Location: Stored Product Insect and Engineering Research
2017 Annual Report
Objectives
Quality and quantity of grain and their products can be enhanced by application of engineering principles to cultivar development, crop monitoring, harvesting, marketing, handling, storage, and processing. Our objectives are the following:
1. Develop technologies and techniques to rapidly evaluate grain quality that increase breeding efficiency and improve marketability.
A. The application of automated single kernel deoxynivalenol (DON) analysis to aid breeders in studying Fusarium head blight (FHB) resistance mechanisms in wheat.
B. Develop spectroscopic methods for rapid phenotyping to detect barley yellow dwarf (BYD) virus infection and resistance.
C. Develop fourier-transform near-infrared (FT-NIR) spectroscopy methods to measure grain traits.
D. Develop a rapid, non-destructive method to predict bread quality of hard red winter wheat (HRW) at the first point of sale.
E. Develop imaging and near-infrared and visible spectroscopy instrumentation for sorting haploid and hybrid maize seeds.
F. Develop integrated measurement systems for rapid and efficient phenotyping of seeds.
G. Develop automated single kernel and bulk analysis methods to determine damage levels in wheat kernels caused by the Sunn pest, Eurygaster integriceps.
2. Enable stored grain management practices that enhance grain quality, mitigate effects of changing climates, and prevent insect infestations.
A. Determine the accuracy, safety enhancements, and labor reduction of automated insect monitoring probe traps.
B. Develop improved grain aeration and fumigation strategies for insect-pest control in stored grain.
C. Determine the effect of time in storage and aeration on stored grain packing factors.
Pre-harvest quality can be improved through rapid phenotyping technology that relates phenotypic traits to plant genetics. Post-harvest quality can be improved though methods to measure grain traits and methods to enhance storage conditions. Changing climates are expected to produce extreme weather conditions, leading to a need for accelerated breeding programs and improved storage technology to maintain and improve yields and quality. Our unique facilities include the ability to study climate change influences on plant physical, physiological and morphological status through our expertise in instrumentation combined with use of our grain storage facilities and access to greenhouses.
Approach
United States farmers grow over 77 million metric tons of corn, wheat, soybeans, and other grains, worth over $115 billion annually, to supply the nation and the world with food, animal feed, and biofuels. Our 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 quality during storage. We propose to develop instruments to rapidly measure quality traits for inspection at the first point of grain delivery, for breeders when selecting traits for new lines, and for processors prior to grain buying or processing. We also propose to develop chemical-free technology to control insects and maintain quality during handling and storage. This research will lead to higher profits for the agriculture sector, higher-quality foods reaching consumers, and more food available for a growing world population.
Progress Report
This report documents progress for Project 3020-43440-008-00D “Impacting Quality Through Preservation, Enhancement, and Measurement of Grain and Plant Traits” which started Jun 2015. The project has two main objectives.
Objective 1: Develop technologies and techniques to rapidly evaluate grain quality that increase breeding efficiency and improve marketability. Near-infrared spectroscopy (NIRS) and Fourier-transfer NIRS (FTNIRS) calibrations were developed and improved to measure deoxynivalenol (DON) and fusarium head blight (FHB) in wheat samples. Thousands of breeder samples were evaluated and information provided to breeders to develop lines with DON and FHB resistance traits. Similar NIRS techniques were used to develop calibrations to detect Barley Yellow Dwarf in wheat. The same NIRS principles are being used to detect traits of insects that transmit infectious diseases, such as malaria, Zika, and dengue. Calibrations for single seed NIRS prediction of oat beta-glucans, protein and lipids were developed to evaluate commercial oat varieties and lines to help facilitate increasing beta-glucan content and understand correlations between these constituents. Lipid based discrimination of maize haploid seeds using single kernel NIRS was investigated which can used to reduce hybrid development times for breeders. Potential quality control methods were examined by using discriminate models using near infrared and visible spectra to detect black tip damaged wheat kernels; black tip adversely affects flour quality. Discriminate models to identify insect damaged wheat kernels caused by Sunn pest were developed.
