Beyond the clipboard: data collection with GridScore NEXT
Key improvements to GridScore NEXT include enhanced data collection tools, supporting individual plant phenotyping within plots and enabling new data types such as GPS coordinates and image traits. GridScore NEXT provides customisable user defined validation rules to help prevent errors and incorporates barcode scanning for accurate, efficient data capture. The application offers an increased toolbox of data visualizations over its predecessor including heatmaps and statistical box plots, which aid in identifying potential data issues and understanding trial performance in the field. GridScore NEXT is cross-platform and can operate without an internet connection, making it ideal for field use in remote areas. Its adoption has led to standardisation of methods, significant error reduction, and the timely sharing of data, enabling quicker decision-making in pre-breeding and characterisation experiments. GridScore NEXT is available under an open-source (Apache 2.0) licence and freely available to all with no restrictions. It offers self-hosting options for enhanced data security and privacy. GridScore NEXT shows broad applicability across a diverse range of not only plant phenotyping experiments, but any experiment that requires the collection of accurate data.
Authors
- Tin Huynh Quang
- Gaynor McKenzie
- Manuel Feser (ORCID: https://orcid.org/0000-0001-6546-1818)
- Ruth Hamilton
- Sebastian Raubach (ORCID: https://orcid.org/0000-0001-5659-247X)
- Sarah Trinder (ORCID: https://orcid.org/0000-0002-0767-9912)
- Akanksha Singh (ORCID: https://orcid.org/0000-0001-6480-2641)
- Paul David Shaw
- Shivali Sharma (ORCID: https://orcid.org/0000-0001-5314-484X)
- Alan Humphries (ORCID: https://orcid.org/0000-0002-8700-4340)
- Susan McCallum (ORCID: https://orcid.org/0000-0001-7301-0494)
- Loi Huu Nguyen
- Miriam Schreiber
- Benjamin Kilian
Institutions
- FPT University (VN)
- James Hutton Institute (GB)
- Can Tho University (VN)
- Indian Council of Agricultural Research (IN)
- South Australian Research and Development Institute (AU)
- University of Warwick (GB)
- Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung (IPK) (DE)
- Global Crop Diversity Trust
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2026-01-21
- DOI
- https://doi.org/10.1186/s12859-025-06352-5
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Rural and Environment Science and Analytical Services Division
- James Hutton Institute
- Crop Trust