Leveraging Berry Physiology to Mitigate Late-Season Dehydration. AVF Project #2025-2739.

AVF Proj. ID: 20252739 / /Cat.: ,
Primary Investigator(s): Dr. Megan Bartlett, Associate Professor, Department of Viticulture & Enology, University of California, Davis, CA 95616, Tel: 530-752-2048, Email: mkbartlett@ucdavis.eduby

Summary of Progress:

Hot, dry conditions can exacerbate late-season berry dehydration, reducing yield and altering berry sensory properties.  Late-season dehydration occurs when the berries undergo cell death, and the water released from the ruptured cells is lost to transpiration or backflow to the canopy.  Climate change is expected to worsen these issues, so the goal of this project is to identify management strategies to reduce late-season dehydration.  In Years 1 and 2, we tested whether short (2-week) pulses of increased irrigation before or at the expected onset of cell death would reduce water stress-induced oxidative damage and delay or reduce the rate of cell death, reducing shrivel at harvest.  We found that the irrigation pulse at onset significantly reduced the rate of cell death and shrivel at harvest, providing irrigation guidelines to reduce late-season dehydration.  In Years 3 and 4 (the current project year), we tested (1) whether evaporative cooling (misting) systems would reduce cell death and shrivel with less water than the irrigation pulse and (2) used a rootstock/Cabernet Sauvignon clonal trial to screen for plant material with less susceptibility to these processes.  Last year, we did not find any cell death in >130 berries, and despite extensive troubleshooting, we were unable to find a methodological issue.  However, this year, using the same microscope, reagents, protocols, and imaging settings, we found typical cell death.  Misting systems significantly reduced cluster temperatures and increased gas exchange, water potentials, berry cell vitality, berry and cluster weights, and yield (p<0.05).  However, the systems also used more water than the irrigation pulses.  By harvest, berry weight declined by 5 – 15% across all 21 clone/rootstock combinations.  However, the magnitude and rate of berry shrinkage were not significantly different across combinations, indicating that we did not find plant material that was resistant to late-season dehydration.  Rootstock effects on yield and water potential were consistent across clones, and clonal differences in the catechin/tannin index were consistent across rootstocks, while all other traits were dependent on the scion/rootstock combination.  Clone #35/420A was especially high-performing, with fruit in an appropriate range for pH and TA and high tannins, anthocyanins, and polymeric anthocyanins.

Climate change is expected to exacerbate late-season dehydration (LSD) in the berries, which reduces yield and, in severe cases, berry and wine quality.  This project has successfully identified two management strategies to mitigate LSD.  In the first phase, we showed that a short pulse of supplemental irrigation, timed at the expected onset of cell death in the berries (i.e., 90 – 105 days after anthesis), significantly reduced the cell death rate and, consequently, the amount of berry shriveling at harvest.  In the second phase, we showed that automated misting systems targeting the fruit zone also significantly reduced berry cell death, and increased yield by 35%, compared to unmisted controls.  Further, our screening of 21 rootstock/Cabernet Sauvignon clone combinations showed no significant differences in the magnitude or rate of LSD, indicating that shifting to resistant plant material is not currently a viable solution.  Misting consumed more water than the supplemental irrigation pulse, but the benefits for yield could make this a valuable option for high-production viticulture.  Together, these findings provide growers with two potential management interventions to mitigate yield losses from LSD under hotter, drier growing conditions.

Integrating a Novel Method to Estimate Grapevine Water Use and Stress into Multi-Tiered Precision Irrigation Management. AVF Project #2025-2796.

