食品科学2018，Vol.39Issue(8)：243-248,6.DOI:10.7506/spkx1002-6630-201808038
基于红外光谱指纹和挥发性组分信息融合模型鉴别大米产地来源
Identification of Geographical Origin of Rice Based on Fingerprint Information Fusion Model of Infrared Spectrum and Characteristic Volatile Compounds
摘要
Abstract
This study aimed to establish an accurate model based on fingerprint information fusion of characteristic volatile compounds and infrared spectrum for identifying the geographical origin of rice. A total of 20, 19 and 15 rice samples respectively collected from Panjin, Sheyang and Wuchang were analyzed for their volatile compounds by gas chromatography-mass spectrometry (GC-MS) and Fourier transform infrared spectra of these samples were recorded. Analysis of variance (ANOVA) was employed to screen out the characteristic volatile components and characteristic infrared spectra, which were combined to establish a fingerprint information fusion model by partial least squares discriminant analysis (PLS-DA). The results showed that the identification accuracy of the fingerprint information fusion model was 97.4%, which was increased by 4.5% and 8.5% compared with individual infrared spectrum (92.9%) and volatile fingerprints (88.9%), respectively. Therefore, the PLS-DA information fusion model is feasible to identify the geographical origin of rice with high accuracy.关键词
地理标志大米/产地鉴别/气相色谱-质谱联用/傅里叶红外光谱/偏最小二乘判别分析Key words
geographical indication rice/geographical origin identification/gas chromatography-mass spectrometry (GC-MS)/Fourier transform infrared spectroscopy/partial least squares-discriminant analysis (PLS-DA)分类
轻工纺织引用本文复制引用
杜梦佳,毛波,沈飞,李彭,裴斐,胡秋辉,方勇..基于红外光谱指纹和挥发性组分信息融合模型鉴别大米产地来源[J].食品科学,2018,39(8):243-248,6.基金项目
"十三五"国家重点研发计划重点专项(2016YFD0401203) （2016YFD0401203）
国家农产品质量安全风险评估项目(GJFP201700102) （GJFP201700102）
江苏省优势学科建设工程项目(PDAD) （PDAD）
