Determination of Maturity and Degree Day Indices and their Success in Predicting Peanut Maturity
2006
Rowland, D.L. | Sorensen, R.B. | Butts, C.L. | Faircloth, W.H.
The ability to accurately assess and predict peanut maturity is a strong determinant of the economic return to the producer as 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, grade, and net value; 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 in southwest Georgia, USA. Several 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.
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