1Animal Production Systems Group,Wageningen University & Research,P.O. Box 338,6700 AH Wageningen,The Netherlands.
2Plant Production Systems Group,Wageningen University & Research,P.O. Box 430,6700 AK Wageningen,The Netherlands.
Animal. 2019 Apr;13(4):856-867. doi: 10.1017/S1751731118001738. Epub 2018 Jul 12.
The model LiGAPS-Beef (Livestock simulator for Generic analysis of Animal Production Systems - Beef cattle) has been developed to assess potential and feed-limited growth and production of beef cattle in different areas of the world and to identify the processes responsible for the yield gap. Sensitivity analysis and evaluation of model results with experimental data are important steps after model development. The first aim of this paper, therefore, is to identify which parameters affect the output of LiGAPS-Beef most by conducting sensitivity analyses. The second aim is to evaluate the accuracy of the thermoregulation sub-model and the feed intake and digestion sub-model with experimental data. Sensitivity analysis was conducted using a one-at-a-time approach. The upper critical temperature (UCT) simulated with the thermoregulation sub-model was most affected by the body core temperature and parameters affecting latent heat release from the skin. The lower critical temperature (LCT) and UCT were considerably affected by weather variables, especially ambient temperature and wind speed. Sensitivity analysis for the feed intake and digestion sub-model showed that the digested protein per kg feed intake was affected to a larger extent than the metabolisable energy (ME) content. Sensitivity analysis for LiGAPS-Beef was conducted for ¾ Brahman×¼ Shorthorn cattle in Australia and Hereford cattle in Uruguay. Body core temperature, conversion of digestible energy to ME, net energy requirements for maintenance, and several parameters associated with heat release affected feed efficiency at the herd level most. Sensitivity analyses have contributed, therefore, to insight which parameters are to be investigated in more detail when applying LiGAPS-Beef. Model evaluation was conducted by comparing model simulations with independent data from experiments. Measured heat production in experiments corresponded fairly well to the heat production simulated with the thermoregulation sub-model. Measured ME contents from two data sets corresponded well to the ME contents simulated with the feed intake and digestion sub-model. The relative mean absolute errors were 9.3% and 6.4% of the measured ME contents for the two data sets. In conclusion, model evaluation indicates the thermoregulation sub-model can deal with a wide range of weather conditions, and the feed intake and digestion sub-model with a variety of feeds, which corresponds to the aim of LiGAPS-Beef to simulate cattle in different beef production systems across the world.
模型 LiGAPS-Beef(用于对动物生产系统进行通用分析的牲畜模拟器 - 肉牛)已被开发出来,用于评估世界不同地区肉牛的潜在和饲料限制生长和生产,并确定导致产量差距的过程。在模型开发之后,进行敏感性分析和用实验数据评估模型结果是重要步骤。因此,本文的第一个目的是通过进行敏感性分析来确定哪些参数对 LiGAPS-Beef 的输出影响最大。第二个目的是用实验数据评估体温调节子模型和采食量与消化子模型的准确性。敏感性分析采用逐个参数的方法进行。体温调节子模型模拟的上限临界温度(UCT)受体核温度和影响皮肤潜热释放的参数影响最大。下限临界温度(LCT)和 UCT 受天气变量影响较大,尤其是环境温度和风速。采食量与消化子模型的敏感性分析表明,每公斤采食量消化的蛋白质比可代谢能(ME)含量受影响更大。对澳大利亚的¾ Brahman×¼ Shorthorn 牛和乌拉圭的 Hereford 牛进行了 LiGAPS-Beef 的敏感性分析。在畜群水平上,体核温度、可消化能向 ME 的转化、维持净能量需求以及与热释放有关的几个参数对饲料效率的影响最大。因此,敏感性分析有助于深入了解在应用 LiGAPS-Beef 时要详细研究哪些参数。通过将模型模拟与实验的独立数据进行比较来进行模型评估。实验中测量的产热量与体温调节子模型模拟的产热量相当吻合。两个数据集的测量 ME 含量与采食量和消化子模型模拟的 ME 含量相当吻合。两个数据集的相对平均绝对误差分别为测量 ME 含量的 9.3%和 6.4%。总之,模型评估表明体温调节子模型可以处理广泛的天气条件,采食量和消化子模型可以处理各种饲料,这符合 LiGAPS-Beef 的目标,即在全球不同的肉牛生产系统中模拟牛。