利用叶片反射光谱预测大豆合交98-1667干物重模型

Predicting Model of Dry Matter Accumulation of Dwarf Soybean Hybrid 98-1667 by Leaf Reflectance Spectra

通过对不同波长光谱反射率的分析,确立大豆地上部干物重的敏感波段,计算出相应的植被指数,并建立植被指数与大豆地上部干物质量预测模型。结果表明:在可见光波段范围内,合交98-1667选取510nm和680nm2个波段的光谱反射率与地上部干物重的相关性呈极显著;在近红外区域,选取800nm、900nm和1005nm3个波段,其中800nm和900nm的光谱反射率与合交98-1667地上部干物重的相关性均呈极显著,波长为1005nm时呈显著相关。4种植被指数经过比较RVI相关性最好。通过RVI植被指数建立模型,Y=4.0216×RVI2(900,680)-99.106×RVI(900,680)+625.36,能较为准确预测大豆地上部干物重。

The sensitive wavebands were determined by analyzing relationship with spectra reflectance in different wavebands and the dry matter accumulation in above-ground part of soybean,and the prediction model was established.The results showed that there were highly significant correlations between spectra reflectance of 510 and 680 nm which selected from among visible light and the dry matter accumulation in the above-ground part of hybrid 98-1667,spectra reflectance of 800 and 900 nm in the range of near infrared light were highly significant correlated,and spectra reflectance of 1 005 nm was significantly correlated with the above-ground weight.After compared with those four vegetation indices,the RVI has the best relativity.The corresponding prediction model established by vegetation indices of RVI was Y = 4.0216 × RVI2（900,680）-99.106 × RVI（900,680） ＋ 625.36,and it could be accurate to predict the dry matter accumulation in above-ground part of soybean.