ArticleScientific data2025
An Africa-wide agricultural production database to support policy and satellite-based measurement systems.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed.
- Disruptions of global crop yields.Nature food · 2026Article
- African Crop Calendar: A geo-referenced dataset of crop growing seasons across diverse agro-ecological regions.Scientific data · 2026Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Agriculture remains a backbone of the African economy, contributing up to 70% of household income in rural areas. Yet crop yields across Africa are rising at a slower rate than the global average. Currently, strategies to improve agricultural productivity are limited by the availability of granular, accurate, and spatially-extensive data. These disaggregated statistics are required to understand how crop yields respond to climate variability, climate extremes, and agronomic practices. Here, we present GROW-Africa, a database that includes n = 535,844 georeferenced observations of crop yields across Africa focusing on 25 key crops including maize, sorghum, cassava, groundnuts, cowpeas, rice, yams, and millet. The database assimilates observations from a range of spatial scales, from regional government statistics, to household farmer surveys, to plot-level crop cuts. We use co-located observations to identify sources of bias and error in these varied data types. Finally, we demonstrate how the GROW-Africa database can be used to train remote sensing algorithms to produce continuous maps of crop yields across Africa.
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Registered trials
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