- Herrman, Tim
- Texas A&M University
- Start date
- End date
- Traceability Research
- Develop a marker that possesses physical and chemical properties similar to native grain, does not segregate during handling, and identifies grain from an individual field.
- Design and test a delivery system for tracing caplets and assess the best point of delivery on the combine or first collection point in the grain marketing system.
- Evaluate scanning technology and create a data retrieval and management system that can trace grain movement and assess the feasibility of scaling this system up to handle the entire U.S. grain marketing system.
- Analyze the economies of implementing a global grain tracing system including the economic benefits of a recall system that tracks the passage of grain from the farm to the end-user.
- Build a mycotoxin surveillance network involving major grain states and Texas including development of a database consisting of mycotoxin incidence, field of origin (GIS coordinates), cropping data including rotation, hybrid, planting date, fertility, weather data.
- Explore individual kernel mycotoxin contamination to quantify the range (high and low levels) of mycotoxin concentration between kernels and provide the necessary data to design sampling schemes with appropriate confidence level and confidence interval.
- Develop sampling designs and associated probability tables for aflatoxin and fumonisin in maize and sorghum.
- More information
- NON-TECHNICAL SUMMARY: Homeland security regulations and risk management strategies necessitate the incorporation of field level traceability in grain. A traceback and trace forward system for U.S. grain must be economically feasible. Mycotoxins pose an animal and human health threat. Proof of concept research will test the feasibility of using tracing caplets to verify field level traceback. This project includes an economic analysis of the costs associated with developing a global grain tracing system. A nationwide database containing mycotoxin data from state regulatory offices with surveillance systems will enable the grain industry to improve their mycotoxin mitigation strategy.
Task 1: Develop a physical marking system using tracing caplets: Caplets will be manufactured using sheeting technology and nonallergenic plant material. Caplet durability measurements will include testing for friability using a tumbling test. Caplet density will be measured using a gas pycnometer (Model 930, Bechman Instruments, Inc., Fullerton, CA). We will explore several applications or bar coding systems using commercial vendors, and assess the ability of the systems to successfully write and read bar codes in laboratory scale production.
Task 2: Design and test a delivery system for tracing caplets: The development of the caplet delivery system will be based on the design objective of dispensing approximately 5 caplets per kilogram of grain, with minimal lost time and inconvenience for the combine operator. We will design, build, and test a system that will attach to the unloading system of the combine. The dispensing mechanism will consist of a small (~30 liter) hopper and an electrically powered metering mechanism.
Task 3: Create a data retrieval and management system that can trace grain movement: A number of key components will be involved in developing the proof of concept system. These components including data entry from grain point of origin and data entry at points along the transportation line.
Task 4: Analyze the economies of implementing a global grain tracing system: Pro-forma budgets will be used to measure costs and will include an examination of the complexity of the traceability system; the time and cost of plan design; cost of training; and cost of control and record keeping for each handler in the grain marketing system. The time and cost of plan design will utilize simulation modeling. To quantify the benefits, we envision studying several product recall events.
Mycotoxins Task 1: Build a mycotoxin surveillance network involving major grain states: Working with other state regulatory entities, establish an information sharing network to track mycotoxin incidence in the U.S. corn belt. Data sharing will occur over the web and result in a map of areas where samples were collected and the incidence of mycotoxin observed.
Task 2: Explore individual kernel mycotoxin contamination to quantify the range: Poisson (or binomial) probability statistics best represent the population distribution of contaminated kernels (finite number) in a grain mass (infinite number). Thus, sampling statistics differ from the normal distribution used for most agricultural research and marketing. Evaluation of individual kernel mycotoxin levels using thin layer chromatography will be augmented with exploration of individual kernel spectral analysis to predict mycotoxin incidence.
Task 3: Develop sampling designs and associated probability tables for aflatoxin and fumonisin in maize and sorghum: Using single kernel mycotoxin data, scientists will develop better sampling schemes based on incidence level.
- Funding Source
- Nat'l. Inst. of Food and Agriculture
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- Bacterial Pathogens
- Risk Assessment, Management, and Communication
- Natural Toxins