用小波变换技术提高食醋近红外光谱分析的精度

    Application of Wavelet Transform Technology to the Improvement of Analyzing Accuracy of Vinegar Near-Infrared Spectrum

    • 摘要: 以食醋的成分还原糖为例,探讨了利用小波变换原理分析近红外吸收光谱并提取有效信息的方法。结果表明:经变换后的光谱能更好地反映出与成分含量之间的相关关系。通过与使用食醋原始吸收光谱的多元回归分析方法比较,得出使用7个尺度变换后的小波系数与还原糖之间的相关关系最为显著,且三元回归分析的预测差值不确定度最小(为0.211),比原始光谱降低0.058。小波变换方法提高了食醋近红外光谱的定量分析精度,从而为实现近红外光谱分析技术应用于食醋成分的在线检测提供参考。

       

      Abstract: In this paper, a method based on wavelet transform, which is used to analyze near-infrared spectrum and abstract useful information, is discussed on the case of reducing sugar of vinegar. The results show that the spectrum transform can reflect their correlation with the element quantitative. By the comparison with the multiple regression analysis for the vinegar absorbed spectrum, the following remarks are found out: the wavelet coefficient 7-scale transformed has the most intimated correlation with the reducing sugar. The prediction difference uncertainty (which is 0.211) of ternary regression analysis is the least, which is 0.058 lower than that of primary spectrum. The method of wavelet transform improved the quantitatively analyzing accuracy, therefore, it is as a reference, which is used to develop the application of near-infrared analyzing technology in vinegar on-line measurement.

       

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