Meat & Livestock News

$6.5 Million AI Project Set to Revolutionise Grazing Planning for Livestock Producers


  • A new $6.5 million project, Foragecaster, aims to utilise Artificial Intelligence (AI) to enhance on-farm forecasting for livestock producers, focusing on predictive data to navigate climate change risks.
  • The project is a collaboration between ten industry research and agtech stakeholders, including Food Agility CRC, Cibo Labs, and Meat & Livestock Australia, and is set to run over three years.
  • Foragecaster will integrate seasonal climate forecasts with pasture and livestock growth models, offering producers a variety of management scenarios through AgriWebb’s livestock management software.

In an ambitious move to empower livestock producers with cutting-edge planning tools, a consortium of ten industry research and agtech stakeholders has launched Foragecaster, a $6.5 million project leveraging Artificial Intelligence (AI).

This three-year initiative seeks to transform grazing planning by providing livestock producers with AI-supported tools to make informed decisions amidst the challenges posed by changing climate conditions.

The collaboration includes notable partners such as Food Agility CRC, Cibo Labs, Meat & Livestock Australia (MLA), AgriWebb, FlintPro, along with research institutions like the Queensland University of Technology, University of Technology Sydney, University of New England Smart Farm, NSW Department of Primary Industries, and agtech leader Optiweigh.

Foragecaster’s goal is to merge seasonal climate forecasts with models of pasture and livestock growth, enabling producers to explore various management scenarios. This innovative tool will be accessible through AgriWebb’s existing livestock management software, aiming to significantly impact how producers plan and manage their resources.

The initiative was preceded by a nine-month feasibility study, which involved over 30 hours of interviews with producers. This research phase helped the team gauge the market demand for such planning tools and gather insights on the integration of Machine Learning (ML) techniques for predicting livestock and pasture growth.

Dr Mick Schaefer, Food Agility’s chief executive, highlighted the role of improved satellite imagery in facilitating data-driven grazing decisions. The Foragecaster project plans to use this imagery to predict landscape changes due to weather events, climate change, or farm management practices, thus aiding the creation of a future-proof grazing planner.

John McGuren, MLA project manager, and Dr Kenneth Sabir, AgriWebb’s vice president of research and development, both emphasised the project’s alignment with the industry’s move towards a data-driven culture. They noted Australian livestock producers’ proficiency in data collection and the growing interest in leveraging this data for enhanced planning and risk mitigation.

Rob Gordon, a livestock producer from the Southern Tablelands, expressed enthusiasm for the Foragecaster application, citing the potential productivity and environmental benefits of combining extensive research with advanced technology and ML.

This groundbreaking project represents a significant step forward in the use of technology in agriculture, promising to equip producers with the tools needed to navigate the complexities of modern farming practices more effectively.