基于激光拉曼光谱的脐橙内部品质无损检测

    Nondestructive measurement of inner-quality of navel orange based on Laser Raman spectroscopy

    • 摘要: 论文初步探讨了运用激光拉曼光谱技术来检测脐橙内部品质的方法。应用激光拉曼光谱仪获取脐橙拉曼谱线,通过对拉曼谱线处理与分析得到了预测脐橙果肉糖度和硬度的谱线特征值,以四个谱线特征值为输入参数、脐橙糖度和硬度为输出建立了三层BP神经网络模型。结果表明,模型的糖度预测值与实测值之间的误差总体方差为0.0656,模型的硬度预测值与实测值之间的误差总体方差为0.0062。研究表明,采用激光拉曼光谱技术检测脐橙内部品质是可行的。

       

      Abstract: The nondestructive inspection of sugar content (SC) and firmness of navel oranges was discussed using laser Raman spectroscopy. After analyzing Raman spectra of navel oranges obtained by Laser Raman spectroscopy, the authors can obtain four eigenvalues of SC and firmness of navel oranges. The three-layer BP neural network was set up and used to predict the firmness and SC of navel oranges, and the eigenvalues were the parameters of input of BP neural network model. The results showed that error variances of SC and firmness between predicted values and experimental measurements were 0.0656 and 0.0062. It is feasible to detect fruit quality nondestructively using laser Raman spectrum technology.

       

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