Determining the Timing of Spore Release by Botryosphaeriaceae Species in Oregon Vineyards.

Botryosphaeria dieback, caused by a group of pathogens in the Botryosphaeriaceae family, is one of the most common grapevine trunk disease complexes (GTDs) found in Oregon vineyards. To understand the period of spores released by spp. in Oregon vineyards, four Burkard 7-day recording volumetric spore traps were placed in vineyard blocks in northern and southern Oregon. Each trap was placed near a younger (<10 years) and older (>30 years) block in both regions. Spore traps were deployed at the beginning of December 2019 and continued until March 2021. Between these timeframes, 475 and 477 days of samples were collected from each spore trap in northern and southern Oregon, respectively. DNA extraction was performed from individual day samples and followed by qPCR analysis of spores trapped in each tape sample. Weather data such as temperature, precipitation, relative humidity (RH), and wind speed were collected from nearby weather stations. Association between these data and number of spores detected were analyzed using Pearson correlation analysis. In northern Oregon, the detection occurred between December and February, and the first spore detection occurred when cumulative growing degree day (GDD) totaled to 4,357 and 4,351 units (T = 0°C, biofix date = January 1) during the first and second seasons, respectively. Similarly, in southern Oregon, the detection occurred between November and January, and the first spore detection occurred when cumulative GDD was 4,405 units during the second season. Hours of continuous RH >86% was significantly associated with number of spores released ( 0.026; = 042). During the spore detected dates, the RH was >86% for at least 19 consecutive hours. These findings provide an important implication to manage Botryosphaeria dieback by protecting pruning wounds during the most-spore-released periods. Furthermore, the knowledge of weather variables and their possible association with spore detection provides important information towards developing predictive models in future studies.