Disease Detection in Ginger Rhizomes

Whilst the ginger industry generates $32 million gross volume for fresh ginger and $50 million in semi - processed ginger, disease is significantly impacting yield and reducing labour inputs.

Fusarium yellow rot is the most common disease with 30-80% losses on some ginger patches occurring.

Zondii aims to address this problem by using multispectral technology with a database model to instantly detect Fusarium in ginger rhizomes prior to planting, via a smartphone.

Project date

31 Aug 2022-11 Apr 2024

Visit website

Enquire about this project

Fill in the information to submit your enquiry about this research project.

First name

Last name

Email address

Contact phone number

Organisation Organisation

Organisation type

Industry

Country

Please tell us which of the following you are

Please tell us a little bit more about your enquiry

Subscribe to receive news and announcements from AgriFutures grow^AG. straight to your inbox.

By submitting this form, you agree that you have read and accept the AgriFutures Australia privacy policy and General Collection Statement

Principal investigator

Danielle Morton

Research organisations

Zondii

Project funded by

Multiple industries

AgriFutures Australia

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

Location
Australia
Organisation type
Research funding body

Focus areas

Industries

Sustainabilities

Technology areas

Related research projects

Search all research projects

Cross industry

Australian Extension Capacity and Capability - A map and a gap analysis

Undertake a mapping and gap analysis project investigating extension capacity and capability resources at a national level, with an RD&…

Funded by
AgriFutures Australia
Project date
14 Apr 2024 - 14 Sep 2024
Research organisation
Enablers of Change

Cross industry

Identifying opportunities from collaborating along and across value chains.

A value-chain involves collaboration, including a willingness to share ideas and resources; knowledge of what is happening upstream and downstream …

Funded by
AgriFutures Australia
Project date
11 Apr 2024 - 16 Jun 2024
Research organisation
SGA Solutions

Pasture, fodder & feed

Dispelling value uncertainty for hay growers – application of high-throughput, low-cost phenomics to predict Oaten hay quality in-crop fields, while improving oat breeding selection efficiency.

Oaten hay quality is determined by the variety grown, management of the crop and environmental conditions, and then estimated once …

Funded by
AgriFutures Australia
Project date
1 Apr 2024 - 14 Jan 2027
Research organisation
The University of Adelaide (UA)

Have questions?

Find out how we can help you.

Find answers to our most frequently asked questions on research projects, commercial opportunities, organisations and more.

Still have questions or have feedback on the site? Please get in touch by completing our enquiry form.

Frequently asked questions Enquire now