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                    U.S. DEPARTMENT OF AGRICULTURE
 Environmental Microbial & Food Safety Laboratory: Beltsville, MD
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ARS Home Northeast Area Beltsville, Maryland (BARC) Beltsville Agricultural Research Center Environmental Microbial & Food Safety Laboratory People & Locations







Diane E Chan
                        Environmental Microbial & Food Safety Laboratory

                        




                        
                        Agricultural Engineer
                        Phone: (301) 504-9460
                        
                        
                        Fax: (Employee information on this page comes from the REE Directory. Please contact your front office staff to update the REE Directory.)
                            **Publications**
                                                (Clicking on the reprint icon
                                                    Reprint Icon
                                                    will take you to the publication reprint.)Federated learning for clients' data privacy assurance in food service industry
                                                        

- (Peer Reviewed Journal)Gorji, H., Saeedi, M., Zadeh, H., Husairik, K., Mojtaba, S., Qin, J., Chan, D.E., Baaek, I., Kim, M.S., Akhbardeh, A., Mackinnon, N., Vasefi, F., Tavakolian, K. 2023. Federated learning for clients' data privacy assurance in food service industry. Applied Sciences. 13(16):9330. https://doi.org/10.3390/app13169330.Hyperspectral imaging techniques for rapid detection of single- and co-contaminant aflatoxins and fumonisins in ground maize
                                                        

- (Peer Reviewed Journal)Kim, Y., Baek, I., Lee, K., Kim, G., Kim, S., Kim, S., Chan, D.E., Herrman, T., Kim, N., Kim, M.S. 2023. Hyperspectral imaging techniques for rapid detection of single- and co-contaminant aflatoxins and fumonisins in ground maize. Toxins. 15(7):472. https://doi.org/10.3390/toxins15070472.A hyperspectral plant health monitoring system for space crop production
                                                        

- (Peer Reviewed Journal)Qin, J., Monje, O., Nugent, M.R., Finn, J.R., O'Rourke, A.E., Wilson, K.D., Fritsche, R.F., Baek, I., Chan, D.E., Kim, M.S. 2023. A hyperspectral plant health monitoring system for space crop production. Frontiers in Plant Science. 14:1133505. https://doi.org/10.3389/fpls.2023.1133505.Hyperspectral imaging techniques for detection of foreign materials from fresh-Cut vegetables
                                                        

- (Peer Reviewed Journal)Tunny, S., Kurniawan, H., Amanah, H., Baek, I., Kim, M.S., Chan, D.E., Farqeerzada, M., Wakholi, C., Cho, B. 2023. Hyperspectral imaging techniques for detection of foreign materials from fresh-Cut vegetables. Postharvest Biology and Technology. 201:112373. https://doi.org/10.1016/j.postharvbio.2023.112373.Deep learning and multiwavelength fluorescence imaging for cleanliness assessment and disinfection in food services
                                                        

- (Peer Reviewed Journal)Gorji, H., Van Kessel, J.S., Haley, B.J., Husarik, K., Sonnier, J.L., Shahabi, S., Zadeh, H., Chan, D.E., Qin, J., Baek, I., Kim, M.S., Akhbardeh, A., Sohrabi, M., Kerge, B., Mckinnon, N., Vasefi, F., Tavakolian, K. 2022. Deep learning and multiwavelength fluorescence imaging for cleanliness assessment and disinfection in food services. Frontiers in Remote Sensing. https://doi.org/10.3389/fsens.2022.977770.Combining deep learning and fluorescence imaging to automatically identify fecal contamination on meat carcasses
                                                        

- (Peer Reviewed Journal)Gorji, H.T., Shahabi, S.M., Sharma, A., Tamde, L.Q., Husarik, K., Qin, J., Chan, D.E., Baek, I., Kim, M.S., Mackinnon, N., Morro, J., Sokolov, S., Akhbardeh, A., Vasefi, F., Tavakolian, K. 2022. Combining deep learning and fluorescence imaging to automatically identify fecal contamination on meat carcasses. Nature Scientific Reports. 12:2392. https://doi.org/10.1038/s41598-022-06379-1.Simulated annealing-based hyperspectral data optimization for fish species classification: Can the number of measured wavelengths be reduced?
                                                        

