Progress 07/05/11 to 03/29/16
Outputs
Progress Report 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. 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. 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. Accomplishments 01 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. 02 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. 03 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. 04 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.
Impacts
(N/A)
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.
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Progress 10/01/14 to 09/30/15
Outputs
Progress Report 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. 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. Significant progress has been made on development and validation of spectral imaging techniques and instrumentation for use on-farm or during processing operations to reduce food safety risks from contaminated fresh produce, and for detecting intentional adulteration of food ingredients. 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 implementing whole-surface inspection of round fruits and of flat leafy green vegetables. In 2015, one of the two U.S. patents pending for the ARS whole-surface produce- imaging methods was issued. Improved prototypes of sample rotation devices and conveyor systems for round fruits and (separately) for relatively flat leafy-greens were designed and developed. For the multitask imaging module, a computer-controllable power management unit for high-power LED-based lighting optimized for online fluorescence imaging of produce was designed. 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. This progress relates to project objective 1 (development of technologies for online produce safety and quality inspection). The Raman chemical imaging technology has shown great promise as a rapid and nondestructive method for identifying, detecting, or quantifying adulterants in food ingredients, with potential for adoption by industry groups as a standard testing method. A new line laser with 40 W laser power was acquired to upgrade the patent pending line-scan Raman chemical imaging system. The upgrade allows Raman chemical imaging with an improved spectral data quality and at speeds that are three orders of magnitude higher than those of conventional Raman imaging systems. The improvements in line-scan Raman imaging will allow the use of the technique 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 and a U.S. patent application for the method and device was submitted in 2015. The technique applies the precise temperature gradients utilized in differential scanning calorimetry to Raman spectroscopy. Applied to molecularly complex materials, the technique allows better elucidation of molecular-level structures useful for fingerprinting of chemical substances. This progress relates to project objective 2 (development of optical sensing technologies to detect contaminants in foods). Handheld fluorescence imaging devices have been demonstrated effective as visual aid tools for improving the efficacy of cleaning and sanitation procedures in food processing. The handheld imaging technology has been patented by ARS and licensed by a U.S. commercial partner. The first commercial version (biofilm imaging monitor) is in development and is expected to be released in 2015. Extended testing and validation of the technology are planned for use of the handheld imaging devices as visual- aid inspection tools, followed by development of standard protocols for end-users, and, ultimately, for regulatory uses. As the technology advances, new component upgrades to optimize the system for real-world use will continue. To reduce the weight of the handheld imaging device, a power management circuit board for LEDs and other electronic components was designed. In June 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. This progress relates to project objective 2 (development of sensing technology to detect contaminants on food processing surfaces and facilities). Efforts to develop methods and instrumentation for detecting fecal material and signs of animal intrusion in produce fields prior to harvest have continued. Design and development of a semi-autonomous cart to serve as a field platform for mounting the laser-induced fluorescence imaging system was initiated. The cart will enhance the potential capabilities of the imaging system by allowing imaging at night as well as detection using time-resolved fluorescence imaging techniques, and will also reduce net operating costs by relieving the need for a human operator. Vehicle design specifications were established, and a collaboration with University of Maryland Baltimore Campus was also established. The imaging system itself was modified, including development of new mounting hardware for optics and integration of a new gated-camera, acquisition in progress, to facilitate conversion of the laboratory system to field use. This progress relates to project objective 2 (development of in-field pre-harvest technology to detect contaminants on foods). Accomplishments 01 Handheld fluorescence imaging device as an aid for detection of food residues on processing surfaces. Contamination of food with pathogenic bacteria can lead to foodborne illnesses. Food processing surfaces can serve as a medium for cross-contamination if sanitization procedures are inadequate. Ensuring that these surfaces are effectively cleaned and sanitized is important for the food industry's efforts to reduce risks of foodborne illnesses and their related costs. A handheld fluorescence imaging device developed by ARS was assessed for detection of three types of food residues (spinach leaf, milk, and bovine red meat) that have been associated with foodborne illness outbreaks, on two common processing surfaces (high-density polyethylene and food- grade stainless steel). Interchangeable optical filters were selected to optimize the contrast between food residues and processing surfaces as detected using hyperspectral fluorescence imaging. The fluorescence imaging plus image analysis differentiated food residues from the processing surfaces more clearly than did human visual inspection in ambient lighting. This optical sensing device can be used over relatively large or complex surfaces of processing equipment to detect food residues, and has potential for use in the food industry as an aid for detection of specific (targeted) food residues. 