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

Session 1 : Improving Eco-Efficiency in Mixed Farming Systems Session 1 : Improving Eco-Efficiency in Mixed Farming Systems 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 accur...

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Bibliographic Details
Main Authors: Hurtado-Uria, Cristina, Hennessy, Deirdre, Delaby, Luc, O'Connor, Declan, Shalloo, Laurence
Other Authors: Moorepark Food Research Centre, Teagasc - The Agriculture and Food Development Authority (Teagasc), Cork Institute of Technology (CIT), Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage Rennes (PEGASE), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, European Project: 244983,EC:FP7:KBBE,FP7-KBBE-2009-3,MULTISWARD(2010)
Format: Conference Object
Language:English
Published: HAL CCSD 2013
Subjects:
Online Access:https://hal.science/hal-01210590
https://hal.science/hal-01210590/document
https://hal.science/hal-01210590/file/13Hurtado201_1.pdf
Description
Summary:Session 1 : Improving Eco-Efficiency in Mixed Farming Systems Session 1 : Improving Eco-Efficiency in Mixed Farming Systems 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 meteorological data. 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 where a number of the parameters in themodel 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 ofIreland. The adapted version of the Jouven Model can be used for grass growth simulation albeit without perfect simulation.