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Prediction Model of Grain Crude Protein and Amylose Content with Canopy Spectral Reflectance in Rice

机译:水稻冠层光谱反射率对谷物粗蛋白和直链淀粉含量的预测模型

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Grain crude protein and amylose content are two important indexes for evaluating rice quality. The objectives of this study were to determine the relationships of grain crude protein content, amylose content to ground-based canopy hyperspectral reflectance and derivative parameters at different growth stages in rice (Oryza sativa L.) on the basis of the data from the field experiments involving two cultivars under different high-temperature stresses of booting stage in 2007 and 2008. Then the relationships of grain crude protein and amylose content to canopy reflectance of single band and all two-band combinations were analyzed. The results showed that there were significantly or very significantly correlation of grain crude protein and amylose content with canopy spectra and the first derivative at different growth stages in some wave band. The relationships of grain crude protein content, amylose content to the ratio, differential and normalized difference vegetation indices of all bands and red edge parameters were also analyzed. The fitting spectral parameter with better correlation was subsequently selected through regression analysis, DVI(810,450) was found to be the best parameter for predicting grain crude protein content (GCPC) and grain amylose content (GAC)in rice. The derived equations were tested with the observed data from the other independent experiments. The estimation precision was 0.393~0.683, estimation accuracy was 0.712~0.923, and RMSE was 8.706%~11.463%, which indicated a good fit between the predicted and observed values of grain crude protein and amylose content.
机译:谷物粗蛋白和直链淀粉含量是评价稻米品质的两个重要指标。这项研究的目的是根据田间试验的数据,确定稻米(Oryza sativa L.)不同生育阶段的谷物粗蛋白含量,直链淀粉含量与地基冠层高光谱反射率和导数参数之间的关系。分别于2007年和2008年在不同高温胁迫下,分别对两个品种进行了分析。分析了籽粒粗蛋白和直链淀粉含量与单波段和所有两个波段组合的冠层反射率之间的关系。结果表明,在某些波段不同阶段,籽粒粗蛋白和直链淀粉含量与冠层光谱和一阶导数之间存在显着或非常显着的相关性。分析了籽粒粗蛋白含量,直链淀粉含量与各波段比例,微分和归一化植被指数以及红边参数之间的关系。随后通过回归分析选择具有更好相关性的拟合光谱参数,发现DVI(810,450)是预测水稻籽粒粗蛋白含量(GCPC)和直链淀粉含量(GAC)的最佳参数。用来自其他独立实验的观察数据测试推导的方程式。估计精度为0.393〜0.683,估计精度为0.712〜0.923,RMSE为8.706%〜11.463%,表明籽粒粗蛋白和直链淀粉含量的预测值与实测值吻合良好。

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