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泌乳牛和生长牛空体及胴体化学成分的估计:成像、脂肪细胞形态及肋骨解剖方法的比较

Estimation of empty body and carcass chemical composition of lactating and growing cattle: comparison of imaging, adipose cellularity, and rib dissection methods.

作者信息

Xavier Caroline, Driesen Charlotte, Siegenthaler Raphael, Dohme-Meier Frigga, Le Cozler Yannick, Lerch Sylvain

机构信息

Ruminants Research Group, Agroscope, 1725 Posieux, Switzerland.

Research Contracts Animals Group, Agroscope, 1725 Posieux, Switzerland.

出版信息

Transl Anim Sci. 2022 Jun 10;6(2):txac066. doi: 10.1093/tas/txac066. eCollection 2022 Apr.

DOI:10.1093/tas/txac066
PMID:35702177
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9186311/
Abstract

The aim of present study was to compare in vivo and post mortem methods for estimating the empty body (EB) and carcass chemical compositions of Simmental lactating and growing cattle. Indirect methods were calibrated against the direct post mortem reference determination of chemical compositions of EB and carcass, determined after grinding and analyzing the water, lipid, protein, mineral masses, and energy content. The indirect methods applied to 12 lactating cows and 10 of their offspring were ultrasound (US), half-carcass and 11th rib dual-energy X-ray absorptiometry (DXA) scans, subcutaneous and perirenal adipose cell size (ACS), and dissection of the 11th rib. Additionally, three-dimensional (3D) images were captured for 8 cows. Multiple linear regressions with leave-one-out-cross-validations were tested between predictive variables derived from the methods tested, and the EB and carcass chemical compositions. Partial least square regressions were used to estimate body composition with morphological traits measured on 3D images. Body weight (BW) alone estimated the EB and carcass composition masses with a root mean squared error of prediction (RMSEP) for the EB from 1 kg for minerals to 12.4 kg for lipids, and for carcass from 0.9 kg for minerals to 7.8 kg for water. Subcutaneous adipose tissue thickness measured by US was the most accurate in vivo predictor when associated with BW to estimate chemical composition, with the EB lipid mass RMSEP = 11 kg and = 0.75; carcass water mass RMSEP = 6 kg and = 0.98; and carcass energy content RMSEP = 236 MJ and = 0.91. Post mortem, carcass lipid mass was best estimated by half-carcass DXA scan (RMSEP = 2 kg, = 0.98), 11th rib DXA scan (RMSEP = 3 kg, = 0.96), 11th rib dissection (RMSEP = 4 kg, = 0.92), and perirenal ACS (RMSEP = 6 kg, = 0.79) in this respective order. The results obtained by 11th rib DXA scan were accurate and close to the half-carcass DXA scan with a reduction in scan time. Morphological traits from 3D images delivered promising estimations of the cow EB and carcass chemical component masses with an error less than 13 kg for the EB lipid mass and than 740 MJ for the EB energy. Future research is required to test the 3D imaging method on a larger number of animals to confirm and quantify its interest in estimating body composition in living animals.

摘要

本研究的目的是比较活体和死后方法,以估计西门塔尔泌乳牛和生长牛的空体(EB)及胴体化学成分。间接方法通过与直接的死后参考测定进行校准,后者是在研磨并分析水、脂质、蛋白质、矿物质质量和能量含量后确定的EB和胴体的化学成分。应用于12头泌乳母牛及其10头后代的间接方法包括超声(US)、半胴体和第11肋双能X射线吸收法(DXA)扫描、皮下和肾周脂肪细胞大小(ACS)以及第11肋解剖。此外,还为8头母牛拍摄了三维(3D)图像。对所测试方法得出的预测变量与EB和胴体化学成分之间进行了留一法交叉验证的多元线性回归测试。使用偏最小二乘回归,根据在3D图像上测量的形态特征来估计身体成分。仅体重(BW)就能估计EB和胴体成分质量,对于EB,预测的均方根误差(RMSEP)从矿物质的1千克到脂质的12.4千克不等,对于胴体,从矿物质的0.9千克到水的7.8千克不等。当与BW相关联以估计化学成分时,通过US测量的皮下脂肪组织厚度是最准确的活体预测指标,EB脂质质量的RMSEP = 11千克,相关系数 = 0.75;胴体水质量的RMSEP = 6千克,相关系数 = 0.98;胴体能量含量的RMSEP = 236兆焦,相关系数 = 0.91。在死后,胴体脂质质量通过半胴体DXA扫描(RMSEP = 2千克,相关系数 = 0.98)、第11肋DXA扫描(RMSEP = 3千克,相关系数 = 0.96)、第11肋解剖(RMSEP = 4千克,相关系数 = 0.92)和肾周ACS(RMSEP = 6千克,相关系数 = 0.79)按此顺序最佳估计。第11肋DXA扫描获得的结果准确,且与半胴体DXA扫描相近,同时扫描时间减少。来自3D图像的形态特征对母牛EB和胴体化学成分质量给出了有前景的估计,EB脂质质量误差小于13千克,EB能量误差小于740兆焦。未来需要对更多动物测试3D成像方法,以确认并量化其在估计活体动物身体成分方面的价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22ac/9186311/fef0f277dabc/txac066_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22ac/9186311/512ca1c90148/txac066_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22ac/9186311/9bde9c8970d3/txac066_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22ac/9186311/cf0f459e0e5d/txac066_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22ac/9186311/fef0f277dabc/txac066_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22ac/9186311/512ca1c90148/txac066_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22ac/9186311/9bde9c8970d3/txac066_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22ac/9186311/cf0f459e0e5d/txac066_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22ac/9186311/fef0f277dabc/txac066_fig4.jpg

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