摘要
利用近红外光谱和模式识别技术建立了大米产地的快速鉴别方法。首先对119个地理标志产品响水大米和90个其他产地的大米(即非响水大米)的近红外光谱进行一阶导数和平滑处理,利用主成分分析法(PCA)对数据进行降维,通过前三个主成分的载荷图确定了相关性最大的特征波段(7 700～6 700cm-1与5 700～4 300cm-1)。在全波段内,凝聚层次聚类和Fisher’s判别鉴别方法都可以100%正确的鉴别响水大米和非响水大米;对于非响水地区的大米的具体产地判别,聚类分析正确率为91.9%,Fisher’s判别分析方法的正确率为96.7%。同时,在特征波段内,对大米产地聚类分析的准确度高于全波段范围内分析结果,说明选取的特征波段具有较强的代表性,是优化模型的有效方法之一。
A rapid method was developed for discrimination of the geographical origins of rice with pattern recognition technique by near infrared spectrocopy（NIRS）.A total of 119 geography signs product Xiangshui rice samples and 90 rice（Non-Xiangshui rice） samples produced from other places were analyzed by NIRS.After first derivative and smooth processing,principal component analysis（PCA） was used to reduce the dimensionality of the spectral data.Through the loading graph of the first three principal components,characteristic wave band（7 700~6 700,5 700~4 300 cm-1） with max-relativity was determined.In whole wave,using agglomerative hierarchical cluster analysis and Fisher＇s linear discriminant,the discrimination of Xiangshui rice and Non-Xiangshui rice was all 100%.The correct rate of specific geographical origins of Non-Xiangshui rice was 91.9% by cluster analysis and 96.7% by discriminant analysis.For analysis in the characteristic wave bands,the correct rate of discriminant by cluster analysis was higher than the analysis result through the range of the whole band.Therefore,characteristic wave band has strong representativeness.The results indicate that it is feasible to discriminate the geographical origins of rice with pattern recognition technique by NIRS,and selecting characteristic wave band is one of the validated methods to improve the precision of the discrimination mode.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2013年第1期102-105,共4页
Spectroscopy and Spectral Analysis
基金
国家水体污染控制与治理科技重大专项项目(2008ZX07209-07)
质检公益行业科研专项项目(200810345)
河北省科技计划项目(12221003D)资助
关键词
近红外
大米
主成分分析
聚类
判别
产地
Near infrared spectrocopy
Rice
Principal component analysis（PCA）
Cluster
Discriminant
Geographical origin
