四川林业科技2024,Vol.45Issue(4) :106-114.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

曾全 王敬 肖银波 李建国 杨双昱 贾玉珍 谢天资 杨远亮
四川林业科技2024,Vol.45Issue(4) :106-114.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

曾全 1王敬 2肖银波 1李建国 3杨双昱 1贾玉珍 1谢天资 1杨远亮1
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作者信息

  • 1. 四川省林业科学研究院,森林和湿地生态恢复与保育四川重点实验室,四川成都 610081
  • 2. 自贡市林业发展保护中心,四川自贡 643002
  • 3. 北京安洲科技有限公司,北京 100085
  • 折叠

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,the spectral image of experimental samples selected in the field was carried out by handheld hyperspectral imager,and the spectral curves were processed and extracted by ENVI software.The results showed that:(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 488.7 nm,550.8 nm,682.2 nm and 779.8 nm.(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 Kvalue.

关键词

手持高光谱/马尾松/松材线虫病

Key words

handheld hyperspectrum/Pinus Massoniana Lamb./pine wilt disease

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基金项目

四川省科技厅重点研发项目(2020YFN0040)

森林和湿地生态恢复与保育四川重点实验室资助项目()

出版年

2024
四川林业科技
四川省林学会 四川省林业科学研究院

四川林业科技

影响因子:0.452
ISSN:1003-5508
参考文献量9
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