Objective 2: Enable stored grain management practices that enhance grain quality, mitigate effects of changing climates, and prevent insect infestations. Heat transfer models were developed to predict the cooling pattern of low-oil distiller dried grains and solubles (DDGS) piles to gain insight on how to prevent or minimize caking which causes problems in transferring material. The models were successfully validated with field data. Grain stored in a bin undergoes compression from the weight exerted from the overlying material in the bin. Calculating compression is essential when estimating the current total U.S. grain supply. The extent of compression depends on crop type, test weight, moisture content, bin wall material, bin size, and other factors and results in an increase in density. Studies were conducted to improve the prediction of grain packing by including storage time, aeration, and effect of loading cycles. The effects of secondary grain quality parameters like high dockage wheat, high damage for corn, and presence of genetically modified organisms (GMO) traits were also investigated. Field data were collected from 16 bins at commercial elevators and farms to determine the effects of time and aeration on grain packing for corn, wheat, soybeans, and barley. In addition, 22 bins were monitored through the spring of 2017 for changes in grain height over time with and without aeration. Four barley bins were tracked for 12 months. This year’s field data will be combined with bin tracking data from other storage seasons for further analysis. Models between test weight (TW) without dockage and the bulk density with dockage were obtained based on the reported scale data during the wheat harvest from three elevators located in Kansas and Oklahoma. A power model was developed to predict bulk density with dockage when TW weight without dockage and dockage levels are given. Hard Red Winter wheat with dockage levels ranging from 0.05% to 5% showed a second order polynomial trend when plotted against decrease in bulk density with dockage values compared to test weight without dockage. These results will be crucial for determining grain packing inventory parameters for wheat bins. Design, construction and evaluation of a novel low cost hand moisture meter suitable for emerging countries was performed. This design was adapted from technology previously developed for the U.S. grain storage industry.
Accomplishments
1. Measuring mycotoxins in single seeds. Fusarium head blight (FHB) disease cause significant yield and quality losses in harvested wheat resulting in numerous problems in grain marketing, processing and utilization leading to severe economic losses. Quality losses include those due to the presence of mycotoxins such as deoxynivalenol (DON) in infected grains which are harmful for human and animal health. In order to improve prediction models, the effect of moisture content variation on the accuracy of single kernel deoxynivalenol (DON) prediction by near-infrared (NIR) spectroscopy was investigated. Sample moisture content (MC) considerably affected accuracy of the current NIR DON calibration. DON in single kernels was most accurately estimated at a MC of 13-14% MC. These results show that NIR absorption regions associated with water are often close to absorption regions associated with fusarium damage. Thus, care must be taken to develop DON calibrations that are independent of grain MC. This information will be useful to instrumentation developers, wheat breeders, and other users utilizing NIR technology to measure FHB and DON in grain.
2. Detecting bacteria in mosquitoes that transmit dengue. We investigated the potential of using near-infrared spectroscopy (NIRS) to detect the presence of Wolbachia pipientis (wMel) in male and female laboratory-reared Aedes aegypti mosquitoes. The release of Wolbachia transinfected mosquitoes is likely to form a key component of disease control strategies in the future. Our aim is to find faster, cheaper alternatives for monitoring those releases than the molecular diagnostics that are currently in use. Our findings indicate that NIRS can differentiate females and males infected with wMel from uninfected wild type samples with accuracies of 92% (N=352) and 89% (N=444). This non-destructive technique is approximately 24 times faster than the standard polymerase chain reaction diagnostic techniques currently used for Wolbachia detection. After the purchase of a NIRS spectrometer, the technique requires little sample processing, is non-destructive and does not consume any reagents.
3. Detection of internally infested popcorn. Rapid detection of insect pests that develop inside grain is a challenge for the grain, milling and food processing industries, since there is little external sign of infestation. We developed a conductive roller mill to detect insect infested seeds by grinding the grain using a pair of grinding rolls with a low voltage connection across them to detect changes in circuit resistance when insect infested seeds are ground. The mill was able to detect 80%-90% of the medium and large insects. The conductive roller mill provided rapid processing and reasonably high detection effectiveness and could be used a useful tool for industry stakeholders in their evaluation of grain during inbound inspection and during storage.
