THANK YOU FOR SUBSCRIBING
Food and Beverages | Thursday, April 07, 2022
The wine industry is being transformed by big data and machine learning, which will result in a higher-quality product, which is fantastic news for both producers and customers.
Fremont, CA: For most, the thought of wine evokes a mental picture replete with rustic cellars, rolling hills, picturesque vineyards, and luscious gleaming grapes lining the countryside in the afternoon sun. For decades, wine culture has been romanticized as a way to bring people together to enjoy a nice drink, excellent food, and good company. Wine is a $300 billion market with fierce competition. With so much at stake, it's no surprise that growers of all sizes are constantly exploring new ways to produce higher quality and more quantity.
As appealing as it may seem for a producer to stroll the vineyard and inspect each grape by hand, it is just not an efficient method of operation. Recent technological advancements have enabled amazing techniques for winemakers and wine drinkers.
Here’s how technology is enhancing the wine industry:
Wine recommendation software
Whether a customer enjoys a powerful shiraz or a buttery chardonnay, there's a decent chance they'll be tempted to try something new at some time. This is made simple by wine suggestion software, which allows consumers to type in a few words based on the traits they like and receive a list of fresh and fascinating options. Their new favorite wine could be just a few mouse clicks away.
Predicting yield and quality
For winemakers, predicting the output of a vineyard is critical. In the same way that it is for anticipating Blatons bourbon production. Winemakers can better manage their resources for the season if they have an accurate yield estimate. Everything from water to fertilizer to barrels to personnel is included. New technologies enable winemakers to blend historical vineyard data with the early activities of the current wine season. This information is then fed into software that can accurately forecast the present yield with up to 90 percent accuracy.
Winemakers can now capture photos of vine leaves and run them through an algorithm that can properly forecast the plant variety and whether it is stressed, thanks to developments in machine learning technology. This is beneficial not just to the vine's health but also to the avoidance of grape variety confusion. Another excellent feature of this technology is that it can detect smoke contamination in grapes. The temperature of a vine will reveal whether or not it has been harmed by smoke. It is feasible to determine which vines have been tainted using a machine learning algorithm.