Wasike Chrilukovian B, Waineina Ruth Wambui, Ngeno Kiplangat, Miyumo Sophie A, Kamidi Christine M, Mwabili Josephine M, Ilatsia Evans D
Livestock Efficiency Enhancement Group (LEEG), Department of Animal and Fisheries Sciences, Maseno University, Maseno, Kenya.
Dairy Research Institute, Kenya Agricultural and Livestock Research Organisation (KALRO-DRI), Naivasha, Kenya.
J Anim Breed Genet. 2025 Nov;142(6):742-752. doi: 10.1111/jbg.12942. Epub 2025 May 28.
Growth performance of juvenile dairy goats influences their rate of growth and consequently (re)productive performance as mature goats. However, dairy goat improvement programmes focus on milk and fertility traits and seldom growth traits. This study aimed at estimating variance components and genetic parameters for growth in juvenile dairy goats to avail these estimates for inclusion in the national dairy goat improvement program. 4072 weekly weights records (from 1 week to 16th week of age) were collected on 453 goats born of 35 dams and 15 sires of Saanen, Toggenburg, Alpine and their crossbred genotypes. The records were subjected to univariate random regression analysis fitting direct additive, maternal genetic and permanent environmental [PE] effects as random effects to estimate variance components and genetic parameters. Phenotypic, additive genetic, maternal genetic and PE variances increased along the growth trajectory. Estimates of variance ratios ranged from 0.015 ± 0.14 to 0.469 ± 0.15, 0.097 ± 0.06 to 0.204 ± 0.08 and 0.407 ± 0.13 to 0.641 ± 0.08 for additive genetic, maternal genetic and PE effects, respectively. Correlation estimates were positive. Additive genetic correlations between the weekly weights were high and near unity. Maternal genetic correlations between the weekly weights were equally high. PE correlations were low between early weights and later weights, although correlations between later weights were high. The correlation estimates decreased as the interval between the weights increased for all the random effects. There is sufficient scope of variance in weekly weights to enable selective breeding. Selection to improve later weights could be done based on early weekly weights given the high additive genetic correlations.
幼年奶山羊的生长性能会影响其生长速度，进而影响其成年后的（再）繁殖性能。然而，奶山羊改良计划主要关注产奶和繁殖力性状，很少关注生长性状。本研究旨在估计幼年奶山羊生长的方差成分和遗传参数，以便将这些估计值纳入国家奶山羊改良计划。收集了453只山羊从1周龄到16周龄的4072条每周体重记录，这些山羊由35只母羊和15只公羊所生，品种包括萨能奶山羊、吐根堡山羊、阿尔卑斯山羊及其杂交基因型。对这些记录进行单变量随机回归分析，将直接加性效应、母体遗传效应和永久环境[PE]效应作为随机效应进行拟合，以估计方差成分和遗传参数。表型方差、加性遗传方差、母体遗传方差和PE方差均沿生长轨迹增加。加性遗传效应、母体遗传效应和PE效应的方差比估计值分别为0.015±0.14至0.469±0.15、0.097±0.06至0.204±0.08和0.407±0.13至0.641±0.08。相关性估计值为正。每周体重之间的加性遗传相关性很高且接近1。每周体重之间的母体遗传相关性同样很高。早期体重与后期体重之间的PE相关性较低，尽管后期体重之间的相关性较高。对于所有随机效应，随着体重间隔的增加，相关性估计值下降。每周体重存在足够的方差范围，可用于选择性育种。鉴于加性遗传相关性较高，可根据早期每周体重进行选择以提高后期体重。
