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Agriculture Technology and Adoption Centre Data Science, Artificial Intelligence and Machine Learning

Data Science, Artificial Intelligence and Machine Learning

JCU is integrating key areas of machine learning, data mining, algorithm development, advanced modelling and big data analytics to address challenges for agriculture and aquaculture. We are increasing the quality, quantity, sustainability and cost-effectiveness of agricultural/aquaculture production, in spite of increasing challenges, through research and development in data science and machine learning.

Case Study

Irrigation system for sugarcane crops

Climate Smart Sugarcane Irrigation Partnerships

Over the past decade the sugar industry has undergone a significant rationalisation and seeks to find efficiencies in the selection, growth and harvest of sugarcane. With the majority of the Australian sugar industry situated along the east coast from Grafton to Mossman, close to the Great Barrier Reef, farmers also seek to reduce irrigation costs and loss of fertilisers to improve production and environmental outcomes.

JCU researchers are working with industry partners AgriTech Solutions and others to minimise nutrient run-off, improve soil health and increase wetlands water quality by facilitating the adoption of world-class irrigation practices in sugarcane farming systems. They have also used the Internet of Things (IoT) to create a two-way communication channel between two existing Irrigation Decision Support Tools (WiSA and IrrigWeb) that provides evidence-based irrigation management as ‘one’ SMARTER technology