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.

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Institutions

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

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article

Beyond the clipboard: data collection with GridScore NEXT

Tin Huynh Quang, Gaynor McKenzie, Manuel Feser, Ruth Hamilton et al.
BMC Bioinformatics
Remote Sensing in Agriculture
article

Beyond the clipboard: data collection with GridScore NEXT

Tin Huynh Quang, Gaynor McKenzie, Manuel Feser, Ruth Hamilton, Sebastian Raubach, Sarah Trinder, Akanksha Singh, Paul David Shaw, Shivali Sharma, Alan Humphries, Susan McCallum, Loi Huu Nguyen, Miriam Schreiber, Benjamin Kilian
article en

Abstract

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.

BMC BioinformaticsVol. 27(1)
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
Rural and Environment Science and Analytical Services Division, James Hutton Institute, Crop Trust
Peace, Justice and strong institutions
Openalex Percentile: Top 85%
Remote Sensing in Agriculture
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