Resumo

MORENO-RAMOS, Eduardo et al. Computation of suboptimal temperature trajectories with the Monte Carlo method to maximize greenhouse tomato (Solanum lycopersicum L.) production. Agrociencia [online]. 2017, vol.51, n.8, pp.849-866. ISSN 2521-9766.

The objective of this study was to obtain a suboptimal temperature trajectory to maximize fresh weight (WF) and harvested fruit weight (WF) of tomato (Solanum lycopersicum L.) using the Monte Carlo method. We posed a problem of dynamic optimization based on a non-linear dynamic crop growth model under greenhouse conditions. In the solution of this problem temperature restrictions in the range of 15 °C to 30 °C, which represents the mean temperature range during the day in the city of Saltillo. Optimization is done considering prediction horizons of 15 min in an interval of 120 d after transplant (dat) and using a dynamic mathematical tomato (Solanum lycopersicum L.) growth model evaluated in a chapel-type greenhouse in Saltillo, Coahuila (25°25’36” N, 100°59’44” O). The suboptimal temperature trajectory that maximizes fruit weight (WF) was determined for the entire simulation time interval (0 to 120 dat). Moreover, the suboptimal temperature trajectory that maximized fruit weight (WF) during pre-harvest (0 to 58 dat) and harvested fruit W HF ) as of the beginning of harvest (day 59), described by the model until the end of simulation (120 dat). The results obtained show that the suboptimal temperature trajectory from day 59, which marks the beginning of harvest, was established around 15 °C to maximize W F and around 30 °C for maximization of W F and W HF . It could also be observed that the suboptimal temperature trajectory for both cases shows periods that emulate day and night, 15 °C to 30 °C, before day 59. The results obtained permit us to propose conditions for either maximizing fruit on the plant or harvested fruit, and the resulting temperature trajectories can be used to obtain a softened curve with more stable cycles that can be put into practice.

Palavras-chave : model of tomato growth dynamics; production maximization; Monte Carlo method.

        · resumo em Espanhol     · texto em Espanhol | Inglês     · Inglês ( pdf ) | Espanhol ( pdf )