Department of Animal Science, Universidade Federal de Santa Maria, Santa Maria, RS 97105-900, Brazil.
Embrapa Caprinos e Ovinos, Rodovia CE-179, Sobral, CE 62010-970, Brazil.
Meat Sci. 2020 Nov;169:108192. doi: 10.1016/j.meatsci.2020.108192. Epub 2020 May 15.
Consumers are demanding additional information to support their decision-making while shopping for meat. In the lamb industry, labelling carcasses with composition information is challenging. This is due to issues with conventional analytical procedures, such as the time spent with determinations and product loss or devaluing due to sampling for analysis. The objective was to evaluate the potential use of bioimpedance analysis (BIA) to determine composition of the soft tissue portion of lamb carcasses. Thirty-one Texel and Ile-de-France crossbreed ram lambs were slaughtered at 20, 26, 32, or 38 kg of body weight. Values of resistance and reactance were collected from hot and cold carcasses, which weighed 12.4 ± 2.99 kg and 11.9 ± 2.94 kg, respectively and measured 53.9 ± 3.25 cm of length. Carcass weight and length were used to calculate other BIA variables such as impedance modulus, phase angle, bioelectrical volume, and both resistive and reactive densities. These variables were used as independent variables to predict the contents of soft tissue, moisture, ash, protein, fat, lean, and crude energy of the carcasses. Multiple regression analyses were carried out to calibrate BIA models. The leave-one-out cross-validation was performed to evaluate precision and accuracy of the BIA technique. Resistive density was the most important BIA variable to predict lamb composition of hot carcasses, which explained 83% to 92% of the variation in composition. In turn, reactive density better predicted lamb carcass composition in cold carcasses, which accounted for 81% to 92% of their variation in carcass composition. In addition, prediction models of the soft tissue portion of lamb carcasses assessed on cold carcasses showed a higher coefficient of determination and smaller root mean square error and Mallows Cp values than hot carcasses. Therefore, BIA has an excellent potential to predict lamb carcass components on either hot as cold carcass; however, higher accuracy was found with cold carcasses in comparison with hot.
消费者在购买肉类时,需要更多信息来辅助他们做出决策。在羊肉行业中,给胴体贴上成分信息标签具有挑战性。这是因为常规分析程序存在问题,例如,由于需要进行测定,以及由于分析需要进行采样,导致产品损失或贬值,所以需要花费大量时间。本研究旨在评估生物阻抗分析(BIA)在确定羊肉胴体软组织部分组成方面的潜在应用。31 只特克赛尔和 Ile-de-France 杂交公羊在体重为 20、26、32 或 38 公斤时进行屠宰。从热胴体和冷胴体收集电阻和电抗值,热胴体和冷胴体分别重 12.4±2.99 公斤和 11.9±2.94 公斤,长度分别为 53.9±3.25 厘米。胴体重量和长度用于计算其他 BIA 变量,如阻抗模量、相位角、生物电容量以及电阻和电抗密度。这些变量被用作预测胴体中软组织、水分、灰分、蛋白质、脂肪、瘦肉和粗能含量的自变量。进行多元回归分析以校准 BIA 模型。采用留一法交叉验证来评估 BIA 技术的精密度和准确性。电阻密度是预测热胴体中羔羊组成的最重要 BIA 变量,可解释 83%至 92%的组成变化。相反,电抗密度更好地预测了冷胴体中羔羊胴体的组成,可解释 81%至 92%的胴体组成变化。此外,在冷胴体上评估的羔羊胴体软组织部分预测模型的决定系数更高,均方根误差和 Mallows Cp 值更小。因此,BIA 具有极好的潜力来预测热或冷胴体中的羔羊胴体成分;然而,与热胴体相比,冷胴体的准确性更高。