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Ginger Ninja: Automating disease detection in seed ginger stock

Pests and diseases pose a significant production concern to most ginger growers and are a constant threat to yields. Fusarium, in particular, is a key threat to ginger seed stock as it can be spread through soil from infected plant material. This project pilots the development of an automated vision system for pest and disease management that is capable of robustly identifying signs of Fusarium in seed ginger stock. The greater intent is to achieve automation for sorting diseased from non-diseased ginger.

Project date

1 Jul 2019-16 Apr 2021
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Principal investigator

Matthew Dunbabin

Project led by

Multiple industries
Alternative protein Aquaculture Cereal grains Cross industry Essential oils Fruits Game Honey bees Nuts Other rural industries Pasture, fodder & feed Poultry Pulse grains

AgriFutures Australia

AgriFutures Australia proudly focuses on building a rich future for Australian agriculture. We live and work in the regions and …

Multiple industries
Alternative protein Aquaculture Cereal grains Cross industry Essential oils Fruits Game Honey bees Nuts Other rural industries Pasture, fodder & feed Poultry Pulse grains
  • Location

    Australia

  • Organisation type

    Research funding body

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Technology areas

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