双能x线吸收法测定鸡加工体重:由于禁食、出血和寒冷导致体重变化

D.A. Martinez, N. Suesuttajit, J.T. Weil, P. Maharjan , A. Beitia , K. Hilton , C. Umberson, A. Scott, C.N. Coon
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引用次数: 6

摘要

现代肉鸡胸重的增加,凸显了研究整个生长期加工体重动态的便利性。为了预测这些性状的模型在纵向研究中适用于非禁食的活禽,有必要确定鸟类因禁食和出血而导致的体重变化以及因冷却而导致的尸体。本研究旨在建立肉仔鸡空腹减重预测模型,确定因出血和低温引起的体重变化,并评估肉鸡胗脂肪占腹部脂肪的比例。模型拟合空腹体重损失数据来自文献。在初步研究中获得的出血BW损失值与文献进行了比较。这一个和单一来源砂砾在腹部脂肪值的百分比被用作参考值。选取两个试验中不同年龄的禽类,测定以下变量:未禁食和禁食体重、血重、未冷冻和冷冻胴体重、砂囊脂肪和腹部脂肪垫重量。以预测值和参考值的95%置信区间与观测数据进行比较,若无统计学差异,则对拟合模型和参考值进行验证。将禁食体重损失模型修正为实验数据,并比较模型对两个数据集的拟合估计。空腹体重损失遵循三参数指数模型,随年龄增长呈递减趋势,预测值与实测值无统计学差异(P >0.05)。参考出血体重损失(2.76%)和砂囊脂肪率(18%)值无差异(P >0.05)与肉鸡试验数据相比较,冷态胴体增重为2.79%。禁食体重损失模型的规模和相对增长率估计值没有差异(P >0.05),渐近线显示可能但可以忽略不计的差异。验证空腹体重损失模型、出血性体重损失系数和砂囊脂肪率。本文所得到的模型和系数不仅可用于双能x射线吸收法预测加工权重,还可用于其他建模方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Processing weights of chickens determined by dual-energy X-ray absorptiometry: 1. Weight changes due to fasting, bleeding, and chilling

The increasing breast weight of modern broilers highlights the convenience of studying the dynamics of processing weights across the grow-out period. For models predicting these traits to work with non-fasted live birds under longitudinal studies, it is necessary to determine the changes in the weights of birds due to fasting and bleeding and carcasses due to chilling. This study aimed to develop a model to predict the fasting weight loss of broilers, determine the weight changes due to bleeding and chilling, and assess the percentage of gizzard fat in the abdominal fat. Models were fitted to fasting BW loss data from literature. A bleeding BW loss value obtained in a pilot study was compared to literature. This one and a single-source percent gizzard in the abdominal fat value were used as reference values. Birds from two experiments were selected at different ages to determine the following variables: non-fasted and fasted BW, bled weight, unchilled and chilled carcass weights, and gizzard fat and abdominal fat pad weights. Predicted and reference values were compared to the observed data based on their 95% confidence intervals, and the fitted model and reference values were validated if no statistical differences were inferred. The fasting BW loss model was refitted to the data from experiments, and the estimates of the model fitted to both datasets were compared. The fasting BW loss followed a three-parameter exponential model with reducing values as the bird aged, and the predicted and observed values showed no statistical difference (P > 0.05). The reference bleeding BW loss (2.76%) and gizzard fat percentage (18%) values showed no difference (P > 0.05) to data from broiler experiments, and a chilling carcass weight gain of 2.79% was determined. The scale and relative growth rate estimates of the fasting BW loss model showed no difference (P > 0.05) between datasets, and the asymptote showed a possible but negligible difference. The fasting BW loss model, the bleeding BW loss coefficient, and the gizzard fat percentage were validated. The model and coefficients obtained herein will not only be applied to predict processing weights using Dual-Energy X-ray Absorptiometry but also may be used in other modeling approaches.

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