Determining degree-day thresholds from field observations

This paper compares several methods for determining degree-day (degrees D) threshold temperatures from Geld observations. Three of the methods use the mean developmental period temperature and simple equations to estimate: (1) the smallest standard deviation in degrees D, (2) the least standard deviation in days, and (3) a linear regression intercept. Two additional methods use iterations of cumulative degrees 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 degrees D calculation method. The method giving the best results was verified by comparing observed and predicted phenological periods using years of kiwifruit data and 10 years of cherry tree data. In general, the iteration method using the single triangle method to calculate degrees D provided threshold temperatures with the smallest RMSE values. However, the iteration method using a linear degrees 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 degrees 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.