使用非线性函数建模低地羊的生长
Numan Sharif1,2, Fiona M McGovern2, Noirin McHugh3
1School of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, D04 V1W8, Ireland.
使用各种功能在绵羊中的生长建模显示,Gompertz和von Bertalanffy模型最好地描述了体重概况. 这些模型为遗传评估提供了良好的匹配,融合和生物学上合理的参数.
科学领域:
- 动物科学动物科学
- 量化遗传学 量化遗传学
- 数学的建模数学建模
背景情况:
- 准确的羊生长建模对于理解体重变化和遗传评估程序至关重要.
- 连续测量人体重量为推导生物学上重要的参数提供了有价值的数据.
研究的目的:
- 评估六种不同的数学函数 (Brody,Gompertz,Logistic,负指数,Richards和von Bertalanffy) 的性能,以建模低地羊的生长.
- 探索这些函数内和跨这些函数的模型参数之间的关系.
主要方法:
- 配备了6个生长功能,用于158,463个体重记录,来自13,090只雌性低地绵羊.
- 通过确定系数 (R2),根平均平方误差 (RMSE) 和收率来评估模型匹配.
- 分析了跨函数的估计增长参数 (A,B,K) 之间的相关性.
主要成果:
- 戈珀茨和·伯塔兰菲的功能表现出了很好的适应性和收性 (100%),与生物学上有意义的参数一起.
- 理查兹函数显示了最高的R2 (0.98),但收率较低 (82.39%).
- 异常权重 (A) 和成熟率 (K) 参数之间的相关性在各个函数中一般是负的.
结论:
- 建议使用Gompertz和von Bertalanffy函数来建模爱尔兰雌性低地绵羊的生长概况.
- 这些模型为在绵羊繁殖计划中对遗传参数估计提供了强大的框架.
- 模型选择应考虑参数的合适性,收性和生物解释性.
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