Crop growth and development are impacted by weather, which is a main contributor to year-to-year variability in crop yield. Farmers minimize the economic risk of yield variability through empirical knowledge of seasonal trends and their land, but this limits their ability to take advantage of favorable weather conditions. Accurate and reliable methods for in-season estimation of crop yield are important for agri-food decision-makers and farmers to maximize yield, reduce losses, and limit the environmental impact of agriculture. Crop simulation models (CSMs) coupled with seasonal climate forecasts (SCFs) are gaining interest for in-season yield estimates, especially in areas with strong climate signals like the United States, Africa, and Australia. However, SCFs are less reliable in Mediterranean environments due to the complex interplay between orography, atmospheric variability, and large-scale climatic phenomena. This proposal aims to explore the potential of coupling SCFs and CSMs for in-season crop yield estimates in Mediterranean environments to develop a tool for timely crop input resource management. This will aid in designing climate-resilient farming systems and promoting sustainable agro-ecological practices, including precision agriculture and smart irrigation, in the context of the green and digital “twin” transition.

The ideal candidate should be highly organized, capable of working independently and in a team environment, and possess interpersonal and written communication skills. Additionally, they should have a good command of English, above-average interest in academic studies, and an analytical mind. A doctoral program requires a research-oriented approach, and the candidate should enjoy exploring a subject in-depth, differentiating between primary and secondary issues, and connecting data and insights as they pursue their research. Moreover, the candidate should have basics of plant ecophysiology, and crop modelling.

The research team is involved in projects to study the impact of climate change on agro-ecosystems and develop adaptation and mitigation strategies. Their expertise is on innovative tools and approaches, such as crop models, climate projections, weather generators, GIS, and remote sensing, to monitor and predict agro-system responses to environment. The department provides the PhD student with access to databases, equipped laboratories, and technical support needed for research activities. Additionally, the student can benefit from a network of collaborations, which offers opportunities to engage with international scholars and experts to improve their knowledge and skills.