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Adaptation and evaluation of a mechanistic grass growth simulation model for grass-based systems

机译:基于基地系统机械草生长模拟模型的适应与评价

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An accurate grass growth model would be a valuable tool in anticipating grass growth and grass utilization at farm level. Ideally, a grass growth simulation model must be accurate, dynamic, use realistic input parameters and incorporate meteorologicaldata. The objective of this study was to parameterize the grass growth model developed by Jouven et al. (2006) to increase its accuracy of grass growth simulation in the south of Ireland. The model was parameterized using an optimization technique wherea number of the parameters in the model were optimized with the objective function of minimizing the root mean square error (RMSE). Both meteorological and grass growth data for the period 2005 to 2009 were included in the optimization process. During validation the Jouven Model was compared to the Adapted Model. RMSE was reduced from 20.45 kg DM ha~(-1) day~(-1) with the Jouven Model to 14.62 kg DM ha~(-1) day~(-1) with the Adapted Model. MSPE was reduced from 476 to 183. The proposed changes to the Jouven Model improved grass growth simulation in the south of Ireland. The adapted version of the Jouven Model can be used for grass growth simulation; albeit without perfect simulation.
机译:准确的草地增长模型将是一个有价值的工具,即在农场层面预测草地增长和草地利用。理想情况下,草生长仿真模型必须准确,动态,使用现实的输入参数,并包含陨石图。本研究的目的是参数化Jouven等人开发的草生长模型。 (2006)提高爱尔兰南部草地增长模拟的准确性。使用优化技术进行参数化模型,其中模型中参数的数量进行了优化,目的函数最小化了根均方误差(RMSE)。 2005年至2009年期间的气象和草地增长数据都包含在优化过程中。在验证期间,将Jouven模型与适应的模型进行比较。 RMSE从20.45公斤DM HA〜(-1)天〜(-1)减少到jouven型号为14.62千克DM HA〜(-1)天〜(-1),适应模型。 MSPE从476降至183.拟议的jouven模型改变了爱尔兰南部的草地增长模拟。 jouven模型的适应版本可用于草地增长模拟;尽管没有完美的模拟。

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