Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton T6G 2P5, Alberta, Canada.
Department of Biological Sciences, University of Alberta, Edmonton T6G 2P5, Alberta, Canada.
Poult Sci. 2020 Jun;99(6):3237-3250. doi: 10.1016/j.psj.2020.02.005. Epub 2020 Mar 5.
Understanding factors affecting ME availability for productive processes is an important step in optimal feed formulation. This study compared a modelling methodology with the comparative slaughter technique (CST) to estimate energy partitioning to heat production and energy retention (RE) and to investigate differences in heat dissipation. At hatch, 50 broilers were randomly allocated in one of 4 pens equipped with a precision feeding station. From day 14 to day 45, they were either fed with a low-ME (3,111 kcal/kg ME) or a high-ME (3,383 kcal/kg ME) diet. At day 19, birds were assigned to pair-feeding in groups of 6 with lead birds eating ad libitum (100%) and follow birds eating at either 50, 60, 70, 80, or 90% of the paired lead's cumulative feed intake. Heat production and RE were estimated by CST and with a nonlinear mixed model explaining daily ME intake (MEI) as a function of metabolic BW and average daily gain (ADG). The energy partitioning model predicted MEI = (145.10 + u) BW + 1.09 × BW × ADG + ε. The model underestimated heat production by 13.4% and overestimated RE by 22.8% compared with the CST. The model was not able to distinguish between net energy for gain values of the diets (1,448 ± 18.5 kcal/kg vs. 1,493 ± 18.0 kcal/kg for the low-ME and high-ME diet, respectively), whereas the CST found a 148 kcal/kg difference between the low-ME and high-ME diets (1,101 ± 22.5 kcal/kg vs. 1,249 ± 22.0 kcal/kg, respectively). The estimates of the net energy for gain values of the 2 diets decreased with increasing feed restriction. The heat increment of feeding did not differ between birds fed with the low- or high-ME diet (26% of MEI). Additional measurements on heat dissipation, physical activity, and immune status indicated that the energetic content of the diet and feed restriction affect some parameters (shank temperature, feeding station visits) but not others (leukocyte counts, heterophil to lymphocyte ratio, and immune cell function).
了解影响 ME 可用于生产过程的因素是优化饲料配方的重要步骤。本研究比较了一种建模方法和比较屠宰技术(CST),以估计能量分配给产热和能量保留(RE),并研究散热的差异。在孵化时,将 50 只肉鸡随机分配到 4 个配备精密喂料站的围栏中的一个中。从第 14 天到第 45 天,它们要么喂食低 ME(3,111 kcal/kg ME)要么喂食高 ME(3,383 kcal/kg ME)饮食。在第 19 天,将鸟类分组进行配对喂养,每组 6 只,领头鸟自由采食(100%),跟随鸟采食领头鸟累积采食量的 50%、60%、70%、80%或 90%。通过 CST 和解释每日 ME 摄入量(MEI)作为代谢 BW 和平均日增重(ADG)函数的非线性混合模型来估计产热和 RE。能量分配模型预测 MEI =(145.10 + u)BW + 1.09×BW×ADG + ε。与 CST 相比,该模型低估了产热 13.4%,高估了 RE 22.8%。该模型无法区分两种饮食的净能增益值(低 ME 饮食为 1,448 ± 18.5 kcal/kg,高 ME 饮食为 1,493 ± 18.0 kcal/kg),而 CST 发现低 ME 饮食和高 ME 饮食之间存在 148 kcal/kg 的差异(分别为 1,101 ± 22.5 kcal/kg 和 1,249 ± 22.0 kcal/kg)。两种饮食的净能增益值估计值随着饲料限制的增加而降低。饲喂的热增量在喂食低 ME 或高 ME 饮食的鸟类之间没有差异(MEI 的 26%)。对散热、身体活动和免疫状态的额外测量表明,饮食的能量含量和饲料限制会影响一些参数(跖骨温度、饲料站访问次数),但不会影响其他参数(白细胞计数、异嗜性粒细胞与淋巴细胞比值和免疫细胞功能)。