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329 results

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Multiple industries
Cereal grains Pulse grains
Imagery
Research project

CropPhen: Remote mapping of grain crop type and phenology

This project aims to develop a software-based tool to remotely map crop type (wheat, barley, chickpea, lentils, sorghum and mungbean) …

Multiple industries
Cereal grains Pulse grains
Imagery
  • Funded by

    Grains Research and Development Corporation (GRDC)

  • Project date

    24 Feb 2020 -
    30 Jan 2024

  • Research organisation

    The University of Queensland (UQ)

Logo for CropPhen: Remote mapping of grain crop type and phenology
Multiple industries
Cereal grains Oilseeds Pasture, fodder & feed Pulse grains
Data and AI
Research project

Identifying a machine learning approach to weed recognition in Australian grain production systems

The project will create an open source weed image library to make weed recognition data freely available to the weed …

Multiple industries
Cereal grains Oilseeds Pasture, fodder & feed Pulse grains
Data and AI
  • Funded by

    Grains Research and Development Corporation (GRDC)

  • Project date

    17 Feb 2020 -
    16 Feb 2021

  • Research organisation

    The University of Sydney (USYD)

Logo for Identifying a machine learning approach to weed recognition in Australian grain production systems
Multiple industries
Cereal grains Oilseeds Pasture, fodder & feed Pulse grains
Data and AI
Research project

Applying machine learning to improve genetic gain delivered from genomic selection in plant breeding

Machine learning is the next-generation solution to identifying patterns in large datasets and involves using computer science and statistics to …

Multiple industries
Cereal grains Oilseeds Pasture, fodder & feed Pulse grains
Data and AI
  • Funded by

    Grains Research and Development Corporation (GRDC)

  • Project date

    17 Feb 2020 -
    16 Feb 2022

Logo for Applying machine learning to improve genetic gain delivered from genomic selection in plant breeding
Multiple industries
Cereal grains Oilseeds Pasture, fodder & feed Pulse grains
Data and AI
Research project

Using machine learning to increase genetic gain in canola blackleg resistance breeding

This project will extend current research into deep learning and the genomics of disease resistance and apply findings to improve …

Multiple industries
Cereal grains Oilseeds Pasture, fodder & feed Pulse grains
Data and AI
  • Funded by

    Grains Research and Development Corporation (GRDC)

  • Project date

    17 Feb 2020 -
    16 Feb 2022

  • Research organisation

    The University of Western Australia (UWA)

Logo for Using machine learning to increase genetic gain in canola blackleg resistance breeding
Multiple industries
Cereal grains Oilseeds Pasture, fodder & feed Pulse grains
Data and AI
Research project

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

This project will advance upon existing techniques for image analytics by setting up datasets from a greater range of situations, …

Multiple industries
Cereal grains Oilseeds Pasture, fodder & feed Pulse grains
Data and AI
  • Funded by

    Grains Research and Development Corporation (GRDC)

  • Project date

    17 Feb 2020 -
    16 Feb 2022

  • Research organisation

    The University of Queensland (UQ)

Logo for Machine learning applied to high-throughput feature extraction from imagery to map spatial variability
Multiple industries
Cereal grains Oilseeds Pulse grains
Data and AI
Research project

Using Machine Learning To Develop New Methods For Genetic Gain In Crops Challenged By Fungal Diseases

This project will apply a machine learning approach to genetic and high throughput phenotyping data to draw out genetic markers …

Multiple industries
Cereal grains Oilseeds Pulse grains
Data and AI
  • Funded by

    Grains Research and Development Corporation (GRDC)

  • Project date

    17 Feb 2020 -
    16 Feb 2022

  • Research organisation

    Curtin University

Logo for Using Machine Learning To Develop New Methods For Genetic Gain In Crops Challenged By Fungal Diseases
Multiple industries
Cereal grains Oilseeds Pulse grains
Data and AI
Research project

Machine learning to map soil constraint variability and predict crop yield

This project will use a variety of Machine Learning techniques to bring together previously underutilised on-farm, satellite, and weather data …

Multiple industries
Cereal grains Oilseeds Pulse grains
Data and AI
  • Funded by

    Grains Research and Development Corporation (GRDC)

  • Project date

    17 Feb 2020 -
    31 Oct 2021

  • Research organisation

    The University of Sydney (USYD)

Logo for Machine learning to map soil constraint variability and predict crop yield
Multiple industries
Cereal grains Oilseeds Pulse grains
Data and AI
Research project

Deep Learning for early detection and classification of crop disease and stress

This project will utilise deep learning for the detection, identification, and evaluation of crop stress factors using a variety of …

Multiple industries
Cereal grains Oilseeds Pulse grains
Data and AI
  • Funded by

    Grains Research and Development Corporation (GRDC)

