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

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

Location: Environmental Microbial & Food Safety Laboratory

2016 Annual Report

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

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

Progress Report
With most of the proof-of-concept for the critical technologies and fundamental research already established previously, significant progress has been made for all objectives in advancing the sensing and instrumentation technologies for use in food production, processing and distribution chains. For Objective 1, various hardware components for on-line automated whole-surface inspection systems have been designed and developed in cooperation with University of Maryland, Baltimore County, Maryland. This collaboration has resulted in 3-d printing of custom-designed sensing and optical support structures to build commercial prototypes of inspection conveyor systems for round fruits and for relatively flat leafy greens. Significant progress has been made for Objective 2, targeting detection of microbial, chemical, and biological contaminants using fluorescence, Raman, and hyperspectral imaging technologies. Animal feed prepared with the inclusion of meat and bone meal (MBM) has been the source of bovine spongiform encephalopathy (BSE) in cattle and other livestock animals. Many countries have banned the use MBM as an animal feed ingredient. Spectral imaging techniques have shown potential for rapid assessment and authentication of various food and feed ingredients. ARS researchers in Beltsville, Maryland, initiated a cooperative agreement with the University of Cordoba, Spain, to develop rapid and accurate spectral imaging methods for assessing MBM in animal feed. A preliminary investigation of hyperspectral fluorescence and Raman chemical imaging techniques for differentiating poultry and pork MBM exhibited promising results. The Gradient Temperature Raman Spectroscopy (GTRS) technique, developed by the scientists in Beltsville, Maryland, can detect molecular and macromolecular changes such as phase transitions and protein denaturation in situ. The temperature range of GTRS was extended to analyze samples under cryogenic conditions. This enabled characterizing phase transitions unique to polyunsaturated lipids and those unique to or shared in common by structurally different omega-3 fatty acids docosapentaenoic acid (DPA, 22:5n-6) and docosahexaenoic acid (DHA, 22:6n-3). Research will continue to investigate changes in phospholipid folding/unfolding in a temperature gradient as a portal to detecting temperature-associated changes in cell walls and lipid bilayer membranes of microbes. Recent Raman imaging experiments on intact biofilms generated on stainless steel metal identified bioflim marker peaks corresponding to their carbohydrate and protein structures. Different microbes result in different sets of marker peaks. Films on stainless steel are detectable by Raman imaging at concentrations lower than those that can be detected visually, and biofilms from more than one microbe can be distinguished from each other. Further research is planned to also investigate biofilm formation on surfaces of other metals. Cryptosporidium parva is an infectious parasite that sickened ten school children in Litchfield, Minnesota, in May 2016. Bleach is an ineffective treatment because of the spherical oocysts’ membrane layer which protects the parasite. Raman microimaging enables identification of the chemical structures characteristic of this morphological site and of chemo-markers for sites of vulnerability in this membrane. The oocysts must have sites of non-uniformity; otherwise, the parasites would never “hatch” from inside the membrane. From this information, effective chemical treatments can be designed and optimized to protect against and prevent future outbreaks. In addition, ARS researchers in Beltsville, Maryland, have developed a new line-scan hyperspectral imaging system to acquire shortwave infrared (SWIR) images for biological sample evaluation. The system uses a mercury-cadmium-telluride focal plane array detector, which extends the effective spectral imaging region beyond the 400 – 1000 nm and 900 – 1700 nm regions that are typically imaged by systems using more common silicon-based CCD cameras and Indium-Gallium-Arsenide CCD cameras, respectively. Previously, agricultural applications of infrared imaging were limited to near-infrared wavelengths up to 1700 nm; the new system extends infrared imaging from 900 to 2500 nm. The new imaging technique and system can be used in non-destructive evaluation for food inspection, contaminant detection, and ingredient authentication. For Objective 3, significant design changes were made for the handheld contamination and sanitation inspection devices to extend testing and validation of the technology for use as visual-aid inspection tools and to develop standard protocols for end-users. The upgraded design incorporated a detachable rechargeable battery and improvement in weight distributions of the internal components to enhance ergonomics. An interagency agreement with the U.S. Army Natick Soldier Research Development and Engineering Center was established to further test and validate the imaging devices for use in the U.S. Army food safety audit programs. For Objective 4, efforts to develop methods and instrumentation for detecting fecal material and signs of animal intrusion in produce fields prior to harvest were continued in the new project. An ARS scientist in Beltsville, Maryland, began development of a semiautonomous cart to serve as the vehicle for mounting the imaging platform. The cart will enhance the potential capabilities of the imaging system by allowing imaging at night and also allowing detection using time-resolved 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 a local university established. The imaging system itself was modified, including development of a new mounting system for optics and integration of a new intensified charge-coupled device (CCD) camera to facilitate conversion of the laboratory system to field use.

