Heringstad B, Chang Y M, Gianola D, Klemetsdal G
Department of Animal Science, Agricultural University of Norway, P.O. Box 5025, N-1432 As, Norway.
J Dairy Sci. 2003 Aug;86(8):2676-83. doi: 10.3168/jds.S0022-0302(03)73863-6.
Clinical mastitis records for 36,178 first-lactation daughters of 245 Norwegian Cattle (NRF) sires were analyzed with a Bayesian longitudinal threshold model. For each cow, the period going from 30 d before calving to 300 d after calving was divided into 11 intervals of 30 d length each. Absence or presence of clinical mastitis within each interval was scored as "0" or "1", respectively. A Bayesian threshold model consisting of a set of explanatory variables plus Legendre polynomials on time of order four was used to describe the trajectory of liability to clinical mastitis. Heritability ranged between 0.07 and 0.13 before calving, from 0.04 to 0.15 during the first 270 d after calving, and increased sharply thereafter, as a consequence of the form of the polynomial. Genetic correlations between adjacent days were close to 1, and decreased when days were further apart. Most genetic correlations were moderate to high. A measure of probability of future daughters contracting clinical mastitis during lactation was computed for each sire. A typical curve had a peak near calving followed by a decrease thereafter. The best sires had a low peak around calving and a low expected probability of mastitis among daughters throughout lactation. Expected fraction of days without mastitis was derived from the probability curves and used for ranking of sires. Rank correlations with genetic evaluations of sires obtained from cross-sectional models were high. However, sire selection was affected markedly, especially at high selection intensity. An advantage of the longitudinal model for clinical mastitis is its ability to take multiple treatments and time aspects into account.
利用贝叶斯纵向阈值模型,对245头挪威红牛(NRF)种公牛的36178头头胎女儿的临床乳腺炎记录进行了分析。对于每头奶牛,从产犊前30天到产犊后300天的时间段被划分为11个长度均为30天的区间。每个区间内临床乳腺炎的有无分别记为“0”或“1”。采用由一组解释变量加上四阶时间勒让德多项式组成的贝叶斯阈值模型来描述临床乳腺炎发病倾向的轨迹。产犊前遗传力在0.07至0.13之间,产犊后前270天为0.04至0.15,此后由于多项式的形式,遗传力急剧上升。相邻天数之间的遗传相关性接近1,间隔天数增加时相关性降低。大多数遗传相关性为中度到高度。为每头种公牛计算了其未来女儿在泌乳期患临床乳腺炎概率的度量值。典型曲线在产犊附近有一个峰值,随后下降。最佳种公牛在产犊前后峰值较低,且其女儿在整个泌乳期患乳腺炎的预期概率较低。无乳腺炎天数的预期比例由概率曲线得出,并用于种公牛排名。与从横断面模型获得的种公牛遗传评估的秩相关很高。然而,种公牛的选择受到显著影响,尤其是在高选择强度下。临床乳腺炎纵向模型的一个优点是它能够考虑多次治疗和时间因素。