  • Project date

    17 Feb 2020 -
    16 Feb 2022

  • Research organisation

    The University of Western Australia (UWA)

Logo for Deep Learning for early detection and classification of crop disease and stress
Cereal grains
Automation
Research project

SIP2 - Smarter irrigation in rice growing systems - John Hornbuckle

As the Australian rice industry moves to implement 'Dry Rice' strategies that aim to minimise ponded water time and reduce …

Cereal grains
Automation
  • Funded by

    AgriFutures Australia

  • Project date

    15 Jan 2020 -
    15 Feb 2022

  • Research organisation

    Cotton Research and Development Corporation (CRDC)

Logo for SIP2 - Smarter irrigation in rice growing systems - John Hornbuckle
Multiple industries
Cereal grains Oilseeds Pasture, fodder & feed Pulse grains
Input management
Research project

Maximising The Uptake Of Phosphorus By Crops To Optimise Profit In Central And Southern NSW, Victoria And South Australia

This project explores the effect fertiliser placement has on nutrient (and water) use efficiency given nutrient stratification, soil water availability …

Multiple industries
Cereal grains Oilseeds Pasture, fodder & feed Pulse grains
Input management
  • Funded by

    Grains Research and Development Corporation (GRDC)

  • Project date

    10 Jan 2020 -
    30 Apr 2024

  • Research organisation

    Department of Regional New South Wales (DRNSW)

Logo for Maximising The Uptake Of Phosphorus By Crops To Optimise Profit In Central And Southern NSW, Victoria And South Australia
Cereal grains
Plant science
Research project

Utilising novel genetic diversity to increase Barley yields nationally

This project aims to utilize an exotic barley population (HEB-25) to enhanced yield potential of future Australian barley varieties by …

Cereal grains
Plant science
  • Funded by

    Grains Research and Development Corporation (GRDC)

  • Project date

    1 Jan 2020 -
    31 Mar 2023

  • Research organisation

    The University of Adelaide (UA)

Logo for Utilising novel genetic diversity to increase Barley yields nationally
Cereal grains
Food processing technology
Research project

LMA Project B – A novel high-throughput, low-cost test to determine cause of starch damage in wheat grain

Late maturity ?-amylase (LMA) is a grain defect causing a reduction in Hagberg falling number and results in potential failing …

Cereal grains
Food processing technology
  • Funded by

    Grains Research and Development Corporation (GRDC)

  • Project date

    1 Jan 2020 -
    31 Dec 2022

  • Research organisation

    Department of Jobs Precincts and Regions (DJPR) [Vic]

Logo for LMA Project B – A novel high-throughput, low-cost test to determine cause of starch damage in wheat grain
Multiple industries
Cereal grains Oilseeds Pasture, fodder & feed Pulse grains
Crop protection
Research project

Facilitating adoption of integrated weed management strategies for feathertop Rhodes grass in the northern region, Prg 2. (southern NSW)

Feathertop Rhodes grass is a highly aggressive weed that is continuing to increase in incidence and severity in northern farming …

Multiple industries
Cereal grains Oilseeds Pasture, fodder & feed Pulse grains
Crop protection
  • Funded by

    Grains Research and Development Corporation (GRDC)

  • Project date

    1 Dec 2019 -
    30 Jun 2022

  • Research organisation

    Department of Regional New South Wales (DRNSW)

Logo for Facilitating adoption of integrated weed management strategies for feathertop Rhodes grass in the northern region, Prg 2. (southern NSW)
Multiple industries
Cereal grains Cotton Fruits Oilseeds Pulse grains Wine
Crop protection
Research project

Area Wide Management for cropping systems weeds: investigating the weed management, social and economic opportunity

The traditional approach to tackling weeds has been to focus on paddock or farm scale management. Instead this project aims …

Multiple industries
Cereal grains Cotton Fruits Oilseeds Pulse grains Wine
Crop protection
  • Funded by

    Grains Research and Development Corporation (GRDC)

  • Project date

    1 Nov 2019 -
    30 Jun 2022

  • Research organisation

    Commonwealth Scientific and Industrial Research Organisation (CSIRO)

Logo for Area Wide Management for cropping systems weeds: investigating the weed management, social and economic opportunity
Multiple industries
Cereal grains Oilseeds Pulse grains
Imagery
Research project

Synchrotron Postdoctoral Fellow no. 1: Soil - root interactions using intact field soil cores.

Research on root morphology, distribution and function are complicated by the difficulties associated with taking root measurements without causing root …

Multiple industries
Cereal grains Oilseeds Pulse grains
Imagery
  • Funded by

    Grains Research and Development Corporation (GRDC)

  • Project date

    15 Oct 2019 -
    30 Jun 2023

  • Research organisation

    The University of Queensland (UQ)

Logo for Synchrotron Postdoctoral Fellow no. 1: Soil - root interactions using intact field soil cores.
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