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气相色谱结合化学计量学区分大米贮藏时间与产地 被引量:12

Determination of the Storage Time and Geographical Origin of Rice by GC and Chemometrics
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摘要 香气是衡量大米质量的一个主要因素,对大米的食用品质有重要影响。该文以顶空固相微萃取(SPME)技术为基础,采用气相色谱法分别分析了不同贮藏时间和不同产地大米样本的挥发性成分,通过主成分分析法(PCA)和偏最小二乘判别分析法(PLS-DA)对大米样本进行分类和判别分析。PCA及PLS投影图显示不同储藏时间的大米明显聚为4类,通过留一交叉验证法(LOO)计算PLS预报的准确率为96%,相对标准误差为8.2%。同时,PCA投影图中可将4个不同产地的大米样本进行区分,分类效果显著;所建PLSDA模型可靠,不同产地大米样本均能被准确识别,正确率为100%。以顶空固相微萃取/气相色谱检测大米中挥发性成分,利用主成分分析法和偏最小二乘判别分析法鉴别大米新鲜程度和产地具有可行性。 Aroma is one of the main factors of rice quality and is important for the evaluation of nutritional value and quality.In order to explore an objective method to evaluate the quality of rice,this paper provided a new possible measure to distinguish the rice of different storage length of time and different original places by gas chromatography(GC) based on head space solid phase micro extraction (HS-SPME) technique and to analyze the volatile components of rice samples with different storage time and original places using principal component analysis(PCA) and partial least squares discriminant analysis(PLS-DA).Results showed that rice samples stored for different time periods were classified correctly in the PCA and PLS plot,cross using the leave one out cross validation (LOO),the prediction accuracy of the samples stored for different time periods was 96% and the relative standard error(RSE) was 8.2% in the model of PLS.Samples from four different original places clustered into four different groups in the PCA plot.The PLS-DA method was applied in the determination of the rice of different original places,which was verified to be very effective and reliable,also the accuracy of this model reached to 100%.It could be safely concluded that this study has provided a reliable and effective method for discriminating the storage time period and original places of rice based on HS-SPME-GC-FID technique combined with PCA and PLS-DA.
机构地区 同济大学化学系
出处 《分析测试学报》 CAS CSCD 北大核心 2013年第10期1227-1231,共5页 Journal of Instrumental Analysis
关键词 大米 固相微萃取 气相色谱 主成分分析 偏最小二乘判别分析法 rice solid phase micro extraction (SPME) GC PCA PLS-DA
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