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基于多元统计的米饭品质评价研究 被引量:2

Study on Rice Quality Evaluation Based on Multivariate Statistics
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摘要 目的:明确影响米饭品质的关键性理化指标,探索感官评价和理化试验之间的关系,建立一种简单易行的大米食用品质评价方法。方法:以三种代表性大米为原料,在三种蒸煮工艺下得到9组米饭,通过聚类与相关性分析,筛选出影响米饭食用品质的关键指标,再经主成分分析,得到综合得分公式。结果:影响米饭食用品质的指标为:水分、脂肪、硬度、粘着性、弹性、回复性,综合得分公式为:Z=0.42×水分+0.0532×脂肪-0.0597×硬度-0.447×粘着性+0.266×弹性+0.114×回复性。验证实验显示康弘1号的最佳蒸煮方法为IH常压蒸煮,稻花香、吉林小町米最佳蒸煮方法为直热式常压蒸煮。结论:各样品的主成分综合得分排名与感官评分排名基本一致,有较高匹配度,能够较好地预测米饭的食用品质。 Objective: To clarify the key physical and chemical indexes affecting the quality of rice, explore the relationship between sensory evaluation and physical and chemical test, and establish a simple and easy evaluation method of rice edible quality. Methods: Nine groups of rice were obtained from three representative rice under three cooking processes. Through cluster and correlation analysis, the key indexes affecting the edible quality of rice were selected, and then the comprehensive score formula was obtained by principal component analysis. Results: The indexes affecting the edible quality of rice were water, fat, hardness, adhesion, elasticity and recoverability. The comprehensive score formula was Z=0.42×water+0.0532×fat-0.0597×hardness-0.447×adhesion+0.266×elasticity+0.114×recoverability. The validation experiment showed that the best cooking method of Kanghong 1 was IH atmospheric cooking, and the best cooking method of Daohuaxiang and Jilin Xiaoting rice was direct heating atmospheric cooking. Conclusion: The principal component comprehensive score ranking of each sample was basically consistent with the sensory score ranking, would have a high matching degree, and could better predict the edible quality of rice.
作者 吴艺婕 马胤鹏 潘思轶 王鲁峰 WU Yijie;MA Yinpeng;PAN Siyi;WANG Lufeng(College of Food Science and Technology,Huazhong Agricultural University,Wuhan 430070,China;Key Laboratory of Environment Correlative Dietology,Ministry of Education,Huazhong Agricultural University,Wuhan 430070,China)
出处 《食品工业科技》 CAS 北大核心 2022年第10期8-15,共8页 Science and Technology of Food Industry
关键词 米饭 品质 多元统计 评价方法 rice quality multivariate statistics evaluation method
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