1a. Objectives (from AD-416):
The first objective is to develop and validate multitask in-line real-time inspection technologies for small to large processors that simultaneously detect contaminants and defects of fruits and vegetables. 1a) Evaluate visible/near-infrared reflectance and fluorescence imaging techniques for whole-surface detection of fecal material, damage, defects, and spoilage artifacts on fruits and vegetables. 1b) Identify multispectral wavebands and develop detection algorithms and image segmentation procedures for whole-surface inspection of produce that can be utilized for multitask screening for safety and quality concerns. Integrate and test methods for use in in-line multitask inspection systems. 1c) Develop and evaluate methods to facilitate whole-surface line-scan imaging of fruits and vegetables for in-line inspection. 1d) Develop and evaluate two prototype multitask inspection systems, one for fruits such as apples and tomatoes and a second for leafy green vegetables such as spinach and lettuce. The second objective is to develop and validate portable optical sensing technologies for detecting the presence of chemical and biological contaminants on food products and processing surfaces. 2a) Evaluate fluorescence, reflectance, and Raman spectral and imaging technologies for use in rapid sample analysis to detect fecal contamination, organic residues, bacterial biofilms, and food adulterants. 2b) Develop and validate a portable Raman-based hyperspectral imaging platform that can be used for macro-scale imaging of food samples as large as intact fruits and vegetables. 2c) Develop and validate handheld imaging devices for contamination and sanitation inspection in processing environments. 2d) Develop and validate imaging platform for in-field detection of fecal contamination.
1b. Approach (from AD-416):
The previous project included four patents (pending/issued) for methods and technologies developed: multitask line-scan imaging inspection, macro-scale laser-induced fluorescence imaging, Raman spectral detection of melamine adulteration, and image-based portable handheld sanitation inspection devices. This new project will build upon these previous accomplishments to develop prototype devices for commercialization. Rapid line-scan imaging technologies developed during the previous project cycle will be used to construct prototype whole-surface in-line inspection systems for simultaneously detecting surface contamination and defects using a single camera. This research focuses primarily on fresh fruits and vegetables, such as leafy greens, apples, and tomatoes, and on the detection of defects and of fecal contamination (a recognized source of human pathogens associated with fresh fruits and vegetables). Two prototype whole-surface in-line inspection systems will be developed, one for flat leafy produce such as Romaine lettuce and baby spinach, and a second for round-shaped produce such as apples and tomatoes. These systems will incorporate multitasking capabilities that allow users to select desired inspection criteria, and to optimize wavelengths and thresholds to address changes in produce characteristics on-the-fly. To detect chemical and biological substances of food safety interest, and to address the needs of the fruit and vegetable industries for evaluation or inspection tools for rapid on-site or in situ assessment of food safety risks, portable NIR (1000 to 2200 nm) hyperspectral imaging and Raman hyperspectral macro-scale imaging systems will be developed and validated . These enhanced capabilities will improve the existing toolbox of available imaging technologies for addressing unforeseen biological/chemical contamination problems in a timely manner. To enhance existing survey methods in produce processing plants, a previously developed handheld imaging device for inspecting poultry processing areas will serve as the basis for the development of a similar system for inspecting produce processing surfaces. The handheld inspection devices are intended as assistive tools for human inspectors to use during off-line inspection of processing equipment surfaces. To address the industry-identified need to survey produce fields for fecal contamination, technology to detect feces in produce fields will be developed based on a previously patented laser-induced fluorescence imaging technique. The proposed field imaging platform will assist industry in addressing in-field in situ detection of fecal contamination. As an applied engineering research project, the effective outcome of this work should be commercialization of the technologies developed. Critical to this end is collaboration with industry partners. Thus, this project will continue strategic partnerships with four companies with whom Cooperative Research and Development Agreements (CRADAs) have been established.
3. Progress Report:
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).
1. 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.
2. 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.
3. 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).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.
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.
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.
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.