Location: National Peanut Research LaboratoryTitle: Reducing the number of probes for a farmers’ stock grade for a semi-drying trailer
Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 5/8/2023
Publication Date: N/A
Interpretive Summary: After harvest peanuts are taken to buying points for grading and sale. Approximately half of the harvested peanuts are taken to the buying points in semi-trailers modified for top loading and peanut drying. Under the current instructions for official farmers’ stock grade from a semi-drying trailer, the probe for the pneumatic sampler must be inserted into the trailer a minimum of 15 times to extract peanuts for the official sample. Sampling a semi-drying trailer takes a proficient sampler operator at least 30 minutes to properly probe the trailer and obtain the official farmers’ stock grade sample. During the 2022 peanut harvest a study was done to see if semi-drying trailer loads of peanuts could be graded using fewer probe insertions while producing the same grade results. Comparing the grades from 219 loads showed no statistical difference between using six or nine probe insertions and using 15 probe insertions when collecting peanuts for grading.
Technical Abstract: It is estimated that more than half the US peanut crop is harvested and delivered on flat-bottomed semi-drying trailers. Under the current instructions for official farmers’ stock grade from a semi-drying trailer, the probe for the pneumatic sampler must be inserted into the trailer a minimum of 15 times to extract peanuts for the official sample. This extracts approximately 100 kg of peanut material from the trailer, that is then subsampled as it is emptied from the sample bin back onto the trailer. Sampling a semi-drying trailer takes a proficient sampler at least 30 minutes to properly probe the trailer and obtain the official farmers’ stock grade sample. A study was conducted during the 2022 harvest to determine if a representative sample could be obtained from a semi-drying trailer using fewer than 15 probes. To test the hypothesis, a trailer was selected at a buying point prior to the official grade being obtained. It was sampled according to current protocol using 15 probes to obtain the official sample. It was sampled a second time using 9 probes to obtain the sample and a third time using 6 probes to obtain a sample. The 15-, 9-, 6-probe sequence was repeated to obtain 2 replications for each number of probes. Each sample was evaluated using the official protocol for determining farmers’ stock grades. Sampling and grading were carried out by Federal-State inspectors. Recorded data included, percent foreign material (FM), loose shelled kernels (LSK), sound mature kernels riding a prescribed screen (SMKRS), sound splits (SS), other kernels (OK), damaged splits, and total damaged kernels (TDK), and hulls. A paired T-test was used to compare the grade factors obtained using 15-, 9-, and 6-probe samples. Forty-two peanut buying points across seven states participated in the study, grading 219 trailers in the study. Approximately 70 percent of the loads were graded in Georgia. Runner-type peanuts made up 89% of the loads graded. There were 24 virginia-type of 219 loads graded. No difference in the variability of repeated grades for the same trailer was found due to the number of probes. There were no significant differences between the 15-probe and the 9-probe grades, nor between the 15-probe and 6-probe grades factors. No differences were observed between the grade factors for the 9- and 6-probe samples. The largest difference was observed for the SMKRS and TSMK with the 15-probe values 0.5% less than the 9- and 6-probe samples. These differences resulted in a net farmers’ stock loan value for the 15-probe value being approximately $1.99/ton lower than the 9- and 6-prove values. In summary, there was no evidence that the variability is any higher in the 6-probe or 9-probe samples relative to the 15-probe. In addition, there is no evidence for any systematic bias introduced by the reduced numbers of probes. Therefore, it can be concluded that reducing the number of probes will have no negative impacts on data quality.