- (Peer Reviewed Journal)Chauvin, J., Duran, R., Tavakolian, K., Akhbardeh, A., Mackinnon, N., Qin, J., Chan, D.E., Hwang, C., Baek, I., Kim, M.S., Isaacs, R., Yilmaz, A., Roungchun, J., Hellberg, R., Vasefi, F. 2021. Simulated annealing-based hyperspectral data optimization for fish species classification: Can the number of measured wavelengths be reduced? Food Control. 11:10628. https://doi.org/10.3390/app112210628.Handheld multispectral fluorescence imaging system to detect and disinfect surface contamination
                                                        

- (Peer Reviewed Journal)Sueker, M., Stromsodt, K., Gorji, H.T., Vesafi, F., Khan, N., Schmidt, T., Varma, R., Mackinnon, N., Sokolov, S., Akhbardeh, A., Qin, J., Chan, D.E., Baek, I., Kim, M.S., Tavakolian, K. 2021. Handheld multispectral fluorescence imaging system to detect and disinfect surface contamination. Sensors. https://doi.org/10.3390/s21217222.Investigation of reflectance, fluorescence, and Raman hyperspectral imaging techniques for rapid detection of aflatoxins in ground maize
                                                        

- (Peer Reviewed Journal)Kim, Y., Baek, I., Lee, K., Qin, J., Kim, G., Shin, B.K., Chan, D.E., Herman, T.J., Cho, S., Kim, M.S. 2021. Investigation of reflectance, fluorescence, and Raman hyperspectral imaging techniques for rapid detection of aflatoxins in ground maize. Food Control. 132:108479. https://doi.org/10.1016/j.foodcont.2021.108479.Shortwave infrared hyperspectral imaging system coupled with multivariable method for TVB-N measurement in pork
                                                        

- (Peer Reviewed Journal)Baek, I., Lee, H., Cho, B., Mo, C., Chan, D.E., Kim, M.S. 2020. Shortwave infrared hyperspectral imaging system coupled with multivariable method for TVB-N measurement in pork. Food Control. 124, 107854. https://doi.org/10.1016/j.foodcont.2020.107854.Hyperspectral imaging from a multipurpose floating platform to estimate chlorophyll-a concentrations in irrigation pond water
                                                        

- (Peer Reviewed Journal)Kim, G., Baek, I., Stocker, M., Smith, J., Van Tessel, A., Qin, J., Chan, D.E., Pachepsky, Y.A., Kim, M.S. 2020. Hyperspectral imaging from a multipurpose floating platform to estimate chlorophyll-a concentrations in irrigation pond water. Remote Sensing. 13(12):2070. https://doi.org/doi:10.3390/rs12132070.Raman spectroscopy method for subsurface detection of food powders through plastic layers

- (Proceedings)Dhakal, S., Chao, K., Qin, J., Kim, M.S., Chan, D.E. 2017. Raman spectroscopy method for subsurface detection of food powders through plastic layers. Proceedings of SPIE, Sensing for Agriculture and Food Quality and Safety IX, 1021706.A spatially offset Raman spectroscopy method for non-destructive detection of gelatin-encapsulated powders

- (Peer Reviewed Journal)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.Identification and evaluation of composition in food powder using point-scan Raman spectral imaging

- (Peer Reviewed Journal)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.Line-scan hyperspectral imaging techniques for food and agricultural applications

- (Peer Reviewed Journal)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.Hyperspectral fluorescence imaging of animal feces and soil: potential use of fluorescence imaging for assessment of soil fecal contamination and compost maturity

- (Peer Reviewed Journal)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.Evaluation of turmeric powder adulterated with metanil yellow using FT-Raman and FT-IR spectroscopy

- (Peer Reviewed Journal)Dhakal, S., Chao, K., Schmidt, W.F., Qin, J., Kim, M.S., Chan, D.E. 2016. Evaluation of turmeric powder adulterated with metanil yellow using FT-Raman and FT-IR spectroscopy. Foods. 5(2):36-51.Detection of metanil yellow contamination in turmeric using FT-Raman and FT-IR spectroscopy

