Composition of grape grown on different Homogenous Terroir Units (HTU)

Oak barrels form an integral part of wine production, especially that of high quality wines. However, due to its porosity, wood presents an ecological niche for microbial proliferation and is highly susceptible to microbial spoilage which could cause considerable economic losses. Brettanomyces bruxellensis, the most commonly encountered microorganism responsible for spoilage during barrel ageing, can remain in barrels after barrel sanitation to contaminate new batches of wine after refilling. Therefore, effective sanitation treatments are of utmost importance to prevent recurring wine spoilage.

Grapes infected with grey mould due Botrytis cinerea are widespread in vineyards during certain growing conditions.

Developing a tractable genetic engineering and gene editing system is an essential tool for grapevine. We initiated a plant transformation and biotechnology program at Oregon State University using the grape microvine system (V. vinifera) in 2018 to interrogate gene-to-trait relationships using traditional genetic engineering and gene editing. The microvine model is also used for nanomaterial-assisted RNP, DNA, and RNA delivery. Most reference genomes and annotations for grapevine are collapsed assemblies of homologous chromosomes and do not represent the specific microvine cultivar ‘043023V004’ under study at our institution.

Typically, subjective, and visual methods are used by grape growers to assess harvest maturity. These methods may not accurately represent the maturity of an entire vineyard – especially if extensive and representative sampling was not used. New technologies have been investigated for improved harvest management decisions. Spectroscopy methods utilizing the near-infrared region of the light spectrum is one such technology investigated as an alternative to classic methods and particularly the application of hyperspectral imaging (HSI) has recently gained attention in research. HIS is a spectroscopic technique that obtains hundreds of images at different wavelengths collecting spectral data for each pixel in the sample i.e., providing both spectral and spatial data.

Artificial intelligence (AI) for winegrowers refers to robotics, smart sensor technology, and machine learning applied to solve climate change problems. Our research group has developed novel technology based on AI in the vineyard to monitor vineyard growth using computer vision analysis (VitiCanopy App) and grape maturity based on berry cell death to predict flavor and aroma profiles of berries and final wines.