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  • Title: Detection of powdery mildew in two winter wheat plant densities and prediction of grain yield using canopy hyperspectral reflectance.
    Author: Cao X, Luo Y, Zhou Y, Fan J, Xu X, West JS, Duan X, Cheng D.
    Journal: PLoS One; 2015; 10(3):e0121462. PubMed ID: 25815468.
    Abstract:
    To determine the influence of plant density and powdery mildew infection of winter wheat and to predict grain yield, hyperspectral canopy reflectance of winter wheat was measured for two plant densities at Feekes growth stage (GS) 10.5.3, 10.5.4, and 11.1 in the 2009-2010 and 2010-2011 seasons. Reflectance in near infrared (NIR) regions was significantly correlated with disease index at GS 10.5.3, 10.5.4, and 11.1 at two plant densities in both seasons. For the two plant densities, the area of the red edge peak (Σdr680-760 nm), difference vegetation index (DVI), and triangular vegetation index (TVI) were significantly correlated negatively with disease index at three GSs in two seasons. Compared with other parameters Σdr680-760 nm was the most sensitive parameter for detecting powdery mildew. Linear regression models relating mildew severity to Σdr680-760 nm were constructed at three GSs in two seasons for the two plant densities, demonstrating no significant difference in the slope estimates between the two plant densities at three GSs. Σdr680-760 nm was correlated with grain yield at three GSs in two seasons. The accuracies of partial least square regression (PLSR) models were consistently higher than those of models based on Σdr680760 nm for disease index and grain yield. PLSR can, therefore, provide more accurate estimation of disease index of wheat powdery mildew and grain yield using canopy reflectance.
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