Shared challenges: How PNG research has helped advance tech in Australia’s native nut industry

Date released

16 September 2025

In Papua New Guinea (PNG), galip nuts are traditionally collected by women living in rural and remote communities from long-lived wild trees, or from village trees they inherit from their parents and grandparents. However, government research identified galip as a prime commercialisation opportunity.

But the emerging industry soon faced a challenge. That is, it’s hard to tell from an unshelled nut what quality lies within. ACIAR support provided expertise and funding to operate a pilot plant to test processing methods for galip in PNG, which has led to application of new technology in both PNG and Australia.

Two women in green-coloured clothing holding a tray of nuts — Ms Wilma Oli and Associate Professor Hosseini Bai working on galip nut research in Papua New Guinea, which has provided a new way to assess the quality of nuts. Photo: Griffith University

Hyperspectral imaging innovation

Associate Professor Shahla Hosseini Bai leads a research team at Griffith University developing imaging technologies for food and agriculture, as well as multiple ACIAR projects advancing nut industries in PNG. She worked with galip nut producers and processors on the pilot processing plant.

‘We quickly realised that the pilot plant processing galip nuts in PNG had no real way of testing the quality of the nuts,’ said Associate Professor Hosseini Bai.

‘Oven drying galip and testing the moisture content took more than 24 hours. Laboratory tests for rancidity took 2 to 3 weeks. By the time the results came out, the nuts might already have been spoiled.’

This challenge led Associate Professor Hosseini Bai to start utilising hyperspectral cameras for nut quality assessments, evolving the work of a colleague who was using the technology to rapidly test soil nutrients.

Hyperspectral cameras provide powerful imaging that can see more than 460 colour channels, revealing chemical bonds and subtle changes in the surface of foods. These changes can indicate whether nuts are rancid. They can also identify moisture content and nutrient concentration in the nuts in real time.

Technologies and practices identified and developed through ACIAR research programs often address the shared challenges for farmers across the Indo-Pacific region, Australia included.

As a long-term collaborator with the Australian macadamia industry, Associate Professor Hosseini Bai was excited to share the findings from the galip nut project, recognising that the imaging technology could also benefit Australian nut growers. She was able to partner with the Australian Macadamia Society, independently of ACIAR, for a separate macadamia proof-of-concept project.

The hyperspectral technology proved a real game changer.

A person working on a computer assessing a tray of macadamia nuts

A researcher at Griffith University uses hyperspectral imaging to assess macadamia nut quality. Photo: Griffith University

A hyperspectral imaging technique identified through ACIAR-supported research in Papua New Guinea is being developed to assess the quality of macadamia nuts in Australia. Photo: Australian Macadamia Society

A pile of macadamia nuts on the ground in their shells

Australia is the world’s third-largest producer of Macadamia nuts. Photo: Australian Macadamia Society

Shared challenges

Macadamias are native to Australia, which is the third largest producer of macadamias globally. The international market is growing at the rate of 10% a year. Australia’s 800 growers produce a crop worth up to $300 million a year at the farm gate, depending on the season. About 25% of the crop is sold domestically and 75% is exported to 40 countries around the world. The industry includes 15 processors.

‘But we face a lot of international competition, so it’s really important to maintain our provenance and our quality edge, particularly over countries with low-cost production,’ said Ms Leoni Kojetin, Industry Development Manager with the Australian Macadamia Society.

‘Several commercial processors helped to design the proof-of-concept trial [using the hyperspectral technology], working with Griffith University. Each one is now working individually with different imaging technology partners on designs to incorporate the technology into their processing facilities.’

Ms Kojetin said hyperspectral imaging could identify a range of quality parameters quickly, efficiently and accurately, without having to destroy nuts in the testing process.

We have far less waste in the system, and the testing itself is faster. The technology also had the potential to scan every nut, rather than just a sample of larger batches, as is often done. It will give us a much greater confidence in our quality.

Ms Kojetin indicated further research would look at how machine learning could be used to improve the quality analysis and correlate it with other invisible characteristics important to consumers, such as butteriness, texture, crunch and taste.

‘Further advances might allow these characteristics to be assessed in conjunction with growing conditions to provide feedback to growers. The stronger the correlations we can make between seasonal conditions and quality parameters, the easier it will be for growers to do a better job, and the better we can protect our market advantage,’ said Ms Kojetin.

ACIAR Projects: ‘Developing markets and products for the Papua New Guinea Canarium nut industry’ (FST/2010/013); ‘Enhancing private sector-led development of the Canarium nut industry in Papua New Guinea’ (FST/2014/099); ‘Enhancing private sector-led development of the canarium industry in Papua New Guinea (Phase 2)’ (FST/2017/038)