When you're sitting at home sipping your chardonnay, you might not think about it. There's an incredible amount of work in the bottle you pull off the shelf at the supermarket or from the wine merchant.
But now, some of that work may be eliminated. Or at least made significantly easier.
Researchers from the Faculty of Engineering and the Faculty of Science have teamed up with the companies Capra Robotics and Newtec to investigate how hyperspectral imaging and a mobile robot platform can help winemakers assess when their grapes are ready for harvest.
They also collaborate with Kimesbjerggaard Vingård in South Funen to test the technology.
Learn more about the project in the video below.
As it stands, the winemaker has to pick individual grapes and make chemical measurements of sugar and acidity levels as harvest time approaches. It takes a long time, and it only tells something about the ripeness of the few grapes that are actually measured.
The idea of the research project is to let a robot with a hyperspectral camera roam the field and take pictures of the grapes. While a regular camera can only see three colors – blue, green, and red – a hyperspectral camera can take pictures in many wavelengths – or colors – and therefore see things we otherwise cannot see. Including the amount of sugar and acid in a grape.
Eventually, it should all happen automatically. The robot should drive up and down the rows and then send the images to a computer model that tells the winemaker when to harvest the grapes. Not only does it make it easier for the farmer, but ideally, it also ensures that the grapes are completely ripe when harvested, which can result in a higher yield and perhaps better wine.
First and foremost, however, the computer model needs to be trained. This means that the researchers have to make traditional chemical measurements of all the grapes they take pictures of and compare the two to teach the robot what a ripe grape looks like.
The technology will also be applicable in many other contexts and in other types of agriculture.