Evaluating the PhenoGlad Model as a Decision-Support Tool for Gladiolus Production in Tropical and Subtropical Environments

The expansion of floriculture into climatic transition regions requires precise tools to mitigate thermo-hydric risks. Gladiolus (Gladiolus × grandiflorus Hort.) is sensitive to temperature extremes, requiring strategic planning of planting schedules and heat stress mitigation. The objective in this study was to evaluate the PhenoGlad model for its ability to simulate developmental stages and heat stress damage in eight gladiolus cultivars across multiple environments and planting dates in the state of Mato Grosso do Sul, Midwest Brazil. Field experiments were conducted in five municipalities during the autumn, winter, and spring growing seasons. Model performance was evaluated by starting the simulation at planting or at emergence, using the statistics root mean square error (RMSE), bias index (BIAS), Willmott’s index of agreement (d), and the correlation coefficient (r). Simulations starting at emergence reduced the error in predicting the timing of developmental stages (from 5.34 to 3.16 days). For leaf development, the model was highly accurate, with an RMSE lower than one leaf for different planting dates, sites, and cultivars. Furthermore, the model accurately predicted extreme heat stress events (daily maximum temperatures > 34 °C associated with low relative humidity), which resulted in severe damage and inhibition of reproductive development in the field. In conclusion, the PhenoGlad model is a robust decision-support system and agricultural engineering tool for production scheduling and climate loss mitigation in tropical floriculture.