Discerning Spatial Patterns of Grapevine Red Blotch Virus-Infected Vines in the Absence of Visually Diagnostic Symptoms

<h3>Abstract</h3> <h3>Background and goals</h3> In plant disease epidemics, consistent visual symptoms are cues for identifying infections that, when monitored over time, reveal spatial patterns of disease. In the absence of diagnostic visual symptoms, disease may remain unnoticed, delaying necessary interventions. We studied the grapevine red blotch virus (GRBV)–<i>Vitis vinifera</i> pathosystem in three Napa Valley vineyard blocks. Due to cultivar (Sauvignon blanc) or viral co-infections, none of the blocks had visual symptoms characteristic of grapevine red blotch disease. In the absence of these visual cues, our aim was to reveal spatial patterns of viral infection by strategically selecting vines for diagnostic testing with loop-mediated isothermal amplification (LAMP). <h3>Methods and key findings</h3> Adaptive cluster sampling was used to select vines for LAMP diagnostics and explore the extent of virus aggregation. In each study year (2021 to 2023), 3 to 4% of vines in each block were randomly selected and tested. A GRBV-positive (GRBV+) result triggered the selection of neighboring vines for diagnostic testing (i.e., the condition to adapt). Cluster outlier analysis and optimized hotspot analysis identified significant aggregations of GRBV+ vines in each block. We discerned block-specific spatiotemporal variability, which we principally attribute to local inoculum pressure and secondary spread. <h3>Conclusions and significance</h3> Selecting vines for LAMP diagnostics with an adaptive sampling approach is effective for revealing spatial aggregations of GRBV+ vines in the absence of characteristic visual symptoms. This strategy can be employed to assess the risk of secondary spread and mitigate the negative effects of red blotch disease.