02 High-throughput Raman chemical imaging-based detection of food adulterants. Food safety incidents in recent years due to milk adulteration have brought increased interest in developing rapid and accurate screening methods for authenticating milk products. ARS researchers in Beltsville, MD have developed a point-scan Raman chemical imaging technique to detect various adulterants in milk powder. One limitation of previous Raman detection methods included the long sampling time, typically measured in hours, needed to collect images using a point-scan Raman imaging system, which precluded use of the method for rapid screening for adulterants in food powders such as dry milk powder. To address this limitation, a high-throughput line-scan Raman imaging system was developed. The system uses a 785 nm line laser to project a 24 cm long excitation line on the sample surface. Raman scattering signals along the laser line are collected by a detection module consisting of a lens, a dispersive Raman imaging spectrograph, and a Charge Coupled Device (CCD) camera. A hypercube is accumulated line-by-line as a motorized table moves the samples transversely across the laser line. Compared to the point-scan system, the line-scan system is capable of imaging larger sample areas in shorter sampling times�i.e. , minutes instead of hours. The developed system was used to collect Raman images from milk powder samples mixed with different concentrations of chemical adulterants. Images were created for visualizing the distribution of adulterant particles in the milk powder. The reduced scan times make the method feasible for high-throughput Raman imaging-based inspection of food powders and other materials in food processing plants. 03 Development of a three-CCD portable multispectral imaging system. ARS researchers in Beltsville, Maryland, have developed a myriad of nondestructive spectral imaging technologies for safety and quality evaluations of fruits and vegetables. Recent studies have suggested the need for imaging devices capable of multispectral imaging beyond the visible region that will allow for both quality and safety evaluations of agricultural commodities, compared to conventional multispectral imaging devices that lack flexibility in spectral waveband selectivity for such applications. A portable three-CCD camera with significant improvements over existing imaging devices was developed with a beam- splitter prism assembly to accommodate three interference filters, to use with the three CCD sensors, that can be easily changed for application-specific multispectral waveband selection in the 400 to 1000 nm region. Integrated electronic components on printed circuit boards with firmware programming were designed to enable parallel processing, synchronization, and independent control of the three CCD sensors, ensuring the transfer of data without significant delay or data loss due to buffering. The system can stream 30 frames (three single-waveband images in each frame) per second. The utility of the 3CCD camera system was demonstrated in the laboratory for detecting defect spots on apples and the imaging system can be used to enhance the current online machine vision technologies for fruit inspection. 04 Multispectral image algorithms for inspection of fecal contamination on leafy greens. Consumption of fresh leafy green vegetables (e.g., lettuce, and spinach) or fresh fruits contaminated by fecal matter can result in foodborne illnesses caused by human pathogens such as E. Coli or Salmonella. Hyperspectral fluorescence imaging with ultraviolet-A excitation was used to evaluate the feasibility of two-waveband fluorescence algorithms for the detection of bovine fecal contaminants on the abaxial and adaxial surfaces of Romaine lettuce and baby spinach leaves. Correlation analysis was used to select the most significant waveband pairs for two-band ratio and difference methods in distinguishing contaminated and uncontaminated leaf areas. Two-band ratios using bands at 665.6 nm and 680.0 nm (F665.6/F680.0) for lettuce and at 660.8 nm and 680.0 nm (F660.8/F680.0) for spinach were found to effectively differentiate all contamination spots from normal leaf areas. These methods for fecal contamination detection could be implemented for online screening of raw leafy greens using multispectral imaging with high spectral resolution for use in produce processing operations. 05 Determination of optimal bands for detecting fecal contamination on spinach leaves. Ensuring food safety in the production of fresh produce for human consumption is a global issue and must be addressed to decrease the incidence of foodborne illnesses and the associated costs. Hyperspectral fluorescence imaging using violet (405 nm) excitation was coupled with multivariate image analysis techniques and evaluated for the detection of fecal contaminants on spinach leaves. Fluorescence images were acquired spanning 464 to 800 nm for fecal contamination on both fresh leaves (pre-storage) and leaves subjected to a 27-day period of controlled storage. During the storage period, fluorescence emission profiles of the spinach leaves were monitored; peak emission blue- shifts were observed to accompany a color change from green to green- yellow-brown. A detection model developed using partial least squares discriminant analysis correctly detected fecal contamination on 100% of the fresh green spinach leaves, with 19% false positives for the non- fresh post-storage leaves. A wavelength ratio technique using four wavebands (680, 688, 703 and 723 nm) successfully identified 100% of fecal contaminations on both fresh and non-fresh leaves. These methods have potential for implementation in on-line fluorescence imaging inspection of fresh produce for fecal contaminant detection to help reduce the risk of foodborne illnesses.