- (Proceedings)Dhakal, S., Chao, K., Qin, J., Kim, M.S., Schmidt, W.F., Chan, D.E. 2016. Detection of metanil yellow contamination in turmeric using FT-Raman and FT-IR spectroscopy. Proceedings of SPIE 9864, Sensing for Agriculture and Food Quality and Safety VII, 98640A.Raman spectral imaging for quantitative contaminant evaluation in skim milk powder

- (Peer Reviewed Journal)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.A parameter selection for Raman spectroscopy-based detection of chemical contaminants in food powders

- (Peer Reviewed Journal)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.Multispectral fluorescence imaging for detection of bovine feces on Romaine lettuce and baby spinach leaves

- (Peer Reviewed Journal)Lee, H., Everard, C., Kang, S., Cho, B., Chao, K., Chan, D.E., Kim, M.S. 2014. Multispectral fluorescence imaging for detection of bovine feces on Romaine lettuce and baby spinach leaves. Biosystems Engineering. 127:125-134.Differentiation of deciduous-calyx Korla fragrant pears using NIR hyperspectral imaging analysis

- (Peer Reviewed Journal)Rao, X., Yang, C., Ying, Y., Kim, M.S., Chan, D.E., Chao, K. 2014. Differentiation of deciduous-calyx Korla fragrant pears using NIR hyperspectral imaging analysis. Transactions of the ASABE. 57:1875-1883.Raman spectroscopy and imaging to detect contaminants for food safety applications

- (Proceedings)Chao, K., Qin, J., Kim, M.S., Peng, Y., Chan, D.E., Cheng, Y. 2013. Raman spectroscopy and imaging to detect contaminants for food safety applications. Proceedings of SPIE 8721, Sensing for Agriculture and Food Quality and Safety V, 87210S.Multispectral fluorescence image algorithms for detection of frass on mature tomatoes

- (Peer Reviewed Journal)Yang, C., Kim, M.S., Millner, P.D., Chao, K., Cho, B., Chan, D.E., Mo, C. 2014. Multispectral fluorescence image algorithms for detection of frass on mature tomatoes. Postharvest Biology and Technology. 93:1-8.Inspection of fecal contamination on strawberries using line-scan led-induced fluorescence imaging techniques

- (Abstract Only)Chuang, Y., Yang, C., Kim, M.S., Delwiche, S.R., Lo, Y., Chen, S., Chan, D.E. 2012. Inspection of fecal contamination on strawberries using line-scan led-induced fluorescence imaging techniques. [abstract].Inspection of fecal contamination on strawberries using line-Scan LED-induced fluorescence imaging techniques

- (Proceedings)Chuang, Y., Yang, C., Kim, M.S., Delwiche, S.R., Chen, S., Chan, D.E. 2012. Inspection of fecal contamination on strawberries using line-Scan LED-induced fluorescence imaging techniques. ASABE Annual International Meeting.  Paper No. 21337179.Quantitative detection of pesticide concentration by Raman chemical method

- (Abstract Only)Chao, K., Qin, J., Kim, M.S., Chan, D.E., Fu, X. 2012. Quantitative detection of pesticide concentration by Raman chemical method. [abstract].The development of line-scan image recognition algorithms for the detection of frass on mature tomatoes

- (Proceedings)Yang, C., Kim, M.S., Millner, P.D., Chao, K., Chan, D.E. 2012. The development of line-scan image recognition algorithms for the detection of frass on mature tomatoes. Proceedings of SPIE. 8369(08):1-7.An investigation of FT-Raman spectroscopy for quantification of additives to milk

- (Abstract Only)Cheng, Y., Qin, J., Lim, J., Chan, D.E., Kim, M.S., Chao, K. 2012. An investigation of FT-Raman spectroscopy for quantification of additives to milk. Proceedings of SPIE. 8369:83690W.Nondestructive imaging technologies for agro-food safety inspection

- (Abstract Only)Kim, M.S., Chao, K., Lefcourt, A.M., Yang, C., Chan, D.E. 2012. Nondestructive imaging technologies for agro-food safety inspection. [abstract].Visible to SWIR hyperspectral imaging for produce safety and quality evaluation

