Study on the Quantitative Relationship Among Canopy Hyperspectral Reflectance, Vegetation Index and Cotton Leaf Nitrogen Content

Study the response mechanism of Canopy spectral reflectance (CSR) to cotton nitrogen fertilizer, propose the sensitive band and center wavelength of cotton leaf nitrogen content (LNC), and compare the response characteristics of various vegetation indexes to LNC, propose a vegetation index that responds well to LNC and construct estimating model. This experiment sets five nitrogen fertilizer levels, namely N-0 (control), N-120 (120 kg/hm(2)), N-240 (240 kg/hm(2)), N-360 (360 kg/hm(2)), N-480 (480 kg/hm(2)). Among them, referring to the conventional nitrogen fertilizer is applied by local farmers (N-330, 330 kg/hm(2)). The results showed the following: (1) Visible light and near-infrared (NIR) can be used as two large ranges for precise monitoring of nitrogen, especially the CSR in the NIR range differs significantly under different nitrogen fertilizers. In the early stage of cotton growth, the CSR decreased with the nitrogen application rate increase, in a suitable nitrogen environment (360 kg/hm(2)), and beyond N-360, vice versa. In the later growth period, the CSR increases with the increase in nitrogen fertilizer. This trend is most evident in the short-wave NIR regions;(2) the range of 690-709 nm, 717-753 nm, and 940-958, which can be remote sensed by the spectral reflectance when cotton is affected in poor or rich nitrogen. The center wavelength corresponding to the nitrogen-sensitive band, respectively, are 697 nm, 735 nm, 953 nm, the band width can maintain 5-15 nm, generally not more than 20 nm;(3) compared with the ratio vegetation index, difference vegetation index, and normalized vegetation index, the combined vegetation index of more than two bands has a better effect on cotton LNC monitoring, of which the index (R-560-R-670)/(R-560 + R-670-R-450), (R-700-1.7 x R-670 + 0.7 x R-450)/(R-700 + 2.3 x R-670-1.3 x R-450) are significantly related to LNC in this papers, and the correlation coefficients can reach, respectively, 0.935* and 0.936*. These findings help to estimate the model of LNC. The model is as follows: Y = 19.883 x x + 42.285, where x refers to the combined vegetation index (R-700-1.7 x R-670 + 0.7 x R-450)/(R-700 + 2.3 x R-670-1.3 x R-450), Y is LNC, but the model accuracy will be affected in the crop different phenological stage, and the model has the highest monitoring accuracy during the bud period.