Bartlett Factor Scores in Multiple Linear Regression Equation as a Tool for Estimating Economic Traits in Broilers

O. Jesuyon
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Abstract

To propose a simpler tool that eliminates the age-long problems associated with the traditional index method for selection of multiple traits in broilers, the Barttlet factor regression equation is being proposed as an alternative selection tool. 100 day-old chicks each of Arbor Acres (AA) and Annak (AN) broiler strains were obtained from two rival hatcheries in Ibadan Nigeria. These were raised on deep litter system in a 56-day feeding trial in the University of Ibadan Teaching and Research Farm, located in South-west Tropical Nigeria. The body weight and body dimensions were measured and recorded during the trial period. Eight (8) zoometric measurements namely Live weight (g), Abdominal Circumference, Abdominal length, Breast width, leg length, Height, Wing length and Thigh circumference (all in cm) were recorded randomly from 20 birds within strain, at a fixed time on the first day of the new week respectively with a 5-kg capacity Camry scale. These records were analyzed and compared using completely randomized design (CRD) of SPSS analytical software, with the means procedure, Factor Scores (FS) in stepwise Multiple Linear Regression (MLR) procedure for initial live weight equations. Bartlett Factor Score (BFS) analysis extracted 2 factors for each strain, termed Body-length and Thigh-meatiness Factors for AA, and; Breast Size and Height Factors for AN. These derived orthogonal factors assisted in deducing and comparing traitcombinations that best describe body conformation and Meatiness in experimental broilers. BFS procedure yielded different body conformational traits for the two strains, thus indicating the different economic traits and advantages of strains. These Factors could be useful as selection criteria for improving desired economic traits. The final Bartlett Factor Regression equations for prediction of body weight were highly significant with P<0.0001, R2 of 0.92 and above, VIF of 1.00, and DW of 1.90 and 1.47 for Arbor Acres and Annak respectively. These FSR equations could be used as a simple and potent tool for selection during poultry flock improvement, it could also be used to estimate selection index of flocks to discriminate between strains, and evaluate consumer preference traits in broilers.
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多元线性回归方程中Bartlett因子得分作为肉鸡经济性状估计工具的研究
为了提出一种更简单的工具,以消除传统指数法在肉鸡多性状选择中存在的年龄问题,提出了Barttlet因子回归方程作为一种替代选择工具。从尼日利亚伊巴丹两个互为竞争对手的孵化场分别获得Arbor Acres (AA)和Annak (AN)肉鸡品系各100日龄雏鸡。在位于尼日利亚热带西南部的伊巴丹大学教学和研究农场进行的为期56天的饲养试验中,这些鸡在深凋落物系统中饲养。在试验期间测量并记录体重和体尺寸。采用5 kg容量的凯美瑞秤,在新一周第一天的固定时间,随机记录20只家禽的活重(g)、腹围、腹长、胸宽、腿长、身高、翼长和大腿围(均以cm为单位)8项动物测量数据。采用SPSS分析软件的完全随机设计(CRD)对这些记录进行分析和比较,采用均值程序,初始活权方程采用逐步多元线性回归(MLR)程序中的因子得分(FS)。Bartlett因子评分(BFS)分析为每个菌株提取了2个因子,分别为AA的体长因子和腿肉度因子;AN的乳房尺寸和身高因素。这些导出的正交因子有助于推断和比较最能描述试验肉鸡体形和肉质的性状组合。BFS处理得到的菌株体构象特征不同,说明菌株的经济性状和优势不同。这些因子可作为改良理想经济性状的选择标准。预测体重的最终Bartlett因子回归方程P<0.0001, R2为0.92及以上,VIF为1.00,DW分别为1.90和1.47。这些FSR方程可作为禽群改良过程中一个简单有效的选择工具,也可用于估计禽群的选择指数,以区分不同品系,以及评价肉鸡的消费偏好性状。
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