- (Peer Reviewed Journal)Kim, M.S., Delwiche, S.R., Chao, K., Lefcourt, A.M., Chan, D.E. 2012. Visible to SWIR hyperspectral imaging for produce safety and quality evaluation. Sensing and Instrumentation for Food Quality and Safety. 5(5):155-164.Red to far-red multispectral fluorescence image fusion for detection of fecal contamination on apples

- (Peer Reviewed Journal)Yang, C., Kim, M.S., Kang, S., Cho, B., Chao, K., Lefcourt, A.M., Chan, D.E. 2011. Red to far-red multispectral fluorescence image fusion for detection of fecal contamination on apples. Journal of Food Engineering. 108:312-319.Control Interface and Tracking Control System for Automated Poultry Inspection

- (Peer Reviewed Journal)Chao, K., Kim, M.S., Chan, D.E. 2014. Control Interface and Tracking Control System for Automated Poultry Inspection. Computer Standards & Interfaces. 36(2):271-277.Line-scan hyperspectral imaging platform for agro-food safety and quality evaluation: System enhancement and characterization

- (Peer Reviewed Journal)Kim, M.S., Chao, K., Chan, D.E., Jun, W., Lefcourt, A.M., Delwiche, S.R., Lee, K. 2011. Line-scan hyperspectral imaging platform for agro-food safety and quality evaluation: System enhancement and characterization. Transactions of the ASABE. 54(2):703-711.Development of a Simple Multispectral Algorithm Using a Hyperspectral Line-Scan Imaging System for Detection of Fecal Contamination on Apples

- (Peer Reviewed Journal)Yang, C., Kim, M.S., Kang, S., Tao, T., Chao, K., Lefcourt, A.M., Chan, D.E. 2010. Development of a Simple Multispectral Algorithm Using a Hyperspectral Line-Scan Imaging System for Detection of Fecal Contamination on Apples. Sensing and Instrumentation for Food Quality and Safety. 5:10-18.Vis/NIR line-scan hyperspectral imaging techniques for food safety and quality inspection

- (Abstract Only)Kim, M.S., Chao, K., Yang, C., Lefcourt, A.M., Chan, D.E. 2010. Vis/NIR line-scan hyperspectral imaging techniques for food safety and quality inspection. Meeting Abstract.Optical sensing technologies for rapid food safety and quality inspection

- (Proceedings)Kim, M.S., Chao, K., Chan, D.E., Jun, W., Lefcourt, A.M., Yang, C. 2010. Optical sensing technologies for rapid food safety and quality inspection.  [abstract]. 4th International Symposium on Recent Advances in Food Analysis book of abstracts, p. 182.Hyperspectral and Multispectral Imaging Technique for Food Quality and Safety Evaluation

- (Book / Chapter)Kim, M.S., Chao, K., Chan, D.E., Yang, C., Lefcourt, A.M., Delwiche, S.R. 2011. Hyperspectral and multispectral imaging technique for food quality and safety evaluation. In: Cho, Y., Kang, S. editors. Emerging Technologies for Food Quality and Food Safety Inspection. New York, N.Y.: CRC Press. p. 207-234.Hyperspectral Imaging Technologies for Nondestructive Agro-Food Evaluation

- (Proceedings)Kim, M.S., Chao, K., Chan, D.E., Yang, C., Lefcourt, A.M., Delwiche, S.R. 2010. Hyperspectral Imaging Technologies for Nondestructive Agro-Food Evaluation. International Symposium on New Sensing Technology for Measuring Agro-Food Quality Proceedings.  p. 57-71.Spectroscopic imaging technologies for online food safety and sanitation inspection

- (Abstract Only)Kim, M.S., Chao, K., Chan, D.E., Lefcourt, A.M., Yang, C., Qin, J. 2010. Spectroscopic imaging technologies for online food safety and sanitation inspection. [abstract] National Meeting of Institute of Food Technologists/Food Expo.IFT-10 Abstracts, 170-01.Classification of fecal contamination on leafy greens by hyperspectral imaging

