基于积分回归法的寒地玉米产量动态评估

Research on Dynamic Assessment of Maize Yield Based on An Integral Regression Method in Cold Region

利用黑龙江省1981~2014年80个站点气象资料、44个县市的玉米产量资料和31个农业气象站玉米生育期资料,通过气象要素膨化处理,应用积分回归建立5~7月以旬为时间尺度的玉米产量动态评估模型。根据业务需求将全省划分为4个区域,用1981~2010年资料进行模型准确率回代检验,并用2011~2014年资料进行预估。结果表明,全省平均回代准确率为87.4%,Ⅱ区最高为89.9%,Ⅰ区和Ⅳ区次之,分别为89.5%和87.8%,Ⅲ区最低为82.5%;预估平均准确率也达到87.4%,Ⅰ区和Ⅱ区模型评估准确率分别为91.5%和92.0%,均好于Ⅲ区和Ⅳ区。

Based on meteorological data of 80 representative meteorological stations,maize yield of 44 counties and maize growth period of 31 agrometeorological stations in Heilongjiang Province from 1981 to 2014.Methods for dynamic prediction of maize in the period of ten days of March to July were established according to principles of integral regression through the expansion of meteorological data.The province was divided into 4 regions as needed.The results showed that:the average accuracy of the back tests was 87.4%.The last in Ⅲ region was 82.5%.The model average prediction accuracy rates were also 87.4%.The accuracy in Ⅰ region and Ⅱ region were 91.5%and 92.0%separately,moreover they were performing better in the two regions than in Ⅲ region and Ⅳ region.