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ARS Home » Southeast Area » Dawson, Georgia » National Peanut Research Laboratory » Research » Publications at this Location » Publication #263659

Title: Improving the accuracy of electronic moisture meters for runner-type peanuts

Author
item Lamb, Marshall
item Butts, Christopher - Chris
item BLANKENSHIP, PAUL - Retired ARS Employee

Submitted to: Peanut Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/5/2011
Publication Date: N/A
Citation: N/A

Interpretive Summary: Runner-type peanut kernel moisture content is measured periodically during curing and post harvest processing with electronic moisture meters for marketing and quality control. The peanut industry may expand marketing of farmer stock peanuts to higher moisture contents and it is imperative that moisture content determination be as accurate as current technology allows. Electronic moisture meters are used to determine moisture content of shelled peanut. To examine the accuracy and range of a commercial moisture meter, samples were measured with the meter and compared to ASAE Oven Moisture Standard Data. A calibration equation was derived from capacitance, conductance, temperature, and test weight data provided by the meter and compared to the oven moisture content. Results of the study indicate that the accuracy of the meter in predicting moisture content can be improved considerably utilizing the derived calibration equation. Utilization of the equation requires only low level data manipulation capability and should not significantly impede utilization.

Technical Abstract: Runner-type peanut kernel moisture content (MC) is measured periodically during curing and post harvest processing with electronic moisture meters for marketing and quality control. MC is predicted for 250 g samples of kernels with a mathematical function from measurements of various physical properties. To examine the accuracy of the function used in the Dickey-john GAC2100 for measuring MC of runner-type peanuts, 421 samples were measured with the meter and compared to oven MC data subsequently determined using ASAE Standard S410.1. Peanut moisture content for the peanuts according to the meter averaged 19.1% with a SD of 15.4%. Oven moisture contents had a mean of 17.3% and a SD of 8.5%. Means were significantly different (P = 0.001). A calibration equation was derived from capacitance, conductance, temperature, and test weight data provided by the meter and compared to oven MC data. Moisture contents calculated from the calibration equation had a 17.3% mean and an 8.5% SD equaling values for oven determined moisture contents. Results of the study indicate that the accuracy of the meter in predicting moisture content can be improved considerably utilizing currently collected data and the derived calibration equation developed.