits such as apples and tomatoes and a second for leafy green vegetables such as spinach and lettuce. The second objective is to develop and validate portable optical sensing technologies for detecting the presence of chemical and biological contaminants on food products and processing surfaces. 2a) Evaluate fluorescence, reflectance, and Raman spectral and imaging technologies for use in rapid sample analysis to detect fecal contamination, organic residues, bacterial biofilms, and food adulterants. 2b) Develop and validate a portable Raman-based hyperspectral imaging platform that can be used for macro-scale imaging of food samples as large as intact fruits and vegetables. 2c) Develop and validate handheld imaging devices for contamination and sanitation inspection in processing environments. 2d) Develop and validate imaging platform for in-field detection of fecal contamination.


1b. Approach (from AD-416):
The previous project included four patents (pending/issued) for methods and technologies developed: multitask line-scan imaging inspection, macro-scale laser-induced fluorescence imaging, Raman spectral detection of melamine adulteration, and image-based portable handheld sanitation inspection devices. This new project will build upon these previous accomplishments to develop prototype devices for commercialization. Rapid line-scan imaging technologies developed during the previous project cycle will be used to construct prototype whole-surface in-line inspection systems for simultaneously detecting surface contamination and defects using a single camera. This research focuses primarily on fresh fruits and vegetables, such as leafy greens, apples, and tomatoes, and on the detection of defects and of fecal contamination (a recognized source of human pathogens associated with fresh fruits and vegetables). Two prototype whole-surface in-line inspection systems will be developed, one for flat leafy produce such as Romaine lettuce and baby spinach, and a second for round-shaped produce such as apples and tomatoes. These systems will incorporate multitasking capabilities that allow users to select desired inspection criteria, and to optimize wavelengths and thresholds to address changes in produce characteristics on-the-fly. To detect chemical and biological substances of food safety interest, and to address the needs of the fruit and vegetable industries for evaluation or inspection tools for rapid on-site or in situ assessment of food safety risks, portable NIR (1000 to 2200 nm) hyperspectral imaging and Raman hyperspectral macro-scale imaging systems will be developed and validated . These enhanced capabilities will improve the existing toolbox of available imaging technologies for addressing unforeseen biological/chemical contamination problems in a timely manner. To enhance existing survey methods in produce processing plants, a previously developed handheld imaging device for inspecting poultry processing areas will serve as the basis for the development of a similar system for inspecting produce processing surfaces. The handheld inspection devices are intended as assistive tools for human inspectors to use during off-line inspection of processing equipment surfaces. To address the industry-identified need to survey produce fields for fecal contamination, technology to detect feces in produce fields will be developed based on a previously patented laser-induced fluorescence imaging technique. The proposed field imaging platform will assist industry in addressing in-field in situ detection of fecal contamination. As an applied engineering research project, the effective outcome of this work should be commercialization of the technologies developed. Critical to this end is collaboration with industry partners. Thus, this project will continue strategic partnerships with four companies with whom Cooperative Research and Development Agreements (CRADAs) have been established.


