摘要
以8种食用油纯油的43个样品为对象，研究了近红外透射光谱结合聚类分析法快速鉴别食用油种类的可行性．采集样品在12500-4000cm^-1范围内的傅立叶变换近红外透射光谱，利用光谱模式识别法中的聚类分析法对图谱进行定性分类鉴别．实验证明，光谱经二阶导数预处理后，最短距离法、最长距离法和方差平方和法均可准确无误地将食用油样品分为8类，判别模型对预测集样品的准确率达到100％．研究表明，近红外透射光谱结合聚类分析法可以为快速无损鉴别食用油种类提供一种准确可靠的方法．
The objective of this study was to develop a rapid, undamaged method for the discrimination of the kinds of edible oil. The NIR（near infrared spectroscopy） transmission spectra of 43 samples covering 8 kinds of edible oil were collected over 12 500-4 000 cm^-1. The spectra were pretreated with 2nd derivative method. The discrimination models were established using different clustering analysis methods. The best algorithms were the single linkage algorithm, the complete linkage algorithm and the ward＇s algorithm with a 100% prediction accuracy. The results suggest that near infrared transmission spectroscopy combined with clustering analysis is both accurate and stable for edible oil discrimination.
出处
《中国计量学院学报》
2008年第3期278-282,共5页
Journal of China Jiliang University
基金
国家"863"高新技术研究发展计划项目(No.2007AA10Z216)
关键词
近红外技术
聚类分析
食用油鉴别
透射光谱
near infrared spectroscopy
clustering analysis
edible oil discrimination
transmission spectra
