期刊文献+

稻谷有害霉菌侵染的近红外光谱快速检测 被引量:9

Rapid Detection of Harmful Mold Infection in Rice by Near Infrared Spectroscopy
下载PDF
导出
摘要 稻谷是我国主要储粮品种。为快速、准确鉴定稻谷霉变状态,建立了一种基于近红外光谱的稻谷霉菌污染定性、定量分析方法。首先,将四种谷物中常见有害霉菌(黄曲霉3. 17、黄曲霉3. 3950、寄生曲霉3. 3950、灰绿曲霉3. 0100)分别接种在灭菌稻谷样品上。其次,将接种霉菌样品进行人工模拟储藏(28℃、RH 80%),并采集不同储藏时间(0,2,4,7和10 d)稻谷的近红外漫反射光谱信号。最后,利用主成分分析(PCA)、判别分析(DA)和偏最小二乘回归(PLSR)方法建立稻谷霉菌污染的快速分析模型。结果显示,近红外光谱可有效区分感染不同霉菌的稻谷样品,平均判别正确率达87. 5%。稻谷霉变随储藏时间逐渐加深,近红外光谱对感染单一霉菌稻谷样品霉变状态的判别正确率达92. 5%,多种霉菌的判别正确率达87. 5%。稻谷中的菌落总数的PLSR模型定量结果为:有效决定系数(R2P)为0. 882 3、验证均方根误差(RMSEP)为0. 339 Lg CFU·g-1,相对标准偏差(RPD)为2. 93。结果表明,近红外光谱法可以作为一种快速、无损的分析方法来判定稻谷霉菌侵染状况,确保稻谷储运安全。 China has huge rice reserves.In order to develo parapid and accurate method for harmful mold infection detection in rice,near infrared(NIR)spectroscopy was applied for qualitative and quantitative analys is of the process of rice mildew in this study.Sterilized rice samples were fir stly inoculated with four mold Aspergillus spp.species(A.flavus 3.17,A.flavus 3.3950,A.parastiticus 3.3950,A.glaucus 3.0100),respectively.Then the rice samples were stored under appropriate conditions(28℃,80%RH)for mould growth.NIR spectra of samples were collected during the storage on different days(0,2,4,7 and 10 d).Analysis models of mold infection in rice were developed by principal component analysis(PCA),discriminant ana lysis(DA)and partial least squares regression(PLSR),respectively.The result s indicated that rice samples infected by different mold species could be effectively distinguished by NIR spectroscopy,and the average classification accuracy was 87.5%.The degree of mildew intensified during storage.The average correct classification accuracy of storage time(mildew degree)was found to be 92.5%for samples infected by one mold species,and 87.5%for samples infected by the four mold species.The PLSR prediction results of mould cell concentration in samples was:RP^2=0.882 3,root mean square error of prediction(RMSEP)=0.339 Log(CFU·g^-1)and residual predictive deviation(RPD)=2.93.Overall,the results demonstrated that the NIRS can be used as a rapid and non-destr uctive method for harmful mold infection detection in rice,ensuring the safety of grain storage and transportation.
作者 沈飞 魏颖琪 张斌 邵小龙 宋伟 杨慧萍 SHEN Fei;WEI Ying-qi;ZHANG Bin;SHAO Xiao-long;SONG Wei;YANG Hui-ping(College of Food Science and Engineering/Collaborative Innovation Center for Modern Grain Circulation and Safety/Key Laboratory of Grains and Oils Quality Control and Processing,Nanjing University of Finance and Economics,Nanjing 210023,China)
出处 《光谱学与光谱分析》 SCIE EI CAS CSCD 北大核心 2018年第12期3748-3752,共5页 Spectroscopy and Spectral Analysis
基金 国家自然科学基金项目(31301482 31772061) 江苏省自然科学基金项目(BK20131007) 粮食公益性行业科研专项(201513002-5) 江苏高校优势学科建设工程项目(PAPD)(2014-124)资助
关键词 近红外光谱 稻谷 霉菌侵染 快速检测 Near infrared spectroscopy Paddy Fungal infection Rapid detection
  • 相关文献

参考文献1

二级参考文献18

  • 1周竹,刘洁,李小昱,李培武,王为,展慧.霉变板栗的近红外光谱和神经网络方法判别[J].农业机械学报,2009,40(S1):109-112. 被引量:19
  • 2J. Sundaram,C. V. K. Kandala,C. L. Butts.Classification of in-shell peanut kernels nondestructively using VIS/NIR reflectance spectroscopy[J]. Sensing and Instrumentation for Food Quality and Safety . 2010 (2)
  • 3Alberto Guillén,F. G. Moral,L. J. Herrera,G. Rubio,I. Rojas,O. Valenzuela,H. Pomares.Using near-infrared spectroscopy in the classification of white and iberian pork with neural networks[J]. Neural Computing and Applications . 2010 (3)
  • 4J.A.K. Suykens,J. Vandewalle.Least Squares Support Vector Machine Classifiers[J]. Neural Processing Letters . 1999 (3)
  • 5Pasti L,Jouan-Rimbaud D,Massarta D,et al.Application of Fourier transform to multivariate calibration of near-infrared data. Analytica Chimica Acta . 1998
  • 6M Hana,W F McClure,T B Whitaker.Applying artificial neural networks.I.Estimating nicotine in tobacco from near infrared data. Journal of Near Infrared Spectroscopy . 1995
  • 7Burns D A,Ciurczak E W.Handbook of Near-Infrared Analysis. . 2007
  • 8J. Kim,A. Mowat,P. Poole,N. Kasabov.Linear and non-linear pattern recognition models for classification of fruit from visible-near infrared spectra. Chemometr. Intell. Lab. Syst . 2000
  • 9Wu W,Walczak B,Penninckx W,et al.Feature reductionby Fourier transform in pattern recognition of NIR data. Analytica Chimica Acta . 1996
  • 10Huang Cheng Lung,Wang Chieh Jen.A GA-basedfeature selection and parameters optimization for support vectormachines. Expert Systems With Applications . 2006

共引文献33

同被引文献128

引证文献9

二级引证文献44

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部