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ARS Home » Plains Area » Manhattan, Kansas » Center for Grain and Animal Health Research » Stored Product Insect and Engineering Research » Research » Research Project #439612

Research Project: Advancing Technologies for Grain Trait Measurement and Storage Preservation

Location: Stored Product Insect and Engineering Research

2021 Annual Report

OBJECTIVE 1: Improve stored grain management, technology and processing practices to maintain grain end-use quality by controlling or eliminating adverse storage environments, insect infestations. Sub-objective 1A: Develop an insect monitoring and identification device for behavioral study and pest management in food facility environments. Sub-objective 1B: Increase efficacy of fumigation of milled and whole grain products through improved monitoring and modeling of fumigant applications. Sub-objective 1C: Increase efficacy of insecticidal aerosol applications in grain processing facilities based on measurement and modeling of droplet distribution and deposition. OBJECTIVE 2: Resolve existing issues and develop new technologies and techniques to rapidly and accurately evaluate intrinsic grain and seed quality to improve breeding efficiency, marketability, end-product use and environmental influences. Sub-objective 2A: Develop imaging methods for the detection of hard vitreous amber color (HVAC) of Durum wheat seeds as a replacement for manual wheat inspection. Sub-objective 2B: Selecting maize seeds for breeding programs using single seed near infrared spectroscopy (NIR) to improve hybrid development.

United States farmers annually (2016-2018) grow 562 million metric tons of corn, soybeans, wheat, sorghum and other grains to supply the nation and the world with food, animal feed and biofuels. Our project goal is to improve U.S. grain quality and international competitiveness through the application of engineering principles to rapidly measure grain traits and to maintain grain and grain-based product quality after harvest. We propose to develop unique instrumented systems to rapidly measure quality or compositional traits for breeders when selecting traits for varietal development. We also propose to develop technology to detect and control insects and maintain product quality during handling, processing and storage. This research will lead to expedited development of varieties and hybrids by breeders; better systems and information for storage management by farmers and processors, resulting in better profitability and production efficiency, less waste and increased food availability using fewer resources.

Progress Report
All main objectives and subobjectives of this project were met or substantially met. This is the first-year report for 3020-43440-010-00D, "Impacting Quality through Preservation, Enhancement, and Measurement of Grain and Plant Traits." Objective 1: ARS researchers studied and reported on various aspects of stored-product insecticide aerosol applications in food storage warehouses, in collaboration with Kansas State University, Manhattan, Kansas. Modeling of spray drop movement in a laboratory spray chamber, by measurement of deposition onto petri dishes, was conducted. Using a standard computer modeling technique, computational fluid dynamics (CFD), individual aerosol droplets were tracked. Predicted deposition of pyrethrin increased with increasing droplet size. Larger droplets tended to settle more while smaller droplets tended to continually flow with the air without settling out. Large droplets above the dish settled in the dish 92% of the time, while 12% of the small droplets settled in the dish. These results, showing many larger droplets impacting the insects and dishes, helps explain previous experimental results showing greater insect knockdown from larger versus small droplets. Industry collaborators and ARS scientists commenced a long-term study of railcar fumigation effectiveness using phosphine treatments. Data from these studies will be used for modelling the internal effectiveness of fumigation and provide industry with more effective fumigation protocols. Insects resistant to phosphine fumigation were studied by ARS scientists by collecting imaging data on the health and movement of susceptible and phosphine-resistant strains of red flour beetles and lesser grain borer after being treated with 1000 ppm or 3000 ppm of phosphine for 15 and 90 minutes. Results from these studies provided valuable information on insect mobility and behavioral responses to fumigation treatments in relation to their resistance to phosphine. Pilot-scale studies demonstrated that cross-contamination during routine handling in elevator boot pit areas cause insect infested and sound grain kernels to mix and move throughout the facility, contaminating additional grain. Large-scale investigations of ways to mitigate this would be expensive and time consuming, but computer simulations using the discrete element method (DEM) to account for all grain kernel interactions in the process could reduce this. DEM requires particle (grain) properties in order to develop accurate models for infested grain kernels. ARS scientists measured the properties of infested wheat and corn kernels as insects developed internally. These measured values can be used to develop effective particle models for DEM modeling of grain commingling of infested and sound grain in a bucket elevator system, providing a tool for developing methods that reduce or eliminate contamination. Objective 2: ARS scientists studied automated classification of durum wheat samples using a flat-bed scanner in collaboration with the Federal Grain Inspection Service (FGIS), Kansas City, Missouri. Methods were developed using transmitted lighting and sample grids for holding seeds in individual seed cells. Image processing software and data processing software routines were developed to analyze samples provided and manually graded by the FGIS. This method shows good potential for replacing the tedious manual method of human visual inspection by providing an objective and fast grading method. An ARS scientist designed and fabricated two automated single-seed near-infrared (NIR) analyzers for maize. These will be used for maize seed analysis and for segregating maize haploid seeds from hybrid seeds for maize breeding programs with collaborators at the University of Florida and Iowa State University. Preliminary NIR calibrations for oil and weight were developed and haploid-hybrid classifications examined. The methodology as to how to best integrate this into the breeding programs are being discussed and expedite the development of hybrids. ARS scientists developed imaging methods, in collaboration with Kansas State University, which extracts shape features for small grains. Length, width, and volume are of interest to breeders as they affect milling performance for many types of grains such as wheat, rice, and oats. Novel software methods were developed to do this and provide very accurate measurements. The measurement platform hardware, which uses a mirrored surface, provides comprehensive views of the seeds and should provide a good method for examining defects as well.

