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首页> 外文期刊>Journal of Animal Science >Prediction of fat percentage within marbling score on beef longissimus muscle using 3 different fat determination methods1
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Prediction of fat percentage within marbling score on beef longissimus muscle using 3 different fat determination methods1

机译:使用3种不同的脂肪测定方法预测牛肉背最长肌的大理石花纹中的脂肪百分比1

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摘要

Consumers are concerned with fat consumption from meat products, and the ability to determine fat has changed with recent technological advances. The objective of this study was to predict fat percentage within marbling scores and compare 3 fat analysis procedures. Steaks (n = 119) were selected by USDA grading system using an E + V Vision Grading camera at a commercial beef plant during 1 d. Two samples per carcass were cut from the 13th rib, both sides, and transported to the University of Missouri meat laboratory. The sample from the right side of the carcass was allotted to Warner-Bratzler shear force, and the sample from the left side, which was graded by the camera, was allotted to fat extraction. Warner-Bratzler shear force samples were cut into 2.54-cm steaks and aged for 14 d. Steaks allotted to fat extraction were trimmed of all external fat and twice ground using 8- and 4-mm grinding plates. The finely ground beef was then split into its allotted fat-extraction methods. The 3 methods used in fat extraction were 2:1 chloroform/methanol (Folch), ether-extractable fat (ether), and microwave drying and nuclear magnetic resonance (CEM). Warner-Bratzler shear force values were not different between marbling scores (P > 0.05). Regardless of fat extraction method, fat percentage increased as marbling score increased (P < 0.05). All regression equations for fat percentage, regardless of extraction method, were linear. Prediction equation for fat percentage using CEM was -3.46 + 0.016 (marbling score), R^sup 2^ of 0.824 (P < 0.0001). Prediction equation for fat percentage using ether was -3.08 + 0.017 (marbling score), R^sup 2^ of 0.859 (P < 0.0001). Prediction equation for fat percentage using Folch was -3.42 + 0.019 (marbling score), R^sup 2^ of 0.816 (P < 0.0001). When the CEM, Folch, and ether methods were compared, CEM and Folch regression lines had different slopes (P 0.05) from CEM or Folch. Overall, ether is the most accurate method based on the R^sup 2^ value, but CEM is environmentally safe and the fastest method for determining total crude fat percentage. [PUBLICATION ABSTRACT]
机译:消费者关注肉类产品中的脂肪消耗,并且随着最新技术的发展,确定脂肪的能力也发生了变化。这项研究的目的是预测大理石花纹分数中的脂肪百分比,并比较3种脂肪分析程序。在1 d内,通过USDA分级系统使用E + V Vision分级相机选择了牛排(n = 119)。从第13条肋骨的两侧切下每只cas体两个样品,然后运到密苏里大学肉实验室。将来自from体右侧的样品分配给Warner-Bratzler剪切力,将来自左侧的样品(由相机分级)分配给脂肪提取。将Warner-Bratzler剪切力样品切成2.54厘米的牛排,陈化14天。将分配给脂肪提取的牛排修剪掉所有外部脂肪,并使用8毫米和4毫米研磨板研磨两次。然后将细碎的牛肉分成分配的脂肪提取方法。用于脂肪提取的3种方法是2:1的氯仿/甲醇(Folch),可醚萃取的脂肪(醚)以及微波干燥和核磁共振(CEM)。大理石花纹得分之间的Warner-Bratzler剪力值没有差异(P> 0.05)。无论采用哪种脂肪提取方法,脂肪含量都随着大理石花纹评分的增加而增加(P <0.05)。不论提取方法如何,所有脂肪百分比的回归方程都是线性的。使用CEM的脂肪百分比预测方程为-3.46 + 0.016(大理石花纹得分),R ^ sup 2 ^为0.824(P <0.0001)。使用醚的脂肪百分比的预测方程为-3.08 + 0.017(大理石花纹得分),R ^ sup 2 ^为0.859(P <0.0001)。使用Folch的脂肪百分比预测方程为-3.42 + 0.019(大理石花纹得分),R ^ sup 2 ^为0.816(P <0.0001)。比较CEM,Folch和以太方法时,CEM和Folch回归线与CEM或Folch的斜率不同(P 0.05)。总体而言,基于R ^ sup 2 ^值,醚是最准确的方法,但是CEM对环境安全,也是确定总粗脂肪百分比的最快方法。 [出版物摘要]

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