ML Project E: Extracting value from agronomy and farming systems R&D datasets

This tender consists of seven interrelated procurements. The applicant may apply for all seven Projects A-G, but successful applicants will only be contracted for Project A alone, any combination of Projects B-G, or all Projects B-G.

For full details, including links to relevant documents and information on any Questions and Answers, visit:

https://grdc.com.au/research/applying-and-reporting/current-procurement/open-tenders

Background:

Machine learning (ML) could improve agronomic and farming systems decision support provided to growers. The grains industry conducts a lot of R&D targeting agronomy and farming systems R&D questions, with prominent R&D projects including: Better Fertiliser Decisions for Cropping, National Paddock Survey, and Grain and Graze. There is great opportunity to apply ML to this agronomy and farming systems R&D data, leading to outputs that can assist growers in making decisions.

Evaluation Criteria, Outcomes and Outputs:

Applications must address the evaluation criteria, outcomes, and outputs relevant to the specific procurement being applied for.

For details visit:

https://grdc.com.au/research/applying-and-reporting/current-procurement/open-tenders