Field-Deployed Spectroscopy from 350 to 2500 nm: A Promising Technique for Early Identification of Powdery Mildew Disease (Erysiphe necator) in Vineyards

AGRONOMY-BASEL(2024)

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摘要
This study explores spectroscopy in the 350 to 2500 nm range for detecting powdery mildew (Erysiphe necator) in grapevine leaves, crucial for precision agriculture and sustainable vineyard management. In a controlled experimental vineyard setting, the spectral reflectance on leaves with varying infestation levels was measured using a FieldSpec 4 spectroradiometer during July and September. A detailed assessment was conducted following the guidelines recommended by the European and Mediterranean Plant Protection Organization (EPPO) to quantify the level of infestation; categorising leaves into five distinct grades based on the percentage of leaf surface area affected. Subsequently, spectral data were collected using a contact probe with a tungsten halogen bulb connected to the spectroradiometer, taking three measurements across different areas of each leaf. Partial Least Squares Regression (PLSR) analysis yielded coefficients of determination R-2 = 0.74 and 0.71, and Root Mean Square Errors (RMSEs) of 12.1% and 12.9% for calibration and validation datasets, indicating high accuracy for early disease detection. Significant spectral differences were noted between healthy and infected leaves, especially around 450 nm and 700 nm for visible light, and 1050 nm, 1425 nm, 1650 nm, and 2250 nm for the near-infrared spectrum, likely due to tissue damage, chlorophyll degradation and water loss. Finally, the Powdery Mildew Vegetation Index (PMVI) was introduced, calculated as PMVI = (R755 - R675)/(R755 + R675), where R755 and R675 are the reflectances at 755 nm (NIR) and 675 nm (red), effectively estimating disease severity (R-2 = 0.7). The study demonstrates that spectroscopy, combined with PMVI, provides a reliable, non-invasive method for managing powdery mildew and promoting healthier vineyards through precision agriculture practices.
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关键词
Erysiphe aka Uncinula necator,early detection,vegetation health monitoring,tempranillo,plant stress,non-invasive,spectral signatures,pathogen detection,precision agriculture,proximal sensing
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