Resumen
- In this study, variations on the output of the Tomgro model are analysed, as a function of variations in solar radiation intensity S, greenhouse air temperature TA and CO2 concentration CA, common for the production of greenhouse tomato in the Bogota Plateau, Colombia. The variation on the output of the model is apportioned to the sources of variation to obtain an analysis of sensitivity. Among the results of this test, a similar degree of variability on the prediction of fruit dry weight WF is detected for the three climate variables, while S and TA were the most sensitive climate variables. Fruit dry weight increased with S and CA, while for TA an optimal range is detected. Next, a factorial experiment is performed where the same climate variables are varied in a small range. Variance decomposition showed that S is the most sensitive climate variable for WF, followed by TA and CA. The development of the vegetative plant parts is more sensitive to TA than to S and CA. The two innovative techniques that are presented for assessing the sensitivity to climate conditions can be used for the selection of production locations or for optimising greenhouse design.