【作者】 吕慧茹； 刘刚； 时有明； 郭杰； 雀晓芬； 王雅劼； 欧全宏；

【Author】 Lü Hui-ru;LIU Gang;SHI You-ming;GUO Jie;QUE Xiao-fen;WANG Ya-jie;OU Quan-hong;School of Physics and Electronic Information,Yunnan Normal University;Yunnan Key Laboratory of Opto-electronic Information Technology;School of Physics and Electronic Engineering,Qujing Normal University;

【机构】 云南师范大学物理与电子信息学院； 云南省光电信息技术重点实验室； 曲靖师范学院物理与电子工程学院；

【摘要】 运用傅里叶变换红外光谱结合SIMCA模式识别方法对3种不同年限30个宣威火腿样品进行鉴别研究。结果显示,3种不同年限宣威火腿的傅里叶变换红外原始光谱差异不明显。选取1 800～800 cm^-1范围光谱数据进行二阶导数处理,运用SIMCA模式识别法对3种不同年限宣威火腿样品的二阶导数光谱数据进行主成分分析（PCA）和系统聚类分析（HCA）)。结果表明:利用傅里叶变换红外光谱结合SIMCA模式识别方法能够很好的对不同年限宣威火腿进行区分,其中PCA分析3种不同年限宣威火腿样品的组间和组内差异明显,系统聚类分析的正确识别率达到93%。表明傅里叶变换红外光谱结合SIMCA模式识别方法是一种有力的火腿鉴别工具。更多还原

【Abstract】 In this paper Fourier Transform Infrared spectroscopy combined with SIMCA pattern recognition was used to analyze three ages of Xuanwei hams.The results showed that the difference of the original infrared spectrum was not obvious.So the second derivative were processed which select the 1 800～800 cm^-1 range of spectral data,the principal component analysis（PCA） and system cluster alalysis（HCA） of the second derivative spectra were investigated by SIMCA.The results showed that in the case of three different years,PCA analysis and system cluster analysis can be used to distinguish three different samples of Xuanwei hams,PCA analysis showed that the differerce between the two groups was significant,the correct recognition rate of the system cluster analysis reached 93%.Therefore,the Fourier Transform Infrared spectroscopy combined with the SIMCA pattern recognition method was a powerful hams discrimination tool.更多还原