High-resolution yield forecasting is essential for advancing precision agriculture and improving the sustainability of wheat and barley production. While most previous studies focus on field-scale predictions, pixel-level approaches are needed to capture intra-field variability a…
Modern combine harvesters can collect real-time geolocated yield data, but it is subject to errors. Various protocols have been proposed to clean this data, each with varying levels of complexity. This data is valuable for precision agriculture to implement site-specific manageme…
This study explores the use of remote sensing and machine learning (ML) for early detection of Pyricularia oryzae (rice blast) in ‘Bomba’ rice. Conducted in Spain’s Albufera Natural Park over four seasons (2021–2024), 94 fields were monitored using Sentinel-2 imagery and Topcon Y…