Temporal and Spatial Dynamics of the Aerial Fungal Microbiome in the Grapevine Canopy
Year: 2026
Type: article
Abstract: Air sampling is used to monitor aerially dispersed grape fungal pathogens. Capturing the airborne fungal community (aeromycobiome) is a promising approach for monitoring fungi that may impact grapevine health. However, the optimal sampler type, placement, and weather conditions for aerial community-based surveillance in vineyards remain ill-defined. In this study, air and rainwater samplers captured the aeromycobiome at three canopy heights (0.61m, 1.37m, and 1.83m) using ITS1 amplicon-based sequencing (n= 117 samples). Various meteorological factors were identified as influencing community composition from July to September 2022 (nine weeks) within a Vitis interspecific hybrid ‘Vignoles’ vineyard in Michigan. Air samplers recovered 464 genera, and rainwater samplers recovered 598 genera. Taxa of interest included Botrytis spp. and Cladosporium spp. in the air samplers and Aureobasidium spp. and Hanseniaspora spp. in the rainwater samplers. PERMANOVA results indicated significant differences in community composition between air and rainwater samplers ( R 2 = 0.27, p = 0.001) and by week in both air ( R 2 = 0.70, p = 0.001) and rainwater samples ( R 2 = 0.28, p = 0.001). Height had no effect on air community composition ( R 2 = 0.036, p = 0.272) but impacted rainwater community composition ( R 2 = 0.057, p = 0.017). Height’s minimal effect suggests that the aerial fungi present within the canopy remain consistent. Minimum relative humidity correlated with the shifts in aerial community composition. These findings provide baseline data on sampler choice, sampler height, and weather conditions that influence fungal dynamics, potentially aiding in the detection of pathogens and yeasts of viticultural interest.
Source: PhytoFrontiers™
Institutions: Pennsylvania State University, Michigan State University
Language: English
Subfield: Plant Science
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W7225591736