Impacts
(N/A)
Publications
- Qin, J., Chao, K., Cho, B., Kim, M.S. 2015. High-throughput Raman chemical imaging for rapid evaluation of food safety and quality. Transactions of the ASABE. 57:1783-1792.
- Schmidt, W.F., Broadhurst, C., Qin, J., Lee, H., Nguyen, J.K., Chao, K., Hapeman, C.J., Shelton, D.R., Kim, M.S. 2015. Temperature dependent Raman spectroscopy of melamine and structural analogs in milk powder. Applied Spectroscopy. 669:398-406.
- 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.
- Lefcourt, A.M., Beck, E., Lo, Y., Kim, M.S. 2015. Using hyperspectral fluorescence spectra of deli commodities to select wavelengths for surveying deli food contact surfaces. Journal of Biosystems Engineering. 40(2):145-152.
- Beck, E., Lefcourt, A.M., Kim, M.S., Lo, M. 2015. Use of a portable fluorescence imaging device to facilitate cleaning of deli slicers. Food Control. 51:256-262.
- Lee, H., Park, S.H., Boh, S.H., Lim, J., Kim, M.S. 2014. Development of a portable 3CCD camera system for multispectral imaging of biological samples. Sensors. 14:20262-20273.
- Kandpal, L.M., Lee, S., Kim, M.S., Bae, H., Cho, B. 2015. Short wave infrared (SW-IR) hyperspectral imaging technique for examination of aflatoxin B_1 on corn kernels. Food Control. 51:171-176.
- Baek, I., Kim, M.S., Lee, H., Cho, B. 2014. Optimal fluorescence waveband determination for detecting defect cherry tomatoes using fluorescence excitation-emission matrix. Sensors. 14:21483-21496.
- Lohumi, S., Lee, S., Lee, W., Kim, M.S., Mo, C., Bae, H., Cho, B. 2014. Detection of starch adulteration in onion powder by FT-NIR and FT-IR spectroscopy. Journal of Agricultural and Food Chemistry. 62:9246-9251.
- 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.
- Garrido-Novell, C., Perez-Marin, D., Guerrero-Ginel, E., Kim, M.S., Garrido-Varo, A. 2015. Quantification and spatial characterization of moisture and NaCl content of Iberian dry-cured ham slices using NIR hyperspectral imaging. Journal of Food Engineering. 153:117-123.
- Lee, H., Kim, M.S., Jeong, D., Delwiche, S.R., Chao, K., Cho, B. 2014. Detection of cracks on tomatoes using hyperspectral near-infrared reflectance imaging system. Journal of Food Engineering. 14(10):18837- 18850.
- Le, H.D., Kim, M.S., Hwang, J., Yang, Y., U-Thainual, P., Kang, J.U., Kim, D. 2014. An average enumeration method of hyperspectral imaging data for quantitative evaluation of medical device surface contamination. Journal of Biomedical Optics. 5:3613-3627.
- Lim, J., Mo, C., Kim, G., Kang, S., Lee, K., Kim, M.S., Moon, J. 2014. Non- destructive and rapid prediction of moisture content in red pepper (Capsicum annuum L.) powder using near-infrared spectroscopy and a partial least squares regression model. Journal of Biosystems Engineering. 39:184- 193.