- (Proceedings)Yang, C., Kim, M.S., Chao, K., Kang, S., Lefcourt, A.M., Chan, D.E. 2010. Classification of fecal contamination on leafy greens by hyperspectral imaging.  Proceedings of SPIE. 7676, 76760F.Classification of Fecal Contamination on Leafy Greens by Hyperspectral Imaging

- (Proceedings)Yang, C., Jun, W., Kim, M.S., Chao, K., Kang, S., Chan, D.E., Lefcourt, A.M. Classification of Fecal Contamination on Leafy Greens by Hyperspectral Imaging. Meeting Proceedings.    http://dx.doi.org/10/1117/12.851069.Microbial biofilm detection on food contact surfaces by macro-scale fluorescence imaging

- (Peer Reviewed Journal)Jun, W., Kim, M.S., Cho, B., Millner, P.D., Chao, K., Chan, D.E. 2010. Microbial biofilm detection on food contact surfaces by macro-scale fluorescence imaging. Journal of Food Engineering. 99(3):314-322.Machine vision system for online wholesomeness inspection of poultry carcasses

- (Peer Reviewed Journal)Yang, C., Chao, K., Kim, M.S., Chan, D.E., Early, H., Bell, M. 2010. Machine vision system for online wholesomeness inspection of poultry carcasses. Poultry Science. 89(6):1252-1264.Nondestructive sensing technologies for food safety

- (Proceedings)Kim, M.S., Chao, K., Chan, D.E., Jun, W., Lee, K., Kang, S., Yang, C., Lefcourt, A.M. 2009. Nondestructive sensing technologies for food safety. International Symposium for Improvement of Agro-Food Safety Proceedings. p. 119-126.Line-scan imaging for improved high-speed food safety inspection

- (Popular Publication)Kim, M.S., Chao, K., Chan, D.E., Lefcourt, A.M. 2009. Line-scan imaging for improved high-speed food safety inspection. SPIE News Room Article, 10.1117/2.1200903.1564.HIGH THROUGHPUT SPECTRAL IMAGING SYSTEM FOR WHOLESOMENESS INSPECTION OF CHICKEN

- (Peer Reviewed Journal)Chao, K., Yang, C., Kim, M.S., Chan, D.E. 2008. High throughput spectral imaging system for wholesomeness inspection of chicken. Applied Engineering in Agriculture. 24(4):475-485.MULTISPECTRAL LINE-SCAN IMAGING SYSTEM FOR SIMULTANEOUS FLUORESCENCE AND REFLECTANCE MEASUREMENTS OF APPLES: MULTITASK APPLE INSPECTION SYSTEM

- (Peer Reviewed Journal)Kim, M.S., Lee, K., Chao, K., Lefcourt, A.M., Jun, W., Chan, D.E. 2008. Multispectral line-scan imaging system for simultaneous fluorescence and reflectance measurements of apples: multitask apple inspection system. Sensing and Instrumentation for Food Quality and Safety.  2(2):123-129.DETECTION OF FECAL/INGESTA CONTAMINANTS ON POULTRY PROCESSING EQUIPMENT SURFACES BY VISIBLE AND NEAR-INFRARED REFLECTANCE SPECTROSCOPY

- (Peer Reviewed Journal)Chao, K., Nou, X., Liu, Y., Kim, M.S., Chan, D.E., Yang, C., Patel, J.R., Sharma, M. 2008. Detection of fecal/ingesta contaminants on poultry processing equipment surfaces by visible and near-infrared reflectance spectroscopy. Applied Engineering in Agriculture.  24(11):49-55.HYPERSPECTRAL/MULTISPECTRAL LINE-SCAN IMAGING SYSTEM FOR AUTOMATED POULTRY CARCASS INSPECTION APPLICATIONS FOR FOOD SAFETY

- (Peer Reviewed Journal)Chao, K., Yang, C., Chen, Y.R., Kim, M.S., Chan, D.E. 2007. Hyperspectral/multispectral line-scan imaging system for automated poultry carcass inspection applications for food safety. Poultry Science. 86(11):2450-2460.HYPERSPECTRAL REFLECTANCE AND FLUORESCENCE LINE-SCAN IMAGING FOR ONLINE QUALITY AND SAFETY INSPECTION OF APPLES