AVF Proj. ID: 20252796 / /Cat.: ,
Primary Investigator(s): Dr. Andrew McElrone, Research Plant Physiologist and Adjunct Professor, USDA-ARS & Department of Viticulture and Enology, University of California, Davis. Email: andrew.mcelrone@usda.gov Dr. Nicolas Bambach, Project Scientist and Biometeorologist, Department of Viticulture and Enology, University of California, Davis. Email: nbambach@ucdavis.eduby

Summary of Progress:

We continued our efforts on this project to test and refine the use of IRT wavelet method as a method to track vine water use and stress across a variety of field sites and vineyard settings.  In year 2, we repeated a second year of study in experimental vineyard located in Davis with variable rate irrigation system, where we conducted a drought experiment with heavily instrumented and measured vines.  Physiological measurements were also taken on days when a drone was flown to capture aerial thermal and spectral imagery for comparison with the ground-based measures.  Data from these image collection dates is still being processed and should be completed before the beginning of the 2026 growing season.  Measurements were made in upper and lower leaves within the canopy as we will be comparing the effectiveness of the TSEB and 3SEB ET models to partition canopy water use vs middle water use and is being compared against the various viewing angles of the IRTs.  We also installed a new wavelet IRT station at the Oakville South Station.  This station includes additional sensors to test what is needed for effective pairing of the ground-based remote sensing approaches.  Working with a computer science technician the team developed a web-based dashboard that will be used for the ingestion of wavelet IRT, OpenET and other relevant irrigation management.  It allows the user to enter data on irrigation amounts and timing.  We will test and refine the dashboard for operational irrigation management in 2026 (see images below).  We are still analyzing data from the previous year of effort and will submit multiple manuscripts in the next year related to this work.

IRT wavelet analysis was performed on various sites during the 2025 field season.  An array of 10 IRT sensors was installed on vines in an experimental vineyard in Davis where a variable rate irrigation system was used to deliver varying amounts of water.  Measurements at this site were paired with regular diurnal physiological measurements and other instrumentation for comparison.  An additional station was established in UC Davis Oakville Station on the south property in a Cabernet Sauvignon commercial production block.  We continue to maintain eddy covariance flux towers at GRAPEX sites in Barelli, Sierra Loma and Ripperdan ranches, at sites where 1 Hz IRT data is available it is being compared against eddy covariance flux tower measurements.  We will install additional IRTs at these sites in the summer of 2026 with various sensor orientation within the flux footprint to determine the spatial range of inference for each IRT sensor.  This will also include sensors pointing solely at the vine canopy as well as the soil/cover mix in the middles to be able to run the TSEB model locally from this tower data.  This output will be compared against the wavelet method, OpenET and flux data at each site.

Assessment of the Variability in Soil Health Indicators and Incorporating Healthy Soil Management Practices in Napa Valley, Paso Robles, and Lodi regions. AVF Project #2022-2722.

AVF Proj. ID: 20222722 / /Cat.: ,
Primary Investigator(s): Dr. Cristina Lazcano, Assistant Professor, Department of Land, Air and Water Resources, University of California Davis. (530) 754 176, clazcano@ucdavis.eduby

Summary of Final Report:

Adoption of sustainable soil management practices is becoming common in winegrape production in response to an increased awareness of the value of soil health to maintain environmental quality.  Soil health is characterized by the functions it provides to the vineyard (i.e water retention, nutrient supply, carbon sequestration etc.) and is often impacted by vineyard soil management practices (i.e., compost application, no till, cover crops).  However, the magnitude of the effect of these practices on soil organic matter and other soil health indicators is difficult to predict.  A major impediment for the diagnosis and establishment of target values of soil health in vineyards is the large diversity of soils and physiographic conditions across and within growing regions.

During the 2020-2021 funding cycle, we conducted semi-structured interviews to growers paired with ongoing sampling efforts across 32 vineyards in Napa Valley to (i) establish a baseline of soil health indicators within the various Napa Valley soil types; and (ii) examine grower perception and comprehension of these indicators and the desired qualities of a healthy soil relative to production goals.  This was replicated in the Paso Robles AVA during the 2021-2022 funding cycle, and in Lodi during the 2022-2023 funding cycle followed by a no-cost extension during the 2023-2024 cycle to finalize research activities across the three regions.