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Progress 10/01/13 to 09/30/14
Outputs
Progress Report 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. 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. Research on development and validation of spectral imaging technologies for use in rapid sample analysis to detect defects, fecal contamination, organic residues, bacterial biofilms, and food adulterants has made significant progress. A second U.S. patent for the ARS automated poultry safety inspection system was issued in January 2014 and a licensing agreement with a commercial partner for the poultry inspection technologies was signed in March, 2014. The Raman chemical imaging technology has shown great promise as a rapid and nondestructive method for identifying, detecting, or quantifying adulterants in food ingredients, with potential for adoption by industry groups as a standard testing method. A new line-scan based Raman chemical imaging system was designed and a U.S. patent application entitled, �Line-scan Raman imaging method and system for sample evaluation� was filed to the USPTO in November, 2013. Preliminary experiments suggested that the new line-scan system is capable of acquiring spatially-resolved Raman spectra three orders of magnitude faster than the previous version. A line-laser with higher output power (a minimum of 30 W) will be acquired to further improve the ARS line-scan Raman system. The improvement in the line-scan Raman imaging will allow the use of the technique as a routine scanning tool in food industries. This progress relates to project objectives 1, (multi-task real-time inspection technologies for food safety inspection) and 2, (detection of contaminants on foods processing surfaces). In addition, due to globalization of food production and import/export, food safety and security risks are of great international concern. International cooperative research projects (1245-42000-018-23T: Spectral imaging for contaminant detection on fresh food produce; and 1245-42000- 018-29T: Development of a Real-Time In-Situ Evaluation Sensing System for Hazardous and Adulterated Food Materials) have been initiated to jointly work on the development of sensing technologies and instrumentation suitable for rapid screening of agricultural commodities to address food safety concerns. Research has demonstrated that a fluorescence imaging-based handheld inspection tool can be used to improve the efficacy of cleaning and sanitation procedures in produce processing plants with no additional labor costs. The handheld imaging technology has been patented by ARS and licensed by a U.S. commercial partner, and a commercial system is under development. As of April, 2014, the licensed technology has received 40 preproduction orders by various food processing facilities. In addition, the uses of the portable handheld imaging devices for cleaning and sanitation inspection of food processing surfaces have been expanded to evaluate delicatessen meat and cheese residues. The preliminary results demonstrate that fluorescence imaging techniques have the potential to enhance surface hygiene inspection in delicatessen operations and, given the immediate availability of imaging results, to help optimize routine cleaning procedures. This progress relates to project objective 2, (development of sensing technology to detect contaminants on food processing surfaces). International cooperative research was initiated with a food safety and quality regulatory agency in South Korea that includes evaluation of the use of portable optical sensing devices for food safety assessment for regulatory purposes as related to various agricultural products and food processing environments. Efforts to develop methods and equipment for detecting fecal material and signs of animal intrusion in produce fields prior to harvest continue. To enable measurement of fluorescence responses in the presence of ambient solar radiation, a novel laser-induced fluorescence imaging system was constructed and tested. A bench-mounted LIF (laser induced fluorescence) imaging system that uses a pulsed laser for excitation illumination to acquire and detect the fluorescence responses of fecal material was modified to allow the system to acquire hyperspectral image data. The system is now being hardened to allow it to be used in field environments. For inline whole-surface inspection of round fruits and of relatively flat leafy-greens, improved prototypes of sample rotation devices and conveyor systems were developed with the integration of high- power LED-based lighting for optimal fluorescence imaging detection of contaminants and with programmable fruit rotation and conveyor speed controls. These ARS technologies will allow thorough online safety inspection of fruits and leafy-greens and address food safety hazards related to surface contamination and defects. This progress relates to project objective 2, (development of in-field pre-harvest technology to detect contaminants on foods). Raman Spectroscopy is an analytical technique used for rapid molecular- level fingerprinting of chemical substances, enabling, for example, real- time detection of contamination/adulteration of food. However, for any given molecular compound, the Raman spectral frequencies that can be used to identify that compound are actually fingerprints of specific structural fractions that make up the larger compound; structurally different molecular compounds can show similar fingerprints because they may have specific structural fractions in common. With the efforts of an ongoing collaborative project (1245-42000-018-20S: Development of Line- Scan Chemical Imaging Techniques for Detection of Food Contaminants and Adulterants), EMFSL research demonstrated that innovative, highly specific, spectral information (assignable to chemical structure) can be obtained using temperature dependent Raman (TDR) spectroscopy. Contaminants and degradation products will respond differently to a temperature gradient than the parent product itself. Since TDR is a brand new technology (invented in this lab), the types and ranges of molecular level changes that are actually occurring (in any specific temperature range) in products are almost totally unknown and await investigation by this new method. An invention disclosure for temperature dependent Raman method and apparatus was submitted for the ARS patent committee evaluation. This progress relates to project objective 2, (development of optical sensing technologies to detect contaminants in foods). Accomplishments 01 Automated online poultry wholesomeness inspection. 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 February 2012 and January 2014 (method and system for wholesomeness inspection of freshly slaughtered chickens on a processing line), and a commercial licensing agreement with a commercial partner was signed in March, 2014. 02 Handheld imaging devices for monitoring efficacy of cleaning and sanitation. Organic residues on processing equipment surfaces in food processing plants can generate cross-contamination and increase the risk of unsafe food for consumers. For sanitation inspection in food processing environments, 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. The 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 August 2013 for commercialization of handheld devices. In addition, under a Material Transfer Agreement, ARS prototypes were provided to the commercial partner to help develop a commercial version. As of April 2014, the commercial partner has sold 40 preproduction units. 03 Line-scan Raman imaging-based detection of food contaminants. The need for non-destructive methods to screen food ingredients for contaminants that pose food safety hazards was effectively illustrated by incidents of profit-driven adulteration of milk and wheat ingredients in dairy products and pet foods that caused widespread cases of illness and even death. ARS researchers in Beltsville, Maryland, developed a line-scan hyperspectral imaging system to achieve macro-scale Raman chemical imaging, using a high-power 785 nm line laser for line-scan Raman imaging of samples placed within a 23-cm wide sample area. The system optics were designed to be insensitive to variations in sample height, and the imaging spectrograph and camera are optimized for rapid high- throughput Raman imaging of large sample areas using 785-nm laser line excitation for pushbroom imaging. The performance of the developed system was demonstrated by an example application for simultaneous detection of two adulterants in milk powder. Both melamine and dicyandiamide particles mixed together into dry milk powder were effectively detected based on the chemical detection images generated using a simple image classification method. A U.S. patent application entitled, �Line-scan Raman imaging method and system for sample evaluation� was filed to the USPTO (11/01/2013).
