Global sensitivity analysis by means of EFAST and Sobol methods and calibration of reduced state-variable TOMGRO model using genetic algorithms
FAST and Sobol sensitivity analysis methods were compared. Genetic algorithms were performed to calibrate reduced TOMGRO model. Reduced TOMGRO model calibration allowed an adequate goodness-of-fit of the simulations. Sensitivity analysis showed the effect of growing conditions on TOMGRO parameters. Current TOMGRO structure can be used to simulate tomato growth in Central Mexico.
sensitivity analysis efast sobol tomgro genetic algorithms tomato