The activities in this project were carried out through a collaboration between researchers, extension specialists and grower groups including the Napa Valley Grapegrowers Association, Paso Robles Wine Country Alliance, Independent Grape Growers Paso Robles Area, and Upper Salinas-Las Tablas Resource Conservation District.  The data gathered so far for the three regions shows that most grape growers consider soil health to be important for wine grape production due to perceived benefits to reduce soil erosion, improve vine health and grape quality.  Through grower input, researchers were able to extract the soil properties that are perceived as the most important for these beneficial outcomes, namely a balanced soil structure and nutrient supply.  Finally, data collected in the interviews revealed a strong grower knowledge of how the physical and chemical aspects of soil health are related to beneficial agronomic outcomes, as well as strong grower interest in understanding the role of soil organic matter and the soil biome on these outcomes.

Results from the soil health assessment show no significant differences for most chemical, physical, and biological properties such as soil pH or inorganic N between soil categorized as ‘ideal’ and ‘challenging’ by growers.  However, a strong negative correlation was observed between active soil carbon, bulk density, and surface hardness, indicating that soils with more C, had lower compaction issues.  Results of this research were presented 33 times in three years including scientific conferences and outreach events.  Furthermore, we have published one paper and one more is under development to be submitted for publication in October 2024.  Finally, together with the Napa Valley Grape Grower Association, we have developed a handbook of soil health in Napa to be published at the end of 2024.

Integrating a Novel Method to Estimate Grapevine Water Use & Stress into Multi-Tiered Precision Irrigation Management. AVF Project #2023-2796.

AVF Proj. ID: 20232796 / /Cat.: ,
Primary Investigator(s): Dr. Andrew J. McElrone- Research Plant Physiologist and Adjunct Professor, USDA-ARS & Department of Viticulture and Enology, University of California, Davis, CA.by

Proposal Objective(s) and Experiments Conducted – Summary of Progress:

  • We will evaluate our new method in commercial and experimental vineyards, where research grade flux tower systems are already in place, and integrate output with remotely sensed approaches. We will leverage existing datasets and expand installations to new vineyards to determine appropriate sensor orientation to best represent varying canopy types and row orientation.
  • We will initiate the development of a web-based platform displaying sensor output to grower cooperators in near real-time.
  • We will initiate the development of instructional materials for a citizen-scientist model showing users how to implement this new method independently.

Our efforts during the 2024 field season focused on Objective #1 using a combination of existing datasets, continuation of data collection in various GRAPEX sites, and installation of new sensors in an experimental vineyard in Davis.  In 2025, we will also utilize large, mature vines growing in harvest collecting bins that are sitting on load cells.  This system will allow us to track water use continuously and compare ET measured with the IRT wavelet sensor.  This arrangement will also allow us to modify the orientation of the vines relative to incoming solar radiation, and to target a sustained deficit irrigation that treatment that relies on the IRT sensor output to trigger irrigation of appropriate amounts to match water use.  Data analysis and interpretation of results is ongoing, and we expect much progress in the next two months.  We can provide further updates to the review panel as we proceed.  We will start to tackle Objectives 2&3 in the coming year of the project.