3. Progress Report:
This is the final report for the project 8042-42000-018-00D which terminated in March 2016. Significant progress was made on all objectives during the life of the Project. Current USDA regulations prohibit the sale of systemically diseased chickens for human consumption; these birds are detected by human inspectors for removal from processing lines. A line-scan spectral imaging system was developed for automated wholesomeness inspection of freshly slaughtered chickens. In collaboration with a commercial partner, a commercial prototype version was developed and tested extensively for real-time image-based inspection at a processing speed of 140 birds per minute. Use of the automated line-scan imaging inspection system will help the U.S. poultry industry to improve online processing efficiency and reduce food safety risks while maintaining global competitiveness. Two U.S. patents for this technology were issued, in 2012 and 2014, and a licensing agreement with a commercial partner was signed in 2014 for commercialization of automated online poultry wholesomeness inspection. To assure comprehensive online quality and safety inspection of fruits and vegetables in processing plants, whole-surface sample presentation and imaging regimes must be considered. Because of the morphological differences between fruits and leafy greens, separate methods and processing conveyor systems were developed for whole-surface inspection of round fruits and for flat leafy green vegetables (Objective 1). Currently, no such whole-surface online imaging inspection technologies exist for industry use. Two U.S. patents for sample presentation and imaging methods for online whole-surface produce inspection were submitted in 2013, and one U.S. patent was issued in 2015. Improved prototypes of sample rotation devices and conveyor systems for round fruits and (separately) for relatively flat leafy-greens were designed and developed. The whole-surface imaging methods coupled with the patented ARS multitask imaging technology will allow thorough safety and quality inspection of round fruits and leafy greens on commercial processing lines. For Objective 2, significant advancement in Raman technologies for use in rapid food adulterant detection was made. Incidents in recent years of profit-driven adulteration of milk and wheat ingredients subsequently used to make dairy products and pet foods have highlighted the need for non-destructive methods to screen food ingredients for contaminants that can pose significant food safety hazards. A point-scan Raman chemical imaging system was developed that allows for acquisition of high resolution hyperspectral Raman image data–i.e., spatial and spectral measurements–of relatively large quantities of minimally-prepared sample materials. The Raman imaging-based analytical methods were developed for detecting multiple adulterants in dry skim milk powder. The methods can be used to help prevent future incidents of adulteration of milk products driven by the ability to dupe conventional protein assessment methods. A U.S. patent for melamine detection methods was issued in May 2013. Significant improvement was made to the ARS Raman chemical imaging technology, with enhanced spectral data quality and acquisition speeds that are three orders of magnitude higher than those of conventional Raman imaging systems. The improvements will allow line-scan Raman imaging technique to be used as a routine scanning tool in food industries for safety and quality applications. In addition, a new gradient temperature Raman spectroscopy (GTRS) technique was developed. The technique applies the precise temperature gradients used in differential scanning calorimetry to Raman spectroscopy. U.S. patent applications for the line-scan Raman chemical imaging and GTRS were submitted in 2013 and 2014, respectively. Organic residues on food processing equipment surfaces in food processing plants can generate cross-contamination and increase the risk of unsafe food for consumers. For Objective 2, ARS researchers in Beltsville, Maryland, designed and developed inexpensive fluorescence-based handheld imaging devices with Wi-Fi capabilities to display live inspection images on smartphone or tablet devices. The aim is to provide the imaging devices as assistive tools that can be used by human inspectors performing visual sanitation inspection of food processing/handling equipment surfaces. In-plant testing demonstrated that existing sanitation and safety surveys performed by human inspectors could be greatly enhanced by the use of these tools. The devices can provide an objective means to assess the effectiveness of sanitation procedures and can help processors minimize food safety risks or determine potential problem areas within a processing environment. A U.S. patent was granted in November 2012 and a licensing agreement with a commercial partner was signed in 2013 for commercialization of handheld devices. The first commercial version (biofilm imaging monitor) is in development and is expected to be released in late 2016. In 2015, the latest ARS version of the handheld imaging device was transferred under a Material Transfer Agreement to the U.S. Army Natick Soldier Research Development and Engineering Center. U.S. Army Public Health Command personnel serve as Department of Defense (DOD) executive agents and inspect all food and water procured by the DOD. The handheld imaging device will be tested and evaluated during audits of food preparation facilities by Veterinary Inspectors at remote overseas locations.


4. Accomplishments
1. Development of a line-scan spatially offset Raman spectroscopy measurement technique. Spatially offset Raman spectroscopy (SORS) is a useful noninvasive method of chemical-specific evaluation of subsurface materials. Conventional methods of SORS typically use single-fiber optical measurement probes to slowly and incrementally collect a series of spatially offset point measurements moving away from the laser excitation point on the sample surface. ARS researchers in Beltsville, Maryland, have developed a new line-scan SORS measurement technique which utilizes a line-scan hyperspectral Raman imaging system to simultaneously collect a series of offset measurements in shorter time, and with greater options for the offset range (distance from excitation) and the offset intervals (narrow or wide), than offered by the conventional methods. This new line-scan SORS measurement technique was demonstrated by measuring the Raman signals of melamine powder placed under layers of butter that ranged between 1 and 10 mm in thickness. The method shows promise as a more rapid and less costly method for SORS evaluation of packaged food stuffs and for complex sample materials, and will benefit food processors and regulatory agencies.

2. Raman spectroscopy-based detection of chemical contaminants in food powders. Raman imaging-based methods have shown potential for commercial use in safety inspection of dry food powders for chemical contaminant detection. ARS scientists in Beltsville, Maryland, evaluated parameters of laser penetration depth, laser power, and spatial imaging resolution needed for effective quantitative detection of contaminants in food powders such as wheat flour and tapioca starch. Laser penetration depth and power were evaluated by testing melamine detection through layers of the food powders, while spatial resolution was evaluated for detection of benzoyl peroxide mixed into flour and of maleic acid mixed into tapioca starch. Positive correlations between the detected numbers of contaminant image pixels and the actual contaminant concentrations in the samples showed that the method developed in this study can be used for nondestructive quantitative detection of chemical contaminants present in food powders at low concentrations, and holds promise for commercial use by food processors to ensure safety and quality of powdered ingredients that could be contaminated from economically motivated or accidental adulteration.

3. Multivariate near-infrared spectral image analyses for detection of melamine in milk powders. ARS researchers in Beltsville, Maryland, used near-infrared (NIR) hyperspectral imaging combined with numerical analysis models to effectively and nondestructively detect melamine particles in milk powders easily and quickly compared to conventional analysis methods that are more time- and labor-intensive as well as more costly. Hyperspectral reflectance images in the NIR range of 990-1700 nm were acquired from melamine-milk powder mixtures prepared at concentrations ranging from 0.02 to 1%. Numerical analysis models positively correlated the spectral data to the melamine concentrations in the powder mixtures, and were applied to produce binary detection images visualizing the suspected melamine pixels in the sample images. As the melamine concentration was increased, the numbers of suspected melamine pixels in the binary detection images also increased, suggesting that the technique can be an effective tool for detection of melamine in milk powders to help protect consumers of dairy products from economically driven, illegal chemical adulteration methods designed to dupe conventional food testing techniques.

