摘要
针对白酒以次充好等食品安全问题,发展具有潜在应用价值的快速检测技术是目前研究的热点之一。采集品牌白酒的紫外光谱,结合相关系数法量化分析了各品牌白酒的相似度差异情况。以海之蓝白酒为主要研究对象,研究发现同品牌海之蓝白酒基于紫外光谱原始数据计算而得的相关系数值达到了0.999以上,而基于二次微分处理的紫外光谱计算而得的相关系数值可达到0.993左右。进一步研究比较发现,基于紫外光谱原始数据可判断出大部分品牌白酒与海之蓝白酒存在不同,但难以区分洋河系列白酒与海之蓝白酒。而在通过二次微分提高谱图分辨率的情况下,洋河系列白酒、各品牌白酒与海之蓝白酒谱图的相关系数值得以降低,可以得到有效区分。因此,通过二次微分紫外光谱结合相关系数法,可高效、快速的实现白酒品牌鉴别,具有较高的实际应用潜质。
For the problems of food safety, such as liquor shoddy, a potential rapid identification technique has been developed, as a hot topic at present. The ultraviolet spectra of the brands liquor were obtained, and the similarity of each brand liquor was quantified by the correlation coefficient method. Hai zhilan liquor was used as the main research object in this work, the correlation coefficient was calculated with the brand of Hai zhilan liquors based on the original ultraviolet spectral data reached above 0.999, the correlation coefficient was about 0.993 based on their two order differential treated ultraviolet spectral data. Furthermore, the most brands of Chinese liquor and Hai zhilan liquor can be distinguished based on the original ultraviolet spectral data, however, it is difficult to distinguish the series of Yanghe liquors and Hai zhilan liquor. The correlation coefficients of the series of Yanghe liquors, the other brands of Chinese liquor and Hal zhilan liquor can be reduced based on their two order differential treated ultraviolet spectral data, respectively, and they can be effectively distinguished because the two order differential treated spectral data can improve the resolution of the spectra. Therefore, through the two differential ultraviolet spectroscopy combined with correlation coefficient method, an efficient and fast method to identify the brands of Chinese liquor can be established, and this method has a great potential practical application in food safety.
出处
《酿酒》
CAS
2017年第2期75-79,共5页
Liquor Making
基金
江苏省高校自然科学研究面上项目(16KJ B150015)
国家自然科学基金(61602217
61373058
71433006)资助
关键词
紫外光谱
相关系数
白酒
复杂体系
品牌鉴别
Ultraviolet spectroscopy
correlation coefficient
Chinese liquor
complex system
brand identification
