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ARS Home » Southeast Area » Dawson, Georgia » National Peanut Research Laboratory » Research » Publications at this Location » Publication #190557
Title: DETERMINATION OF MATURITY AND DEGREE DAY INDICES AND THEIR SUCCESS IN PREDICTING PEANUT MATURITY

Author
item Rowland, Diane
item Sorensen, Ronald - Ron
item Butts, Christopher - Chris
item Faircloth, Wilson

Submitted to: Peanut Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/8/2006
Publication Date: 8/15/2006
Citation: Rowland, D., Sorensen, R.B., Butts, C.L., Faircloth, W.H. 2006. Determination of maturity and degree day indices and their success in predicting peanut maturity. Peanut Science. 33:125-136.

Interpretive Summary: Accurately assessing and predicting peanut maturity is really the cornerstone to economic success in peanut production. This is because peanut maturity affects quality, flavor, and yield; therefore, a peanut grower can do everything right all season, but if he/she fails to predict peanut maturity correctly, can lose everything invested in the crop. This study determined a simplified maturity index based on pod color (determined after removing the outer part of the peanut hull) that could predict peanut quality, yield, and economic return successfully. This index was then used to test whether degree day methods could predict an accurate digging date for peanuts. Degree day methods are used in the harvest of many other crops but are not currently utilized in peanut production. This study determined that the Mills degree day method developed in 1964 and based on maximum and minimum soil temperatures and the amount of water applied to the crop through the season was accurate in predicting peanut maturity.

Technical Abstract: The ability to accurately assess and predict peanut maturity is the ultimate determinant of the economic return to the producer because it governs crop quality, flavor, and yield. However, the currently available methods used to predict peanut maturity are based on hull color determination and are somewhat labor-intensive and subject to the observer’s ability to finely discriminate color classes. The objectives in this study were: 1) create an index of maturity based on the distribution of peanut pods within the accepted maturity profile board classes that give the best quantifiable correlation with peanut yield and grade; and 2) test degree day models to determine their efficacy in predicting the optimum maturity index. Peanuts were harvested on 7 and 6 sequential dates in 2003 and 2004, respectively, at two sites (Dawson and Sasser) in southwest Georgia, USA. Maturity indices were calculated at each harvest based on the percentage of pods in each color class of the maturity profile board. For both sites and years, Maturity Index 1 (the percentage of brown and black pods) showed the best relationship with grade (TSMK), yield, and net value as evidenced by adjusted R2 values. Ten degree day models and associated environmental parameters were compared using stepwise regression models against Maturity Index 1. The best fit (as determined by adjusted R2, mean square error, and coefficient of variation values) was the model first proposed for peanut by Mills in 1964 and modified with the measurement of cumulative water applied over the growing season. These results provide a simplified measure of maturity based on hull colors (Maturity Index 1) and demonstrate that cumulative degree day models can be used successfully to predict peanut maturity in the southeastern U.S.