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为探究双波段光谱仪CGMD-302在监测小麦长势上的可靠性与精准性,同时使用高光谱仪UniSpec SC与双波段光谱仪CGMD-302测试各生育时期小麦冠层信息,并定量分析了植被指数NDVI、RVI、DVI与叶面积指数和叶片干重之间的线性关系。结果表明,基于相同波段反射率计算出的高光谱仪植被指数和双波段光谱仪植被指数均能较好监测小麦群体长势。在CGMD-302监测的叶面积指数模型中,拟合方程的决定系数(R~2)均高于0.89,用以检验模型的均方根误差(RMSE)和相对误差(RE)分别小于0.792和0.225;叶片干重模型中,决定系数(R2)均高于0.85,用以检验模型的均方根误差(RMSE)和相对误差(RE)分别小于440kg/hm~2和0.239。通过分析发现,施氮270kg/hm~2既能保证产量又能兼顾品质,可作为适宜施氮量。适宜施氮量下,拔节期和孕穗期小麦适宜叶面积指数分别为:3.65±0.09和5.95±0.32;适宜叶干重分别为:(1 554±168)和(2 231±130)kg/hm~2。结合CGMD-302监测模型可推算出拔节期和孕穗期适宜冠层群体的植被指数区间并应用于冠层群体诊断。
In order to explore the reliability and accuracy of dual-band CGMD-302 in monitoring wheat growth, the canopy information of wheat at different growth stages was tested by using UniSpec SC and dual-band CGMD-302. Quantitative analysis of vegetation index NDVI, Linear relationship between RVI, DVI and leaf area index and leaf dry weight. The results show that both the hyperspectral vegetation index and the dual-band spectrometer vegetation index can better monitor the growth of wheat population based on the same band reflectance. In the model of leaf area index monitored by CGMD-302, the coefficient of determination (R ~ 2) of the fitting equation was higher than 0.89, and the root mean square error (RMSE) and relative error (RE) of the model were less than 0.792 and 0.225, and the determinant coefficient (R2) was higher than 0.85 in the leaf dry weight model. The root mean square error (RMSE) and relative error (RE) of the model were less than 440 kg / hm ~ 2 and 0.239, respectively. Through the analysis, we found that nitrogen application rate of 270kg / hm ~ 2 could not only ensure the yield but also take the quality into consideration, which could be used as suitable nitrogen application rate. The suitable leaf area index of wheat at the jointing and booting stages was 3.65 ± 0.09 and 5.95 ± 0.32, and the suitable leaf dry weight was (1 554 ± 168) and (2 231 ± 130) kg / hm ~ 2. Combined with the CGMD-302 monitoring model, the vegetation index interval of suitable canopy population at jointing stage and booting stage can be deduced and applied to the canopy group diagnosis.