Morocco, like other Mediterranean countries, is characterized by a great diversity of indigenous varieties of vines, “Vitis vinifera ssp. vinifera”, due to the climate and the heterogeneity of the landscapes, as well as the know-how and agricultural practices adopted by traditional farmers who have contributed preserving the genetic diversity of these indigenous grape varieties. Within the framework of this study, we seek the identification and characterization of 36 indigenous grape varieties sampled in northern and southern Morocco. The samples studied were taken from traditional vineyards in these regions. For the ampelographic and ampelometric descriptions, 26 characters were used according to a list of descriptors developed by the International Organization of Vine and Wine (OIV). Thus, the ampelographic and ampelometric approaches were refined by a principal component analysis (PCA), which made it possible to group the grape varieties into five distinct groups according to their correlations to the variables linked to the bunch, the berry, and the seed. The results obtained from these different approaches confirmed the presence of great inter-grape and intra-grape variability within the samples studied. This observation encourages us to make more efforts to maintain this variability and to fight against genetic erosion and the threat of environmental changes.

The Mediterranean fig (Ficus carica L.) is a dioecious fruit tree of high nutritional and economic value in the Mediterranean basin. In northern Morocco, phenological desynchronization between male and female fig trees limits pollination and production. This study aimed to characterize the phenological stages of indigenous fig and caprifig varieties using the BBCH scale and to evaluate the predictive capacity of artificial neural networks (ANNs). This study was conducted in the Bni Ahmed region over two consecutive years (2021 and 2022) at two sites. At each site, a total of 80 female fig trees were selected. Caprifig trees were selected in accordance with their availability (37 trees/site 1; 24 trees/site 2). Local meteorological data were incorporated into the analysis to evaluate the influence of climatic conditions on phenological stages. Our results revealed significant effects of temperature, humidity, and rainfall on phenological dynamics, along with a clear inter-varietal variability and pronounced desynchronization between male and female fig trees. Early-ripening caprifig varieties showed limited pollination efficiency, whereas late-ripening varieties were better synchronized with the longer receptivity period of female fig trees. Importantly, the ANN model demonstrated exceptional predictive performance (R² up to 0.985, RMSE < 1 day), serving as a robust and practical tool for forecasting key phenological stages and minimizing potential yield losses. These findings demonstrate the value of combining phenological monitoring with AI-based modeling to improve adaptive management of fig orchards under Mediterranean climate change. This is the first study in Morocco to implement such an integrated approach to fig and caprifig trees.