- (Peer Reviewed Journal)Kim, M.S., Chen, Y.R., Cho, B., Chao, K., Lefcourt, A.M., Chan, D.E. 2007. Hyperspectral reflectance and fluorescence line-scan imaging for online quality and safety inspection of apples. Sensing and Instrumentation for Food Quality and Safety. 1(3):151-159.Fast Line-Scan Imaging System For Broiler Carcass Inspection

- (Peer Reviewed Journal)Chao, K., Yang, C., Chen, Y.R., Kim, M.S., Chan, D.E. 2007. Fast Line-Scan Imaging System For Broiler Carcass Inspection. Jrnl of Sensing and Instrumentation for Food Quality and Safety. 1:62-71.DEVELOPMENT OF SIMPLE ALGORITHMS FOR THE DETECTION OF FECAL CONTAMINANTS ON APPLES FROM VISIBLE / NEAR INFRAED HYPERSPECTRAL REFLECTANCE IMAGING

- (Peer Reviewed Journal)Liu, Y., Chen, Y.R., Kim, M.S., Chan, D.E., Lefcourt, A. M. 2007. Development of simple algorithms for the detection of fecal contaminants on apples from visible/near infrared hyperspectral reflectance imaging. Jrnl. of Food Eng. 81:412-418.DEVELOPMENT OF ONLINE LINE-SCAN IMAGING SYSTEM FOR CHICKEN INSPECTION AND DIFFERENTIATION

- (Proceedings)Yang, C., Chan, D.E., Chao, K., Chen, Y.R., Kim, M.S. 2006. Development of online line-scan imaging system for chicken inspection and differentiation. Proceedings of SPIE. 6381:Y1-Y10.POULTRY CARCASS INSPECTION BY A FAST LINE-SCAN IMAGING SYSTEM: RESULTS FROM IN-PLANT TESTING

- (Proceedings)Chao, K., Yang, C., Chen, Y.R., Chan, D.E., Kim, M.S. 2006. Poultry carcass inspection by a fast line-scan imaging system: results from in-plant testing. Proceedings of SPIE. 6381:Q1-Q10.DETECTION OF FECAL / INGESTA CONTAMINANTS AT SLAUGHTER PLANTS FROM A NUMBER OF CHARACTERISTIC VISIBLE AND NEAR INFRARED BANDS

- (Proceedings)Liu, Y., Chao, K., Chen, Y.R., Nou, X., Chan, D.E., Yang, C. 2006. Detection of fecal / ingesta contaminants at slaughter plants from a number of characteristic visible and near infrared bands. Proceedings of SPIE. 6381:6381OU-1 - 6381OU-9.COMPARISON OF VISIBLE AND NEAR INFRARED REFLECTANCE SPECTROSCOPY FOR THE DETECTION OF FAECES/INGESTA CONTAMINANTS FOR SANITATION VERIFICATION AT SLAUGHTER PLANTS

- (Peer Reviewed Journal)Liu, Y.D., Chao, K., Chen, Y.R., Kim, M.S., Nou, X., Chan, D.E., Yang, C. 2006. Comparison of visible and near infrared reflectance spectroscopy for the detection of faeces/ingesta contaminants for sanitation verification at slaughter plants. Near Infrared Spectroscopy Journal. 14:325-331.DEVELOPMENT OF FUZZY LOGIC-BASED DIFFERENTIATION ALGORITHM AND FAST LINE-SCAN IMAGING SYSTEM FOR CHICKEN INSPECTION

- (Peer Reviewed Journal)Yang, C., Chao, K., Chen, Y.R., Kim, M.S., Chan, D.E. 2006. Development of fuzzy logic-based differentiation algorithm and fast line-scan imaging system for chicken inspection. Biosystems Engineering. 95(4):483-496.DEVELOPMENT OF TWO-BAND COLOR-MIXING TECHNIQUE FOR IDENTIFICATION OF BROILER CARCASS CONDITIONS

