Predicting Physiological Growth Period based on Cumulative Climatic Suitability of Spring Maize

Abstract

The growth period prediction at the various physiological stage of spring maize is an essential component in agricultural management decisions. An Improved Climate Suitability (ICS) model was established by integrating temperature, precipitation, sunshine and soil moisture and setting individual weight coefficient in each subordinate function according to the observation data of spring maize growth and meteorological factors of 14 agrometeorological stations in the Liaoning Province of northeast China from 1981 to 2010. The predicted value (Bjk) and reference value (Bk) of the cumulative climatic suitability index were calculated by the ICS model for arranging farming activities in advance when the Bjk > Bk at the various physiological growth stage of spring maize. The ICS model was further verified by the observation data at the whole and various physiological stages of spring maize. The result showed that the Bjk was linearly correlated with the observed days at each physiological growth stage of spring maize with R² of 0.75-0.88, P<0.001, Thus, the Bjk can be used to determine the growth period of the various physiological stage of spring maize. The prediction days were significantly correlated with the observed days at the whole and each physiological growth stage of spring maize (R² of 0.57-0.98, P<0.001) with the absolute error (ABSE) of 1.1-4.1 d. Thus, the precision of the ICS model is acceptable for forecasting the growth period and arranging farming activities in advance. Thus, the ICS model should be promoted further in the management of spring maize plantation.