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Spatiotemporal characteristics of white mold and impacts on yield in soybean fields in South Dakota

机译:白色模具的时空特征及南达科他州大豆田的影响

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White mold of soybeans is one of the most important fungal diseases that affect soybean production in South Dakota. However, there is a lack of information on the spatial characteristics of the disease and relationship with soybean yield. This relationship can be explored with the Normalized Difference Vegetation Index (NDVI) derived from Landsat 8 and a fusion of Landsat 8 and the Moderate Resolution Imaging Spectroradiometer (MODIS) images. This study investigated the patterns of yield in two soybean fields infected with white mold between 2016 and 2017, and estimated yield loss caused by white mold. Results show evidence of clustering in the spatial distribution of yield (Moran’s I = 0.38; p < 0.05 in 2016 and Moran’s I = 0.45; p < 0.05 in 2017) that can be explained by the spatial distribution of white mold in the observed fields. Yield loss caused by white mold was estimated at 36% in 2016 and 56% in 2017 for the worse disease pixels, with the most accurate period for estimating this loss on 21 August and 8 September for 2016 field and 2017 field, respectively. This study shows the potential of free remotely sensed satellite data in estimating yield loss caused by white mold.
机译:大豆白霉菌是影响南达科他州大豆产量的最重要的真菌疾病之一。然而,缺乏有关疾病的空间特征和与大豆产量的关系的信息。这种关系可以用源自Landsat 8的归一化差异植被指数(NDVI)和Landsat 8和中等分辨率成像光谱仪(MODIS)图像的融合来探索这种关系。本研究调查了2016年和2017年在2016年至2017年间白色霉菌中感染的两种大豆田的产量模式,以及白色模具造成的估计产量损失。结果显示在产量的空间分布中聚类的证据(Moran的I = 0.38;在观察到的领域中的模具。白色模具引起的产量损失估计2016年的36%和2017年为56%,对于更严重的疾病像素,分别为2016年8月21日和2017年9月8日估算这一损失的最准确期。本研究表明,在白色模具估算屈服损失方面的自由偏心感测卫星数据的潜力。

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