- (Peer Reviewed Journal)Chao, K., Chen, Y.R., Ding, F., Yang, C., Chan, D.E. 2007. Development of two-band color-mixing technique for identification of broiler carcass conditions. Journal of Food Engineering. 80(1):276-283.DEVELOPMENT OF HYPERSPECTRAL IMAGING TECHNIQUE FOR THE DETECTION OF CHILLING INJURY IN CUCUMBERS

- (Proceedings)Liu, Y., Chen, Y.R., Wang, C.Y., Chan, D.E., Kim, M.S. 2004. Development of hyperspectral imaging technique for the detection of chilling injury in cucumbers. In: Chen, Y.R., Tu, S.I, editors. Proceedings of Nondestructive Sensing for Food Safety, Quality, and Natural Resources. The International Society for Optical Engineering Conference, October 26-27, 2004, Philadelphia, Pennsylvania. p. 18-28.DEVELOPMENT OF HYPERSPECTRAL IMAGING TECHNIQUE FOR THE DETECTION OF CHILLING INJURY IN CUCUMBERS:  SPECTRAL AND IMAGE ANALYSIS

- (Peer Reviewed Journal)Liu, Y., Chen, Y.R., Wang, C.-Y., Chan, D.C., Kim, M.S. 2006. Development of hyperspectral imaging technique for the detection of chilling injury in cucumbers; spectral and image analysis. Applied Eng. in Agric. 22:(1):101-111.DEVELOPMENT OF HYPERSPECTRAL IMAGING TECHNIQUE FOR THE DETECTION OF CHILLING INJURY IN CUCUMBERS: PART I. SPECTRAL ANALYSIS

- (Peer Reviewed Journal)Liu, Y., Chen, Y.R., Wang, C.Y., Chan, D.E., Kim, M.S. 2005. Development of hyperspectral imaging technique for the detection of chilling injury in cucumbers: Part I. Spectral Analysis. Applied Engineering in Agriculture. 22:101-111.TWO-COLOR MIXING FOR CLASSIFYING AGRICULTURAL PRODUCTS FOR SAFETY AND QUALITY

- (Peer Reviewed Journal)Ding, F., Chen, Y.R., Chao, K., Chan, D.E. 2006. Two-color mixing for classifying agricultural products for safety and quality. Applied Optics. 45(4):668-677.CHARACTERIZING WHOLESOME AND UNWHOLESOME CHICKENS BY CIELUV COLOR DIFFERENCE

- (Peer Reviewed Journal)Chao, K., Chen, Y.R., Ding, F., Chan, D. E. 2005. Characterizing wholesome and unwholesome chickens by CIELUV color diffference. Applied Engineering in Agriculture. 21(4):653-659.DEVELOPMENT OF SIMPLE ALGORITHM FOR THE DETECTION OF CHILLING INJURY IN CUCUMBERS FROM VISIBLE/NEAR INFRARED HYPERSPECTRAL IMAGING

- (Peer Reviewed Journal)Liu, Y., Chen, Y.R., Wang, C.Y., Chan, D.E., Kim, M.S. 2005. Development of simple algorithm for the detection of chilling injury in cucumbers from visible/near infrared hyperspectral imaging. Applied Spectroscopy. 59:136-143.DEVELOPMENT OF HYPERSPECTRAL IMAGING TECHNIQUE FOR THE DETECTION OF CHILLING INJURY IN CUCUMBERS: PART II. IMAGE ANALYSIS

- (Peer Reviewed Journal)CHARACTERIZING WHOLESOME AND UNWHOLESOME CHICKENS BY CIELUV COLOR DIFFERENCE

- (Peer Reviewed Journal)Chao, K., Chen, Y.R., Ding, F., Chan, D.E. 2004. Characterizing wholesome and unwholesome chickens by cieluv color difference. ASAE Annual International Meeting.  ASAE Paper No. 043101.A SPECTROSCOPIC SYSTEM FOR HIGH-SPEED INSPECTION OF POULTRY CARCASSES

