不同积温模型的稳定性评估——以东北春玉米为例

Stability evaluation of different accumulated temperature models: A case of spring maize in Northeast China

本研究基于春玉米品种"丹玉13"、"龙单13"和"四单19"生长发育资料和同期的地面观测资料,分别拟合了沈国权、高亮之和殷新佑的非线性积温模型,获取各模型参数并对模型进行检验,将3种积温模型模拟结果进行比较和稳定性评价,并与常用积温法计算的结果对比。结果表明:在拟合检验中,出苗-成熟阶段,高亮之模型的模拟效果最好;在出苗-拔节阶段,3个模型的模拟效果相差不大;在拔节-抽雄、抽雄-成熟阶段,高亮之模型优于殷新佑模型优于沈国权模型。在稳定性分析中,在出苗-成熟整个生育期,3种非线性积温模型优于常用积温法,表现出更好的稳定性;出苗-拔节阶段,沈国权模型稳定性最好;拔节-抽雄阶段以沈国权和殷新佑模型最稳定;抽雄-成熟阶段4种方法的稳定性相差不大。综上所述,考虑参数有效性情况,出苗-拔节阶段,选择沈国权模型效果最好;拔节-抽雄、抽雄-成熟阶段宜采用殷新佑模型;在出苗-成熟全生育期,选用高亮之模型。研究结果可为东北春玉米发育期预报及产量预报等提供理论依据和技术支持。

In this study, the field observation data of spring maize varieties including ＂Danyu 13＂, ＂Longdan 13＂ and ＂Sidan 19＂ in Northeast China were used to fit three nonlinear accumu- lated temperature models proposed by Shen Guoquan, Gao Liangzhi and Yin Xinyou respectively, and to obtain the model parameters. Precision and stability of the simulation results were as- sessed, and compared with that of the commonly used accumulated-temperature method. The re- suits showed that the simulation result of Gao Liangzhi model was the best during the period from emergence to maturity. The three nonlinear accumulated temperature models had the similar re- sults in fitting effective accumulated temperature during the period from emergence to jointing. During the jointing-heading and heading-maturity stages, Gao Liangzhi model performed best, followed by Yin Xinyou model and Shen Guoquan model. On the analysis of variation coefficient and relatively extreme value of the effective accumulated temperature calculated by the four meth- ods, the stability of the three nonlinear accumulated temperature models was consistently superior to the commonly used method during the whole growth period. During the emergence-jointing stage, Shen Guoquan model had better stability. During the jointing-heading stage, the stability of Shen Guoquan and Yin Xinyou models was the best. The stability of the four methods was simi- lar during the period from heading to maturity. However, a parameter validity problem was found in the process of fitting the three accumulated temperature nonlinear models. In conclusion, Shen Guoquan model could be selected during the period from emergence to jointing. From jointing to heading stage, Yin Xinyou model was the best. Gao Liangzhi model was suitable for the whole growth period. Our results can provide theoretical basis and technical support for spring maize development and yield prediction in Northeast China.