Impacts
(N/A)
Publications
- 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.
- Qin, J., Chao, K., Kim, M.S., Lee, H., Peng, Y. 2014. Development of a Raman chemical imaging detection method for authenticating skim milk powder. Journal of Food Measurement & Characterization. 8(2):122-131.
- Qin, J., Chao, K., Kim, M.S. 2014. A line-scan hyperspectral system for high-throughput Raman chemical imaging. Applied Spectroscopy. 8(2):122-131.
- Lee, H., Cho, B., Kim, M.S., Lee, W., Tewari, J., Bae, H., Sohn, S., Chi, H. 2013. Prediction of crude protein and oil content of soybeans using Raman spectroscopy. Sensors and Actuators B: Chemical. 185:694-700.
- Delwiche, S.R., Souza, E.J., Kim, M.S. 2013. Near-infrared hyperspectral imaging for milling quality of soft wheat. Biosystems Engineering. 115:260- 273.
- Kandpal, L., Lee, H., Kim, M.S., Cho, B. 2013. Hyperspectral reflectance imaging technique for visualization of moisture distribution in cooked chicken breast. Sensors. 13(10):13289-13300.
- Jung, D., Kim, M.S., Chao, K., Hasegawa, M., Lee, H., Lee, H., Cho, B. 2013. Detection algorithm for cracks on the surface of tomatoes using Multispectral Vis/NIR Reflectance Imagery. Biosystems Engineering. 38(3) :199-207.
- Fu, X., Kim, M.S., Chao, K., Qin, J., Lim, J., Lee, H., Ying, Y. 2013. Detection of melamine in milk powders based on NIR hyperspectral imaging and spectral similarity analyses. Journal of Food Engineering. 124:97-104.
- Leewang-Hee, Kim, M.S., Lee, H., Delwiche, S.R., Bae, H., Kim, D., Cho, B. 2014. Hyperspectral near-infrared imaging for the detection of physical damages of pear. Journal of Food Engineering. 130:1-7.
- 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.
- Changyeun, M., Jongguk, L., Kangjin, L., Sukwon, K., Kim, M.S., Giyoung, K. , Cho, B. 2013. Determination of germination quality of cucumber (Cucumis sativus) seed by LED-induced hyperspectral reflectance imaging. Journal of Biosystems Engineering. 38(4):318-326.
- Mo, C., Kim, G., Lee, K., Kim, M.S., Cho, B., Lim, J., Kang, S. 2014. Non- destructive quality evaluation of pepper (Capsicum annuum L.) seeds using LED-induced hyperspectral reflectance imaging. Sensors. 14:7489-7504.
- Lim, J., Kim, M.S., Baek, I., Mo, C., Lee, H., Kang, S., Lee, K., Kim, G. 2013. Non-destructive prediction of low levels of melamine particles in milk powder using hyperspectral reflectance imaging and partial least square regression model. Food Engineering Progress. 17(4):377-386.
