近红外光谱结合化学计量法快速无损鉴别燕麦

Rapid and non-destructive identification of different brands and inferior oats by near infrared spectroscopy combined with chemometrics methods

提出了一种基于近红外光谱技术与化学计量学的燕麦无损鉴别方法。通过近红外光谱仪测定了5个品牌与劣质燕麦的光谱曲线,利用连续小波变换方法对光谱进行预处理,然后基于标准偏差与相对标准偏差的变量筛选方法筛选出具有代表的15个波数点,最后结合主成分分析法对不同燕麦样品快速鉴别。结果表明:连续小波变换可以有效地消除光谱中的背景干扰,提取光谱有效信息,波长筛选方法可以大大提高主成分分析结果的鉴别能力。通过结合近红外光谱分析技术与化学计量学方法,可对中国国产品牌、进口品牌和劣质燕麦进行准确鉴别。

In order to identify the inferior oat samples, and the samples from different local and imported brands, a nondestructive identification method based on near infrared spectroscopy and chemometrics methods was proposed. Spectra of five different brands of oat samples and inferior samples were obtained. Continuous wavelet transform was used for the baseline elimination. Wavenumber selection based on the standard deviation and relative standard deviation was discussed for improving the accuracy of the method, and 15 informative wavenumbers were obtained. Principal component analysis method was used for classification. The results showed that the baseline elimination was achieved by continuous wavelet transform method. Acceptable classification can be achieved with the help of principal component analysis and informative wavenumber selection. It shows that the near infrared spectroscopy combined with chemometrics methods can be used to the rapid identification of the oat samples of different brands and inferior.