Comparison of Spectral and Molecular Analyses for Classification of Long Term Stored Wheat Samples  

作　　者：Fatih Kahriman Cem Omer Egesel 

机构地区：[1]Canakkale Onsekiz Mart University,Faculty of Agriculture,Department of Field Crops Department,Ganakkale,Turkey [2]Canakkale Onsekiz Mart University,Faculty of Agriculture,Department of AgriculturalBiotechnology,Canakkale,Turkey

出　　处：《光谱学与光谱分析》2016年第4期1266-1272,共7页Spectroscopy and Spectral Analysis

摘　　要：This study aimed to determine whether NIR spectroscopy and protein band analysis can differentiate the grain samples of 15 wheat genotypes stored for different periods:Group Ⅰ(91weeks),Group Ⅱ(143weeks),Group Ⅲ(194weeks),and GroupⅣ(246weeks).Samples were harvested from previously-conducted field trials,and stored at+4 ℃.A-PAGE and SDS-PAGE methods were utilized to separate gliadin and glutenin fractions,respectively.A qualitative calibration model based on the Support Vector Machine(SVM)method was generated and validated using NIR spectra taken from samples.Results indicated storage length did not have an effect on molecular band fractions.Use of this method would not be considered an effective tool for discrimination of samples stored for different lengths of time.Spectral techniques may have potential in sorting samples based on their storage time.The SVM calibration model generated here had an acceptable true classification rate(over 80%)for separating all groups,while only GroupsⅡ andⅣ were precisely separated(100%true classification rate)in the validation step.This study aimed to determine whether NIR spectroscopy and protein band analysis can differentiate the grain samples of 15 wheat genotypes stored for different periods：Group Ⅰ（91weeks）,Group Ⅱ（143weeks）,Group Ⅲ（194weeks）,and GroupⅣ（246weeks）.Samples were harvested from previously-conducted field trials,and stored at＋4 ℃.A-PAGE and SDS-PAGE methods were utilized to separate gliadin and glutenin fractions,respectively.A qualitative calibration model based on the Support Vector Machine（SVM）method was generated and validated using NIR spectra taken from samples.Results indicated storage length did not have an effect on molecular band fractions.Use of this method would not be considered an effective tool for discrimination of samples stored for different lengths of time.Spectral techniques may have potential in sorting samples based on their storage time.The SVM calibration model generated here had an acceptable true classification rate（over 80%）for separating all groups,while only GroupsⅡ andⅣ were precisely separated（100%true classification rate）in the validation step.

关 键 词：存储trutucyn 小麦近红外光谱 醇溶谷蛋白 

分 类 号：O657.3[理学—分析化学]