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Smoke taint Symposium
Assessment and Management of Risk Associated with Wildfire Smoke Exposure of Grapes in the Vineyard
This symposium will provide an overview of a systems approach to vineyard monitoring and comprehensive update on research into all aspects of the impact of wildfire smoke exposure to wine grapes by leading researchers in air quality modeling, viticulture and physiology, enology and sensory evaluation. Topics will include an evaluation of barrier sprays and smoke composition according to fuel source, evaluation of modeling frameworks to simulate atmospheric smoke-taint conditions in the western US, smoke emissions, atmospheric aging, and deposition, dose-response smoking trials and vineyard mitigation practices; sensing potential to detect smoke impacts on vine function and berry composition; decision support tools for vineyards threatened by wildfire smoke, scaling up small-scale fermentations and consumer preference of smoke impacted wines. The symposium promises to reveal impactful research findings and provide opportunities for discussion with researchers.
Symposium Chair: Elizabeth Tomasino, Oregon State University, Corvallis
Program:
Program is subject to change.
| 9:00 am – 9:15 am | A Systems Approach Vineyard Monitoring Elizabeth Tomasino, Oregon State University, Corvallis | To be announced |
| 9:15 am – 9:45 am | Smoke Emissions, Atmospheric Aging, and Deposition in California Mike Kleeman, University of California, Davis | To be announced |
| 9:45 am – 10:15 am | A WRF-Chem-HYSPLIT Modeling Framework Simulating Atmospheric Smoke-Taint Conditions in the Western US Ana Carla Fernandez Valdes, Washington State University, Pullman | To be announced |
| 10:15 am – 10:45 am | Break | |
| 10:45 am – 11:15 am | Dose-Response Smoking Trials and Vineyard Mitigation Practices Alec Levin, Oregon State University, Central Point | To be announced |
| 11:15 am – 11:45 am | Managing Smoke in the Vineyard: Evaluation of Fuel Sources and Barrier Sprays Tom Collins, Washington State University, Tri-Cities | To be announced |
| 11:45 am – 12:15 pm | Proximate Sensing Potential for Detecting Smoke Impacts on Vine Function and Berry Chemistry Beth Forrestel, University of California, Davis | To be announced |
| 12:15 pm – 1:15 pm | Box Lunch Included | To be announced |
| 1:15 pm – 1:45 pm | Decision Support Tools for Vineyards Threatened by Wildfire Smoke Amod Sugiyama, Oregon State University, Corvallis | To be announced |
| 1:45 pm – 2:15 pm | Smoke Perception Thresholds and Understanding the Consumer Response to Smoke Taint Jenna Fryer, Oregon State University, Corvallis | To be announced |
| 2:15 pm – 2:30 pm | Break | |
| 2:30 pm – 3:00 pm | Relating Grape and Small Fermentation Smoke Data to Production Scale Outcome Tom Collins, Washington State University, Tri-Cities Elizabeth Tomasino, Oregon State University, Corvallis | To be announced |
| 3:30 pm – 4:00 pm | Panel Discussion Q/A Tom Collins, Washington State University, Tri-Cities Mike Kleeman, University of California, Davis Alec Levin, Oregon State University, Central Point Elizabeth Tomasino, Oregon State University, Corvallis | To be announced |
| 4:00 pm – 5:00 pm | Poster Session and Reception | To be announced |
Eve Laroche-Pinel | Kaylah Vasquez | Madison Flasco | Monica Cooper | Marc Fuchs | Luca Brillante
Scalable Vine-Level Assessment of Grapevine Red Blotch Virus Infections from Aerial Hyperspectral Images
Eve Laroche-Pinel, Kaylah Vasquez, Madison Flasco, Monica Cooper, Marc Fuchs, and Luca Brillante*
*Department of Viticulture and Enology, California State University Fresno, 2360 E Barstow Ave, Fresno, CA, 93740 (lucabrillante@csufresno.edu)
Grapevine red blotch virus (GRBV) poses a significant threat to viticulture, leading to substantial economic losses because infected vines must be removed to prevent further spread. In this study conducted in October 2021 within a 3-ha Cabernet franc vineyard, we employed hyperspectral remote sensing with a drone-mounted camera to enhance efficiency of red blotch virus detection. The hyperspectral camera captured images in 25 spectral bands within the visible to near-infrared (VIS-NIR) domains (520 to 820 nm).
A total of 264 vines were selected randomly and sampled for PCR analysis to confirm the red blotch virus’s presence. Concurrently, images were acquired using the drone and processed through segmentation techniques to extract the vine canopy signal of the selected vines. Additionally, field experts visually inspected the vines to identify infected plants. The accuracies of both the hyperspectral images and the expert assessments were compared to the PCR results.
Six machine-learning models were trained using spectral bands as predictors. Additionally, a radiative transfer model (PROSPECT) was applied in reverse mode to predict leaf pigment concentration (anthocyanins, carotenoids, and chlorophyll) based on vine reflectance, and the output was explored as an alternative set of predictors for detecting vine infections. The overall accuracy reached 87.0% using raw spectral images and 81.4% using the PROSPECT output. The highest feature importance was attributed to the estimated anthocyanin content in leaves.
This preliminary study marks a crucial advancement toward developing an automatic system for the plant-level detection of red blotch-infected vines. Integrating hyperspectral remote sensing, PCR analysis, and machine learning techniques demonstrates promising potential for more efficient and accurate identification and management of red blotch viruses in vineyards.
Funding Support: CDFA SCBGP, CSU ARI, F3, CDFA-PDGWSS
This work is supported by the Specialty Crop Research Initiative, project award no. 2021-5118-35862, from the U.S. Department of Agriculture’s National Institute of Food and Agriculture. Any opinions, findings, conclusions, or recommendations expressed are those of the author(s) and should not be construed to represent any official USDA or U.S. Government determination or policy.
