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The ability of CROPGRO-Tomato model to simulate the growth characteristics of Thomas F1 tomato cultivar grown under open field conditions

Published online by Cambridge University Press:  24 November 2021

N. Muntean
Affiliation:
Department of Agroecology and Crop Production, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Czech Republic
R. A. Chawdhery
Affiliation:
Department of Agroecology and Crop Production, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Czech Republic
V. Potopová*
Affiliation:
Department of Agroecology and Crop Production, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Czech Republic
L. Tűrkott
Affiliation:
Department of Agroecology and Crop Production, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Czech Republic
*
Author for correspondence: V. Potopová, E-mail: [email protected]

Abstract

There are few studies about the ability of CROPGRO-Tomato model to simulate tomato growth under field conditions as a function of both local weather and soil conditions. The aim of this work was to calibrate the CROPGRO-Tomato model, included in the Decision Support System for Agrotechnology Transfer (DSSAT) software, for the Thomas F1 indeterminate tomato cultivar grown under open field conditions at two locations in the Czech Republic with different soil and climate conditions. Additionally, this paper focuses on modelling the impact of compound weather events (CEs) on the growth characteristics of the hybrid field tomato variety. The genotype file, including the main parameters of crop phenology and plant growth, was adapted to the Thomas F1 indeterminate tomato cultivar. The CROPGRO-Tomato model was calibrated by inputting the soil characteristics, weather data and crop management data and then by adjusting the genetic coefficients to simulate the observed Leaf Area Index (LAI) and Above Ground Biomass (AGB) from transplanting to harvest under the farmers' field conditions. The comparison of the LAI simulated by the model and measured under field conditions showed adequate representation with the root mean square error of 0.86 and 1.11 m2/m2. Although there was a good fit for LAI and AGB between the simulated and measured data during the first part of the growing season, increasing differences were found in the growing season with cool-wet and/or hot-dry thresholds of CEs.

Type
Climate Change and Agriculture Research Paper
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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