基于透射光谱的玉米叶片水分含量快速检测
为实现玉米叶片水分含量快速检测,利用近红外光谱仪在300~1700 nm采用透射法对玉米叶片水分含量进行快速检测.试验利用烘干法对叶片水分梯度进行控制,并测量玉米叶片的透射光谱曲线和含水率.对透射光谱数据采用Savitzky-Golay方法进行平滑预处理,滤除光谱波动噪声干扰.分析了叶片透射光谱与含水率之间的相关关系,通过相关性分析提取敏感波长800、932、1423 nm;利用主成分分析法提取敏感波长478、748、1058和1323 nm.综合二者敏感波长最终筛选出水分敏感波长800、1323、1058和1423 nm.利用这4个波长的组合得到比值植被指数、差值植被指数和归一化植被指数等1...
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| Published in | 农业工程学报 Vol. 33; no. z1; pp. 137 - 142 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
中国农业大学现代精细农业系统集成研究教育部重点实验室,北京,100083%中国农业大学现代精细农业系统集成研究教育部重点实验室,北京 100083
2017
中国农业大学农业部农业信息获取技术重点实验室,北京 100083%中国农业大学农业部农业信息获取技术重点实验室,北京,100083 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1002-6819 |
| DOI | 10.11975/j.issn.1002-6819.2017.z1.021 |
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| Abstract | 为实现玉米叶片水分含量快速检测,利用近红外光谱仪在300~1700 nm采用透射法对玉米叶片水分含量进行快速检测.试验利用烘干法对叶片水分梯度进行控制,并测量玉米叶片的透射光谱曲线和含水率.对透射光谱数据采用Savitzky-Golay方法进行平滑预处理,滤除光谱波动噪声干扰.分析了叶片透射光谱与含水率之间的相关关系,通过相关性分析提取敏感波长800、932、1423 nm;利用主成分分析法提取敏感波长478、748、1058和1323 nm.综合二者敏感波长最终筛选出水分敏感波长800、1323、1058和1423 nm.利用这4个波长的组合得到比值植被指数、差值植被指数和归一化植被指数等12种植被指数,选取了最优差值植被指数DVI(1423、800)与透射率T1323和T1058建立了玉米叶片含水率多元线性回归诊断模型,建模集决定系数Rc2=0.9688,验证集决定系数Rv2=0.9519,预测结果方根误差为0.061.结果表明,利用透射光谱技术检测的玉米叶片水分含量具有较高的精度,可为植物叶片水分快速检测仪器开发提供指导. |
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| AbstractList | 为实现玉米叶片水分含量快速检测,利用近红外光谱仪在300~1700 nm采用透射法对玉米叶片水分含量进行快速检测.试验利用烘干法对叶片水分梯度进行控制,并测量玉米叶片的透射光谱曲线和含水率.对透射光谱数据采用Savitzky-Golay方法进行平滑预处理,滤除光谱波动噪声干扰.分析了叶片透射光谱与含水率之间的相关关系,通过相关性分析提取敏感波长800、932、1423 nm;利用主成分分析法提取敏感波长478、748、1058和1323 nm.综合二者敏感波长最终筛选出水分敏感波长800、1323、1058和1423 nm.利用这4个波长的组合得到比值植被指数、差值植被指数和归一化植被指数等12种植被指数,选取了最优差值植被指数DVI(1423、800)与透射率T1323和T1058建立了玉米叶片含水率多元线性回归诊断模型,建模集决定系数Rc2=0.9688,验证集决定系数Rv2=0.9519,预测结果方根误差为0.061.结果表明,利用透射光谱技术检测的玉米叶片水分含量具有较高的精度,可为植物叶片水分快速检测仪器开发提供指导. O434.13; 为实现玉米叶片水分含量快速检测,利用近红外光谱仪在300~1700 nm采用透射法对玉米叶片水分含量进行快速检测.试验利用烘干法对叶片水分梯度进行控制,并测量玉米叶片的透射光谱曲线和含水率.对透射光谱数据采用Savitzky-Golay方法进行平滑预处理,滤除光谱波动噪声干扰.分析了叶片透射光谱与含水率之间的相关关系,通过相关性分析提取敏感波长800、932、1423 nm;利用主成分分析法提取敏感波长478、748、1058和1323 nm.综合二者敏感波长最终筛选出水分敏感波长800、1323、1058和1423 nm.利用这4个波长的组合得到比值植被指数、差值植被指数和归一化植被指数等12种植被指数,选取了最优差值植被指数DVI(1423、800)与透射率T1323和T1058建立了玉米叶片含水率多元线性回归诊断模型,建模集决定系数Rc2=0.9688,验证集决定系数Rv2=0.9519,预测结果方根误差为0.061.结果表明,利用透射光谱技术检测的玉米叶片水分含量具有较高的精度,可为植物叶片水分快速检测仪器开发提供指导. |
| Abstract_FL | Water is essential for plant growth, and water shortage will have an impact on plant yield, growth and quality, therefore, rapid and nondestructive detection of water content in maize leaves is of great significance for scientific guidance of irrigation, and it is also important for improving crop yield. In order to rapidly detect the moisture content of maize leaves, transmission spectrum on the band of 300-1700 nm was selected to predict moisture content of maize leaves. The testing system included the light source and sensors. The light source part was provided by Wuling Optical Instrument Company. The transmission spectral range of 350-820 nm was obtained with ocean STS-VIS spectrometer, and the spectrum of 900-1700 nm was measured by Wuling NIRez near-infrared spectrometer. Although the 820-900 nm transmission spectrum was absent, the transmittance curves obtained from different water gradients showed the same trend. Ten maize plants at stage V9 were detected. In order to eliminate the interference of different blade thickness on the experimental results, the first piece of fully expanded leaves from the top of the plant was selected as the experimental sample. The samples were taken back to the laboratory, and 10 cm long strips were cut along the veins from the middle of the leaves. The experiment measured and recorded transmission spectra curve and the moisture content of maize leaves under different water gradient. The moisture content measured by fresh weight moisture content