The aim of this work was to calibrate CROPGRO-Tomato model, included in the Decision Support System for Agrotechnology Transfer (DSSAT) software, for a cherry tomato genotype grown in a photovoltaic greenhouse in southern Europe (39°19'59"N; 8°59'19"E). The experiment was carried out in Decimomannu, Sardinia, in an East-West oriented pitched-roof greenhouse with two spans (50×9.6 m each) covering an area of 960 m2. Silicon photovoltaic panels were used to completely replace the south-oriented roof of each span, resulting in a 50% roof cover ratio. Tomato was grown hydroponically with a plant density of 2.3 plants m-2. An autumnwinter tomato crop cycle was carried out from August 2011 to January 2012. Microclimatic conditions were monitored for the whole lifespan of the experiment (e.g., internal global and PAR radiation and greenhouse internal temperature). Phenology was monitored at weekly interval. Leaf area, aboveground biomass, and fresh fruit production was determined at fifteen day interval. CROPGRO-Tomato model was calibrated over the uncovered roof data and it was evaluated over the covered roof data. The genotype file (cultivar), including the main parameters of crop phenology and plant growth, was adapted to the cherry tomato cultivar 'Shiren'. The first flowering date showed a good agreement between simulated and observed data. The model fitted well the observed leaf area index data with an index of agreement (D-Index) of 0.87 and an average root mean square error (RMSE) of 0.53. Good agreement was observed between the measured and simulated plant development parameters as biomass and fresh weight yield. Overall, the CROPGRO-Tomato model proved to be suitable for predicting tomato growth and yields inside PV greenhouses and under different light intensity conditions. However, model validation is also necessary to show how the model works under a spring-summer cycle and with supplementary lighting system.

Modeling tomato growth and production in a photovoltaic greenhouse in southern Italy / Deligios, P. A.; Cossu, M.; Murgia, L.; Sirigu, A.; Urracci, G.; Pazzona, A.; Pala, T.; Ledda, L.. - In: ACTA HORTICULTURAE. - ISSN 0567-7572. - 1182:(2017), pp. 203-210. (Intervento presentato al convegno Proc. V International Symposium on Models for Plant Growth, Environment Control and Farming Management in Protected Cultivation (HortiModel2016)) [10.17660/ActaHortic.2017.1182.24].

Modeling tomato growth and production in a photovoltaic greenhouse in southern Italy

Deligios, P. A.;Pazzona, A.;Ledda, L.
2017-01-01

Abstract

The aim of this work was to calibrate CROPGRO-Tomato model, included in the Decision Support System for Agrotechnology Transfer (DSSAT) software, for a cherry tomato genotype grown in a photovoltaic greenhouse in southern Europe (39°19'59"N; 8°59'19"E). The experiment was carried out in Decimomannu, Sardinia, in an East-West oriented pitched-roof greenhouse with two spans (50×9.6 m each) covering an area of 960 m2. Silicon photovoltaic panels were used to completely replace the south-oriented roof of each span, resulting in a 50% roof cover ratio. Tomato was grown hydroponically with a plant density of 2.3 plants m-2. An autumnwinter tomato crop cycle was carried out from August 2011 to January 2012. Microclimatic conditions were monitored for the whole lifespan of the experiment (e.g., internal global and PAR radiation and greenhouse internal temperature). Phenology was monitored at weekly interval. Leaf area, aboveground biomass, and fresh fruit production was determined at fifteen day interval. CROPGRO-Tomato model was calibrated over the uncovered roof data and it was evaluated over the covered roof data. The genotype file (cultivar), including the main parameters of crop phenology and plant growth, was adapted to the cherry tomato cultivar 'Shiren'. The first flowering date showed a good agreement between simulated and observed data. The model fitted well the observed leaf area index data with an index of agreement (D-Index) of 0.87 and an average root mean square error (RMSE) of 0.53. Good agreement was observed between the measured and simulated plant development parameters as biomass and fresh weight yield. Overall, the CROPGRO-Tomato model proved to be suitable for predicting tomato growth and yields inside PV greenhouses and under different light intensity conditions. However, model validation is also necessary to show how the model works under a spring-summer cycle and with supplementary lighting system.
2017
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/286419
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