Modelado predictivo del rendimiento de trigo bajo estrés por inundación: enfoque basado en el algoritmo Chaid - Hoceme, Degaichia; Sara, Hezil; Touati, Bakria; HAKEM, Ahcène (Revista Mexicana de Ciencias Agrícolas, 2026)
Our research aims to examine the impact of waterflooding on durum wheat yield using a predictive modelling approach based on CHAID analysis. Randomized complete block trials were conducted in two locations, with and without waterflooding, using four durum wheat cultivars (GTA dur, Citra, Simeto, and Boussalem). The assessment of yield loss highlighted significant sensitivity of cultivars to waterflooding, with Simeto showing the highest yield loss (64.33%). The CHAID analysis enabled the identification and prioritization of factors influencing yield, revealing that waterflooding is the most important predictor (71.14%), followed by the average number of tillers per plant (16.74%), cultivar (6.32%), and plant emergence density (5.8%). Beyond merely observing the negative impact, our model allows for predicting yield losses based on various agronomic parameters. The results showed that waterflooding significantly reduces yield (16.89 q ha-1) but tillering and cultivar also play an important role in wheat response to waterflooding. The study highlights the importance of predictive modelling to anticipate yield losses and guide crop management decisions in flood-prone areas.