formula, the transmission rate calculated according to Lambert-Beer law. The total number of experimental samples was 98, validation set was 33, and modeling set was 65. The total moisture content of maize leaves was 10%-85% and the average moisture content was 57.9%. In order to eliminate the influence of the noise caused by the spectrometer itself, the Savitzky-Golay method was used for pretreatment. The data was processed using correlation analysis between the transmission spectra and the moisture content, and principal co. As a result, the sensitive wavelengths at 800, 932 and 1423 nm were selected by the correlation analysis, and the sensitive wavelengths at 478, 748, 1058 and 1323 nm were extracted by principal component analysis. To further improve the determination ability of the model, four sensitive wavelengths were selected, which were 800, 1323, 1058 and 1423 nm. Using the combination of these four wavelengths, 12 vegetation index such as ratio vegetation index, difference vegetation index and normalized difference vegetation index were obtained. In the 12 vegetation indices, the modeling accuracy and prediction accuracy were significantly higher than other vegetation indices, so the DVI (1423, 800) andDVI(1423, 1503) were respectively used to predict the moisture content. The results showed that DVI, which was derived from the combination of strong water absorption band (1423 nm) and weak water absorption wavelength (800 and 1503 nm), could effectively restrain the disturbance caused by structural changes, and it could sensitively reflect the moisture content of maize leaves. Multivariate linear regression model was established based on DVI (1423, 800), T1323 and T1058, the calibration R2 reached to 0.9688, the validation R2 reached to 0.9519, and the root mean square error of prediction was 0.061. The results showed that water prediction model established by transmission spectroscopy could provide efficient guidance for plant leaf water rapid detecting instrument development. |
| Author | 陈香 李民赞 孙红 杨玮 张俊逸 毛博慧 |
| AuthorAffiliation | [1]中国农业大学现代精细农业系统集成研究教育部重点实验室,北京,100083;[2]中国农业大学现代精细农业系统集成研究教育部重点实验室,北京 100083,中国农业大学农业部农业信息获取技术重点实验室,北京 100083;[3]中国农业大学农业部农业信息获取技术重点实验室,北京,100083 |
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| Keywords | spectrum analysis transmitted spectrum leaves 农作物 含水率 data processing 透射法 光谱分析 叶片 crops 数据处理 moisture content |
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| Notes | 11-2047/S spectrum analysis;moisture content;crops;leaves;transmitted spectrum;data processing Water is essential for plant growth, and water shortage will have an impact on plant yield, growth and quality, therefore, rapid and nondestructive detection of water content in maize leaves is of great significance for scientific guidance of irrigation, and it is also important for improving crop yield. In order to rapidly detect the moisture content of maize leaves, transmission spectrum on the band of 300-1700 nm was selected to predict moisture content of maize leaves. The testing system included the light source and sensors. The light source part was provided by Wuling Optical Instrument Company. The transmission spectral range of 350-820 nm was obtained with ocean STS-VIS spectrometer, and the spectrum of 900-1700 nm was measured by Wuling NIRez near-infrared spectrometer. Although the 820-900 nm transmission spectrum was absent, the transmittance curves obtained from different water gradients showed the same tr |
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| Snippet | 为实现玉米叶片水分含量快速检测,利用近红外光谱仪在300~1700... O434.13; 为实现玉米叶片水分含量快速检测,利用近红外光谱仪在300~1700... |
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| SubjectTerms | 光谱分析;含水率;农作物;叶片;透射法;数据处理 |
| Title | 基于透射光谱的玉米叶片水分含量快速检测 |
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