Evaluation of long-term degree-days estimated with several methods for corn in Nebraska, USA

The concept of thermal time, measured in degree-days, is widely used among the agricultural community in Nebraska to make decisions in corn (Zea mays L.) production. Instead of the real-time temperatures that are experienced by corn plants, most of the widely available temperature data are limited to daily timescale observations from standard meteorological stations. And a variety of equations are used by different agricultural groups (e.g., researchers, advisors, farmers, and seed companies) to estimate thermal time for corn. Two problems could arise: (a) the estimation method is lacking in accuracy; and (b) different estimation methods are used for the same purpose by different groups. Consequently, citing these inaccurate and maybe inherently different thermal time results could lead to biased decisions in corn production. The goal of this study is to evaluate six commonly used estimation methods by comparing the estimated thermal time with the hourly temperature approximated thermal time. We analyzed the root mean square error and mean absolute error for six metrics of total growing season (from May through September) degree-days based on the temperature data from a total of 14 long-term observing locations in Nebraska. In particular, we selected four location-extreme year cases to demonstrate the six methods’ estimation performance on a daily timescale. We found that the most commonly used adjusted T_max and T_min rectangle method provided poor estimation in the study area. Instead, single-sine, double-sine, or T_avg-based method was more superior depending on the metric of degree-days.