Fred Morley Centre, School of Agricultural, Environmental and Veterinary Sciences, Charles Sturt University, Wagga Wagga, NSW 2650, Australia.
Gulbali Institute, Charles Sturt University, Wagga Wagga, NSW 2650, Australia.
J Anim Sci. 2024 Jan 3;102. doi: 10.1093/jas/skae216.
Livestock producers would benefit from more precise predictions of the growth response from nutrients consumed. Previously published models are often limited by the realities of data collection and are unable to account for alterations to body composition, due in part to the response of visceral organs to an alternate diet. The computerized tomography (CT) scanning of lambs enables the analysis of changes in body composition of individual animals over time, potentially supporting better model development and testing. The aim of this experiment was to develop a repeatable method for the analysis of live lamb body composition using CT scans. A secondary aim was to compare the data collected from CT scanning during a feeding trial to 2 predictive lamb growth models. Cross-bred lambs were fed 2 feeding levels at 2 stages of maturity, with CT scans at the beginning and end of each 8-wk feeding period. The CT scan-derived values for body composition taken at the beginning of feeding periods were used as inputs for 2 existing lamb growth models. Predictions of body composition were compared with CT scan-derived values at the end of feeding periods. The CT scan analysis method used a proportion of images from each lamb to reduce manual image editing. The method was developed by comparing the estimated mass and volume of empty body components using all available CT scans to estimated values using a reduced number of scans from 12 lambs. The CT scan-derived lean tissue mass aligned with model predictions at the end of each feeding period, however, CT scan-derived fat mass was greater than predictions by both models especially for the high feeding level at the later stage of maturity. These results highlight that the analysis of body composition using CT scans requires further validation, particularly for the viscera, and that models likely require refinement to better predict the efficiency of energy utilization by different tissues. The use of live animal CT scans can provide more accurate predictions of the growth of saleable products than measuring liveweight alone and will enable ruminant growth models to better adapt to different genetics and changing diets than comparative slaughter. To replicate the current data using comparative slaughter would require 4 times the animals, as individual lambs were CT scanned 4 times in this study, demonstrating the potential value of CT scanning in live animal research.
家畜饲养者将从消耗的营养物质的生长反应的更精确预测中受益。以前发表的模型通常受到数据收集现实的限制，并且由于内脏器官对替代饮食的反应，无法解释身体成分的变化。对羔羊进行计算机断层扫描 (CT) 扫描可以分析个体动物随时间变化的身体成分，这可能有助于更好地开发和测试模型。本实验的目的是开发一种可重复的方法，用于使用 CT 扫描分析活羔羊的身体成分。次要目的是将在喂养试验中从 CT 扫描收集的数据与 2 种预测羔羊生长模型进行比较。杂交羔羊在成熟的 2 个阶段以 2 个喂养水平喂养，在每个 8 周的喂养期开始和结束时进行 CT 扫描。在喂养期开始时进行的 CT 扫描得出的身体成分值被用作 2 种现有羔羊生长模型的输入。对身体成分的预测与喂养期结束时的 CT 扫描衍生值进行了比较。CT 扫描分析方法使用每只羔羊的一部分图像来减少手动图像编辑。该方法是通过比较使用所有可用 CT 扫描估计的空体成分的质量和体积与使用 12 只羔羊的少数扫描的估计值来开发的。CT 扫描衍生的瘦组织质量与每个喂养期结束时的模型预测相符，然而，CT 扫描衍生的脂肪质量大于两个模型的预测值，尤其是在成熟后期的高喂养水平下。这些结果表明，使用 CT 扫描分析身体成分需要进一步验证，特别是对于内脏，并且模型可能需要改进，以更好地预测不同组织对能量利用的效率。与单独测量活体重相比，使用活体动物 CT 扫描可以更准确地预测可销售产品的生长情况，并使反刍动物生长模型能够更好地适应不同的遗传和变化的饮食，而不是比较屠宰。要使用比较屠宰来复制当前数据，需要将动物数量增加 4 倍，因为本研究中每个羔羊都进行了 4 次 CT 扫描，这表明 CT 扫描在活体动物研究中的潜在价值。
