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 Stored Product Insect and Engineering Research: Manhattan, KS
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                        Center for Grain and Animal Health Research: Manhattan, KS
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ARS Home Plains Area Manhattan, Kansas Center for Grain and Animal Health Research Stored Product Insect and Engineering Research Research





- Pordesimo, Lester
- Armstrong, Paul
- Brabec, Daniel - Dan
- Campbell, James - Jim
- 2023
- 2022
- 2021
- Publications
- Product Quality and New Uses (306)

Research Project: Advancing Technologies for Grain Trait Measurement and Storage Preservation **Location:
                            Stored Product Insect and Engineering Research** 2022 Annual Report **Objectives**
                                

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. **Approach**
                                

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**
                                


Objective 1, Sub-objective 1A. A camera-based imaging system was assembled, and artificial intelligence (AI) was used to train models to identify stored grain insect pests. Identification of warehouse beetle and cigarette beetle in near-real-time in the initial testing phase was completed. This research is leading to the development of new methods for monitoring insect activity and improved and efficient pest management programs. 

Sub-objective 1B. Preliminary results from railcar fumigation were completed for hopper bottom railcars carrying corn grits by monitoring phosphine gas concentrations during shipment. Additional tests and modelling of the fumigation concentrations will provide much needed information and provide future recommendations for applicators.

Sub-objective 1C. High performance liquid chromatography (HPLC) chemistry methods were evaluated to estimate the amount of Methoprene pesticide found in filter paper placed in petri dishes during aerosol pesticide applications. This method may provide a method for commercial applicators to determine the effectiveness of aerosol applications.  

Sub-objective 1C. The 2-dimensional model for aerosol entrapment efficiency for dishes tested in a spray chamber has been refined and compared to a 3-dimensional model for the dishes. Also, development has begun for the 3-dimensional model for unobstructed spaces in processing facilities.
  
Objective 2, Sub objective 2A. Research continued on measuring chalkiness in Durum wheat using a flatbed scanner to provide a less subjective method over the human scoring used in federal grading standards.  

Sub-objective 2B. Two near infrared (NIR) single seed instruments were constructed and are being tested and used by collaborators at two university maize breeding programs, Ames, Iowa, and Gainesville, Florida, to sort haploid maize seeds from hybrid seeds. Haploid seeds are valuable in creating inbred lines needed for hybrid development. These instruments will help in the development of new maize hybrids by greatly reducing the time required for inbred development. Continued model prediction performance will be enhanced by adding new kernel populations to the model. **Accomplishments**
                                

