基于生理生态过程的大麦顶端发育和物候期模拟模型检验

为测试研究I 模型BarleyGrow,采用4个生态区(南京、扬州、武汉、昆明)、10个大麦品种在不同播期下的顶端发育和物候期资料,对BarleyGrow、YDmodel和SUCROS模型进行对比检验和评价.利用遗传-模拟退火算法确定各品种的遗传参数,提高了应用程序求算参数的精度.从模型的整体预测效果来看,BarleyGrow对不同地区、不同播期、不同品种的各顶端发育和物候期预测准确而稳定,均方差RMSE在1.06～7.94d之间,而YDmodel为6.26～13.35d,SUCROS为11.22～20.28d.各参试品种对BarleyGrow中灌浆期基点温度、生理春化时间、临界日长、最短苗穗期4参数反应敏感.经改进的生理发育时间(PDT)模拟模型(BarleyGrow)对中国广大地区不同温光条件下的大麦顶端发育和物候发育均具有较好的预测效果,尤其对药隔期、二裂期、毛状期、抽穗期、灌浆期、成熟期的模拟精度高而稳定,表现出较强的机理性以及较好的预测性.

A process-based simulation model on apical and phenological stages in barley: Model validation

To test BarleyGrow model reported in the study I, 14 barley cultivars were grown at different sowing dates in 4 ecological areas (Nanjin, Yangzhou, Wuhan and Kunming). Apical and phenological stages of different cultivars were observed to validate the BarleyGrow model which is compared with YDmodel and SUCROS. The optimum values of the model parameters were obtained through genetic-simulated annealing algorithms. As a whole, BarleyGrow model had an accurate and stable estimation. The root mean square error (RMSE) with the BarleyGrow model was ranged between 1.06 and 8.13 days for various cultivars, compared to 6.26 and 13.35 days with YDmodel, and 8.84 and 20.28 days with SUCROS. BarleyGrow model was quite sensitive to basic temperature in grain filling time, physiological vernalization time, critical daylength and minimum time from emergence to heading. The improved model gave good predictions of apical and phenological development for a diverse range of temperature and photoperiod conditions across China. Especially, effects in anther separation, pollen mother cells, tetrad, heading, grain filling and maturity stages were better predicted.