Plant leaf chlorophyll content retrieval based on a field imaging spectroscopy system.
Plant leaf chlorophyll content retrieval based on a field imaging spectroscopy system.
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DOI：
10.3390/s141019910
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发表时间：
2014-10-23
期刊：
影响因子：
--
通讯作者：
Wang KL
中科院分区：
文献类型：
--
作者：
Liu B;Yue YM;Li R;Shen WJ;Wang KL
为农业应用设计了一套田间成像光谱仪系统(FISS；380-870 nm，344个波段)。在这项研究中，FISS被用来收集大豆叶片的光谱信息。利用多元线性回归(MLR)、偏最小二乘(PLS)回归和支持向量机(支持向量机)回归方法对叶片的叶绿素含量进行了反演。我们的目标是通过对叶绿素含量的估计来验证FISS在定量光谱分析中的性能，并确定处理FISS数据的合适的定量光谱分析方法。结果表明，导数反射率是一个更敏感的叶绿素含量指标，比光谱反射率能更有效地提取叶绿素含量信息，对于FISS数据比ASD(分析光谱设备)数据更有意义，相应的均方根误差(RMSE)降低了3.3%~35.6%。与光谱特征相比，回归方法对反演精度的影响较小。多变量线性模型可能是利用少量有效波长提取叶绿素信息的理想模型。最小均方根误差为0.201 mg/g，比基于非成像ASD光谱仪的均方根误差降低了30%以上，与采样叶片的平均叶绿素含量(4.05 mg/g)相比具有较高的估计精度。研究表明，FISS能同时获得高质量的光谱和空间细节信息。它的图像光谱合一的优点促进了FISS在定量光谱分析中的良好性能，并有可能在农业领域得到广泛应用。
A field imaging spectrometer system (FISS; 380–870 nm and 344 bands) was designed for agriculture applications. In this study, FISS was used to gather spectral information from soybean leaves. The chlorophyll content was retrieved using a multiple linear regression (MLR), partial least squares (PLS) regression and support vector machine (SVM) regression. Our objective was to verify the performance of FISS in a quantitative spectral analysis through the estimation of chlorophyll content and to determine a proper quantitative spectral analysis method for processing FISS data. The results revealed that the derivative reflectance was a more sensitive indicator of chlorophyll content and could extract content information more efficiently than the spectral reflectance, which is more significant for FISS data compared to ASD (analytical spectral devices) data, reducing the corresponding RMSE (root mean squared error) by 3.3%–35.6%. Compared with the spectral features, the regression methods had smaller effects on the retrieval accuracy. A multivariate linear model could be the ideal model to retrieve chlorophyll information with a small number of significant wavelengths used. The smallest RMSE of the chlorophyll content retrieved using FISS data was 0.201 mg/g, a relative reduction of more than 30% compared with the RMSE based on a non-imaging ASD spectrometer, which represents a high estimation accuracy compared with the mean chlorophyll content of the sampled leaves (4.05 mg/g). Our study indicates that FISS could obtain both spectral and spatial detailed information of high quality. Its image-spectrum-in-one merit promotes the good performance of FISS in quantitative spectral analyses, and it can potentially be widely used in the agricultural sector.
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DOI：
10.3390/s110707063
发表时间：
2011
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Delegido J;Verrelst J;Alonso L;Moreno J
通讯作者：
Moreno J
DOI：
10.3964/j.issn.1000-0593(2009)02-0313-05
发表时间：
2009-02-01
影响因子：
0.7
作者：
Liang Bi-yan;Li Shu-yuan;Sun Su-qin
通讯作者：
Sun Su-qin
影响因子：
5
作者：
Quemada, Miguel;Luis Gabriel, Jose;Zarco-Tejada, Pablo
通讯作者：
Zarco-Tejada, Pablo
影响因子：
5.5
作者：
ElMasry, Garnal;Wang, Ning;Ngadi, Michael
通讯作者：
Ngadi, Michael
影响因子：
1.9
作者：
Oumar, Z.;Mutanga, O.
通讯作者：
Mutanga, O.