利用脂肪厚度和胸长肌特征的实时超声波测量来预测杂交毛母羊的体脂储量

IF 1.6 3区 农林科学 Q2 AGRICULTURE, DAIRY & ANIMAL SCIENCE Small Ruminant Research Pub Date : 2024-11-05 DOI:10.1016/j.smallrumres.2024.107400
José Carlos García-Cigarroa , Armin Abelardo Luna-Mendicuti , Jorge Rodolfo Canul-Solís , Luis Enrique Castillo-Sanchez , José Herrera-Camacho , Einar Vargas-Bello-Pérez , Alfonso J. Chay-Canul
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引用次数: 0

摘要

本研究旨在通过对杂交毛母羊脂肪厚度和胸长肌特征的超声波测量(USM)来预测体脂库。共使用了 24 只平均体重 (BW) 为 37 ± 4 千克、体况评分为 2.39 ± 0.49 的母羊。屠宰前 24 小时记录 USM,包括:胸肌皮下脂肪厚度(SFT)、面积(LTMA)、振幅(LTA)和深度(LTD)以及肾脏脂肪厚度(µKFT)。屠宰后,将内部脂肪(IF)分离、分类并称重为肠系膜脂肪(MF)、网膜脂肪(OF)或盆腔脂肪(PF)。然后将左半身分为皮下脂肪和肌间脂肪(CF),肌肉和骨骼组织分别称重,并根据整只动物的情况进行调整。体脂总量(TBF)被确定为 IF 加上 CF 的重量。LTA和LTMA与脂肪储量的相关性从较差到中等(0.37 ≤ r ≤ 0.74,P <0.05)。除 CF 外,µKFT 与身体其他脂肪层的相关性从较差到中等(0.44 ≤ r ≤ 0.75,P < 0.05)。用于预测 MF 的回归模型的 r2 为 0.87(RSD=0.14 千克),其中包括体重和 LTMA(P<0,05)。预测 OF 和 PF 的 r2 分别为 0.55 和 0.44,包括 µKFT (RSD=0.20 和 0.17 千克)。空腹体重、LTMA 和 µKFT 预测 IF 的 r2 为 0.81(RSD=0.30 千克)。对于 TBF,EBW 和 LTMA 可解释其 72% 的变化(RSD=0.59 千克)。脂肪厚度和胸肌特征的 USM 可以提高预测杂交毛母羊体能储备的准确性。
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Use of real-time ultrasound measurements of fat thickness and longissimus thoracis muscle characteristics for predicting body fat depots in crossbred hair ewes
This study aimed to predict body fat depots using ultrasound measurements (USM) of fat thickness and longissimus thoracis muscle characteristics in crossbred hair ewes. A total of 24 animals with a mean body weight (BW) of 37 ± 4 kg and a body condition score of 2.39 ± 0.49 were used. USM was recorded 24 h before slaughter and included: subcutaneous fat thickness (SFT), area (LTMA), amplitude (LTA), and depth (LTD) of the l. thoracis muscle and kidney fat thickness (µKFT). After slaughter, the internal fat (IF) was separated, classified, and weighed as mesenteric (MF), omental (OF), or pelvic fat (PF). The left half was then separated into subcutaneous and intermuscular fat (CF), and the muscle and bone tissues were weighed separately and adjusted to take account of the whole animal. Total body fat (TBF) was determined to be the IF plus the CF weights. LTA and LTMA correlated poorly to moderately with fat depots (0.37 ≤ r ≤ 0.74, P < 0.05). Other than CF, µKFT showed poor to moderate correlation with the other depots of body fat (0.44 ≤ r ≤ 0.75, P < 0.05). The regression model used to predict MF had r2 of 0.87 (RSD=0.14 kg) and included BW and LTMA (P<0,05). OF and PF were predicted with r2 of 0.55 and 0.44, respectively, including µKFT (RSD = 0.20 and 0.17 kg). IF was predicted by empty BW, LTMA, and µKFT with r2 as 0.81 (RSD=0.30 kg). For TBF, EBW and LTMA explained 72 % of its variation (RSD= 0.59 kg). USM of fat thickness and l. thoracis muscle characteristics can improve the accuracy of predicting body energy reserves in crossbred hair ewes.
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来源期刊
Small Ruminant Research
Small Ruminant Research 农林科学-奶制品与动物科学
CiteScore
3.10
自引率
11.10%
发文量
210
审稿时长
12.5 weeks
期刊介绍: Small Ruminant Research publishes original, basic and applied research articles, technical notes, and review articles on research relating to goats, sheep, deer, the New World camelids llama, alpaca, vicuna and guanaco, and the Old World camels. Topics covered include nutrition, physiology, anatomy, genetics, microbiology, ethology, product technology, socio-economics, management, sustainability and environment, veterinary medicine and husbandry engineering.
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