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A new spectral index for the quantitative identification of yellow rust using fungal spore information

机译:用真菌孢子信息定量鉴定黄铁锈的新光谱指标

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Yellow rust (Puccinia striiformis f. sp. Tritici ) is a frequently occurring fungal disease of winter wheat (Triticum aestivum L. ). During yellow rust infestation, fungal spores appear on the surface of the leaves as yellow and narrow stripes parallel to the leaf veins. We analyzed the effect of the fungal spores on the spectra of the diseased leaves to find a band sensitive to yellow rust and established a new vegetation index called the yellow rust spore index (YRSI). The estimation accuracy and stability were evaluated using two years of leaf spectral data, and the results were compared with eight indices commonly used for yellow rust detection. The results showed that the use of the YRSI ranked first for estimating the disease ratio for the 2017 spectral data (R~(2)?=?0.710, RMSE?=?0.097) and outperformed the published indices (R~(2)?=?0.587, RMSE?=?0.120) for the validation using the 2002 spectral data. The random forest (RF), k-nearest neighbor (KNN), and support vector machine (SVM) algorithms were used to test the discrimination ability of the YRSI and the eight commonly used indices using a mixed dataset of yellow-rust-infested, healthy, and aphid–infested wheat spectral data. The YRSI provided the best performance.
机译:黄色锈病( Puccinia striormis f。sp。tritici)是冬小麦的经常发生的真菌疾病( Triticum aestivum L.)。在黄色防锈期间,真菌孢子在叶子的表面上出现为黄色和狭窄的条纹,平行于叶静脉。我们分析了真菌孢子对患病叶的光谱的影响,为黄色生锈找到一个敏感的乐队,并建立了一种称为黄色锈孢子指数(YRSI)的新植被指数。使用两年的叶谱数据评估估计精度和稳定性,并将结果与​​八个常用用于黄色防锈检测的索引进行比较。结果表明,使用YRSI排名第一用于估计2017频谱数据的疾病率(R〜(2)?=?0.710,RMSE?=?0.097),并且优于发布的指数(R〜(2)? =?0.587,RMSE?=?0.120)用于使用2002频谱数据的验证。随机森林(RF),K最近邻(KNN)和支持向量机(SVM)算法用于测试YRSI和八个常用指数的辨别能力,使用混合数据集的黄色生锈侵染,健康,蚜虫侵染的小麦谱数据。 YRSI提供了最佳性能。

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