Review Publications
Armstrong, P.R., Maghirang, E.B., Yaptenco, K.F., Pearson, T.C. 2016. Visible and near-infrared instruments for detection and quantification of individual sprouted wheat kernels. Transactions of the ASABE. 59(6):1517-1527. doi:10.13031/trans.59.11566.
Dowell, F.E., Dowell, C.N. 2017. Reducing grain storage losses in developing countries. Quality Assurance and Safety of Crops & Foods. 9(1):93-100. doi:10.3920/QAS2016.0897.
Brabec, D.L., Dowell, F.E., Campbell, J.F. 2016. Detection of internally infested popcorn using electrically conductive roller mills. Journal of Stored Products Research. 70:37-43. doi:10.1016/j.jspr.2016.11.002.
Peiris, K.S., Dong, Y., Bockus, W.W., Dowell, F.E. 2016. Moisture effects on the prediction performance of a single kernel near-infrared deoxynivalenol calibration. Cereal Chemistry. 93(6):631-637. doi:10.1094/CCHEM-04-16-0120-R.
Bhadra, R., Casada, M.E., Turner, A., Boac, J.M., Thompson, S.A., Maghirang, R.G., Montross, M.D., McNeill, S.G. 2017. Technical Note: Field-observed angles of repose for stored grain in the United States. Applied Engineering in Agriculture. 33(1):131-137. doi:10.1303/aea.11894.
Turner, A.P., Jackson, J.J., Koeninger, N.K., McNeill, S.G., Montross, M.D., Casada, M.E., Boac, J.M., Bhadra, R., Maghirang, R.G., Thompson, S.A. 2017. Technical Note: Stored grain volume measurement using a low density point cloud. Applied Engineering in Agriculture. 33(1):105-112. doi:10.13031/aea.11870.
Bhadra, R., Ambrose, K.P., Casada, M.E., Simsek, S., Siliveru, K. 2017. Optimization and modeling of flow characteristics of low-oil DDGS using regression techniques. Transactions of the ASABE. 60(1):249-258. doi:10.13031/trans.11928.
Sikulu-Lord, M.T., Masabho, P.M., Henry, M., Wirtz, R.A., Hugo, L.E., Dowell, F.E., Devine, G.J. 2016. Near-infrared spectroscopy, a rapid method for predicting the age of male and female wild-type and Wolbachia infected Aedes aegypti. PLOS Neglected Tropical Diseases. 10(10):e0005040. doi:10.1371/journal.pntd.0005040.
Arthur, F.H., Casada, M.E. 2016. Temperature stratification and insect pest populations in stored wheat with suction versus pressure aeration. Applied Engineering in Agriculture. 32(6):849-860. doi:10.13031/aea.32.11757.
Patwa, A., Ambrose, R., Casada, M.E. 2016. Discrete element method as an approach to model the wheat milling process. Powder Technology. 302:350-356. doi:10.1016/j.powtec.2016.08.052.
Armstrong, P.R., Dell'Endice, F., Maghirang, E.B., Rupenyan, A. 2017. Discriminating oat and groat kernels from other grains using near infrared spectroscopy. Cereal Chemistry. 94(3):458-463. doi:10.1094/CCHEM-06-16-0162-R.
Montilla-Bascon, G., Armstrong, P.R., Han, R., Sorrells, M. 2017. Quantification of betaglucans, lipid and protein contents in whole oat groats (Avena sativa L.) using near infrared reflectance spectroscopy. Journal of Near Infrared Spectroscopy. 25(3):172-179. doi: 10.1177/0967033517709615.
Brabec, D.L., Guttieri, M.J., Pearson, T., Carsrud, B. 2017. Effectiveness of an image-based sorter to select for kernel color within early segregating hard winter wheat (Triticum aestivum L.) populations. Cereal Research Communications. 45(3): 488-499. doi: 10.1556/0806.45.2017.034.