1. Single seed near infrared instrument facilitates corn hybrid development. Single seed, near infrared (NIR) instruments developed by ARS researchers in Manhattan, Kansas, are being used by collaborators at two university maize breeding programs in Ames, Iowa, and Gainesville, Florida. They are being used to sort doubled haploid (DH) seeds from hybrid seeds which has been a major bottle neck in the use of DH technology. Sorting is based on detection of the small oil content differences naturally found between DH and hybrid seeds. DH seeds are valuable in creating inbred lines used for hybrid development. The instruments will enable a faster and more cost-effective development of inbred plants, which in turn are used to create commercial hybrids. Ultimately, the time to develop hybrids will be shortened, allowing breeders greater flexibility to address issues of plant disease resistance, climate adaptability, and improved agronomic traits, which will also benefit farmers. 2. Computer simulation modelling improves fumigation in grain storage bunkers. A computer model was developed by ARS researchers in Manhattan, Kansas, and used to determine causes of fumigation failures in sealed grain storage bunkers. Fumigation failures in grain storage facilities allow some of the targeted insects to survive, which leads to resistant stored grain insect populations. As a result, phosphine—currently the most widely used fumigant to control the insects in stored grain—is in danger of becoming ineffective for insect control. Modeling results showed that the movement of the covering tarpaulin is the driving force of phosphine behavior in bunkers, and that phosphine distribution is very sensitive to motions caused by weather conditions. Based on these results, fumigation techniques can be modified in several ways, such as by locating the fumigant in more effective locations within the bunkers and orienting bunkers so that prevailing winds are more effective at helping distribute the phosphine gas. **Review Publications**
                            *Brabec, D.L., Morrison III, W.R., Campbell, J.F., Arthur, F.H., Bruce, A.I., Yeater, K.M. 2021. Evaluation of dosimeter tubes for monitoring phosphine fumigations. Journal of Stored Products Research. 91. Article 101762. https://doi.org/10.1016/j.jspr.2021.101762.*
                                *Lin, H., Bean, S.R., Tilley, M., Peiris, K., Brabec, D.L. 2020. Qualitative and quantitative analysis of sorghum grain composition using ATR-FTIR spectroscopy. Journal of Food Analytical Methods.14:268-279. https://doi.org/10.1007/s12161-020-01874-5.*
                                *Agrafioti, P., Brabec, D.L., Morrison III, W.R., Campbell, J.F., Athanassiou, C.G. 2021. Scaling recovery of susceptible and resistant stored product insects after short exposures to phosphine by using automated video-tracking software. Pest Management Science. 77(3):1245-1255. https://doi.org/10.1002/ps.6135.*
                                *Asuncion, F.B., Brabec, D.L., Casada, M.E., Maghirang, R.G., Arthur, F.H., Campbell, J.F., Zhu, K., Martin, D.E. 2020. Spray characterization of aerosol delivery systems for use in stored product insect facilities. Transactions of the ASABE. 63(6):1925-1937. https://doi.org/10.13031/trans.14010.*
                                *Wu, X., Maghirang, E.B., Armstrong, P.R. 2022. Predicting single kernel moisture and protein content of mushroom popcorn using NIR spectroscopy: Tool for detecting their effect on popping performance. Applied Engineering in Agriculture. 38(3):469-476. https://doi.org/10.13031/aea.14875.*
                                *Elsayed, S., Casada, M.E., Maghirang, R., Wei, M. 2021. Evolution of phosphine from aluminum phosphide pellets. Transactions of the ASABE. 64(2):615-624. https://doi.org/10.13031/trans.14326.*
                                *Armstrong, P.R., Maghirang, E.B., Chen, M., McClung, A.M., Yaptenco, K.F., Brabec, D.L., Wu, T., Wei, Y. 2022. Predicting single kernel and bulk milled rice alkali spreading value and gelatinization temperature class using nir spectroscopy. Cereal Chemistry. 99(6):1234-1245. https://doi.org/10.1002/cche.10587.*
                                *Gokhan, H., Armstrong, P.R. 2022. Flax and Sorghum: Multi-Elemental Contents and Nutritional Values within 210 Varieties and Potential Selection for Future Climates to Sustain Food Security.. Plants. 11(3). Article 541. https://doi.org/10.3390/plants11030451.*
                                *Su, K., Maghirang, E.B., Tan, J., Yoon, J., Armstrong, P.R., Kachroo, P., Hildebrand, D. 2022. NIR spectroscopy for rapid measurement of moisture and cannabinoid contents of industrial hemp (Cannabis sativa). Industrial Crops and Products. https://doi.org/10.1016/j.indcrop.2022.115007.*
                                *Brabec, D.L., Pordesimo, L.O. 2022. Estimating chalkiness in endosperm of typical and bleached durum kernels from transmission scanned images. Applied Engineering in Agriculture. 38(4):651-658.  https://doi.org/10.13031/aea.15023.*
                                *Petingco, M.C., Casada, M.E., Maghirang, R.G., Thompson, S.A., McNeill, S.G., Monbtross, M.D., Turner, A.P. 2022. Discrete element method simulation of wheat bulk density as affected by grain drop height and size distribution. Transactions of the ASABE. 65(3):555-566. https://doi.org/10.13031/ja.14811.*
                                *Boac, J., Casada, M.E., Pordesimo, L.O., Arthur, F.H., Maghirang, R., Mina, C.D. 2022. Effect of internal insect infestation on single kernel mass and particle density of corn and wheat. Applied Engineering in Agriculture. 38(3):583-588. https://doi.org/10.13031/aea.14858.*


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