Central Queensland University (CQUniversity), Australia, has built the world’s first mango auto-harvester, with the first prototype achieving 75% efficiency in automatically identifying and picking fruit in view during its first field trials at Yepoon.
According to the university, the prototype harvester takes approximately five seconds to harvest a fruit, from detection to placement.
Elaborating on the machine's functions, Ian Groves, of Groves Grown Fruit, Yeppoon, says: “That technology is also able to measure the size range of that fruit and so knowing how much fruit is in that block, knowing when it’s going to be mature and knowing the size of the fruit, means we can schedule our workforce, order the right number of cartons, the size of the inserts going into those cartons – this could be a real game changer, not only for our farm but for the entire industry.”
He adds: “The machinery identifying and counting fruit in the orchard turned out to be within just a few per cent of the actual number of fruit in the entire block last year.”
In regards to the significance this technology holds for the future, CQUniversity Professor Kerry Walsh believes it could help produce companies and their growers manage difficulties caused by labor shortages.
“The auto-harvester has the potential to solve some of the major labour force issues that currently limit the industry.”
The machine is already turning heads within the industry as a result of its early positive results, says CQUniversity.
It notes that its researchers are now working to take their mango sensor and auto-harvest technologies to commercial-ready deployment.
Walsh says he will reveal details of the auto-harvester at this week’s Australian Mango Industry Association conference in Darwin, including researchers' aims to improve the harvester's performance to over 90% efficiency in picking fruit in view, to increase its speed, and to refine its construction to reduce costs.
One possible modified version of the prototype would see it mounted on a terrestrial drone to operate autonomously, at faster speeds and higher accuracies.
“The end goal is to save costs and improve productivity on farms while driving consumer demand by ensuring a top-quality eating experience every time,” Walsh explains.
The prototype was developed as part of a RND4Profit Commonwealth-funded research project led by Horticulture Innovation.
It is just the latest technology created by Walsh's team, which previously delivered to industry a near-infrared spectroscopy (NIRS) measurement system to access the eating quality of mangos and predict their ideal harvest time.
Now adopted within the mango industry, the university asserts that this advancement laid the foundation for research into in-field machine vision systems to count fruit and estimate fruit size for fruit load estimates before harvest, allowing farmers to better plan how many pickers to hire at which time periods.
"Both harvest estimates and autoharvest works best deployed in small tree-high density orchards, so this work complements the Queensland DAF work on such orchard designs,” concludes Walsh.