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Progress 10/01/12 to 09/30/13
Outputs
Progress Report 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. 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. Improved prototypes of sample rotation devices and conveyor systems for whole-surface inspection of round fruits and of relatively flat leafy- greens were developed; currently, no such whole-surface online inspection technologies exist for industry use. For the leafy-green inspection system, a second method to flip relatively soft leafy-greens to allow inspection of both surfaces was also developed and tested. These whole- surface image-based inspection methods will allow thorough safety/quality inspection of round fruits and leafy greens on commercial processing lines. An enhanced version of a high-power light-emitting-diode-based lighting system with computer control capabilities and selectivity in either ultra-violet of violet was developed. This new lighting system provides optimize illuminations for in-line produce inspection using fluorescence-based imaging technologies. These ARS technologies will allow thorough online safety inspection of fruits and leafy-greens and address food safety hazards related to surface contamination and defects. A new line-scan based Raman chemical imaging system was designed and developed. Preliminary experiments suggested that the new line-scan system is capable of acquiring spatially-resolved Raman spectra three orders of magnitude faster than the previous version. The improvement in scanning speed allows the use of the technique as a routine scanning tool in food industries. For sanitation inspection in food processing environments, a recently developed fluorescence-based hyperspectral imaging system was tested at two commercial fresh-cut produce processing plants to examine the efficacy of routine sanitation and cleaning procedures. Visualization of the contaminants using the imaging system allowed normal cleaning and sanitation procedures to be revised to better utilize cleaning efforts. Handheld commercial prototype versions were built and transferred to a commercial partner under an MTA to allow reverse engineering for development of commercial units. During some visits to the commercial facilities, micro-biological samples were taken from selected surfaces. Of particular interest was the ability of recovered bacteria to form biofilms. In collaboration with other EMFSL scientists, a number of biofilm-forming bacteria were identified and characterized, and their ability to form viable dual-species biofilms with pathogenic strains evaluated. To enable measurement of fluorescence responses in the presence of ambient solar radiation, a novel laser-induced fluorescence imaging system was constructed and tested. Subsequently, a spectral adapter was added to allow hyperspectral image acquisition. The final component needed to complete the development of an integrated imaging system was a method for converting a 4 mm Gaussian laser pulse into a line illumination source. This year, tests demonstrated that Powell lenses can be used to expand the laser beam into a homogenous line illumination source. The integrated system is now being tested by imaging apples and spinach leaves artificially contaminated with nano-gram quantities of bovine manure. Accomplishments 01 Handheld imaging devices for contamination and sanitation inspection of food contact surfaces. For sanitation inspection in food processing environments, we recently 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. Fluorescence imaging techniques with high power LED illumination and multispectral emission bands are used to detect the presence of fecal contamination, organic residues, and bacterial biofilms on surfaces under ordinary conditions of ambient light. 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 (�Hand-held Inspection Tool and Method�) was granted in November 2012 and a licensing agreement for the technology is in its final negotiation stage. Under an MTA, ARS prototypes were provided to a commercial partner to help develop a commercial version. 02 Point-scan Raman imaging-based detection of food contaminants. 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 Raman chemical imaging system and method were developed for detecting multiple adulterants in dry skim milk powder. Ammonium sulfate, dicyandiamide, melamine, and urea were mixed into petri dishes containing milk powder, at concentrations between from 0.1% to 5.0%. Using the 785-nm laser system, a 25 mm � 25 mm square area of each mixture was imaged. Spectral image processing methods were developed to remove interference from background fluorescence, and to create Raman chemical images visualizing the distribution of the different adulterants in the milk powder using unique Raman peaks of the adulterants. A correlation was found between adulterant concentration and the number of adulterant pixels identified in the images, demonstrating the potential of this method for quantitative analysis of adulterants in milk powder. A U.S. patent 8,467,052 (�System and Methods for Detecting Contaminants in a Sample�) was granted in May 2013. 