摘要
We used five nonlinear models to calculate the weight gain of rainbow trout (122.11±15.6 g) during the final grow-out phase of 98 days under three different feed types (two commercials diets, A and B, and one experimental diet, C) in triplicate groups. We fitted the von Bertalanffy growth function with allometric and isometric scaling coefficient, Gompertz, Logistic, and Brody functions to weight (g) at age data of 900 fish, distributed in nine tanks. The equations were fitted to the data based on the least squares method using the Marquardt iterative algorithm. The accuracy of the fitted models was evaluated using a model performance metrics, combining mean squared residuals (MSR), mean absolute error (MAE), and Akaike’s Information Criterion corrected for small sample sizes (AICc). All models converged in all cases tested. The evaluation criteria for the Logistic model indicated the best overall fit (0.704) under all different feed types, followed by the Gompertz model (0.148), and the von Bertalanffy-I and von Bertalanffy-A with 0.074 each. The obtained asymptotic values are in agreement with the biological attributes of the species, except for the Brody model, whose values were massively exceeding the biologic traits of rainbow trout in 0.556 of tested cases. Additionally, ∆AICc results identify the Brody model as the only model not substantially supported by the data in any case. All other models are capable of reflecting the effects of various feed types; these results are directly applicable in farm management decisions.
摘要译文
我们使用五种非线性模型来计算虹鳟鱼在最终生长阶段（98天的生长阶段）在三种不同饲料类型（两种商业日粮A和B，以及一种实验日粮C）下的体重增加（122.11±15.6 g）。一式三份。在分布在9个水箱中的900条鱼的年龄数据中，我们将von Bertalanffy生长函数与异速和等距缩放系数，Gompertz，Logistic和Brody函数拟合为体重（g）。使用Marquardt迭代算法，基于最小二乘法将方程拟合到数据。使用模型性能指标，结合均方差（MSR），平均绝对误差（MAE）和针对小样本量（AICc）校正的Akaike信息准则，评估了拟合模型的准确性。在所有测试情况下，所有模型都收敛。 Logistic模型的评估标准显示在所有不同的饲料类型下最佳总体拟合度（0.704），其次是Gompertz模型（0.148），以及von Bertalanffy-I和von Bertalanffy-A各自为0.074。除布罗迪模型外，所获得的渐近值与该物种的生物学特性相符，布罗迪模型的值在0.556个测试病例中已大大超过虹鳟的生物学特性。此外，∆AICc结果将Brody模型确定为在任何情况下数据均基本不支持的唯一模型。所有其他模型都能够反映各种饲料类型的影响；这些结果直接适用于农场管理决策。
JANAMPA-SARMIENTO; Peter Charrie et al.. Modeling the weight gain of freshwater-reared rainbow trout ( Oncorhynchus mykiss ) during the grow-out phase.[J]. Revista Brasileira de Zootecnia, 2020,49(49)