GNAFOR Field Collector a mobile-first web application for systematic field data collection in tropical forage grass experiments

GNAFOR Field Collector is an open-source, mobile-first web application for systematic field data collection in tropical forage grass experiments. Implemented as a single self-contained HTML file (HTML5/CSS3/JavaScript) under the MIT licence, the application requires no installation, has no external runtime dependencies, and operates fully offline, synchronising data to a Google Sheets spreadsheet when connectivity is restored. It provides four purpose-built data entry modules — leaf morphogenesis, tillering counts, dry mass production, and canopy height — together with automatic GPS tagging every 30 s, an offline local-storage queue with automatic retry and a soft / hard occupancy gauge, client-side input validation with biologically meaningful sanity checks, a bilingual Portuguese / English interface with a runtime language selector, CSV export with UTF-8 BOM encoding, a high-contrast accessibility mode, an in-app configuration overlay for non-technical users, and an automated test suite executed in continuous integration. The application was developed and validated in the Dunamis Experiment (Urochloa decumbens cv. Basilisk, deferred grazing study, UEMG – Unidade Divinópolis, Brazil, 2026), and is configurable for use with any tropical forage species; it addresses a methodological gap in tropical pasture research by replacing paper-based records with a digital, GPS-tagged, real-time system adapted to low-connectivity field environments.

Authors

Institutions

Publication Details

Journal
SoftwareX
Published
2026-06-19
DOI
https://doi.org/10.1016/j.softx.2026.102828
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

GNAFOR Field Collector a mobile-first web application for systematic field data collection in tropical forage grass experiments

Vinicius Valim Pereira
SoftwareX
Remote Sensing in Agriculture
article

GNAFOR Field Collector a mobile-first web application for systematic field data collection in tropical forage grass experiments

Vinicius Valim Pereira
article en

Abstract

GNAFOR Field Collector is an open-source, mobile-first web application for systematic field data collection in tropical forage grass experiments. Implemented as a single self-contained HTML file (HTML5/CSS3/JavaScript) under the MIT licence, the application requires no installation, has no external runtime dependencies, and operates fully offline, synchronising data to a Google Sheets spreadsheet when connectivity is restored. It provides four purpose-built data entry modules — leaf morphogenesis, tillering counts, dry mass production, and canopy height — together with automatic GPS tagging every 30 s, an offline local-storage queue with automatic retry and a soft / hard occupancy gauge, client-side input validation with biologically meaningful sanity checks, a bilingual Portuguese / English interface with a runtime language selector, CSV export with UTF-8 BOM encoding, a high-contrast accessibility mode, an in-app configuration overlay for non-technical users, and an automated test suite executed in continuous integration. The application was developed and validated in the Dunamis Experiment (Urochloa decumbens cv. Basilisk, deferred grazing study, UEMG – Unidade Divinópolis, Brazil, 2026), and is configurable for use with any tropical forage species; it addresses a methodological gap in tropical pasture research by replacing paper-based records with a digital, GPS-tagged, real-time system adapted to low-connectivity field environments.

SoftwareXVol. 35
Universidade do Estado de Minas Gerais (BR), National Research Development Institute for Animal Biology and Nutrition (RO)
Openalex Percentile: Top 7%
Remote Sensing in Agriculture
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.