THE SURENUT ANALYSER
THE RESEARCH
HOW DID THE PROJECT START?
In conjunction with the University of South Australia, we have developed a machine that dramatically improves the accuracy of almond QA.
Working with researchers at UniSA, Surenut have developed a world-first automated technique for simultaneously assessing almond quality and detecting potentially serious mycotoxin contamination in kernels.
In 2019-2020, Australia’s almond crop was worth just over $1 billion, and the value of the sector is expected to expand to $1.5 billion in coming years, with Australian almond growing conditions among the best in the world.
Given the local industry is now exporting to more than 50 nations, accurate and consistent grading of almonds is paramount, ensuring international markets can trust the Australian product.
Traditionally, almonds have been graded manually, with samples taken hourly from production lines to check for consistency of appearance, chips and scratches, double kernels, insect and mould damage, and other defects.
This process, however, is labour intensive, slow, and subjective, all of which can lead to inaccurate and inconsistent grading, particularly from season to season due to staff turnover.
Funded through the Cooperative Research Centres Projects program, a research team led by Associate Professor Sang-Heon Lee combined two high definition cameras and purpose developed AI algorithms to create a system that can examine almond quality in far greater detail than the human eye .
Read the article here >