- (Peer Reviewed Journal)Chao, K., Chen, Y.R., Chan, D.E., 2004. A spectroscopic system for high-speed inspection of poultry carcasses. Applied Engineering in Agriculture. 20(5):683-690.SPECTROSCOPIC DETECTION OF ABNORMALITY IN CHICKEN LIVER AS AN INSPECTION TOOL

- (Proceedings)Dey, B.P., Chan, D.E., Chen, Y.R., Gwozdz, F.B. 2003. Spectroscopic detection of abnormality in chicken liver as an inspection tool.  SPIE Proceedings entitled: Monitoring Food, Safety, Agriculture, and Plant Health.  5271:43-50.ANALYSIS OF VIS/NIR SPECTRAL VARIATIONS OF WHOLESOME, SEPTICEMIA, AND CADAVER CHICKEN SAMPLES

- (Peer Reviewed Journal)CHAO, K., CHEN, Y.R., CHAN, D.E. ANALYSIS OF VIS/NIR SPECTRAL VARIATIONS OF WHOLESOME, SEPTICEMIA, AND CADAVER CHICKEN SAMPLES. APPLIED ENGINEERING IN AGRICULTURE. 2003.ANALYSIS OF VIS/NIR SPECTRAL VARIATIONS OF WHOLESOME AND UNWHOLESOME CHICKEN MEAT

- (Proceedings)Chao, K., Chen, Y.R., Chan, D.E., Kang, S. 2003. Analysis of vis/nir spectral variations of wholesome and unwholesome chicken meat. ASAE Annual International Meeting. 19(4): 453-458.DETECTION OF SEPTICEMIA IN CHICKEN LIVERS BY SPECTROSCOPY

- (Peer Reviewed Journal)DEY, B.P., CHEN, Y.R., HSIEH, C., CHAN, D.E. DETECTION OF SEPTICEMIA IN CHICKEN LIVERS BY SPECTROSCOPY. POULTRY SCIENCE. 82:199-206. 2003.MULTISPECTRAL DETECTION OF FECAL CONTAMINATION ON APPLES BASED ON HYPERSPECTRAL IMAGERY - PART II: APPLICATION OF HYPERSPECTRAL FLUORESCENCE IMAGING

- (Peer Reviewed Journal)Kim, M.S., Lefcourt, A.M., Chen, Y.R., Kim, I., Chan, D.E., Chao, K. 2002. Multispectral detection of fecal contamination on apples based on          hyperspectral imagery - part ii: application of hyperspectral fluorescence imaging. Transactions of the ASAE. 46(2):2039-2047.MULTISPECTRAL DETECTION OF FECAL CONTAMINATION ON APPLES BASED ON          HYPERSPECTRAL IMAGERY - PART I: APPLICATION OF VISIBLE-NEAR INFRARED       REFLECTANCE IMAGING

- (Peer Reviewed Journal)KIM, M.S., CHAO, K., CHEN, Y.R., CHAN, D.E., KIM, I., LEFCOURT, A.M. MULTISPECTRAL DETECTION OF FECAL CONTAMINATION ON APPLES BASED ON          HYPERSPECTRAL IMAGERY - PART I: APPLICATION OF VISIBLE-NEAR INFRARED       REFLECTANCE IMAGING. TRANSACTIONS OF THE AMERICAN SOCIETY OF AGRICULTURAL ENGINEERS. 2002.SEPARATING SEPTICEMIC AND NORMAL CHICKEN LIVERS BY VISIBLE/NEAR INFRARED   SPECTROSCOPY AND BACK-PROPAGATION NEURAL NETWORKS

- (Peer Reviewed Journal)HSIEH, C., CHEN, Y.R., DEY, B.P., CHAN, D.E. SEPARATING SEPTICEMIC AND NORMAL CHICKEN LIVERS BY VISIBLE/NEAR INFRARED SPECTROSCOPY AND BACK-PROPAGATION NEURAL NETWORKS. TRANSACTIONS OF THE AMERICAN SOCIETY OF AGRICULTURAL ENGINEERS. 45(2):459-469.  2002.HYPERSPECTRAL IMAGING SYSTEM FOR FOOD SAFETY: DETECTION OF FECAL           CONTAMINATION ON APPLES

- (Proceedings)


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