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Estimating crop yield via Gaussian quadrature

机译:通过高斯正交估计作物产量

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摘要

The present study proposes a method to estimate the yield of a crop. The proposed Gaussian quadrature (GQ) method makes it possible to estimate the crop yield from a smaller subsample. Identification of plots and corresponding weights to be assigned to the yield of plots comprising a subsample is done with the help of information about the full sample on certain auxiliary variables relating to biometrical characteristics of the plant. Computational experience reveals that the proposed method leads to about 78% reduction in sample size with absolute percentage error of 2.7%. Performance of the proposed method has been compared with that of random sampling on the basis of the values of average absolute percentage error and standard deviation of yield estimates obtained from 40 samples of comparable size. Interestingly, average absolute percentage error as well as standard deviation is considerably smaller for the GQ estimates than for the random sample estimates. The proposed method is quite general and can be applied for other crops as well-provided information on auxiliary variables relating to yield contributing biometrical characteristics is available.
机译:本研究提出了一种估计作物产量的方法。拟议的高斯正交(GQ)方法使从较小的子样本中估算农作物产量成为可能。借助于涉及与植物的生物特征有关的某些辅助变量的全部样品的信息,可以识别出要分配给包含子样品的样地产量的样地和相应权重。计算经验表明,该方法可将样本量减少约78%,绝对百分比误差为2.7%。根据平均绝对百分比误差值和从40个可比较大小的样本中得出的产量估算值的标准偏差,将该方法的性能与随机抽样的性能进行了比较。有趣的是,GQ估计值的平均绝对百分比误差以及标准偏差比随机样本估计值要小得多。所提出的方法相当通用,可用于其他农作物,因为可以提供有关有助于产量的生物特征的辅助变量的充分提供的信息。

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