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首页> 外文期刊>African Journal of Biotechnology >Spectroscopic determination of leaf water content using linear regression and an artificial neural network
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Spectroscopic determination of leaf water content using linear regression and an artificial neural network

机译:线性回归和人工神经网络光谱法测定叶片水分

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摘要

In order to detect crop water status with fast, non-destructive monitoring based on its spectral characteristics, this study measured 33 groups of peach tree leaf reflectance spectra (350 to 1075 nm). Linear regression and backpropagation artificial neural network methods were used to establish?peach tree leaf water content and perform quantitative analyses between spectral indices. The results show that a linear relationship existed between the peach tree leaf water content (relative water content and equivalent water thickness) and its leaf reflectance spectral index. The models performed satisfactorily?and could be used to detect the water content of the peach tree leaves.
机译:为了基于其光谱特征通过快速,无损监测来检测农作物水分状况,本研究测量了33组桃树叶片反射光谱(350至1075 nm)。采用线性回归和反向传播人工神经网络方法建立桃树叶片含水量,并对光谱指标之间进行定量分析。结果表明,桃树叶片含水量(相对含水量和当量水厚)与叶片反射光谱指数之间存在线性关系。该模型的性能令人满意,可用于检测桃树叶片的水分含量。

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