论文部分内容阅读
叶绿素含量是影响作物生长及产量的主要因素。该研究以2017年6月小型试验田获取的抽穗期春小麦叶绿素含量及其对应的光谱反射率为数据源,对红边(627~780 nm)、黄边(566~589 nm)、蓝边(436~495 nm)、绿边(495~566 nm)、吸收谷和反射峰的最大反射率及反射率总和等16个高光谱特征参数与叶绿素含量之间的相关性进行了分析,并结合偏最小二乘回归法(partial least-squares regression,PLSR)对叶绿素含量进行高光谱建模及验证。结果表明:1)对特定的16个光谱特征参数而言,光谱特征参数绿边最大反射率与春小麦叶绿素质量分数之间的决定系数最低(R~2<0.5);决定系数较高(R~2≥0.5)的光谱特征参数包括蓝边最大反射率、蓝边反射率总和、黄边最大反射率、黄边反射率总和、红边最大反射率、红边反射率总和、绿边反射率总和、820~940 nm反射率总和及最大反射率、500~670 nm归一化吸收深度和560~760 nm归一化吸收深度,其中820~940 nm反射率总和决定系数达到最高(R~2为0.8);2)利用16个特征参量进行PLSR建模后,发现波段范围在820~940 nm的最大反射率及反射率总和所建立的PLSR估算模型为最优模型,其精度参数R~2p=0.8、RMSEp=2.0 mg/g、RPD=3.2。因此,该模型具有极好的预测能力。该研究为相关研究及当地精准农业提供科学支持和应用参考。
Chlorophyll content is the main factor affecting crop growth and yield. In this study, the data of spring wheat chlorophyll content at heading stage and its corresponding spectral reflectance obtained from a small experimental field in June 2017 were used as data sources. The data of red edge (627 ~ 780 nm), yellow edge (566 ~ 589 nm), blue edge (436) ~ 495 nm), green edge (495 ~ 566 nm), the maximum reflectivity and the reflectivity of the absorption valley and reflection peak, and chlorophyll content were analyzed. The correlation between chlorophyll content and the 16 hyperspectral parameters was analyzed. The chlorophyll content was modeled and verified by partial least-squares regression (PLSR). The results showed as follows: 1) For 16 specific spectral parameters, the maximum green spectral reflectance and chlorophyll content of spring wheat had the lowest coefficient of determination (R ~ 2 <0.5) 2 ≧ 0.5), the spectral characteristic parameters include the maximum blue edge reflectance, the blue edge reflectance, the yellow edge maximum reflectance, the yellow edge reflectance, the red edge maximum reflectance, the red edge reflectance and the green edge reflectance , The total reflectance at 820-940 nm and the maximum reflectance, the normalized absorption depth at 500-670 nm and the normalized absorption depth at 560-760 nm, of which the coefficient of determination of the total reflectance at 820-940 nm reached the maximum 0.8). 2) After PLSR modeling with 16 eigenparameters, it is found that the PLSR estimation model established by the summation of the maximum reflectance and the reflectance in the wavelength range of 820-940 nm is the optimal model and the accuracy parameter R ~ 2p = 0.8, RMSEp = 2.0 mg / g, RPD = 3.2. Therefore, the model has excellent predictive ability. This research provides scientific support and application reference for related research and local precision agriculture.