Introducing automated 3D-scanning robots to vineyards could be the secret to unlocking the “Holy Grail” of the wine industry.
A project using Lincoln University viticulturalists and led by the University of Canterbury (UC) aims to develop the robots and use them to get far more accurate yield estimations, which would tell growers exactly how much fruit their vines will bear.
The five-year $6.1 million project is supported by the Ministry of Business, Innovation and Employment Endeavour Fund.
Lincoln University Department of Wine Food & Molecular Biosciences Associate Professor Dr Amber Parker said being able to accurately predict yields could be a huge shift for the industry.
Having accurate yield estimation meant growers and winemakers could better prepare for harvest in every step of production. It affects everything, including how much fruit would be harvested, the labour and equipment needed, and what the winery would receive.
“Every step along that chain there’s a financial cost benefit.
“How many tractors do you need? How many drivers? How many people in the winery? How many tanks? Do you need to make changes?”
At present, being within 5-10% in a yield estimation is considered very good, but still leaves a huge amount of room for variation.
Part of the problem with determining yield estimates is that growers are working on averages from other years, but the climate fluctuates annually.
Using the autonomous robot, the actual number of fruit on every vine can be measured without supervision, putting growers in a much better position to deal with those fluctuations, Parker said.
The robot estimates yield by creating a 3D scan with the exact number of flower structures on the vines, called inflorescences.
The current method of estimating yield is to count these in person, whether it be in the vineyard or by removing samples from the vine.
It is more accurate to remove them, but that means a loss in potential fruit.
These are expensive, time-consuming processes and can only be used to work out a rough average, as it is impossible to do every vine, she said.
The robots are being designed by a team at UC, led by Professor Richard Green.
The one metre by one metre device zips down the rows at “a fast walking pace” capturing thousands of images, Green said.
It is loaded with cameras with wide-angle lenses, each taking about 10 pictures per second. The current arrangement features 12 cameras, collecting images on both sides as it moves through the vineyard.
Those images are then fed into an artificial intelligence program that pieces them together into a highly accurate 3D model of the plant, including everything behind the leaves.
Developing the AI to reconstruct the images was the most difficult part of the process, but now that it works the result could be revolutionary for the industry, he said.
“We have access to way more information than ever before.”
The technology is groundbreaking, but it is up to Lincoln’s viticulturalists to make sure it can meet the industry’s needs.
Every few weeks the robot goes through Lincoln’s vineyard scanning the vines. Lincoln’s viticulturalists then collect data manually to compare.
That data was used to determine the practical value the technology had, Parker said.
They were also looking at the bigger picture, as the 3D images collected provided a lot of data that was previously lacking in the field.
“How we go from flowers to fruits is not really well modelled. Part of the work is can we look at that better and understand that in a predictable power better.”
There is potential for it to be used for other purposes, such as determining vine balance, which estimates how the vegetation is growing in comparison to the fruit.
That information is useful for understanding how the vineyard set-up is working and for finding vines that are struggling.
The current method of measuring balance is by weighing the pruned material from the vines, but the robot has the potential to provide far more accurate measurements as part of its automated yield scans.
“We have these balance metrics, but they don’t necessarily work well. They’re also quite time-consuming to measure.”
A second robot will soon be deployed in Marlborough in commercial vineyards and this year will be the first full season of testing.
