Fishers will soon be able to accurately determine the amount of meat in a mud crab thanks to a new device being developed by James Cook University.
JCU Electronic Systems and Internet of Things Senior Lecturer Dr Eric Wang's prototype device uses a near-infrared spectrometer (NIRS) and artificial intelligence (AI) to grade live crabs based on their meat content.
The handheld device, which is still undergoing extensive testing, will ultimately replace the current practice of fishers using thumb pressure applied to the carapace of crabs to determine their meat content.
"The device has a lamp which shines onto the claw of the mud crab, and depending on the chemical composition of the claw, it will reflect or absorb different wavelengths," Dr Wang said.
"Based on the absorbed wavelengths, the developed AI algorithm can then determine what grade of mud crab it is."
Mud crabs are given a grade between A and C with Grade A considered to contain the most meat.
"It will allow a fisher or a market stallholder to point this device over a crab's claw or carapace and determine what grade it is so there is no ambiguity around the meat content," Dr Wang said.
"Right now, a lot of Grade C crabs are caught which isn't sustainable for the environment, so this is a way to help filter those out.
"To make it work consistently, we need to continue testing different samples because different mud crabs from different areas might reflect or absorb different wavelengths."
Dr Wang said he had already been through a couple of thousand samples of mud crabs, all of which were provided by the Queensland Department of Agriculture and Fisheries (DAF).
"In the future, we want to develop an algorithm for the device which can automatically learn the specific features of the local species of mud crab being measured to improve accuracy," he said.
The Rapid Assessment Unit, a joint JCU-DAF organisation focussed on innovative scientific research and development and delivery of rapid, non-invasive technologies, is involved in the project, as is grant facilitator JCU Connect.
While DAF had themselves already developed the technology being used as a proof-of-concept, Dr Wang said the main challenge was how to make it portable.
"What I'm exploring is how we can make this device affordable, waterproof and easier to carry on the boat, as well as integrate all of the AI algorithms into it," he said.
"It's important to get the device to a point where it can eventually be recognised by industry as a reliable tool.
"We need to be able to push the capabilities of it further so it can eventually become a commercial product."
Dr Wang said pending the success of the device, there was potential for it to be used to measure other types of seafood, such as fish or prawns.
