[1]李明,陶光林*,廖华刚.基于冠层高光谱数据的油茶炭疽病病情指数估测[J].江苏林业科技,2023,50(04):25-29.[doi:10.3969/j.issn.1001-7380.2023.04.005]
 Li Ming,Tao Guanglin*,Liao Huagang.Estimation of anthracnose disease index in Camellia oleifera based on canopy hyperspectral data[J].Journal of Jiangsu Forestry Science &Technology,2023,50(04):25-29.[doi:10.3969/j.issn.1001-7380.2023.04.005]
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基于冠层高光谱数据的油茶炭疽病病情指数估测()
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《江苏林业科技》[ISSN:1001-7380/CN:32-1236/S]

卷:
第50卷
期数:
2023年04期
页码:
25-29
栏目:
试验研究
出版日期:
2023-08-31

文章信息/Info

Title:
Estimation of anthracnose disease index in Camellia oleifera based on canopy hyperspectral data
文章编号:
1001-7380(2023)04-0025-05
作者:
李明陶光林*廖华刚
黔东南州林业科学研究所,贵州 凯里 556000
Author(s):
Li MingTao Guanglin* Liao Huagang
Qiandongnan Institute of Forestry,Kaili 556000, China
关键词:
油茶炭疽病连续投影算法竞争性自适应重加权算法
Keywords:
Camellia oleiferaAnthracnose diseaseSuccessive projections algorithmCompetency adaptive reweighting sampling
分类号:
Q433.4;S763.13;S794.4
DOI:
10.3969/j.issn.1001-7380.2023.04.005
文献标志码:
A
摘要:
利用一阶导数、S-G平滑及多元散射校正等光谱预处理方法对油茶炭疽病危害下原始光谱进行预处理后,采用SPXY样本划分法将65个样本按7∶3将样本划分为45个校正集和20个预测集,再对不同预处理的光谱数据建立油茶炭疽病病情指数偏最小二乘回归模型。结果显示,在多种预处理方法中,S-G平滑预处理效果最好。通过连续投影算法(SPA)以及竞争性自适应重加权采样算法(CARS),从S-G平滑预处理的光谱中提取特征波长,进而构建基于偏最小二乘回归(PLSR)的油茶炭疽病病情指数的估测模型。试验结果发现,基于SPA所提特征波长建立的SPA-PLSR模型预测集R2p和预测均方根偏差(RMSEP)分别为0.700和0.072,基于CARS所提特征波长建立的CARS-PLSR模型预测集R2p和RMSEP分别为0.834和0.053;CARS-PLSR预测模型总体上要优于SPA-PLSR模型,可实现油茶炭疽病病情指数的估测。
Abstract:
The original spectra of camellia oleifera affected by anthracnose disease were firstly preprocessed by first-order derivative, S-G smoothing, and multiplicative scattering correction. The SPXY (sample set partitioning based on joint x-y distance) method was then employed to divide 65 samples into 45 calibration sets and 20 prediction sets at a ratio of 7∶3. Subsequently, partial least squares regression (PLSR) models for estimating the anthracnose disease index were established based on different preprocessed spectral data. The result showed that among various preprocessing methods, the S-G smoothing worked best. Feature wavelengths were extracted from the S-G smoothed spectra using successive projections algorithm (SPA) and competitive adaptive reweighting sampling algorithm (CARS). The PLSR models based on SPA-selected feature wavelengths (SPA-PLSR) and CARS-selected ones (CARS-PLSR) were constructed to predict the anthracnose disease index. Experimental results demonstrated that the SPA-PLSR model achieved a prediction set R2p of 0.700 and RMSEP of 0.072, while the CARS-PLSR model got R2p of 0.834 and RMSEP of 0.053.Overall, the CARS-PLSR model outperformed the SPA-PLSR model, and provided a feasible approach for estimating anthracnose disease index in Camellia oleifera.

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备注/Memo

备注/Memo:
收稿日期:2023-05-10;修回日期:2023-06-14
基金项目:贵州省林业局青年人才基金项目“基于植物高光谱特征的油茶主要病虫害监测及诊断模型研究”(黔林科合J字〔2020〕06号)
作者简介:李明(1986- ),男,贵州镇远人,工程师,硕士。从事林业3S技术研究。
*通信作者:陶光林(1971- ),男,高级工程师。从事野生植物引种栽培技术研究。
更新日期/Last Update: 2023-11-15