We originally submitted this proposal in January 2023 with the intent of conducting the first year of field work that summer.  We had a post doc lined up, but he bailed on us just before the start of the field season.  Around the same time, PI McElrone was dealing with a significant family health issue but is elated to report that everyone is doing well now.  Given delays in initiating the proposed work and need to recruit a new post doc, we decided it was best to focus efforts on the 2024 growing season.  Therefore, we did not request a second year of funding in January 2024 because we had yet to spend the funds.  We successfully recruited a post doc, Dr.  Weiyun Hua, to work with us starting in the Spring 2024.  She unexpectedly left for another position at the end of the field season in early Fall 2024.  Luckily, we identified another excellent candidate from the post doc pool, and Dr.  Saroj Dash was able to start one month after Dr.  Hua’s departure.  He dove immediately into our existing datasets and is applying his skills with both ground-based thermal sensing systems and remotely sensed data.  He is an excellent fit for the project and very enthused to continue this work.  In his previous research, he used infrared data from a series of flux towers within a water basin to spatially map the crop water stress index for agricultural systems in India.  He is now working to do the same across our various vineyard sites and links the IRT wavelet sensible heat flux output with the Two Source Energy Balance approaches for modelling ET.  He has quickly become proficient in running the IRT wavelet analysis and comparing output with other ground-based data from our experimental flux towers.  He has also begun the analysis of data collected from the sensor orientation experiment described below.  We also conducted an intensive experiment with both Chardonnay and Cabernet Sauvignon in an experimental vineyard with variable rate irrigation system, where we conducted a drought experiment with heavily instrumented and measured vines.  Below we describe experiments conducted in the summer of 2024 to apply the wavelet method in an experimental vineyard subjected to deficit irrigation and to refine the optimal viewing angle relative to canopy orientation.

Research Success Statements:

We aim to develop a user-friendly tool with off-the-shelf components for growers to use in their fields and integrate into our analysis platform.  We think it has the potential to replace existing traditional measurements of plant stress and provide a more rugged version of an ET sensor that can be integrated with remote sensing tools to measure both vine and cover crop water use simultaneously.  These ground-based measures will provide an improved confidence in data generated by satellite products like those from the OpenET platform.

Variable Rate Irrigation Scheduling Based on High-Resolution Short-Wave Infrared Sensing and Internet-of-Things. AVF Project #2023-2718.

AVF Proj. ID: 20232718 / /Cat.: ,
Primary Investigator(s): Dr. Luca Brillante, Associate Professor, Department of Viticulture and Enology, California State University Fresno, 2360, E Barstow Ave, Fresno, CA, 93740. lucabrillante@csufresno.edu.by

Summary of Final Report:

Amidst escalating drought conditions in the San Joaquin Valley, grapevine growers face an urgent need for effective water management strategies.  This research contributes valuable insights into sustainable viticulture practices, particularly for optimizing water use in vineyards while addressing the physiological responses of grapevines to varying irrigation intensities and timings.

The study was conducted in a commercial Vitis vinifera L.  cv.  Cabernet-Sauvignon vineyard in California’s West San Joaquin Valley.  The vineyard was equipped with a variable rate automated irrigation system administering 12 distinct irrigation regimes across four randomized replicates, creating 48 experimental zones.  Over the 2022 and 2023 seasons, irrigation schedules included sustained deficit irrigation (SDI) at 40%, 60%, 80%, and 100% of ETc and regulated deficit irrigation (RDI) applied at varying intensities pre- and post-veraison (e.g., 100/40, 80/60, 60/100).  Water use was meticulously tracked with flow meters to ensure precision.

Remote sensing technology was integrated into the study to assess plant water status and model physiological responses.  A hyperspectral NIR/SWIR camera (900–1700 nm) mounted on a UAV captured spectral data throughout the growing season, focusing on pure grapevine pixels.  The sensor’s high water absorption in the NIR/SWIR range facilitated the estimation of stem water potential (Ψstem), a key indicator of water stress, using machine learning models.  Hyperspectral images were processed into bottom-of-atmosphere reflectance via standard ground panels and the Quick Atmospheric Correction Method (QUAC).  The best regression models achieved an R² of 0.54 and RMSE of 0.11 MPa, while the top classification model reached 74% accuracy, demonstrating the potential of remote sensing for spatial and temporal water stress mapping.

Field measurements included Ψstem and gas exchange from June to harvest, grape composition from veraison to harvest, and yield components at harvest.  Results revealed that while 40% SDI significantly underperformed compared to 100% ETc, some RDI strategies and SDI regimes with moderate reductions in ETc delivered comparable or superior outcomes while conserving water.

