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不同产量分离方法对豫中地区夏玉米产量预测的影响OA

Effect of Different Yield Separation Methods on Forecast of Summer Maize Yield in Central Henan

中文摘要英文摘要

为探寻不同分离方法对产量预报的影响,利用 1985-2024 年豫中粮食主产区许昌市夏玉米产量数据和气象资料,采用 3a滑动平均法、5a滑动平均法、HP滤波法、五点二次平滑法、二次指数平滑法和ARIMA模型法分离夏玉米气象产量并构建单产预测模型,计算趋势预报正确率、单产预测准确率等指标评估模拟效果.结果表明:3a滑动平均法、5a滑动平均法、五点二次平滑法、二次指数平滑法分离产量效果较好,不同方法分离气象产量的正负关系有所差异;筛选的关键气象因子中,拔节-吐丝期降水量、灌浆期气温和日照时数与气象产量呈显著正相关关系(P<0.05),苗期气温、灌浆期降水量与气象产量呈显著负相关关系(P<0.05),符合玉米生长发育特性;6 种方法构建模型在回代检验中产量趋势预报正确率在 78.1%以上,单产预测准确率超过 94.5%,均方根误差小于 410.5kg·hm-2;预报检验中组合加权预测模型表现最优,单产预测准确率达到 97.2%,好于单一方法模型效果,可为粮食产量精准预报及农业生产科学决策提供参考.

In order to explore the impact of different separation methods on yield forecast accuracy,summer maize yield data and meteorological data from Xuchang city,the main grain producing area in central Henan province from 1985 to 2024 were used.The 3-year moving average,5-year moving average,HP filtering,five point quadratic smoothing,quadratic exponential smoothing and ARIMA model were used to separate meteorological yield and construct a summer maize yield forecast model.The simulation effect was evaluated by calculating indicators such as trend forecast accuracy and yield forecast accuracy.The results showed that the 3-year moving average,5-year moving average,5-point quadratic smoothing and quadratic exponential smoothing had better separation effects on yield,while there were differences in the positive and negative relationship of separating meteorological yield among different methods.Among the key meteorological factors selected,precipitation during the jointing-silking stage,temperature and sunshine hours during the grain-filling stage,showed a significant positive correlation with meteorological yield(P<0.05).The temperature during the seedling stage and precipitation during the grain filling stage showed a significant negative correlation with meteorological yield(P<0.05),which was consistent with the growth and development characteristics of maize.The yield trend forecast accuracy of 6 models in backtesting was over 78.1%,the yield forecast accuracy exceeded 94.5%,and RMSE was less than 410.5kg.ha-1.The combination weighted forecast model performed the best in forecast testing,with an accuracy of 97.2%for yield forecast,which was better than the performance of a single method model.It can provide reliable data reference for accurate grain yield forecasting and scientific decision-making in agricultural production.

王琛

中国气象局·河南省农业气象保障与应用技术重点实验室,郑州 450003||河南省许昌市气象局,许昌 461000

夏玉米产量分离方法气象产量关键气象因子产量预测

Summer maizeYield separation methodMeteorological yieldKey meteorological factorsYield forecasting

《中国农业气象》 2026 (2)

216-224,9

中国气象局农村农业部烤烟气象服务中心开放式联合基金资助项目(KYZX2023-05)许昌市应用气象工程技术研究中心开放基金项目(XQ202402)

10.3969/j.issn.1000-6362.2026.02.005

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