2025-09-18 JOURNAL OF CROP HEALTH 2025 77(卷), 5(期), (null页)
Abiotic stresses, particularly drought and salinity, impact plant germination and growth, posing serious problems in arid or semi-arid regions. This study focused on the germination of Ceratonia siliqua (Fabaceae) from six Moroccan ecotypes and its morphological, physiological and biochemical response to PEG-induced water stress and NaCl-induced salt stress. The results showed that water and salt stress significantly reduced the growth of carob seedlings in all the seeds tested, with a significant difference between ecotypes. In this regard, nineteen machine learning algorithms were used in our study to predict germination rate under water and salt stress. The results showed that the Extra Trees regressor gave the best results, with R2 values greater than 0.99 under both stress conditions. The application of advanced and critical machine learning tools created a highly predictable model that could be used for other similar experiments. The current results could be used to select carob ecotypes to plan reforestation campaigns, especially in arid and semi-arid zones, and to minimise the effects of climate change.