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岳田利,彭帮柱,袁亚宏,高振鹏,张菡,赵志华.基于主成分分析法的苹果酒香气质量评价模型的构建[J].农业工程学报,2007,23(6):223-227.DOI:
基于主成分分析法的苹果酒香气质量评价模型的构建
投稿时间:2006-11-30  修订日期:2007-04-29
中文关键词:  苹果酒  感官评价  HS-SPME-GC-MS  主成分分析法
基金项目:
作者单位
岳田利 (1965-),男,陕西宝鸡人,教授,博士生导师主要从事食品生物工程与食品安全研究。杨凌西北农林科技大学食品科学与工程学院712100。Email:ytl6503@163.com 
彭帮柱 西北农林科技大学食品科学与工程学院杨凌 712100 
袁亚宏 西北农林科技大学食品科学与工程学院杨凌 712100 
高振鹏 西北农林科技大学食品科学与工程学院杨凌 712100 
张菡 西北农林科技大学食品科学与工程学院杨凌 712100 
赵志华 西北农林科技大学食品科学与工程学院杨凌 712100 
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中文摘要:利用顶空法固相微萃取与气相色谱质谱联用(HS-SPME-GC-MS)测定了12种苹果酒中的部分重要香气成分,利用主成分分析法建立了苹果酒香气质量评价模型,并用该模型对12种苹果酒香气质量进行了评价,结果表明苹果酒S12的香气质量最好;进一步通过感官评价法对模型评价结果进行了检验,结果表明2种方法具有很好的一致性,表明该文提出的方法是可行的,为果酒香气质量的评价探索了一种新的途径。
Yue Tianli,Peng Bangzhu,Yuan Yahong,Gao Zhenpeng,Zhang Han,Zhao Zhihua.Modeling of aroma quality evaluation of cider based on principal component analysis[J].Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE),2007,23(6):223-227.DOI:
Modeling of aroma quality evaluation of cider based on principal component analysis
Author NameAffiliation
Yue Tianli College of Food Science and Engineering, Northwest Agriculture and Forestry University, Yangling 712100, China 
Peng Bangzhu College of Food Science and Engineering, Northwest Agriculture and Forestry University, Yangling 712100, China 
Yuan Yahong College of Food Science and Engineering, Northwest Agriculture and Forestry University, Yangling 712100, China 
Gao Zhenpeng College of Food Science and Engineering, Northwest Agriculture and Forestry University, Yangling 712100, China 
Zhang Han College of Food Science and Engineering, Northwest Agriculture and Forestry University, Yangling 712100, China 
Zhao Zhihua College of Food Science and Engineering, Northwest Agriculture and Forestry University, Yangling 712100, China 
Key words:cider  sensory evaluation  HS-SPME-GC-MS  principal component analysis
Abstract:The aroma compounds in 12 different kinds of cider were identified and determined by the Headspace-Solid phase microextraction-Gas Chromatography-Mass Spectrometry. Then a model was established based on principal component analysis method for assessing and ranking the aroma quality of cider. S12 was selected from 12 cider samples for having best aroma by the model. This result was consistent with conventional sensory evaluation. The results indicate that the model is acceptable and available for assessing the aroma quality of cider.
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