1. Handheld fluorescence imaging device for meat safety inspection in slaughter plants. Current meat inspection in slaughter plants for food safety and quality attributes, including potential fecal contamination, is conducted through visual examination by human inspectors working under conditions that are poorly suited to conventional fluorescence detection methods that require ambient darkness. ARS researchers in Beltsville, Maryland, developed a handheld fluorescence-based imaging device (HFID) to highlight contaminated food and equipment surfaces on a display monitor during use under ambient lighting in food processing plants. This study investigated the effectiveness of the HFID in enhancing visual detection of fecal contamination on red meat, fat, and bone surfaces of beef under varying ambient luminous intensities (0, 10, 30, 50 and 70 foot-candles). Overall, diluted feces on fat, red meat and bone surfaces of beef under ambient light ranging from 0- to 50-foot-candles were detectable in the 670-nm single-band fluorescence images. As an assistive tool, this technology will support and improve meat safety inspection programs as implemented by U.S. processors and regulatory inspectors.

2. Evaluation of turmeric powder adulterated with metanil yellow using FT-Raman and FT-IR spectroscopy. Turmeric (Curuma long L.), an herbaceous root commonly used for food seasoning, is also valued for medicinal properties which arise from its natural content of curcumin, a yellow pigment with anti-inflammatory, anti-cancer, antioxidant, and wound healing attributes. However, economically driven adulteration of turmeric has occurred repeatedly, such as the addition of metanil yellow, a known carcinogen, to increase yellow color and product weight. ARS researchers in Beltsville, Maryland used Fourier Transform Raman (FT-Raman) spectroscopy and Fourier Transform Infrared (FT-IR) spectroscopy for detection of metanil yellow in turmeric powder. FT-Raman and FT-IR spectra of metanil yellow, turmeric, and curcumin were acquired and analyzed. Spectral analysis of metanil yellow mixed into turmeric at 8 different concentrations showed that the FT-Raman method was able to detect metanil yellow at 1% concentration, while detection by the FT-IR method was limited to 5% concentration. With the increasing popularity of turmeric as a health food additive, these techniques are a potential tool for food safety inspection that could greatly benefit the food industry, safety regulators, and consumers worldwide.

3. Raman chemical imaging system for detecting low levels of food adulterants. ARS researchers in Beltsville, Maryland, developed a line-scan Raman chemical imaging system to detect adulterants in milk powder, using a 5-W 785-nm line laser (240 mm long and 1 mm wide) as the Raman excitation source. Hyperspectral Raman images were acquired in the wavenumber range of 103–2881 cm-1 for samples of skim milk powder mixed with two nitrogen-rich adulterants, melamine and urea, at eight concentrations ranging from 50 to 10,000 parts per million. Chemical detection images to visualize identification, spatial distribution, and morphological features of the two adulterants in the milk powder were generated by combining individual binary images of melamine and urea. With the limits of detection for both melamine and urea estimated at an order of 50 parts per million, this line-scan Raman imaging system can be used for rapid, nondestructive, and quantitative measurement of melamine and other chemical adulterants that can pose risk of illness and even death when present in dry powdered food ingredients as has been illustrated by various instances of economically-driven adulteration around the world.

4. Surface and subsurface inspection of food safety and quality using a line-scan Raman system. ARS researchers in Beltsville, Maryland, developed a line-scan Raman imaging platform that can perform either Raman chemical imaging (RCI) for macro-scale surface imaging using a 785 nm line laser up to 24 cm long for push-broom imaging, or Spatially Offset Raman spectroscopy (SORS) for subsurface inspection over an offset range of 0-36 mm with a spatial interval of 0.07 mm using one CCD exposure. Large-field-of-view (230 mm wide) and high-spatial-resolution (0.07 mm/pixel) settings of the RCI mode were tested by analyzing fluorescence corrected images at select Raman peaks to view Raman-active analytes (fat on pork shoulder surface and carotenoids across carrot). Testing of the SORS mode showed that the carrot and melamine spectra acquired across a 5-mm thick carrot slice laid atop a layer of melamine powder could be effectively resolved using self-modeling mixture analysis. By using a shared detection module covering a Raman shift range from -674 to 2865 cm-1 for both RCI and SORS modes, the line-scan Raman imaging and spectroscopy platform provides a new tool that may be used for a wider range of food materials for surface and subsurface inspection for safety and quality attributes.


Review Publications
Dhakal, S., Chao, K., Schmidt, W.F., Qin, J., Kim, M.S., Chan, D.E. 2016. Evaluation of turmeric powder adulterated with metanil yellow using FT-Raman and FT-IR spectroscopy. Foods. 5(2):36-51.
Huang, M., Kim, M.S., Chao, K., Qin, J., Mo, C., Esquerre, C., Delwiche, S.R., Zhu, Q. 2016. Penetration depth measurement of near-infrared hyperspectral imaging light for milk powder. Sensors. 16(4):441.