Artificial intelligence (AI)-based protein modeling for the interpretation of grapevine genetic variants

New and developing technologies, that provide sensors and the software systems for using and interpreting them, are becoming pervasive through our lives and society. From smart phones to cars to farm machinery, all contain a range of sensors that are monitored automatically with intelligent software, providing us with the information we need, when we need it. This technological revolution has the potential to monitor all aspects of vineyard activity, assisting growers to make the management choices they need to achieve the outcomes they want. For example, a future vineyard may possess automated imaging that generates a three dimensional model of the vine canopy, highlighting differences from the desired structure and how to use canopy management to improve fruit composition, or generates maps with yield estimates and measurements of berry composition throughout the growing season.

Table grape consumption worldwide has experienced a remarkable growth in the first two decades of the 21st century, becoming the third most consumed fresh fruit in some countries, after bananas and apples. This increase has been attributed to several reasons, including the availability of seedless grapes, which has been a key factor in the increase in consumption.

Wine-grapes in the Willamette Valley, Oregon, are grown on three major soil parent materials: volcanic, marine sediments, and loess/volcanic.

Botrytis cinerea has more than 1200 host plants and is one of the most important plant pathogens in viticulture. Under certain environmental conditions, it can lead to the development of a noble rot, which results in a specific metabolic profile, altering physical texture and chemical composition. The other microbes involved in this process and their functional genes are poorly characterised. We have generated metatranscriptomic [1,2] and DNA metabarcoding data from three months of the Furmint grape variety, representing the four phases of noble rot, from healthy berries to completely dried berries.

Chitosan is a polysaccharide produced from the deacetylation of chitin extracted from crustaceous and fungi. In winemaking chitosan is mainly used in the clarification of grape juice and wine, stabilization of white wines, removal of metals and to prevent wine spoilage by undesired microorganisms. The addition of chitosan to model wine systems was able to retard browning, reduce levels of metallic ions (Fe and Cu) and to protect varietal thiols due to its antiradical activity1. The present experiment was planned in order to evaluate the use of chitosan as a secondary antioxidant at three different stages of Sauvignon blanc fermentation and winemaking. Sauvignon blanc juices from three different locations were obtained at a commercial winery in Marlborough, New Zealand. One lots of grapes was collected from a receival bin and pressed into juice with a water-bag press, and a further juice sample was collected from a commercial pressing operation. Chitosan (1 g/L, low molecular weight, 75 – 85% deacetylated) was added to the juice after pressing, after cold settling, after fermentation, or at all these stages. Controls without any chitosan additions were also prepared.