基于多源信息融合的大米霉变阶段品质的快速判别  

Rapid Quality Discrimination of Rice during the Mildew Process Based on Multi-Source Information Fusion

作　　者：李海瑜 韦紫玉 陈通 黄光伟[2] 胡永志[2] 孟赫诚 LI Haiyu;WEI Ziyu;CHEN Tong;HUANG Guangwei;HU Yongzhi;MENG Hecheng(Guangxi Liuzhou Luosifen Center of Technology Innovation,College of Biological and Chemical Engineering,Guangxi University of Science and Technology,Liuzhou 545006,China;Liuzhou Liangmianzhen Co.Ltd.,Liuzhou 545006,China;School of Food Science and Engineering,South China University of Technology,Guangzhou 510006,China)

机构地区：[1]广西科技大学生物与化学工程学院,广西柳州螺蛳粉技术创新中心,广西柳州545006 [2]柳州两面针股份有限公司,广西柳州545006 [3]华南理工大学食品科学与工程学院,广东广州510006

出　　处：《食品科学》2025年第9期314-321,共8页Food Science

基　　金：国家自然科学基金青年科学基金项目(32202150);广西自然科学基金面上项目(2025GXNSFAA069667,2022GXNSFAA035256)。

摘　　要：为实现快速、无损鉴定大米早期霉变过程的阶段品质。采用顶空固相微萃取-气相色谱-质谱(headspace solid-phase microextraction-gas chromatography-mass spectrometry,HS-SPME-GC-MS)分析大米霉变过程挥发性有机物质的变化,同时借助傅里叶变换红外光谱(Fourier transform infrared spectroscopy,FTIR)监测大米霉变过程淀粉结构的变化,在特征变量筛选的基础上采用特征级融合方法对两类数据进行信息融合,应用正交偏最小二乘判别分析(orthogonal partial least squares-discriminant analysis,OPLS-DA)建立判别模型,实现大米早期霉变过程不同阶段品质的区分。理化指标的聚类结果显示可将其品质划分为3个阶段;霉菌总数结果表明大米在22 d发生霉变;特征变量融合后建立的OPLS-DA模型区分大米霉变过程不同阶段品质的效果最佳,可细分为7个阶段,判别模型的拟合优度R^(2)为0.95,预测优度Q^(2)为0.86。GC-MS融合FTIR技术能够准确区分大米霉变过程的品质阶段,为大米霉变过程品质的快速、无损检测提供参考依据。In this study,a rapid and non-destructive method was proposed for the quality discrimination of rice at different stages during the early mildew process.The change in volatile organic compounds(VOCs)during the mildew process was analyzed using headspace solid-phase microextraction-gas chromatography-mass spectrometry(HS-SPME-GC-MS).Meanwhile,Fourier transform infrared spectroscopy(FTIR)was employed to monitor the structural change of starch.Following feature variable selection,a feature-level fusion method was applied for data fusion of GC-MS and FTIR.Partial least square-discriminant analysis(OPLS-DA)was used to establish a discriminant model for determining the quality of rice during the early mildew process.Cluster analysis performed on physicochemical indicators categorized the mildew process into three stages.Based on total mold counts,rice became moldy on the 22th day.The model developed through feature variable fusion of GC-MS and FTIR data proved to be the most effective in differentiating the quality of rice at different stages of mildew,which was successfully clustered into 7 stages.The model demonstrated a goodness of fit(R^(2)=0.95)and a goodness of prediction(Q^(2)=0.86).In conclusion,data fusion of GC-MS and FTIR could accurately discriminate the quality of rice during the early mildew process,thereby providing the basis for the rapid and non-destructive inspection of rice quality during the early mildew process.

关 键 词：大米风味 傅里叶变换红外光谱 化学计量学 气相色谱-质谱 阶段品质 信息融合 

分 类 号：TS210.7[轻工技术与工程—粮食、油脂及植物蛋白工程]