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ARS Home » Plains Area » Manhattan, Kansas » Center for Grain and Animal Health Research » Stored Product Insect and Engineering Research » Research » Publications at this Location » Publication #307829
Title: Pack Factor Measurementss for Corn in Grain Storage Bins

Author
item BHADRA, RUMELA - Kansas State University
item TURNER, AARON - University Of Kentucky
item Casada, Mark
item MONTROSS, MICHAEL - University Of Kentucky
item THOMPSON, SIDNEY - University Of Georgia
item BOAC, JOSEPHINE - Kansas State University
item MCNEILL, SAMUEL - University Of Kentucky
item MAGHIRANG, RONALDO - Kansas State University

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/16/2015
Publication Date: 7/20/2015
Citation: Bhadra, R., Turner, A.P., Casada, M.E., Montross, M.D., Thompson, S.A., Boac, J.M., Mcneill, S.G., Maghirang, R.G. 2015. Pack Factor Measurements for Corn in Grain Storage Bins. Transactions of the ASABE. 58(3):879-890. DOI: http://dx.doi.org/10.13031/trans.58.11033.

Interpretive Summary: Corn is stored in commercial size silos which are often several meters deep and wide. Grain can support the great pressure without crushing, but it is somewhat compressible and bulk density changes with depth. A science-based model (WPACKING) for compaction of corn is available, which accounts for varying bulk density with overbearing pressure of the grain column. However, this model needs to be calibrated with field data from commercial bins over a wide range of conditions to insure its robust prediction accuracy. The specific objective of this research was to determine the field packing factors and bin capacities for commercial bins (both concrete and steel) used to store corn in United States, then use it for calibration of the WPACKING program. These values were also compared to the technique used by USDA Risk Management Agency (RMA) and USDA Farm Service Agency set of pack factor values. The percentage difference between model predicted and reported mass will help to calibrate WPACKING model and make is accurate and more robust for any type of corn bin. Perpercent differences for USDA-RMA method predicted was slightly more than the percent differences as found in WPACKING model. The results of this study will be incorporated into the WPACKING model which is will be available in a windows based software program along with other major U.S. crops. The software will be powerful, easy to use, reliable, and scientific tool for the governmental insurance agencies, elevator managers, and interested researchers, where they can predict amount of grain and compaction for any crop with any bin configuration.

Technical Abstract: Grain is commonly stored commercially in tall bins, which often are as deep as 35 m (114.8 ft) for tall and narrow concrete bins and about 32 m (105 ft) in diameter for large corrugated steel bins. Grain can support the great pressure without crushing, but it yields somewhat to compaction under its own weight, leading to an increase in bulk density and a change in volume. Reliable grain packing factors are needed to estimate storage capacities and to accurately monitor grain inventories. A science-based model (WPACKING) of compaction is available which uses the differential form of Janssen’s equation and takes into account the variation in density caused by bin height and moisture of the grain. Furthermore, the effects of grain type, test weight, bin geometry, and bin material have been taken into account in this model. However, this model needs to be calibrated with field data from commercial bins (farms and elevators) over a wide range of conditions to insure its robust prediction accuracy. The specific objective of this research was to determine the field packing factors and bin capacities for commercial bins (both concrete and steel) used to store corn in United States. This data set will be used for calibration of the WPACKING program. These values were also compared to the technique used by USDA Risk Management Agency (RMA) and USDA Farm Service Agency which also has their set of pack factor for estimating bin capacities. The % difference range between predicted mass and reported mass was -4.54% to +4.53% for WPACKING model, -2.92% to 4.97% for RMA method, -3.33% to + 5.67% for FSA method. The variability of % differences was more in RMA method than WPACKING model prediction, where most of the data points were close to zero percent difference line.