Assessing Winter Kill Severity in Wheat Using Drone-Captured Plant Health Data
Research Poster Health & Life Sciences 2025 Graduate ExhibitionPresentation by NAVDEEP KAUR
Exhibition Number 196
Abstract
Winter kill in wheat, triggered by extreme cold and thaw cycles, threatens yield stability and grower profitability. Understanding its extent and severity is critical for informed management decisions, optimized replanting strategies, and risk mitigation. This study assessed winter kill severity in a wheat field, developed a spatial classification method using drone imagery and the Normalized Difference Vegetation Index (NDVI), a plant heath indicator, and provided growers with insights for decision-making. Drone images were collected in early spring to capture post-winter crop conditions. Simultaneously, a field survey was conducted with a farmer at 25 georeferenced locations. At each point, the farmer visually assessed crop condition within a 2-meter radius, categorizing it as "acceptable," "borderline," or "not acceptable" based on plant health and survival. NDVI was then calculated for these areas, and its values were grouped into the three farmer-defined categories, establishing NDVI thresholds for each condition. Using these thresholds, the entire field was classified into three winter kill severity zones. Results revealed spatially variable damage, with lower NDVI values in areas of severe winter kill, often corresponding to topographic lows or waterlogged soils. Higher NDVI values indicate healthier stands in well-drained areas. This suggests that environmental factors such as drainage and soil structure influence winter survival. NDVI-based classification enables farmers to identify areas requiring intervention, supporting targeted management strategies. This approach enhances decision-making, ultimately promoting sustainable wheat production in regions prone to winter stress.
Importance
Winter kill can severely impact wheat production, reducing yields and farmer profits. This study helps farmers better understand winter damage in their fields using drone images and a plant health measure called NDVI. By comparing drone data with a farmer’s field observations, researchers developed a way to map areas of high and low winter survival. The findings showed that poor drainage and low-lying areas often had the most damage, while well-drained areas had healthier plants. This method allows farmers to quickly identify problem areas and take action, such as replanting or improving drainage. By using drone technology, farmers can make more informed decisions, reduce losses, and improve wheat production in regions prone to harsh winter conditions.