03 Spectral imaging technologies for safety inspection of agricultural products. The ARS Sensing technology team in Beltsville, MD, has been at the forefront of developing cutting-edge nondestructive food safety evaluation technologies for food processing industry implementations. For meat processing industries, an image-based method (U.S. Patent #7, 460,227) to rapidly detect exposed bone fragments was developed to mitigate potential bone-fragment contamination in processed meat products. Current USDA regulations prohibit the sale of systemically diseased chickens for human consumption; these birds are detected by human inspectors for removal from poultry processing lines. A line- scan spectral imaging system was developed for automated wholesomeness inspection of freshly slaughtered chickens (US Patent # 8,126,123). In order to address multiple safety and quality inspection requirements for the fresh produce industry, a multitask on-line inspection method (U.S. Patent # 7,787,111) for detection of contaminants and defects on fruits and vegetables was developed. The optical technology allows simultaneous acquisition of fluorescence and reflectance images to detect fecal contaminants and defects on the surfaces of produce. A partner requested licensing for the portfolio of above patented ARS sensing technologies for commercial implementations. The Office of Technology Transfer, ARS, is negotiating with the commercial partner to finalize the licensing agreement. These ARS sensing technologies will help US food industries to improve processing efficiency and reduce food safety risks while maintaining their global competitiveness. 04 Near-infrared hyperspectral imaging for rapid detection of food adulterants. Melamine is a nitrogen-rich chemical that is commonly found in the form of white crystals, and in many reported cases was found intentionally added to food products such as milk, infant formula, frozen yogurt, pet food, biscuits, and coffee drinks to boost the perceived protein content. The resulting cases of illness and death have raised concerns about food safety and the tools available to screen foods and food ingredients for harmful adulterants. Hyperspectral imaging techniques that combine the advantages of spectroscopy and imaging have been widely investigated for a variety of food quality and safety evaluations. In this study, a near-infrared hyperspectral imaging technique was used for rapid identification/ detection of melamine particles in milk powders. We demonstrated that spectral similarity analyses of hyperspectral images could successfully identify melamine particles in a range of melamine-milk mixtures with melamine concentrations as low as 0.02% (200 ppm). This spectral imaging method can also be applied to other chemicals or multi- chemicals for adulterant detection in milk powders. 05 Portable hyperspectral imaging system for cleaning and sanitation inspection in produce processing facilities. Effective cleaning and sanitation procedures are critical for reducing risks of foodborne illness. However, it is difficult to validate the effectiveness of such procedures. On a routine basis, effectiveness is currently judged by inspection using the naked eye. Fluorescence imaging has been proposed as a more sensitive method to detect food residues that might remain after cleaning and sanitation procedures. A portable hyperspectral imaging system was developed that allows large surface areas to be surveyed in real time. The system was tested in multiple visits to two commercial fresh-cut processing plants. The imaging system was able to detect residues following cleaning and sanitation that were not visible or were barely visible to the naked eye. Detection of these residues allowed normal cleaning and sanitation procedures to be revised to better utilize cleaning efforts. The net result was cleaner surfaces at no additional cost in manpower. 06 Multispectral fluorescence imaging for detection of frass on tomatoes. Preliminary research by ARS scientists has found that frass (the excrement of insects) is one possible vector for the transmission of pathogens such as E. coli and Salmonella to fresh produce. Therefore, rapid detection on postharvest processing lines for frass contamination of fresh produce could help to prevent or minimize the potential safety risks of fresh produce. A simple multispectral fluorescence image processing algorithm was developed for the detection of tomato hornworm frass contamination on mature red tomatoes. Contamination spots were applied to the tomatoes using frass dilutions prepared at four different concentrations. The results showed over 99% successful detection of spots created using 0.2 and 0.1 g/ml frass dilutions, while spots created using lower concentrations at 0.05 and 0.02 g/ml were more difficult to detect and may require more complex image analysis methods to achieve similar accuracies. The method could be adapted for screening other agricultural products. 07 Spectral imaging techniques for detection of cracked tomatoes. Tomatoes are one of the most popular produce items in the United States, behind only potatoes, lettuce, and onions. Cracking is a serious problem that reduces the quality of tomatoes and increases the cost of tomato production. Open cracks can potentially allow internalization of contaminants, including pathogens. Scientists at ARS have been developing spectral imaging-based inspection techniques for produce safety and quality. In this study, a simple reflectance-based spectral imaging algorithm was developed to detect defect cracks on mature tomatoes. The results demonstrated that the image algorithm could differentiate normal tomatoes from defect cracked tomatoes with high accuracy. This method could be implemented on automated processing lines for rapid and accurate detection of cracked tomatoes.
Impacts
(N/A)
Publications
- Wiederoder, M., Lefcourt, A.M., Kim, M.S., Lo, Y. 2012. Detection of fresh- cut produce processing residues on food contact surface materials using hyperspectral imaging. Sensing and Instrumentation for Food Quality and Safety. DOI: 10.1007/s11694-012-9132-1.
- Lefcourt, A.M., Wiederoder, M., Kim, M.S., Lo, Y., Liu, N. 2013. Development of a portable hyperspectral imaging system for monitoring the efficacy of sanitation procedures in food processing facilities. Journal of Food Engineering. 117(1):59-66.
- Cho, B., Kim, M.S., Baek, I., Kim, D., Kim, Y. 2013. Detection of cuticle defects on cherry tomatoes based on hyperspectral fluorescence imagery. Postharvest Biology and Technology. 76:40-49.
- Qin, J., Chao, K., Kim, M.S. 2013. Simultaneous detection of multiple adulterants in dry milk using macro-scale Raman chemical imaging. Food Chemistry. 138:998-1007.
