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作物叶片含氮量是作物长势监测、产量及品质估测的重要依据,实时、无损地监测植株体内氮素营养状况有助于棉花氮肥的正确施用。本研究比较2种近地可见光传感器的光谱和颜色信息用于监测棉花氮素营养的能力,确定MSI200成像光谱仪和数码相机监测棉花冠层叶片氮含量最佳的波段、光谱指数和颜色参数并建立估测模型。结果表明,在可见光波段,冠层反射率随着冠层叶片氮素含量的增加而降低,且叶片含氮量的光谱敏感波段主要位于绿光和红光区域;与棉花冠层叶片含氮量的拟合效果最好的2种传感器的光谱指数为差值指数DI(R580,R680)和G-R,而颜色参数则分别为b*和H,同一传感器以光谱指数的拟合效果优于颜色参数,不同传感器以MSI200数据的拟合效果优于数码相机;利用独立试验资料检验所建模型的估测性能表明,差值指数对棉花冠层叶片氮素的预测能力优于比值指数和归一化差值指数,DI(R580,R680)和G-R所建模型的估测精度最高,分别为0.8131和0.7636。因此,利用数码相机和MSI200型成像光谱仪可以定量估测棉花冠层叶片氮素营养状况。
Nitrogen content in crop leaves is an important basis for crop growth monitoring, yield and quality estimation. Monitoring nitrogen status of plants in real time and nondestructively helps the proper application of cotton nitrogen fertilizer. In this study, the spectral and color information of two kinds of near-Earth visible light sensors were compared to monitor the ability of nitrogen nutrition in cotton. The MSI200 imaging spectrometer and digital camera were used to monitor the band, spectral index and color parameters with the best nitrogen content in cotton canopy. Estimation model. The results showed that the reflectance of canopy decreased with the increase of canopy nitrogen content in the visible light band, and the spectral sensitive bands of nitrogen content of leaf mainly located in the green and red regions. The spectral indexes of the two sensors with the best fitting effect are the difference indexes DI (R580, R680) and GR, while the color parameters are b * and H respectively. The fitting effect of the same sensor on the spectral index is better than the color parameter , The fitting effect of different sensors with MSI200 data is better than that of digital camera. Using the independent test data to test the estimated performance of the model, it shows that the difference index is better than the ratio index and normalization Difference index, DI (R580, R680) and GR models have the highest prediction accuracy of 0.8131 and 0.7636, respectively. Therefore, using digital cameras and MSI200 imaging spectrometer can quantitatively estimate the nitrogen nutrition status of cotton canopy leaves.