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In a collaboration between Dr Maryam Yazdani and Dr Ben James of CSIRO, the convergence of mineral imaging technology and biosecurity application has led to a significant advancement in threat detection. Dr James, leading the X-ray imaging team at Lucas Heights, NSW, has long been engaged in the development of real-time ore-sorting technology for the mineral industry. His expertise lies in capturing high-precision images of tiny valuable mineral particles embedded in rock, a pursuit vital for optimising mineral processing operations.
However, the application of this technology took an unexpected turn when Dr. James and Dr. Yazdani, who heads the Pest Detection Technologies team in Brisbane, joined forces to address challenges in border fruit inspection methods. Driven by the need for faster, more accurate, and automated fruit inspection processes, they sought to adapt mineral resource scanning technologies to detect pests in fruits.
The breakthrough came when they identified that artefacts appearing in CT scans of infested fruits were actually caused by the movement of coddling moth larvae within the apples during the scanning process. This realisation prompted them to explore the potential of X-ray imaging, which offered a cheaper and faster alternative to CT scans while still capturing the motion of pests within the fruit.
Under the Autonomous Sensors Future Science Platform (ASFSP), a CSIRO research program aimed at advancing Australian industry through the development of autonomous platforms and sensors, Dr. James and Dr. Yazdani’s team embarked on a journey to refine X-ray imaging for biosecurity applications. Their efforts focused on enhancing the accuracy, sensitivity, and resolution of the technology to effectively detect pests and damage in fruits.
Through a series of successful proof-of-concept trials, the team demonstrated the capability of X-ray imaging to identify various pests, including fruit flies, seed weevils, codling moths and other insects, as well as damage and movement within fruits. Dr. Jiasheng Su, a postdoc working with Dr. Yazdani, played a crucial role in developing machine-learning algorithms to automate the detection of pests and damage, despite the challenges posed by variability in damage patterns and insect sizes.
Moving beyond single fruit inspections, the team is now focused on testing the technology’s effectiveness on bulk produce. They are designing a prototype conveyor system equipped with X-ray emitters and detectors to capture high-resolution images of fruits in boxes at high speeds. Additionally, they are refining machine-learning algorithms to match fruit scans with pest verification data, further enhancing the technology’s diagnostic potential.
While still at the proof-of-concept stage, the team is optimistic about the path to commercialisation. Dr. Yazdani highlights the opportunity to leverage CSIRO’s advancements in X-ray imaging technology for mining to revolutionise biosecurity and potentially expand its application to other domains such as agriculture and metal recovery in mining. Dr James emphasises the importance of continued collaboration and innovation to scale up the technology and address broader industry challenges.
The convergence of mineral imaging technology and biosecurity expertise has paved the way for transformative innovation in threat detection. Through interdisciplinary collaboration and technological advancements, Dr. James and Dr. Yazdani’s team are poised to revolutionise fruit inspection methods and enhance biosecurity measures, with far-reaching implications across multiple industries.
