Location: National Peanut Research LaboratoryTitle: Variation of Farmer Stock Grade Factors in Semi-Drying Trailers
Submitted to: American Peanut Research and Education Society Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 5/15/2013
Publication Date: 12/15/2015
Citation: Butts, C.L., Lamb, M.C., Abdo, Z. 2015. Variation of Farmer Stock Grade Factors in Semi-Drying Trailers. American Peanut Research and Education Society Abstracts. Annual meeting presentation.
Interpretive Summary: none required
Technical Abstract: Peanuts are increasingly being loaded into flat bottom semi-drying trailers in the field and transported to peanut buying points for curing, grading, and marketing. Conveyances in excess of 15 t are probed 15 times using the pneumatic sampler requiring considerable time for probing and reducing the resulting sample to two 1800-g samples. The goal of this study is to determine if number of probes can be reduced while maintaining the accuracy of the current sampling plan. During the harvest and marketing of the 2012 peanut crop, inspectors from the Alabama Federal-State Inspection Service (FSIS) selected 18 loads of farmer stock peanuts from all peanut production areas in Alabama. Inspectors selected the loads at random from semi-drying trailers following conventional marketing without regard to the official grade of the load. Each load was divided into a grid consisting of three (3) cells across the width of the trailer and 15 cells along the length for a total of 45 cells. Each cell was probed one time using the pneumatic probe resulting in a sample weighing approximately 3-4 kg each. Each sample was then divided using the farmer stock riffle divider into two official-sized grade samples. Each grade sample was identified by load number, column (1, 2,3), row (1-15), and sub-sample (A or B) then evaluated according to standard FSIS farmer stock grading procedures to determine the percent foreign material (FM), loose shelled kernels (LSK), sound mature kernels (SMK), sound splits (SS), other kernels (OK), damaged kernels (DK), and hulls. Contour maps of each load were developed to visualize the variation of grade factors by position. Adequate representation of the grade consists of an accurate mean plus or minus a similar expected error (variance) of each grade factor. Average grade factors were determined by averaging the data from cells used in the conventional 15-probe pattern. Probe patterns consisting of data from 12 and 9 cells were used to determine 12- and 9-probe grades. Using standard T-tests to determine differences among mean grade factors for each load, there was no significant difference in the mean grade factors for each load using 15, 12, or 9 probes. For the comparison of variances due to number of probes, it was assumed that the variance using data from all 45 cells from each load was the “true” variance of the grade factors for each load. For the purpose of variance comparison, composite samples were generated from the original data by randomly selecting cells until the desired number of probes had been achieved, then the grade data averaged and repeated 1000 times for each load and each number of probes. The variance of these randomly-generated grades were compared to the actual variance of the load. The variance of the percent SMK, TSMK, estimated the actual variance as long as at least 12 probes were used. The variance estimated for the percent hulls and SS compared favorably when 15 probes or more were used. However, when 15 probes were used to estimate FM and LSK, the variance for 8 and 7 loads, respectively, underestimated the true variance. Similar underestimation of the variance for moisture content, OK, and DK for at least 5 loads when using a 15-probe sampling protocol. The authors gratefully acknowledge that the Alabama Federal-State Inspection Service for collecting and processing all of these samples for this study.