Machine Learning in Agriculture

Machine learning applied to high-throughput feature extraction from imagery to map spatial variability.


A technology and analytics platform for improving variety selection.

Optimising Canola Phenology

Optimising Canola Phenology for Australian Target Production Environments

Genetic diversity toolkit

A genetic diversity toolkit to maximise harvest index by controlling the duration of developmental phase

National Phenology Initiative

A nationally validated model of wheat and barley flowering time that can be parameterised for new cultivars using molecular markers, genomic data and/or controlled environment phenotypic data.

Landscape frost

Spatial temperature measurement and mapping tools to assist growers, advisors and extension specialists manage frost risk at a farm scale

Low rainfall

Climate extremes in the low rainfall region of the wheat belt

Trait assessment

Raising water productivity: Trait assessment for Australian rainfed wheat

Frost situation

Frost situation analysis in Australia

National Variety Trial

Adding value to GRDC's National Variety Trial network

Wheat adaptation

Adapting wheat to future warm and dry climates: improved simulation of flowering and tillering