This research advances irrigation management by integrating remote sensing and field measurements, offering a nuanced understanding of how water regimes impact plant water status, gas exchange, berry composition, and yield.  These findings provide practical, data-driven solutions for grapevine growers navigating water scarcity, enabling more resilient and sustainable vineyard practices in the face of climate change.

On-the-Go Mapping of Grape Composition in the Field Through Hyperspectral Machine Vision. AVF Project #2022-2607.

AVF Proj. ID: 20222607 / /Cat.: , ,
Primary Investigator(s): Dr. Luca Brillante, Associate Professor, Department of Viticulture and Enology, California State University Fresno, 2360, E Barstow Ave, Fresno, CA, 93740. lucabrillante@csufresno.edu.by

Summary of Final Report:

This project aimed to develop a non-invasive, real-time method for assessing grape composition in vineyards using hyperspectral imaging technology. This innovative approach helps viticulturists monitor grape quality and make informed decisions about vineyard management and harvesting.

After preliminary work in a varietal collection in the Fresno State vineyard in 2021, we conducted a final study in a Merlot vineyard in Madera, California, in 2022. In this study 160 vines were sampled multiple times throughout the growing season. The UTV used for this research was customized to elevate the vine canopy and expose the grapes, allowing the hyperspectral cameras to capture detailed images. These cameras operated in the visible to shortwave infrared (VIS/SWIR) spectrum, covering wavelengths from 900 to 1700 nm. The cameras were equipped with GPS systems for precise georeferencing and halogen lights for night imaging.

The captured images were processed using a specific vegetation index thresholding method to segment the grape signals from the background and vine leaves. This segmentation was crucial for isolating the spectral data related to the grapes. The study collected approximately 650 grape samples, which were analyzed in the laboratory to determine their chemical composition, including Brix (sugar content), pH, titrable acidity (TA), and anthocyanin profiles.

We employed four machine learning models—Extra Tree Regressor (ETR), Random Forest (RF), Gradient Boosting (GB), and Extreme Gradient Boosting (XGBoost)—to predict grape composition from the spectral data. The models’ performance was evaluated using 10-fold cross- validation, which helps ensure robustness and accuracy. Among the models, the Extra Tree Regressor performed the best, with R² values of 0.91 for Brix, 0.90 for pH, 0.85 for TA, and 0.91 for anthocyanins. These high R² values indicate that the models could accurately predict the grape composition based on the spectral data.

Feature importance analysis using recursive feature elimination identified the most informative spectral bands for predicting grape composition. Using these key bands, we retrained the models, which maintained high predictive performance while reducing data complexity.

Spatial prediction maps were generated to visualize the variability of grape composition across the vineyard. These maps showed how different grape composition parameters, such as Brix, pH, and anthocyanin levels, varied spatially and temporally within the vineyard. Such detailed mapping allows viticulturists to identify areas within the vineyard that require different management practices, optimizing resource use and improving grape quality.

The project demonstrated that hyperspectral imaging combined with machine learning provides a powerful tool for precision viticulture. This approach enables real-time, non-destructive monitoring of grape composition, offering significant advantages over traditional methods, which are labor-intensive, time-consuming, and invasive. The successful deployment of this technology could revolutionize vineyard management, leading to better-quality grapes and wine, more efficient use of resources, and ultimately higher profitability for growers.

Future research will focus on generalizing the predictive models to other grape varieties and vineyard conditions. The goal is to develop robust, adaptable models that can be used in diverse viticultural settings. Additionally, integrating this technology with automated vineyard management systems, such as drones or robotic harvesters, could further enhance its practical applications, paving the way for smarter, more efficient vineyard operations.

Leveraging Berry Physiology To Mitigate Late-Season Dehydration. AVF Project #2024-2739.

