Australian rice is predominantly processed and sold through an industry-owned global rice retailer, SunRice. Rice quality and yield are influenced by a range of on-farm and postharvest variables and practices. Growers supply rice to SunRice in batches which are individually tested for quality and whole grain/head rice yield. This testing may take up to five months. During processing, rice grain is prone to cracking and breaking, which can significantly reduce the grower’s income and the total volume of rice available for sale by SunRice. The breakage of rice grains during milling is a significant problem for the Australian rice industry. Broken grains are worth approximately half the value of whole grains, reducing the overall crop returns to both the growers and processors. To address this problem, this project has developed a centralised data repository, allowing the development of predictive models for rice milling quality and a model-building tool for future researchers to work with the data using a graphical user interface. Supplementary to this was the development of ‘CLOWD’, a location-specific weather data analysis tool. It was aimed that this project would help the Australian rice industry improve farm-level milling quality and post-harvest handling decisions that lift milling yield. More specifically, this project has developed a suite of digital tools to enhance product quality and provenance for whole grain rice. This will allow the Australian rice industry to better predict industry-wide head rice yield and quality based on locally-adjusted seasonal conditions and enterprise-specific crop inputs, both pre- and post-farm gate. Accurate prediction of future rice yield and quality will ultimately allow SunRice to improve industry profitability by maximising yields and segregating quality types for high-value markets. Growers will further benefit through near-real-time feedback of quality and benchmarking information, as well as updated guides for growing each variety.
Original languageEnglish
PublisherFood Agility CRC
Number of pages38
ISBN (Electronic)ISBN 978-0-6486338-5-3
Publication statusPublished - 2024


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