首页> 美国政府科技报告 >Evaluation of the CEAS Trend and Monthly Weather Data Models for Soybean Yields in Iowa,Illinois,and Indiana.
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Evaluation of the CEAS Trend and Monthly Weather Data Models for Soybean Yields in Iowa,Illinois,and Indiana.

机译:评估爱荷华州,伊利诺伊州和印第安纳州大豆产量的CEas趋势和月度天气数据模型。

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The CEAS models evaluated use historic trend and meteorological and agroclimatic variables to forecast soybean yields in Iowa, Illinois, and Indiana. Indicators of yield reliability and current measures of modeled yield reliability were obtained from bootstrap tests on the end of season models. Indicators of yield reliability show that the state models are consistently better than the crop reporting district (CRD) models. One CRD model is especially poor. At the state level, the bias of each model is less than one half quintal/hectare. The standard deviation is between one and two quintals/hectare. The models are adequate in terms of coverage and are to a certain extent consistent with scientific knowledge. Timely yield estimates can be made during the growing season using truncated models. The models are easy to understand and use and are not costly to operate. Other than the specification of values used to determine evapotranspiration, the models are objective. Because the method of variable selection used in the model development is adequately documented, no evaluation can be made of the objectivity and cost of redevelopment of the model.

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