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曾全, 王敬, 肖银波, 等. 川南疫木林区松材线虫病早期诊断模型研究[J/OL]. 四川林业科技, 2024, 45[2024-04-12]. DOI: 10.12172/202403080002
引用本文: 曾全, 王敬, 肖银波, 等. 川南疫木林区松材线虫病早期诊断模型研究[J/OL]. 四川林业科技, 2024, 45[2024-04-12]. DOI: 10.12172/202403080002
Zeng Q, Wang J, Xiao Y B, et al. Study on early diagnosis model of pine wilt disease in infected forest area of southern Sichuan[J/OL]. Journal of Sichuan Forestry Science and Technology, 2024, 45[2024-04-12]. DOI: 10.12172/202403080002
Citation: Zeng Q, Wang J, Xiao Y B, et al. Study on early diagnosis model of pine wilt disease in infected forest area of southern Sichuan[J/OL]. Journal of Sichuan Forestry Science and Technology, 2024, 45[2024-04-12]. DOI: 10.12172/202403080002

川南疫木林区松材线虫病早期诊断模型研究

Study on early diagnosis model of pine wilt disease in infected forest area of southern Sichuan

  • 摘要: 为建立适用于四川省的松材线虫病早期诊断模型。2020年6月至9月,结合松墨天牛生物学特性,利用手持高光谱成像仪对野外选取的实验样株进行光谱影像采集,选用ENVI软件处理并提取光谱曲线。结果表明:(1)对实验样株进行了5次影像采集,目标植株中出现了感病初期至枯黄死亡的典型症状,感病株与对照株各时期的光谱反射率差异显著;(2)对不同波段范围内不同时间光谱反射率方差进行加权平均,提取4个敏感波段,即488.7 nm、550.8 nm、682.2 nm和779.8 nm;(3)基于敏感波段与植被指数的回归拟合,建立3个波段的EVI指数型早期诊断模型,即K=0.6874e0.7293*EVI,利用感病指数K值可定性判断植株感病。

     

    Abstract: To establish an early monitoring model of pine wood nematode disease suitable for Sichuan province. From June to September 2020, combined with the biological characteristics of Monochamus alternatus, spectral image collection of experimental samples selected in the field was carried out using a handheld hyperspectral imager, and ENVI software was used to process and extract spectral curves. The results showed as follows: (1) After 5 times of image collection, the target plants showed typical symptoms from the initial stage of infection to withered and yellow death, and the spectral reflectance of infected and control plants was significantly different at each stage; (2) The weighted average of the variance of spectral reflectance at different time in different bands was carried out to extract four sensitive bands, for 488.7nm, 550.8nm, 682.2nm and 779.8nm; (3) Based on regression fitting of sensitive bands and vegetation index, EVI index type early inversion monitoring model of 3 bands was established, namely K=0.6874e0.7293*EVI, and plant susceptibility could be qualitatively judged by K value.

     

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