AVF Proj. ID: 20242739 / /Cat.: ,
Primary Investigator(s): Dr. Megan Bartlett, Assistant Professor, Department of Viticulture & Enology, University of California, Davis, CA 95616, Tel: 530-752-2048, Email: mkbartlett@ucdavis.eduby

Summary of Progress:

Hot, dry conditions can exacerbate late-season berry dehydration, reducing yield and altering berry sensory properties.  Late-season dehydration occurs when the berries undergo programmed cell death, and the water released from the ruptured cells is lost to transpiration or backflow to the canopy.  Climate change is expected to make many wine regions warmer and drier, exacerbating these issues.  Thus, the goal of this project is to identify management strategies to reduce late-season dehydration and its effects on yield and quality.  In Year 1 and 2, we tested whether short (2-week) pulses of increased irrigation before or at the expected onset of cell death would reduce water stress-induced oxidative damage and delay or reduce the rate of cell death, reducing shrivel at harvest.  We found that the irrigation pulse at onset significantly reduced the rate of cell death and berry shrivel at harvest, providing irrigation guidelines to reduce late-season dehydration.  This year, we tested (1) whether evaporative cooling (misting) systems would reduce cell death and shrivel with less water than the irrigation pulse and (2) used a rootstock/Cabernet Sauvignon clonal trial to screen for plant material with less susceptibility to these processes.  Misting systems significantly reduced cluster temperatures and vine water stress (p<0.05) and, on average, increased berry weight and TA and reduced TSS and pH, though these differences were not significant (p>0.05).  Vine gas exchange and water stress, yield, and berry mass and composition also varied significantly across rootstocks and clones (p<0.05).  However, unexpectedly, we did not find significant cell death in any treatment or rootstock/scion combination in >130 images.  Extensive troubleshooting did not identify a problem with the imaging method; instead, extreme pre-veraison heatwaves could have reduced berry size, making it easier for oxygen to permeate the entire berry, which has been hypothesized to reduce cell death.  This year, we will repeat this work and include additional experiments and troubleshooting to test the hypothesis that heat during fruit set reduces cell death and shrivel, contrary to heat after veraison, or resolve any imaging issues to test the effects of misting and plant material on these processes.

Variable rate irrigation scheduling based on high-resolution short-wave infrared sensing and internet-of-things.

AVF Proj. ID: 20222718 / /Cat.: ,
Primary Investigator(s): Luca Brillanteby

Summary:  Vineyards face climate change, increasing temperatures, and drought affecting vine water status. Water deficit affects plant physiology and can ultimately decrease yield and grape quality when it is not well managed. Monitoring vine water status and irrigation can help growers better manage their vineyards. However, when field measurements, such as stem water potentials (SWP), can be precise, they are time-consuming. In addition, they do not allow for easy assessment of spatial variability, which is a critical factor for water status management. Remote sensing tools can help map plant water status in space and time and streamline data acquisition over whole vineyards several times during the season. In this project, we monitored a variably irrigated vineyard several times during the season with a hyperspectral NIR/SWIR camera mounted on a UAV.

A study was put in place in a Vitis vinifera L. cv. Cabernet-Sauvignon vineyard in the San Joaquin Valley, CA, USA, where a variable rate automated irrigation system was installed to irrigate vines with twelve different water regimes in four randomized replicates, totaling 48 experimental zones. The purpose of this experimental design was to create variability in grapevine water status, in order to produce a robust dataset for modeling purposes. Throughout the growing season, spectral data within these zones was gathered using a Near InfraRed (NIR) – Short Wavelength Infrared (SWIR) hyperspectral camera (900 to 1700nm) mounted on an Unmanned Aircraft Vehicle (UAV). Given the high water-absorption in this spectral domain, this sensor was deployed to assess grapevine stem water potential, a standard reference for water status assessment in plants, from pure grapevine pixels in hyperspectral images. The stem was acquired simultaneously in the field from bunch closure to harvest and modeled via machine-learning methods using the remotely sensed NIR-SWIR data as predictors in regression and classification modes (classes consisted of physiologically different water stress levels). Hyperspectral images were converted to bottom of atmosphere reflectance using standard panels on the ground and through the Quick Atmospheric Correction Method (QUAC) and the results were compared. The best models used data obtained with standard panels on the ground and allowed predicting stem values with an R2 of 0.54 and an RMSE of 0.11 MPa as estimated in cross-validation, and the best classification reached an accuracy of 74%. This project aims to develop new methods for precisely monitoring and managing irrigation in vineyards while providing useful information about plant physiology response to deficit irrigation.

