ASHS 2024 Conference

Incorporating data-driven technologies into agriculture offers an effective strategy for optimizing crop production, particularly in regions reliant on irrigation. This becomes increasingly crucial in the face of escalating heatwaves and droughts associated with climate change. Recent advancements in sensor technologies have spawned various methods for assessing irrigation needs. Notably, infrared thermometry stands out as a non-destructive remote sensing method capable of monitoring transpiration, holding significant potential for integration into drone- or satellite-based remote sensing models. This study focuses on the application of infrared thermometry to develop a Crop Water Stress Index (CWSI) model for European hazelnuts (Corylus avellana), a significant crop in Oregon, the leading hazelnut-producing state in the United States. Using low-cost open-source infrared thermometers and data loggers, this research aims to provide hazelnut farmers with a practical tool for monitoring crop water status, improving irrigation efficiency, and ultimately enhancing hazelnut yields. The study, spanning from June to September 2021 in a ‘Jefferson’ hazelnut (Corylus avellana) orchard, applied three distinct irrigation treatments. The calibration of the low-cost IRT sensors achieved a high accuracy (R² = 0.99), validating their utility in detecting variations in canopy temperature consistent with irrigation treatments. The developed CWSI is well-correlated with traditional plant water status indicators including stem water potential, leaf conductance, and transpiration. These results demonstrate the potential of this model to accurately reflect physiological symptoms of water stress in hazelnuts. This research not only introduces a novel CWSI model tailored to hazelnuts but also underscores the utility of low-cost technology in enhancing agricultural monitoring and decision-making.