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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 #309070
Title: Error analysis in the measurement of stored grain volume

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

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/15/2016
Publication Date: 5/1/2016
Citation: Turner, A.P., Montross, M.D., Jackson, J.J., Koeninger, N.K., McNeill, S.G., Casada, M.E., Bhadra, R., Boac, J.M., Maghirang, R.G., Thompson, S.A. 2016. Error analysis in the measurement of stored grain volume. Transactions of the ASABE. 59(3):1061-1072. https://doi.org/10.13031/trans.59.11501.
DOI: https://doi.org/10.13031/trans.59.11501

Interpretive Summary: Measurement of stored grain volume is important for crop insurance, financial statements, and as a good business practice for inventory control. The recent, rapid increase in bin sizes has caused greater difficulty in measuring bin volumes compared to smaller bins, particularly for accurately estimating bin surface profiles relative to standard cones. The effect of measurement errors caused by the uncertainty in measuring the bin diameter and grain height was evaluated and presented as a function of grain height to diameter ratio. With accurate measurements, the overall uncertainty in the volume measurement never exceeded 5% for small bins (<10 m in diameter) and decreased to less than 1% for large diameter bins (>10 m in diameter). A low-cost, portable bin surface mapping system was developed to accurately measure the grain surface using a laser distance meter, tablet PC, and ArcMap software. This system significantly lowered the coefficient of variation in farm bins to less than 6% and is suitable for large commercial bins.

Technical Abstract: Measurement of the quantity of stored grain is important for crop insurance, financial statements, and as a good business practice for inventory control. Traditionally, the volume of grain has been measured using weighted tape measures along with visual correction of the grain surface to use standard geometric shapes (cylinders and cones). Recently, bins have increased rapidly in size such that irregularities and variations in surface conditions are difficult to take into account in calculating the volume of the grain. The focus of this paper is on the errors associated with the measurement of the grain volume and alternative methods to increase the accuracy of the volume measurement. Error propagation analysis was performed to evaluate the error in the stored volume caused by the uncertainty associated with measuring the bin diameter and grain height as a function of grain height to diameter ratio (H/D). For the case of accurate measurements, defined as a standard deviation of 1.2 cm (0.04 ft) in the diameter and 7.6 cm (0.25 ft) in the height, the overall uncertainty in the volume measurement never exceeded 5% for small bins (<10 m in diameter) and decreased to less than 1% for large diameter bins (>10 m in diameter). As the H/D ratio became smaller, the uncertainty increased, especially with small diameter bins. This increase in inaccuracy was due to the fact that the surface profile of the grain has a larger influence on the total volume of grain in shallow bins relative to the whole volume. Field measurements with three trained FSA and crop insurance agents with farm sized bins (8.2 to 11.0 m; 27 to 36 ft) resulted in a coefficient of variation between 0.13 and 11.65% when the grain surface was not level. When the grain surface inside the bins was manually leveled the coefficient of variation decreased to a level between 0.39 and 2.30%. However, manually leveling of the grain surface within all bins is not a feasible alternative to increase accuracy, but the error propagation analysis and field data indicated that accurate measurement of the surface was critical for accurate volume measurement. A bin surface measuring system was developed that would allow for the low-cost, portable mapping of grain surface conditions. To accurately measure the grain surface, a laser distance meter, tablet PC, and ArcMap were used to map the grain surface. This system significantly lowered the coefficient of variation in farm bins to less than 6% and would be suitable for large commercial bins.