- Mo, C., Lee, K., Lim, J., Kim, M.S., Kang, S., Lee, H., Cho, B. 2013. Development of a pungency measuring system for red-pepper powder. Food Science and Biotechnology. 58(1):137-144.
- Qin, J., Chao, K., Kim, M.S., Lu, R., Burks, T. 2013. Hyperspectral and multispectral imaging for evaluating food safety and quality. Computers and Electronics in Agriculture. 118:157-171.
- Kim, T., Lee, H., Kim, M.S., Cho, B. 2012. Optimal optical filters of fluorescence excitation and emission for poultry fecal detection. Journal of Biosystems Engineering. 37(4):265-270.
- Ahn, C., Baek, I., Mo, C.Y., Kang, S., Kim, M.S., Cho, B. 2012. Development of non-destructive quality measurement technique for cabbage seed (Brassica campestris L) using hyperspectral reflectance imaging. Food Engineering Progress. 16(3):257-262.
- Kim, J., Kim, M.S., Cho, B. 2012. Fluorescence based spectral assessment of pork meat freshness. Food Engineering Progress. 16(3):249-256.
- Lefcourt, A.M., Wiederoder, M., Kim, M.S., Lo, Y., Liu, N. 2013. Use of a portable hyperspectral imaging system for monitoring the efficacy of sanitation procedures in produce processing plants. Journal of Food Engineering. DOI: 10.1016/j.jfoodeng.2013.02.019.
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Progress 10/01/11 to 09/30/12
Outputs
Progress Report 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. 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. Significant progress in the development of multitask in-line inspection technologies for detection of contaminants and defects on fruits and vegetables was made. From hyperspectral imaging and analysis, multispectral imaging algorithms using visible/near-infrared reflectance and fluorescence, respectively, were developed to detect cracks and frass residues--known vectors for pathogenic contamination of fresh produce--on tomatoes. These spectral image-based methods can be implemented into our in-line inspection technologies for rapid inspection on fruit processing lines. In addition, separate methods and prototype device/conveyor systems for whole-surface inspection of round fruits and of relatively flat leafy-greens were developed; currently, no such whole-surface online imaging inspection technologies exist for industry use. The whole-surface imaging methods will allow thorough safety/quality inspection of round fruits and leafy greens on commercial processing lines. Noteworthy progress was also made in improving the imaging platforms� fluorescence lighting with new high-power violet light-emitting-diodes; these are better suited for processing line applications for fruit and vegetable inspection as compared to conventional ultraviolet fluorescence lighting. With the improved lighting, a multispectral imaging algorithm can detect apples contaminated with animal fecal matter with over 99% success. Significant advances have been made in developing sensing technologies to detect the presence of chemical and biological contaminants on food products and processing surfaces. New macro-scale hyperspectral Raman chemical imaging and near-infrared (1000-1700 nm) hyperspectral imaging platforms were developed, expanding the current suite of portable sensing capabilities into the near-infrared and Raman realms. For sanitation inspection in food processing environments, a handheld hyperspectral imaging system was developed; experimental trials were conducted at two commercial fresh-cut produce processing plants to examine the efficacy of routine sanitation and cleaning procedures and identified a number of problematic steps in procedures. In response, cleaning crews successfully revised procedures at no additional cost in time or materials. To assist industry in addressing in-field detection of fecal contamination, a line- scan hyperspectral imaging system that uses a 355-nm pulsed-laser illumination was developed. This system allows automated acquisition of hyperspectral fluorescence responses including time-dependent fluorescence decay curves. This novel laser-based imaging technology is a precursor for the system slated for in-field use during pre-harvest produce inspection. Rapid Raman methods were developed for simultaneous detection of multiple adulterants in dry milk; potential chemical adulterants including ammonium sulfate, dicyandiamide, melamine, and urea, were mixed together with dry milk powder and evaluated. Raman chemical images allowed identification and visualization of spatial distribution of the multiple adulterant particles in the dry milk.
Impacts
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Publications
- 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. 5:155- 164.
- Qin, J., Chao, K., Kim, M.S. 2011. Investigation of Raman chemical imaging for detection of Lycopene changes in tomatoes during postharvest ripening. Journal of Food Engineering. 107(3-4):277-288.
- Qin, J., Chao, K., Kim, M.S. 2012. Nondestructive evaluation of internal maturity of tomatoes using spatially offset Raman spectroscopy. Postharvest Biology and Technology. 71:21-31.
- Chao, K. 2010. Hyperspectral Imaging for Food Quality Analysis and Control. London: Academic Press, Elsevier. p. 241-272.
- 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.
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