As the drought conditions become more familiar to California grapevine growers, the need for effective water management solutions has heightened. Understanding the physiological responses of the plant at various intensities and timings can still provide great context for more advanced developments.

LEVERAGING BERRY PHYSIOLOGY TO MITIGATE LATE-SEASON DEHYDRATION

AVF Proj. ID: 20242739 / /Cat.: ,
Primary Investigator(s): Megan K. Bartlettby

Summary: Warm, dry conditions can exacerbate late-season berry shrivel, reducing yield and altering berry sensory properties. Late-season shrivel occurs when the berries undergo programmed cell death, and the water released from the ruptured cells is drawn from the fruit to the canopy by a water potential gradient. The goal of our project was to test whether we could reduce shrivel by interrupting these processes. First, we tested whether short (2 week) pulses of increased irrigation before or at the expected onset of cell death would reduce water stress- induced oxidative damage and delay or reduce the rate of programmed cell death, reducing shrivel at harvest. Second, we tested whether blocking the petiole water transport tissue (xylem) would reduce shrinkage by impeding water transport to the canopy. We implemented conventional (following standard commercial practices), early-pulse (before expected onset), and late-pulse (at expected onset) irrigation treatments on mature Cabernet Sauvignon vines in an experimental vineyard at UC Davis in 2022 and 2023. We monitored vine water stress, berry cell death and shrivel, reactive oxygen species concentrations, markers for cell oxidative damage, and berry gene expression. We also used glue to partially block the pedicle for berries in the conventional irrigation treatment and compared diameter shrinkage to undamaged berries. The late irrigation treatment significantly reduced the rate of cell death and the magnitude of berry shrivel at harvest compared to the conventional treatment. However, the early irrigation treatment did not significantly impact cell death or shrivel. Concentrations of the reactive oxygen species H2O2 and indicators of cell oxidative damage increased at the same time as cell death, consistent with a role in programmed cell death, but were not significantly different among treatments. We are still analyzing berry chemistry, cell death, and shrivel from 2023. Blocking the pedicle xylem did not significantly reduce shrinkage. Overall, these findings show that the time of onset of cell death is not impacted by water stress but using a short pulse of irrigation near the onset of cell death can slow the rate of cell death and reduce berry shrinkage at harvest.

Baseline Smoke-Taint Volatiles and Glycosides

AVF Proj. ID: 2595 / /Cat.:
Primary Investigator(s): Susan Ebelerby

Summary The increasing incidence of wildfires in grape growing regions of California and the West Coast has highlighted the need for enhanced understanding of the levels of volatile phenols and their non-volatile glycoside precursors that contribute to smoke taint off-flavors in grapes and wines. In this project, we measured ten volatile phenols in non-smoke exposed grapes to begin to understand baseline levels of these compounds in red and white grape varieties. Free and total levels of guaiacol, 4-methylguaiacol (creosol), phenol, 4-ethylguiacol, o-, m-, p-cresol, 4- ethylphenol, 4-methylsyringol, and syringol were measured in grapes from different regions of California. Air quality data for these regions is also presented. The data show a high degree of variability across varieties, regions, and years indicating that it will be important to have large databases to assess the impacts of smoke exposure on free and total volatile phenol composition. We have submitted a proposal to continue this work in 2022-23

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