Determining degree-day thresholds from field observations
This paper compares several methods for determining degree-day (°D) threshold temperatures from field observations. Three of the methods use the mean developmental period temperature and simple equations to estimate: (1) the smallest standard deviation in °D, (2) the least standard deviation in days, and (3) a linear regression intercept. Two additional methods use iterations of cumulative °D and threshold temperatures to determine the smallest root mean square error (RMSE). One of the iteration methods uses a linear model and the other uses a single triangle °D calculation method. The method giving the best results was verified by comparing observed and predicted phenological periods using 7 years of kiwifruit data and 10 years of cherry tree data. In general, the iteration method using the single triangle method to calculate °D provided threshold temperatures with the smallest RMSE values. However, the iteration method using a linear °D model also worked well. Simply using a threshold of zero gave predictions that were nearly as good as those obtained using the other two methods. The smallest standard deviation in °D performed the worst. The least standard deviation in days and the regression methods did well sometimes; however, the threshold temperatures were sometimes negative, which does not support the idea that development rates are related to heat units.
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