首页> 外文OA文献 >Non-invasive determination of body composition in pigs using a Norland XR-26 bone densitometer
【2h】

Non-invasive determination of body composition in pigs using a Norland XR-26 bone densitometer

机译:使用Norland XR-26骨密度仪无创地测定猪的身体成分

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Non-invasive measurement of body composition provides advantages in growth studies compared toconventional techniques. The same individual can be measured several times, the measurement is faster, and thenumber of pigs required as well as the random effect of animal are reduced. The aim of the present study was todetermine the composition of the half carcass and of the ham/shank region by a whole body dual-energy X-rayabsorptiometry (DXA) scan of the live pig using a Norland XR-26. Accuracy and precision of DXAmeasurement were evaluated by regression analysis between DXA-derived values and chemical analysis as wellas dissection. Pigs of different gender were used covering a wide range of body weights and body composition.Single regression analysis for lean and fat mass revealed a close relationship between half carcass DXA andchemical analysis (R² = 0.97 and R² = 0.91, respectively) as well as dissection (R² = 0.99 and R² = 0.98,respectively). The prediction accuracy (R²) was lower for the tissue percentages than for the respective tissuemasses. The relationship between live pig DXA and reference methods was close for dissected lean meat (R² =0.90) and adipose tissue mass (R² = 0.93). For chemical lean and fat mass, R² were slightly lower. Multipleregression analysis using one to four independent variables improved accuracy of prediction. The composition ofham and shank could be predicted more accurately than the half carcass composition.
机译:与传统技术相比,人体成分的无创测量在生长研究中具有优势。可以对同一个人进行多次测量,测量速度更快,并且减少了所需的猪只数量以及动物的随机效应。本研究的目的是通过使用Norland XR-26对活猪进行全身双能X射线骨密度仪(DXA)扫描来确定半car体和火腿/小腿区域的组成。通过对DXA值与化学分析以及夹层之间的回归分析,评估了DXA测量的准确性和精确性。使用了不同性别的猪,其体重和身体组成范围很广。瘦肉和脂肪量的单回归分析显示半half体DXA与化学分析之间的密切关系(分别为R²= 0.97和R²= 0.91)以及解剖(R 2 = 0.99,R 2 = 0.98)。组织百分比的预测准确性(R 2)低于各个组织质量的预测准确性。解剖的瘦肉(R²= 0.90)和脂肪组织质量(R²= 0.93)与生猪DXA和参考方法之间的关系非常接近。对于化学瘦肉和脂肪量,R 2略低。使用一到四个独立变量的多元回归分析提高了预测的准确性。火腿和小腿的组成比半car体的组成更准确。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号