Automation of seed performance testing

Lead Research Organisation: John Innes Centre
Department Name: Crop Genetics

Abstract

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Publications

10 25 50
 
Description There was no scientific research funded on this grant because it was a pathfinder follow-on grant. Instead we conducted market research and background Intellectual property searches to determine the commercial value, if any of new artifical intelligence based software we developed for scoring germination. outcomes include a market report from a consultancy called England Marketing, which outlines the potential market size for the software and identifies a likely user base. A second outcome was an IP report from Venner Shipley which used a global search of patent databases to identify patents in the area of the new technology.
Exploitation Route The outcomes are designed to be used internally for us to develop a commercialisation strategy for the new software
Sectors Agriculture, Food and Drink

 
Description Our new software under development here has been used by three companies in different ways. The first company has a license and uses the software for routine seed technology applications, including research into optimising priming for individual seed batches, or optimising heat treatments for seed sterilisation. A second company has paid a fee to evaluate the hardward and software for their seed technology purposes, but decided not to use the technology further. A third company has paid us for a service to evaluate germplasm and this project helped them decide which varieties had high germination performance such that they could be brought forward to market.
First Year Of Impact 2018
Sector Agriculture, Food and Drink
Impact Types Economic

 
Description Collaboration with the Earlham Institute 
Organisation Earlham Institute
Country United Kingdom 
Sector Academic/University 
PI Contribution We provided expertise in seed germination, and datasets of images of seed germination in a number of species.
Collaborator Contribution Our collaborators used their expertise in machine learning and computer vision to develop algorithms for scoring seed germination
Impact This is an interdisciplinary collaboration, the disciplanes being plant science and artifical intelligence. The outcome is a new automated software tool for scoring seed germination from image stacks.
Start Year 2016
 
Description collaboration with syngenta seeds 
Organisation Syngenta International AG
Department Syngenta Seeds
Country Switzerland 
Sector Private 
PI Contribution we identified a joint research inetrest in automation of seed vigour testing. we provided software for testing for automatic calculation of germination parameters.
Collaborator Contribution They provided seeds and expertise in germination box design.
Impact computer science plant science
Start Year 2016
 
Description market survey for seed germ technology 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Industry/Business
Results and Impact We undertook a market survey by telephone of major seed industry companies, government sector and research institutes based in the UK and Europe. The feedback will help us evaluate the commercial potential of our new technology. The outcome is raised awareness of the technology and how it can be used by seed companies.
Year(s) Of Engagement Activity 2017,2018