4. Fluorescence imaging for assessment of soil fecal contamination and compost maturity. Pathogenic microbial contamination of agricultural products can occur through a variety of pathways, such as immature compost used as an amendment for soil quality or contamination by feces from active wildlife or proximity to livestock. ARS researchers in Beltsville, Maryland, investigated hyperspectral fluorescence imaging techniques to characterize feces samples from bovine, swine, poultry, and sheep species, and to determine feasibilities for detecting and identifying the presence of animal feces and animal origin on or in soil-feces mixtures along with the imaging technique was evaluated for potential determination of manure compost maturity. The animal feces under investigation exhibited dynamic and unique fluorescence emission features that made feasible the detection of fecal presence and the identification of animal origin of the feces in soil-feces mixtures. Simple fluorescence imaging at the emission maximum band for animal feces can be used to potentially assess maturity of manure composts. For vegetable producers, this will help mitigate the safety risks posed by potential field application of immature composts that may contain pathogens.


5. Significant Activities that Support Special Target Populations:
None.


Review Publications
Mo, C., Kim, M.S., Lim, J., Cho, B., Lee, K., Kim, G. 2015. Multispectral fluorescence imaging technique for discrimination of cucumber (Cucumis Sativus) seed viability. Transactions of the ASABE. 58(4):959-968.

Everard, C., Kim, M.S., Cho, H., O’Donnell, C. 2016. Hyperspectral fluorescence imaging using violet LEDs as excitation sources for fecal matter contaminate identification on spinach leaves. Journal of Food Measurement & Characterization. 10(1):56-63.

Mo, C., Kim, G., Lim, J., Kim, M.S., Cho, H., Cho, B. 2015. Detection of lettuce discoloration using hyperspectral reflectance imaging. Sensors. 15(12):29511-29534.

Lohomi, S., Lee, S., Lee, H., Kim, M.S., Lee, W., Cho, B. 2016. Application of hyperspectral imaging for characterization of intramuscular fat distribution in beef. Infrared Physics and Technology. 74:1-10.

Lim, J., Kim, G., Mo, C., Kim, M.S., Chao, K., Qin, J., Fu, X., Baek, I., Cho, Y. 2016. Detection of melamine in milk powders using Near-Infrared Hyperspectral imaging combined with regression coefficient of partial least square regression model. Talanta. 151:183-191.

Dhakal, S., Chao, K., Qin, J., Kim, M.S., Schmidt, W.F., Chan, D.E. 2016. A parameter selection for Raman spectroscopy-based detection of chemical contaminants in food powders. Transactions of the ASABE. 59(2):751-763.

Dhakal, S., Chao, K., Qin, J., Kim, M.S., Chan, D.E. 2016. Raman spectral imaging for quantitative contaminant evaluation in skim milk powder. Journal of Food Measurement and Characterization. 10(2):374-386.

Oh, M., Kim, E.K., Jeon, B.T., Tang, Y., Kim, M.S., Seong, H.J., Moon, S.H. 2016. Chemical compositions, free amino acid contents and antioxidant activities of Hanwoo (Bos taurus coreanae) beef by cut. Meat Science. 119:16-21.

Lee, H., Kim, M.S., Lim, H., Lee, W., Cho, B. 2016. Detection of cucumber green mottle mosaic virus-infected watermelon seeds using short wave infrared (SWIR) hyperspectral imaging system. Biosystems Engineering. 148:138-147.

Qin, J., Kim, M.S., Schmidt, W.F., Cho, B., Peng, Y., Chao, K. 2016. A line-scan hyperspectral Raman system for spatially offset Raman spectroscopy. Journal of Raman Spectroscopy. 47(4):437-443.

Qin, J., Chao, K., Kim, M.S., Cho, B. 2016. Line-scan macro-scale Raman chemical imaging for authentication of powdered foods and ingredients. Food and Bioprocess Technology. 9(1):113-123.

Huang, M., Kim, M.S., Delwiche, S.R., Chao, K., Qin, J., Mo, C., Esquerre, C., Zhu, Q. 2016. Quantitative analysis of melamine in milk powders using near-infrared hyperspectral imaging and band ratio. Journal of Food Engineering. 181:10-19.

Lee, H., Kim, M.S., Song, Y., Oh, C., Lim, H., Kang, S., Cho, B. 2016. Non-destructive evaluation of bacteria-infected watermelon seeds using Vis/NIR hyperspectral imaging. Journal of the Science of Food and Agriculture. doi: 10.1002/jsfa 7832.

Lim, J., Kim, G., Mo, C., Kim, M.S. 2015. Design and fabrication of a real-time measurement system for the capsaicinoid content of Korean red pepper (Capsicum annuum L.) powder by visible and near-infrared spectroscopy. Sensors. 15(11):27420-27435.