Research summary
Project overview
The study explores how historical environmental signals can be translated into more reliable crop-yield forecasts for agricultural planning and resource allocation.
Approach
The student combined weather records, soil information, and predictive modelling techniques to evaluate how localised data improves forecasting quality. Particular attention is paid to data quality and interpretation within a provincial context.
Impact
The project demonstrates how accessible analytics can support agricultural decision-making for producers and stakeholders operating under climate variability.