Research Project: Improved Fruit, Grape and Wine Products through Precision Agriculture and Quality Component Evaluation

Location: Horticultural Crops Production and Genetic Improvement Research Unit

2023 Annual Report

Objectives
This project’s overall goal is to refine agricultural management practices that growers use to improve fruit and fruit product quality. Objective 1: Determine the impacts of variety selection and production management practices on fruit and product quality components to optimize practices for superior fruit and wine production. [NP 305, Component 1, Problem Statement 1B] Subobjective 1A: Determine primary and secondary metabolites and their targeted analyses; evaluate and optimize analytical methods where insufficient data exists. Subobjective 1B: Evaluate developed quality component measurements on new or improved fruit and fruit products, and link to agricultural management. Objective 2: postponed until vacancy is filled. Objective 3: Enhance management practices for small fruit production systems by optimizing soil health, weed suppression, and the interplay between plants and ecosystem dynamics for desired outcomes.

Approach
Project objectives will be accomplished by integrating research across three core disciplines: food chemistry/phytochemical analysis, crop physiology, and plant breeding. A systematic approach, with targeted analyses of fruit quality compounds, will be utilized to predict the magnitude that environmental factors and cultural practices impart to fruit quality. This strategy will allow us to improve and define analytical methods for plant metabolite analyses that advance our comprehension of the interactions between canopy management, vine nutrient treatments, water regimes, vineyard microbiome, vine virus status, and cultivar/genotype selections have upon fruit development, fruit quality components, and vine physiology. An additional growing season will be employed, if necessary, to account for interruptions during the experimental treatment or sampling schedules.

Progress Report
We continued our investigations into fruit, plant, and soil quality advancements made through agricultural management practices. In support of Objective 1, research was conducted on how biotic/abiotic stressors and wine making techniques alter wine grape and wine quality. Winemakers are interested in new ways to enhance consumer wine experience and give their products a marketplace edge. Non-Saccharomyces yeasts (yeasts not traditionally used for alcoholic fermentation) were explored for alcoholic fermentation, to discern if better tasting red and white wines could be made with lower alcohol content, when compared to traditional yeasts (S. cerevisiae). The non-Saccharomyces yeast strains were chosen for their ability to produce the enzyme pectinase, which can breakdown pectin to improve mouthfeel in wine. Experimental wines were tested with and without pectin in young wines and after bottle storage. Our efforts to screen commercial vineyards vine virus status and their impact on grape quality is also ongoing. While some grapevine viruses are detrimental to grapevine health, crop load ratio, fruit characteristics, and ultimately to wine quality, others cause only minor issues. Vine virus identification in commercial Idaho vineyards is the first step towards constructing virus diagnostic tools tailored to the growing area that can be used to mitigate future losses from vine infections. Research on how specific vine viruses, like grapevine-associated tymo-like virus, influence healthy fermentation and quality components is ongoing. In support of Objective 3, a two hectare vineyard was newly planted to study the influence of vineyard management practices, including the use of cover crops and compost, on vineyard soil health. Additionally, a phosphorus (P) fertilization trial was continued to develop a predictive model for P availability in grapes using solid state X-ray spectroscopy rather than traditional liquid extraction techniques. To gauge soil health challenges faced by grape growers in the Pacific Northwest, 40 grower-identified “problematic” soils from Washington and Oregon vineyards were collected and analyzed for a suite of soil health indicators including pH, nutrients, salts, and organic matter. We continued our collaboration with Pacific Northwest National Laboratory and Argonne National Laboratory to identify particulate organic matter in soil aggregates using X-ray microcomputed tomography (XCT), Scanning Electron Microscopy (SEM), and deep learning-based image analysis. These tools can help researchers and growers automate the tedious task of measuring plant growth properties when trying to quantify the influence of soil health improving practices on plant growth.

Accomplishments
1. Idaho ‘Cabernet Sauvignon’ grape composition altered by Grapevine leafroll virus-3. Making fine wine begins in the vineyard with the production of high-quality fruit. Viruses, such as grapevine leafroll-associated virus-3 (GLRaV-3) can have negative impacts on both vine productivity and fruit quality. ARS scientists in Corvallis, Oregon, with University of Idaho collaborators, were the first to report on GLRaV-3 grape quality in ‘Cabernet Sauvignon’ grapes obtained from Idaho industry collaborators. Findings from this work indicate GLRaV-3 may impact wine quality negatively, the importance of obtaining virus-free planting material, and subsequent monitoring of vineyards for GLRaV-3. This work was partially funded by Northwest Center for Small Fruits Research (NCSFR) and Idaho State Department of Agriculture Specialty Crop Block Grant.

