OALib Journal期刊
水稻叶片色素含量近红外光谱估测模型研究
DOI: 10.3724/SP.J.1096.2012.10325
Keywords: 水稻 ,叶片色素 ,近红外光谱 ,最佳因子数 ,偏最小二乘法
Abstract:
以不同品种类型和不同施氮水平的水稻(Oryzasativa)叶片近红外光谱信息为基础,运用逐步多元回归法(Stepwisemultiplelinearregression,SMLR)、主成分回归法(Principalcomponentregression,PCR)、偏最小二乘法(Partialleastsquare,PLS)和BP神经网络法(Back-propagationneuralnetwork,BPNN),建立了水稻叶片中叶绿素a(Chla)、叶绿素b(Chlb)、叶绿素a+b(Chla+b)和类胡萝卜素(Car)的近红外预测模型。结果显示,利用8000~4000cm-1波段范围的一阶导数(Firstderivative,FD)建模效果最佳。其中,基于PLS的预测模型效果最好;4类近红外色素模型的内部交叉验证误差分别为0.251,0.063,0.305和0.073;外部交叉验证的误差RMSEP分别为0.335,0.123,0.302和0.072,表明的预测效果较好。因此,可以基于近红外模型对水稻叶片色素含量进行快速测定。
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