Italian processing tomato market has its dominance at global level but very few studies have been made on modelling this crop. The Cropping System Model CSMCROPGRO- Tomato model of DSSAT (Decision Support System for Agrotechnology Transfer) software, was tested using datasets collected from field experiment in Legnaro, northern Italy. The experiment was carried out in 2009 using four different transplanting dates starting from 11th March (TD1, TD2, TD3, and TD4) with ten-day intervals, four processing tomato varieties, and two agronomic practices (mulched and non-mulched soil). Plants under mulched conditions in all transplanting dates gave better performance in terms of yield, growth and water use efficiency. Under mulched conditions, NPT 63 variety had significantly better yield and water use efficiency than the other three varieties. Mulching the soil was a useful tool to decrease water consumption levels at the transplanting dates studied. Evaluating the model using non-mulched experimental datasets showed that index of agreement (d-Stat) values between observed yield and model simulation for the first planting date with the four varieties ranged between 0.69 and 0.99. The model was able to simulate growth development better for all varieties under TD2, TD3, and TD4 conditions. In order to validate simulation ability of the model for the final yield, further work should be done regarding the genotype coefficients for each variety under study.
Evaluation of the DSSAT CSM-CROPGRO-Tomato Simulation Model for Processing Tomato (Lycopersicon esculentum Mill.) Production in Northern Italy
BONA, STEFANO;SAMBO, PAOLO
2012
Abstract
Italian processing tomato market has its dominance at global level but very few studies have been made on modelling this crop. The Cropping System Model CSMCROPGRO- Tomato model of DSSAT (Decision Support System for Agrotechnology Transfer) software, was tested using datasets collected from field experiment in Legnaro, northern Italy. The experiment was carried out in 2009 using four different transplanting dates starting from 11th March (TD1, TD2, TD3, and TD4) with ten-day intervals, four processing tomato varieties, and two agronomic practices (mulched and non-mulched soil). Plants under mulched conditions in all transplanting dates gave better performance in terms of yield, growth and water use efficiency. Under mulched conditions, NPT 63 variety had significantly better yield and water use efficiency than the other three varieties. Mulching the soil was a useful tool to decrease water consumption levels at the transplanting dates studied. Evaluating the model using non-mulched experimental datasets showed that index of agreement (d-Stat) values between observed yield and model simulation for the first planting date with the four varieties ranged between 0.69 and 0.99. The model was able to simulate growth development better for all varieties under TD2, TD3, and TD4 conditions. In order to validate simulation ability of the model for the final yield, further work should be done regarding the genotype coefficients for each variety under study.
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