CQUniversity professor Kerry Walsh said some cases, farm performance improved by more than 40 per cent by early and accurate assessment of fruit ripeness.

She said the team’s focus was developing new sensor hardware and working with existing sensor hardware to assess agriculture commodities without damaging the product.

“As a consumer, if you go into a retail store and you purchase fruit on the basis of what it looks like, take it home and you have an eating experience that’s bad,” she said.

“Research says that you won't go back to buy that fruit for four to six weeks, so it's not an instant decision but it’s certainly important to repeat purchase.”

Professor Walsh said the team was originally prompted by growers to estimate the quality of the fruit on the packing line non-invasively, but watching the growers prepare for harvest in the orchard led them to look at machine vision in the orchard.

The team is now investigating the use of machine vision to assess mango flowering and fruiting, and robotic harvesting techniques to overcome labour shortages and occupational risks to workers.

“Initially, we were prompted by growers to look at estimating the quality of fruit non-invasively, its internal quality being sugar content or dry matter content and that took us down the path of measuring in-line,” Professor Walsh said.

“So you’re on a pack line, you’re sorting on colour and weight.

Now we were adding in another facility, that is estimating that the sugar content or dry matter content of that fruit.

“We were in the fields doing the dry matter measurements and we could see the grower practice of trying to estimate fruit yields, that is how much crop was on the tree, so that they could be organised in terms of labour requirements, pack house requirements and that was all being done manually with a hand counter, so that lead us into a new line of work looking at machine vision in the field, so rather than just machine vision in the pack house, taking it into the field to estimate crop load across the field.

“The next step on from that of course, having seen the fruit, is to try and reach out to pick the fruit to automate the harvest.”

Groves Grown Tropical Fruit owner Ian Groves said said a big variation between varieties or just a lack of cues in some varieties meant he often had to look at the flesh colour to determine if the mangoes were ripe.

“With one of the NIRS guns we are now able to walk through the orchard testing fruit, seeing if there’s enough to go through a spot pick or whether they’re all ready and train up our workers as to the visual cues as to what a mature mango looks like,” he said.

“It just means we can get our start date correct so that we're picking fully mature fruit that the customer is going to be happy with.”

Last month, the Queensland team captured the attention of the mango industry when it held a successful field trial with the world’s first mango auto-harvester in Yeppoon.