2. Added tools for winemakers. New wines are being made by using unusual yeasts (non-Saccharomyces yeasts) that develop unexpected flavors. As little is known about their influence on wine quality, ARS scientists in Corvallis, Oregon, with Washington State University collaborators, examined how wine made with these yeasts, which are not traditionally used for alcoholic fermentation, might change in taste and flavor after storage. One notable finding was that after storage, red wines made with these yeasts had increased cherry flavor. These yeasts offer winemakers another way to create new or improved products for consumers.

3. First detection of a grapevine-associated tymo-like virus in the United States. The wine grape industry is a $6.5 billion business in the United States, and some grapevine viruses can be detrimental to grapevine health, crop load ratio, fruit characteristics, and wine quality. ARS scientists in Corvallis, Oregon, with University of Idaho collaborators, for the first time in the United States identified grapevine-associated tymo-like virus in Idaho. A reliable diagnostic tool for detecting the variant in vineyards was developed to aid growers, by protecting them from losses through timely deployment of management strategies against the virus. This work was partially funded by Northwest Center for Small Fruits Research (NCSFR) and Idaho State Department of Agriculture Specialty Crop Block Grant.

4. Deep learning technology enables quick image analysis. User-friendly imaging technologies have allowed researchers to capture ever-growing amounts of image data from microscopes, digital cameras, drones, and satellites. Despite the large amount of data collected by these imaging platforms, getting meaningful data from images remains a significant bottleneck for researchers and growers alike. ARS scientists in Prosser, Washington, in collaboration with University of California, Oak Ridge Institute of Science and Education, and California Polytechnic State University researchers, have developed a software workflow that can be used as deep learning models for image analysis and data extracting using vast computing systems. This new tool will help scientists speed up breeding program plant evaluation, crop disease detection, and expand the understanding of environmental systems.

Review Publications
Paup, V.D., Barton, T.L., Edwards, C.G., Lange, I., Lange, B.M., Lee, J., Ross, C.F. 2022. Improving the chemical and sensory characteristics of red and white wines with pectinase-producing non-Saccharomyces yeasts. Journal of Food Science. 87(12):5402-5417. https://doi.org/10.1111/1750-3841.16371.
Paup, V.D., Aplin, J.J., Potter, R.I., Edwards, C.G., Lee, J., Ross, C.F. 2023. Sensory properties of 6- and 18-month-stored wines made with pectinase-producing non-Saccharomyces yeasts. Journal of Food Science. 88(1):462-476. https://doi.org/10.1111/1750-3841.16418.
Dahan, J., Orellana, G.E., Lee, J., Karasev, A.V. 2023. Occurrence of grapevine-associated tymo-like virus in wine grapes in the United States. Plant Disease. 107(2):592. https://doi.org/10.1094/PDIS-05-22-1140-PDN.
Lee, J., Rennaker, C.D., Thompson, B.D., Dahan, J., Karasev, A.V. 2023. Idaho ‘Cabernet Sauvignon’ grape composition altered by grapevine leafroll-associated virus 3. NFS Journal. 31:1-6. https://doi.org/10.1016/j.nfs.2023.02.002.
Dahan, J., Orellana, G., Lee, J., Karasev, A. 2023. Genome sequences of two grapevine rupestris stem pitting-associated virus variants from Vitis vinifera cv. Riesling in Idaho, USA. Microbiology Resource Announcements. 12(4). Article e01366-22. https://doi.org/10.1128/mra.01366-22.
Dahan, J., Orellana, G.E., Lee, J., Karasev, A.V. 2023. Grapevine endophyte endornavirus and two new endornaviruses found associated with grapevines (Vitis vinifera L.) in Idaho, USA. Viruses. 15(6). Article 1347. https://doi.org/10.3390/v15061347.
King, B.A., Shellie, K.C. 2023. A crop water stress index based internet of things decision support system for precision irrigation of wine grape. Smart Agricultural Technology. 4. Article 100202. https://doi.org/10.1016/j.atech.2023.100202.
Momayyezi, M., Rippner, D.A., Duong, F.V., Raja, P.V., Brown, P.J., Kluepfel, D.A., Earles, J., Forrestel, E.J., Gilbert, M.E., McElrone, A.J. 2022. Structural and functional leaf diversity lead to variability in photosynthetic capacity across a range of Juglans regia genotypes. Plant Cell and Environment. 45(8):2351-2365. https://doi.org/10.1111/pce.14370.
Rippner, D.A., Raja, P., Earles, J.M., Momayyezi, M., Buchko, A., Duong, F., Forrestel, E., Parkinson, D., Shackel, K., Neyhart, J.L., McElrone, A.J. 2022. A workflow for segmenting soil and plant X-ray computed tomography images with deep learning in Google’s Colaboratory. Frontiers in Plant Science. 13. Article 893140. https://doi.org/10.3389/fpls.2022.893140.