1. The grain industry requires accurate grain bulk density values for grading, designing storage systems, and estimating the mass of grain in bins. Many factors affect bulk density and make it difficult to predict accurately: the grain overbearing pressure, numerous kernel properties, and handling processes such as grain fall height, filling rate, and spreader versus spout filling. The discrete element method (DEM) of modeling evaluates the movement and interactions of each grain kernel making it effective for studying handling processes and material properties affecting bulk density. ARS researchers in Manhattan, Kansas, in collaboration with Kansas State University, developed two (simple and complex shape) grain kernel DEM sub-models, using simulations of loose-fill bulk density in the laboratory and kernel models to evaluate bulk density simulation methods. DEM models resulted in accurate simulated bulk densities compared to experimental results. Experiments and simulations show it is important to capture true shape and material properties in order to accurately predict grain bulk density. The more complex shape particle model was better for capturing the heap profile of wheat observed in the experiments but has the disadvantage of larger computational effort. This study contributed to a better understanding of the influence of particle shape, contact parameters, drop height, overburden pressure, and size distribution on bulk density and provided an effective approach to simulating wheat bulk density as affected by different handling practices. Resulting models will provide the industry with better estimates of stored grain compaction, improving the accuracy of audits, insurance adjustments, and bin designs.

Review Publications
Serson, W., Armstrong, P.R., Maghirang, E.B., AL-Bakri, A., Phillips, T., AL-Amery, M., Su, K., Hildebrand, D. 2020. Development of whole and ground seed near-infrared spectroscopy calibrations for oil, protein, moisture and fatty acids in Salvia hispanica. Journal of the American Oil Chemists' Society. 97(1):3-13.
Brabec, D.L., Perez-Fajardo, M., Dogan, H., Yeater, K.M., Maghirang, E.B. 2018. Effectiveness of modified 1-hour air-oven moisture methods for determining popcorn moisture. Applied Engineering in Agriculture. 34(3):617-621.
Casada, M.E., Thompson, S.A., Armstrong, P.R., McNeill, S.G., Maghirang, R.G., Montross, M.D., Turner, A.P. 2019. Forces on monitoring cables during grain bin filling and emptying. Applied Engineering in Agriculture. 35(3):409-415.
Al-Amery, M., Geneve, R.L., Sanches, M., Armstrong, P.R., Maghirang, E.B., Lee, C., Vieira, R., Hildebrand, D. 2018. Near-infrared spectroscopy used to predict soybean seed germination and vigor. Seed Science Research. 28(3):245-252.
Antony, R., Kirkham, M., Todd, T., Bean, S.R., Wilson, J.D., Armstrong, P.R., Maghirang, E.B., Brabec, D.L. 2019. Low-temperature tolerance of maize and sorghum seedlings grown under the same environmental conditions. Journal of Crop Improvement. 33(3):287-305.
Siliveru, K., Casada, M.E., Ambrose, R.P.K. 2019. Heat transfer during cooling of bulk distillers dried grains with solubles (DDGS). Applied Engineering in Agriculture. 35(4):569-577.
Clinesmith, M.A., Fritz, A.K., Lemes da Silva, C., Bockus, W.W., Poland, J.A., Dowell, F.E., Peiris, K.H.S. 2019. QTL mapping of Fusarium head blight resistance in winter wheat cultivars 'Art' and 'Everest'. Crop Science. 59(3):911-924.
Morrison III, W.R., Larson, N.R., Brabec, D.L., Zhang, A. 2019. Methyl benzoate as a putative alternative, environmentally-friendly fumigant for the control of stored product insects. Journal of Economic Entomology. 112(5):2458-2468.
Yabwalo, D.N., Berzonsky, W.A., Brabec, D.L., Pearson, T., Glover, K.D., Kleinjan, J. 2018. Impact of grain morphology and genotype by environment interactions on test weight of spring and winter wheat (Triticum aestivum L.). Euphytica. 214:125.
Clohessy, J.W., Pauli, D., Kreher, K.M., Buckler IV, E.S., Armstrong, P.R., Wu, T., Hoekenga, O.A., Jannink, J., Sorrells, M.E., Gore, M.A. 2018. A low-cost automated system for high-throughput phenotyping of single oat seeds. The Plant Phenome Journal. 1(1):1-13.
Armstrong, P.R., McClung, A.M., Maghirang, E.B., Chen, M., Brabec, D.L., Yaptenco, K.F., Famoso, A.N., Addison, C.K. 2019. Detection of chalk in single kernels of long-grain milled rice using imaging and visible/near infrared instruments. Cereal Chemistry. 96(6):1103-1111.
Athanassiou, C.G., Kavallieratos, N.G., Brabec, D.L., Oppert, B.S., Guedes, R.C., Campbell, J.F. 2019. From immobilization to recovery: Towards the development of a rapid diagnostic indicator for phosphine resistance. Journal of Stored Products Research. 80:28-33.
Petingco, M.C., Casada, M.E., Maghirang, R.G., Thompson, S.A., McNeill, S.G., Montross, M.D., Turner, A.P. 2018. Influence of kernel shape and size on the packing ratio and compressibility of hard red winter wheat. Transactions of the ASABE. 61(4):1437-1448.
Gonzales, H., Tatarko, J., Casada, M.E., Maghirang, R., Hagen, L., Barden, C. 2020. Computational fluid dynamics simulation of airflow through standing vegetation. American Society of Agricultural and Biological Engineers. 62(6):1713-1722.
Rodriguez, F.S., Armstrong, P.R., Maghirang, E.B., Yaptenco, K.F., Scully, E.D., Arthur, F.H., Brabec, D.L., Adviento-Borbe, A.A., Suministrado, D.C. 2020. NIR spectroscopy detects chlorpyrifos-methyl pesticide residues in rough, brown, and milled rice. Transactions of the ASABE. 36(6):983-993.