By Wilson da Silva
A new portable hand-held device that is compatible with any smartphone could provide precise on-farm grading of wool and yield farmers a greater return on the value of their wool.
The device — a specialised clip-on lens with accompanying software — is the brainchild of CNBP PhD students Ben Pullen and Vicky Staikopoulos, co-founders of Woven Optics, a company they set up to develop and market it.
Currently, bales of wool are tested using a laser-based technology developed by the CSIRO about 25 years ago, but the price of that device is prohibitive to all but the largest farms.
‘It’s about $95,000 to buy one, so farmers don’t typically use them,’ says Pullen. ‘They usually just send the bales off for testing. They don’t usually do it on-farm unless it is a big farm.’
Woven Optics’ device makes on-farm DIY testing possible at a fraction of the current cost. The technology relies on images captured and read on a farmer’s smartphone. High-quality images of the wool fibres are assessed by Woven Optics software, which produces a micron measurement in seconds.
In the modern wool market, where micron thickness is such an important factor in predicting a fleece’s market value, on-farm testing could be a huge boon.
As things currently stand on most farms, the fleeces from around 50 sheep go into a single bale, from which a sample is taken for testing. While wool classers and farmers are highly skilled at sorting sheep, it’s much more difficult to sort today’s extremely fine wool by touch. In fact, it’s nearly impossible to differentiate between 16 and 18 micron fibres without using technology.
‘Very low micron wool is very, very valuable,’ says Pullen. ‘You could have a several hundred dollar difference per bale based on one micron.’
But with bales containing a mixture of high and low quality wool, the value of the overall bale is dramatically affected by the coarser fibres.
‘If farmers could grade the wool using our device, it would increase the value of their bales as they could ensure they were all of a similar quality, and they wouldn’t have to wait up to 6 weeks for samples to come back,’ says Pullen.
The technology also has potential for breeders when it comes to sorting lambs.
‘You can actually use this to test there and then,’ says Pullen. ‘You don’t have to send samples off. You don’t have to worry about additional costs for that. You can just do this all on-farm.’
He says that the device could also be an invaluable guide for buyers.
‘Say you’re going to spend $40,000 on a ram, it gives you a great deal of peace of mind if you can actually go and test it yourself.’
The Woven Optics idea can be traced to 2017 when the pair first talked about their ambition to translate scientific ideas from the lab into commercial reality.
‘We decided to put our hands up for the Tech eChallenge held at the University of Adelaide,’ says Pullen. ‘It was sponsored by the Australian Wool Innovation (AWI) group. And while it wasn’t exactly what we thought we wanted to be doing, we thought it was a great opportunity to learn about the process.’
As part of that process they sat down with an AWI consultant who suggested a couple of problems that were really important issues in the wool industry that needed to be addressed – one of them being on-farm wool classing.
Pullen says working in academic research prepared him and Staikopoulos for the challenge: ‘We saw a solution based on our experience.’
‘We’ve worked on projects that need an understanding about how to pull a multidisciplinary team together,’ he explains. ‘So we thought, “Take a software solution, a hardware solution, some know-how about how to validate scientific processes and validate the technology to be robust, and pull that together and deliver something.”’
As they have developed the product they have worked with engineers and manufacturers to develop the hardware, as well as a local machine learning specialist in Adelaide.
‘We’ve demonstrated a proof of principle and we are now currently developing the proof of concept,’ says Pullen. Woven Optics has recently secured funding to develop the project further and is working towards creating a prototype by the end of 2020.