Bachelor of Science in Agriculture (Hons), University of Sydney
Rapid Analysis of Rice Grain Quality
Australian rice producers are graded on the milling quality of their deliveries. This grade, however, takes approximately five months to receive, delaying grower payments and inhibiting quality based segregation through storage. This project aims to generate a prediction model which would provide the tools to grade rice quality at the delivery point.
Model development will occur through the application of machine learning algorithms to historical datasets of farm management, environmental conditions, grower deliveries and grain quality appraisals. The insights derived from the model are expected to drive an increase in production of premium Australian rice sold into high-value markets.
Associate Professor Daniel Waters, Professor Chris Blanchard, Zahid Islam, Russell Ford (SunRice)
Food Agility Cooperative Research Centre