Contact us: [email protected] or @germinatehub on Twitter.
Remember, the GridScore documentation with detailed descriptions of each aspect of GridScore is available in case you need it: https://cropgeeks.github.io/gridscore-next-client/
GridScore is available at https://gridscore.hutton.ac.uk
GridScore can be used for pretty much any type of data recording as long as you can define what you want to record data for - the subject of your study - and what attributes/variables you want to record for the subject.
As examples, you could use GridScore to record data on:
- Phenotypic field trials: The original purpose of GridScore was to record trait data for plots of germplasm including things like 'Plant height', 'Yield', 'Disease resistance' for plots or individual plants of things like barley, soft fruits, potatoes or any other crop.
- Laboratory samples: Instead of creating a field layout grid, you can simply define your subjects as a list. This'll allow you to record things like "Colony count" for petri dishes or chemical composition measurements for manganese, copper or beta-glucan on a sample.
- Wild sample collection / Wild specimen sighting: Use a GPS-trait to record the location of where you found a wild specimen and record data on things like "Size", "Taxonomy" or "Health status".
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Keep in mind that GridScore doesn't dictate how you use it. As long as you specify what your subjects and variables are, GridScore allows you to record data for them.
GridScore has been developed by the Information & Computational Sciences Department at the James Hutton Institute just outside of Dundee in Scotland. We have been developing GridScore since around 2020 and recently years there has been a significant improvement on the functionality that GridScore offers its users as well as a significant increase in the interest it generates. For more information on the James Hutton Institute you can have a look at our webpage.
From originally only storing date-based traits and having no data visualizations GridScore now covers every aspect of data collection with support for various data types and data visualizations as well as advanced data synchronization between devices.
We are also keen to get feedback and hear from users on how we can improve the platform.
GridScore supports the Breeding API (BrAPI) for trial creation and data synchonization which means it can communicate with any BrAPI-compliant data provider.
GridScore uses a technology called Progressive Web Apps (PWA) which allows it to run on pretty much any device that can run a web browser but work offline at the same time.
You can access GridScore at https://gridscore.hutton.ac.uk from your laptop, mobile phone or tablet. On mobile devices, it may prompt you to install the app which is recommended as it gives you the best experience.
On Android, there is a dedicated native app that can be installed through Google Play - just search for GridScore NEXT.
There is more information about how to install GridScore at https://cropgeeks.github.io/gridscore-next-client/installation.html but keep in mind that you don't have to install it to use it.
Yes, GridScore is free to use for anyone whether you're using it for academic or commercial purposes. Please not that we appreciate any support you may be able to offer. Get in touch if you would like to support the further development of GridScore.
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What devices does GridScore run on?
Answer: Pretty much any device that can run a web browser including PCs, laptops, tablets and smartphones. -
Is GridScore free to use?
Answer: Yes, it's completely free and open-source. -
Does GridScore support the Breeding API?
Answer: Yes, GridScore can import trial designs and traits during setup and it can export data to BrAPI compliant data providers.
It may be worth adding a bookmark to the GridScore training page.
Next Steps: We have learned a bit about GridScore and how to access it, now let's have a look at the main GridScore user interface in Session 2.
This training is free to use and released under a non-restrictive open source licence.
