| 余蛟洋,常庆瑞,班松涛,田明璐,由明明.猕猴桃叶片SPAD值高光谱估算模型构建[J].干旱地区农业研究,2018,36(6):168~174 |
| 猕猴桃叶片SPAD值高光谱估算模型构建 |
| Hyperspectral models for estimating SPAD values of kiwifruit leaves |
| |
| DOI：10.7606/j.issn.1000-7601.2018.06.25 |
| 中文关键词: 猕猴桃叶片 高光谱；SPAD值；红边参数；估算模型 |
| 英文关键词:kiwifruit hyperspectrum SPAD value red edge parameters estimation models |
| 基金项目:国家高技术研究发展计划（863计划）资助项目（2013AA102401）；中央高校基本科研业务项目（2452017108） |
|
| 摘要点击次数: 1039 |
| 全文下载次数: 475 |
| 中文摘要: |
| 利用便携式野外光谱辐射仪和叶绿素仪在陕西杨凌蒋家寨村测定了猕猴桃不同生育期叶片光谱反射率及其对应的叶绿素相对含量（SPAD）值，通过分析其光谱反射率、一阶微分光谱和SPAD的相关关系，构建了不同生育期基于红边位置、红边幅值、红边偏度和红边峰度的SPAD估算的单因素回归模型和多元逐步回归模型。结果表明：(1)随着猕猴桃叶片叶绿素含量升高，红边位置“红移”，红边幅值随着SPAD值的增大而递减，红边面积有所减小，红边曲线形状由右偏逐渐转变为左偏，峰度值逐渐降低；(2)红边偏度能够更好地反映叶片叶绿素含量；(3)在不同生育期，均以红边偏度建立的单因素模型效果最好，建模R2分别为0.821、0.874、0.842；(4)与单因素多项式回归模型相比，多元逐步回归模型在不同生育期均有更好的建模精度和预测精度，在不同生育期，其预测R2分别为0.848、0.926、和0.850，是估算猕猴桃叶片SPAD值的最佳模型。 |
| 英文摘要: |
| In order to provide a scientific basis for monitoring the conditions of kiwifruit in the northwestern region, the models for estimating chlorophyll content of kiwifruit leaves based on hyperspectrum were constructed. A field experiment were conducted in Jiangjiazhai village of Yangling, Shaanxi Province. During different growth stages, the measurements of the hyperspectral reflectance of kiwifruit leaves were collected using SVC HR-1024i, a portable field spectroradiometer, and also relative chlorophyll content (SPAD) of kiwifruit leaves was measured using SPAD-502, a Chlorophyll Meter. We analyzed the correlations between spectral reflectance, first derivative spectral reflectance, and SPAD values of kiwifruit leaves. Then, single factor regression models and multiple stepwise regression models based on the red edge position, amplitude of the red edge, skewness of the red edge, kurtosis of the red edge were established, respectively, to estimate SPAD values. Our results revealed that: (1) With increase in chlorophyll content, there was a ‘red shift’ phenomenon for the red edge position, in addition, amplitude, area, and kurtosis of the red edge decreased gradually, the shape of red edge skewness curve changed from right to left gradually; (2) The regression models based on srewness of red edge all had good predictive power for SPAD value of kiwifruit leaves; (3) The quadratic polynomial regression models based on red edge of skewness can preferably describe the leaf chlorophyll content, and the regression models based on the red edge of skewness performed best at different growth stages. The determination coefficients for the regression models were 0.821, 0.874, and 0.842, respectively; (4) Compared with polynomial regression models, multiple stepwise regression models were good inversion models for estimating SPAD of kiwifruit leaves, which had better modeling and predictive precision at various growth stages. The determination coefficients of prediction models were 0.848, 0.926, and 0.850, respectively. |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| | |