Utilizing spring dead spot mapping to assess precision management strategies, topographical epidemiology, economic opportunities

Abstract

Spring dead spot (SDS), a monocyclic, soil-borne disease caused by Ophiosphaerella spp., affects the rhizomes and stolons of bermudagrass (Cynodon dactylon L. Pers), and is particularly severe in regions with extended dormancy, such as the transition zone. This research evaluates three aspects of SDS management: environmental influences, disease mapping, and the economic feasibility of precision treatments. To measure the relationship between local topography and SDS localization, UAV imagery was collected from 16 golf course fairways across three locations in Virginia and SDS coordinates were recorded. Using state lidar data, environmental factors such as slope, aspect, annual sunlight, and landform type were quantified. Generalized linear mixed-effects models revealed increased odds of SDS occurrence on north-facing slopes and landforms such as peaks and shoulders (p ≤ 0.001), while pits, valleys, and south-facing slopes were associated with decreased odds (p < 0.001). However, topographic features accounted for only 4.2% of the variance in disease distribution, indicating that other factors also play significant roles in SDS development. In parallel, precision treatment strategies (spot and zonal applications) were evaluated in a randomized complete-block design. Compared to full-coverage and untreated controls, precision treatments achieved similar disease control (p ≤ 0.001) while reducing the treated area by 48–52% (p ≤ 0.001), demonstrating a previously described Python script for spring dead spot detections efficacy in generating actionable disease maps. Finally, the economic viability of precision SDS management was assessed at the Independence Golf Club in Midlothian, VA. Cost analyses comparing precision and conventional treatments showed that a GNSS-equipped sprayer, used for precision applications, provided cost savings over a 10-year horizon when applying isofetamid or a combination product of pydiflumetofen + azoxystrobin + propiconazole. Conversely, this strategy was not cost-effective with annual applications of tebuconazole due to its low cost per application. These findings suggest that adopting precision treatment methods with appropriate fungicides can reduce costs and improve sustainability in SDS management. Together, these studies highlight the potential for integrating disease mapping, environmental analysis, and economic modeling to optimize SDS management strategies in turfgrass systems.