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7种不同品种小麦的制曲理化品质评价

Evaluation of physicochemical quality of Qu fermented by seven different varieties of wheat
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摘要 为了选择优质的曲麦品种,以绵麦902为对照,通过测定多种理化指标,进行相关性和聚类分析来比较四川地区7种不同品种小麦制曲方面的理化品质。结果表明,7种品种小麦各指标均达到国家标准。其中,与对照小麦绵麦902相比,绵麦905、绵麦161、绵麦907的粗脂肪含量、直链淀粉含量和支链淀粉含量等指标无显著性差异(P>0.05)。此外,聚类分析结果表明,绵麦905、绵麦161、绵麦907和绵麦902归为一类,相较于绵麦916、绵麦903和MR1101更具有制曲优势。综上所述,基于对四川地区7种不同品种小麦制曲性能的分析和比较,认定绵麦905、绵麦161和绵麦907是制曲方面有应用前景的候选品种。 In order to select the superior Qu,based on the measurement of various physiochemical indicators and the analysis of correlation and cluster,the physiochemical qualities of 7 different wheat varieties in Sichuan region were compared,using Mianmai 902 as the control.The results showed that all 7 wheat varieties met the national standards for each indicator.Among them,Mianmai 905,Mianmai 161,and Mianmai 907 did not show significant differences(P>0.05)in terms of crude fat content,amylose content,and amylopectin content compared to the control variety Mianmai 902.Cluster analysis results revealed that Mianmai 905,Mianmai 161,Mianmai 907,and Mianmai 902 belonged to the same cluster,and they possessed advantages in Qu-making compared to Mianmai 916,Mianmai 903,and MR1101.In conclusion,based on the analysis and comparison of Qu-making performance among 7 different wheat varieties in Sichuan region,Mianmai 905,Mianmai 161,and Mianmai 907 were considered as promising varieties with application prospect for Qu-making.
作者 李英杰 何员江 向生远 李瑞 龚利娟 任勇 马振兵 LI Yingjie;HE Yuanjiang;XIANG Shengyuan;LI Rui;GONG Lijuan;REN Yong;MA Zhenbing(College of Biological Engineering,Sichuan University of Science&Engineering,Yibin 644000,China;Sichuan Engineering Technology Research Center for Liquor-Making Grains,Yibin 644000,China;Mianyang Agricultural Science Research Institute/Tingshi Gongjian Crop Characteristic Resources Creation andApplication Sichuan Provincial Key Laboratory,Mianyang 621023,China)
出处 《中国酿造》 CAS 北大核心 2024年第2期194-198,共5页 China Brewing
基金 四川省酿酒专用粮工程技术研究中心项目(E10527001)。
关键词 小麦 制曲 理化品质 淀粉含量 聚类分析 wheat Qu-making physicochemical quality starch content cluster analysis
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