Predicting yield loss in winter wheat due to frost damage during stem elongation in the central area of Huang-huai plain in China

Abstract

Natural frost during stem elongation of winter wheat is one of the most destructive weather-related events in the Huang-Huai plain of China. Early prediction for yield loss helps to guide the timely implementation of a post-frost management strategy. Currently, frost stress indices calculated using the minimum Stevenson screen temperature (ST) only consider the effects of low temperature and duration of frost damage, exhibiting a limited ability for the early prediction of yield loss. Therefore, this study aimed to propose a new index to improve the accuracy of early prediction for yield loss. In this study, Shangqiu was selected for a survey during 2015–2019 where we proposed a method to calculate the percent yield difference (PYD) based on samples of wheat collected during the reproductive stage. In addition, we considered the impact of the compensation of regenerated tillers on PYD. An integrated frost stress (IFS) index was proposed based on the hourly minimum grass temperature (GT) at the regional scale. The IFS index integrated the influence of low temperature, duration, and developmental progress of winter wheat on frost damage and was compared with two accumulated frost degree-days (AFDD) indices to predict PYD. Frost reduced the grain number per ear and grain yield significantly ( p < 0.05), and reduced ear number and 1000-grain weight to a lesser extent. The average PYD reached 18.3% in 2018, followed by 11.2% in 2015, 4.2% in 2016, and 1.8% in 2017. Regenerated tillers contributed to yield only if the PYD increased to a certain extent. Compensation by regenerated tillers for PYD in 2018 was only 2.8% and 0.4% in the experimental field and non-experimental fields, respectively, without significant impact ( p > 0.05) on the PYD. Compared with the AFDD indices, the IFS index improved the accuracy of early prediction for PYD significantly, with the lowest root mean square error (RMSE) of 6.4%, which showed the advantage of considering the developmental progress and the hourly GT. The IFS, which adopted a critical temperature of − 3 ℃, produced the best calibration model, with the highest interpretation rate of 69.5% for variation in PYD. Although the calibration model did not show the highest accuracy in the validation, its fitted line was closest to the 1:1 line, which indicated the smallest deviation of predicted PYD from measured PYD. This research demonstrated the potential of the IFS index calculated by hourly GT data to evaluate frost damage to winter wheat during stem elongation, which will help guide site-specific, post-frost management. • An integrated frost stress (IFS) index based on hourly minimum grass temperature was proposed. • The IFS integrated low temperature, frost duration, and developmental progress of winter wheat. • The IFS with a temperature of − 3 ℃ yielded the best accuracy for predicting percent yield difference.