Articles
SENSITIVITY ANALYSES OF TOMGRO OUTPUT VARIABLES TO VARIATIONS IN CLIMATE CONDITIONS
Article number
654_37
Pages
317 – 324
Language
English
Abstract
The sensitivity of the second version of the modified TOMGRO model to climate is analyzed using a database that was compiled for the Bogotá Plateau.
The variability of an output variable is defined as the variation caused on that variable when the climate factor is varied in its estimated distribution space.
On the other hand, the sensitivity is defined here as the variation caused on the output variable, per unitary variation on the climate factor.
In a first test, the radiation intensity, air temperature and CO2 concentration are tested one-by-one within the possible range for different situations in the Bogotá Plateau.
The relative ranges of the slopes of the output variables are computed to quantify variability.
The relation of the relative range of the output variable with the relative range of the respective climate factor is calculated to quantify the sensitivity of each climate factor.
Among the results of this test, a similar degree of variability on the prediction of fruit dry weight is detected for the three climate factors, while the radiation intensity and temperature are the most sensitive climate factors.
In a second test, the climate factors are varied in a small and similar range to ensure a linear response.
A general linear model is applied to describe the slopes of each output variable as a function of the level of each climate factor.
The contribution to the total variance apportions the variance in the output to the variance in the input and is a measure of how much each climate factor contributes to the total sensitivity of the model.
This test shows that the solar radiation is the most sensitive climate factor for fruit weight, followed by temperature and CO2 concentration.
The variability of an output variable is defined as the variation caused on that variable when the climate factor is varied in its estimated distribution space.
On the other hand, the sensitivity is defined here as the variation caused on the output variable, per unitary variation on the climate factor.
In a first test, the radiation intensity, air temperature and CO2 concentration are tested one-by-one within the possible range for different situations in the Bogotá Plateau.
The relative ranges of the slopes of the output variables are computed to quantify variability.
The relation of the relative range of the output variable with the relative range of the respective climate factor is calculated to quantify the sensitivity of each climate factor.
Among the results of this test, a similar degree of variability on the prediction of fruit dry weight is detected for the three climate factors, while the radiation intensity and temperature are the most sensitive climate factors.
In a second test, the climate factors are varied in a small and similar range to ensure a linear response.
A general linear model is applied to describe the slopes of each output variable as a function of the level of each climate factor.
The contribution to the total variance apportions the variance in the output to the variance in the input and is a measure of how much each climate factor contributes to the total sensitivity of the model.
This test shows that the solar radiation is the most sensitive climate factor for fruit weight, followed by temperature and CO2 concentration.
Publication
Authors
A. Cooman, E. Schrevens
Keywords
tomato, growth model, temperature, solar radiation, CO2 concentration, sensitivity analysis
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