作　　者： (成林）; (刘荣花）;

机构地区： 中国气象局·河南省农业气象保障与应用技术重点开放实验室,郑州450003 河南省气象科学研究所,郑州450003

出　　处： 《气象与环境科学》 2017年第2期28-32,共5页

摘　　要： 根据冬小麦理论产量由单位面积有效茎、穗粒数和千粒重求积的农学原理,结合冬小麦生长季气温、日照和水分适宜度的计算模型,在河南省选择5个代表站点,利用1995-2013年冬小麦生长季的逐旬气象要素,构建了气温、日照、降水和土壤水分适宜度序列,分别建立了各代表站点产量要素的变化率或距平百分率的动态预报模型。结果表明:有效茎与气象条件的直接相关性不显著,但株成穗数的变化率与气温和水分适宜度的相关性较好,千粒重距平与土壤水分适宜度的相关性显著,穗粒数与气象因子适宜度的相关性小。除穗粒数变化率预报模型外,构建的株成穗数变化率及千粒重距平的动态预报模型显著性水平均较高。模型可从4月1日起,逐旬预报各产量要素值,各代表站点对株成穗数、穗粒数和千粒重的预报回代检验平均准确率分别为80.4%、88.5%和94.0%,5月上旬以后对理论产量的预报平均准确率为93.3%。利用2014年资料进行外推检验,对穗粒数和千粒重的预报准确率均在92.0%以上。因此基于主要气候因子适宜度与农学模式相结合的方法,可实现产量动态预报,预报准确率基本满足业务服务需求,但模型对产量的丰歉趋势预报准确率仍相对较低。 According to the agronomic principle that the theoretic yield of winter wheat is the multi- plication of productive tiller in unit area, kernels per spike and thousand seed weight, suitability indexes models of air temperature, sunshine hour, precipitation and soil water during the growing season of winter wheat were used. The 5 representative stations were chosen in Henan province, and by taking advantage of meteorology elements in period of ten days in 1995--2013, suitable indexes sequence of air temperature, sunshine hour,precipitation and soil water were calculated, and then, dynamic forecasting models for the variation rate or departure of the yield elements were established respectively. The results indicated that, although productive tiller was not obviously related to meteorological conditions, the variation of plant spike number had better correlation coefficients with temperature and water suitable index, and the depar- ture of thousand seed weight was related to soil moisture suitable index obviously, however, the correlation between kernel number and suitable index of meteorological elements was small. Except for the forecasting model of kernel number variation, the forecasting models for plant spike number variation and thousand seed weight departure all passed the significance test. The models could forecast the yield elements step by ten days from April 1 , and for the 5 representative stations,the average accuracy rate of back substitu- tion test for plant spike number,kernels number per spike and thousand seed weight was 80.4% ,88.5% and 94.0% respectively,and after the first ten day of May,the average accurate rate was 93.3% for the theoretical yield forecasting. For the extrapolation test with data of 2014 ,the accurate rate of kernel num- ber and thousand seed weight was higher than 92.0%. So by the method of combination of suitability in- dexes of meteorological elements with agronomic model, dynamic forecasting of final yield could be feasible,and the accuracy could satisfy the demand of ope

关 键 词： 农学模式 穗粒数变化率 动态预报 温度适宜度