The GesCoN model was evaluated for its capability to simulate growth, nitrogen uptake, and productivity of open field tomato grown under different environmental and cultural conditions. Five datasets collected from experimental trials carried out in Foggia (IT) were used for calibration and 13 datasets collected from trials conducted in Foggia, Perugia (IT), and Florida (USA) were used for validation. The goodness of fitting was performed by comparing the observed and simulated shoot dry weight (SDW) and N crop uptake during crop seasons, total dry weight (TDW), N uptake and fresh yield (TFY). In SDW model calibration, the relative RMSE values fell within the good 10–15% range, percent BIAS (PBIAS) ranged between −11.5 and 7.4%. The Nash-Sutcliffe efficiency (NSE) was very close to the optimal value 1. In the N uptake calibration RRMSE and PBIAS were very low (7%, and −1.78, respectively) and NSE close to 1. The validation of SDW (RRMSE = 16.7%; NSE = 0.96) and N uptake (RRMSE = 16.8%; NSE = 0.96) showed the good accuracy of GesCoN. A model under- or overestimation of the SDW and N uptake occurred when higher or a lower N rates and/or a more or less efficient system were used compared to the calibration trial. The in-season adjustment, using the “SDWcheck” procedure, greatly improved model simulations both in the calibration and in the validation phases. The TFY prediction was quite good except in Florida, where a large overestimation (+16%) was linked to a different harvest index (0.53) compared to the cultivars used for model calibration and validation in Italian areas. The soil water content at the 10–30 cm depth appears to be well-simulated by the software, and the GesCoN proved to be able to adaptively control potential yield and DW accumulation under limited N soil availability scenarios and consequently to modify fertilizer application. The DSSwell simulate SDW accumulation and N uptake of different tomato genotypes grown under Mediterranean and subtropical conditions.
All Science Journal Classification (ASJC) codes
- Plant Science