摘要
为探究适用于制作卤煮牛肉的超声频率及牛肉部位,以牛腱、牛霖和牛米龙为原料,分别在0、20、28和50 k Hz条件下进行超声处理,通过测定色泽、蒸煮损失率、质构特性、嫩度及风味物质等指标,结合主成分分析(PCA)与模糊数学感官评价法综合评估卤煮牛肉的品质。结果表明:超声辅助卤煮可显著改善各部位牛肉的色泽、保水性、质构特性及嫩度;GC-MS共鉴定出27种关键风味物质(OAV≥1);PCA分析显示,经20 k Hz超声处理的牛米龙所制得的卤煮牛肉综合品质最佳,该结果与模糊数学感官评价结果一致。研究为卤煮牛肉生产企业提供了科学、客观且具有较高应用价值的理论依据与技术参考,有助于提升产品品质和生产效率。
To explore the suitable ultrasonic frequency and beef cut for braised beef preparation,this study used beef shank,beef knuckle(top round),and beef rump cap(sirloin tip)as raw materials.Ultrasonic treatments were conducted at frequencies of 0,20,28,and 50 kHz.Indicators including meat color,cooking loss,texture properties,tenderness,flavor compounds,and fuzzy mathematics sensory score were determined,and principal component analysis(PCA)was applied to comprehensively evaluate the quality of braised beef.The results showed that ultrasonic-assisted braising significantly improved the color,water-holding capacity,texture properties,and tenderness of beef from all cuts.Gas chromatography-mass spectrometry(GC-MS)analysis identified 27 key flavor compounds with odor activity values(OAV)≥1.PCA results indicated that braised beef prepared from beef rump cap treated with 20 kHz ultrasound exhibited the best comprehensive quality,which was consistent with the fuzzy mathematics sensory evaluation.This result provides a scientific,objective,and highly applicable theoretical basis and technical reference for braised beef production enterprises,contributing to improved product quality and production efficiency.
作者
包一枫
陈刚
王恒鹏
孟祥忍
BAO Yifeng;CHEN Gang;WANG Hengpeng;MENG Xiangren(School of Tourism and Cuisine,Yangzhou University,Yangzhou,Jiangsu 225127,China;Key Laboratory of Chinese Cuisine Intangible Cultural Heritage Inheritance,Ministry of Culture and Tourism,Yangzhou,Jiangsu 225127,China)
出处
《美食研究》
北大核心
2025年第4期77-83,I0010-I0016,共14页
Journal of Researches on Dietetic Science and Culture
基金
江苏省高等学校基础科学(自然科学)研究面上项目(24KJB550013)
四川省川菜发展研究中心重点项目(CC24ZD01)。
关键词
超声波
牛肉部位
卤煮牛肉
主成分分析
ultrasonic wave
beef cut
braised beef
principal component analysis
