This work was supported by QUT Centre for Data Science and our industry partner Black Box Co.
Context
Black Box is a start-up company co-founded by two young women in northern Queensland. Their stated vision is to ‘bring out the best in beef businesses with the power of data’. Black Box has the largest base of phenotypic records for cattle across the whole supply chain. This database currently includes information on around 350,000 animals. In this project, these data will be analysed appropriately using statistical and machine learning methods in order to make a real difference to the industry through research, product development, and genomic analysis. This project will align to the Data for Discovery, Models and Algorithms, and Applied Data Science Research Programs, and to the Business and Engineering Systems Domain.
The project aim is to aggregate diverse datasets and provide improved real-time predictive and prescriptive capability (‘foresight’), particularly for genomic prediction, production forecasting, and methane efficiency.
Project Team
Prof. Moe T. Wynn QUT
Kalpani Ishara Duwalage QUT
Kerrie Mengersen QUT
Dale Nyholt
Dimitri Perrin
Project Outcomes
The project will produce statistical and machine learning methods, algorithms, computer software, industry reports and journal articles.
