Graduate Program in Production Engineering, Universidade Paulista, R. Dr. Bacelar 1212, São Paulo, 04026-002, Brazil.
Animal Science, Universidade Federal de Roraima, BR 174, km 12, Monte Cristo, Boa Vista, 69300-000, Brazil.
Trop Anim Health Prod. 2024 Oct 14;56(8):343. doi: 10.1007/s11250-024-04188-4.
Sheep were among the first animals domesticated by humans, and to this day, small ruminants are primarily raised for their meat, milk, and wool. This study evaluated the goodness of fit for growth curve models using observed age and weight data from crossbred lambs of various breeds based on the mean values between paired breeds. We employed a hybrid metaheuristic algorithm, combining a simulated annealing (SA) algorithm and a genetic algorithm (GA) called SAGAC, to determine the optimal parameter values for growth models, ensuring the best alignment between simulated and observed curves. The goodness of fit and model accuracy was assessed using the coefficient of determination (R), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE). Errors were measured by comparing the criteria differences between simulated and observed data. Thirty crossbreed combinations were simulated, considering the average weight. Analysis of the observed and simulated growth curves indicated that specific crossbreeding scenarios produced promising results. This simulation approach is believed to assist geneticists in predicting potential crossbreeding outcomes, thereby saving time and financial resources in field research.
绵羊是人类最早驯化的动物之一，时至今日，小反刍动物主要还是以其肉、奶和羊毛为主要养殖目的。本研究通过基于配对品种均值的杂种羔羊各品种间的观察到的年龄和体重数据，评价了生长曲线模型的拟合优度。我们采用了一种混合元启发式算法，将模拟退火（SA）算法和遗传算法（GA）相结合，称为 SAGAC，用于确定生长模型的最优参数值，确保模拟曲线与观测曲线之间的最佳拟合。通过决定系数（R）、平均绝对误差（MAE）、均方根误差（RMSE）和平均绝对百分比误差（MAPE）来评估拟合优度和模型准确性。通过比较模拟数据和观察数据之间的标准差异来衡量误差。我们模拟了 30 个杂交组合，考虑了平均体重。对观察到的和模拟的生长曲线的分析表明，特定的杂交方案产生了有希望的结果。这种模拟方法被认为可以帮助遗传学家预测潜在的杂交结果，从而节省实地研究中的时间和财务资源。
