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Sankore

Named after the University of Sankore in Timbuktu — one of the world’s oldest centres of learning. Every figure here is computed from work-level records in our own graph, never copied from a source’s summary count.

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Coverage is partial and says so. A country appears with its research output only once its works have been swept; until then the portal shows whatever the graph happens to hold for it and labels it as exactly that.

Modeling maize yield and agronomic efficiency using machine learning models: A comparative analysis

2025Agronomy JournalJournalOpen access

10.1002/agj2.70206 Full text1 citations

Authors

4 authors across 6 institutions in 4 countries.

Eric AsamoahFirst authorCorresponding
- Université Mohammed VI Polytechnique (MA)
- Council for Scientific and Industrial Research (GH)
Gerard B.M. Heuvelink
as printed: Gerard B. M. Heuvelink
Prem S. Bindraban
- Africa Rice Center (CI)
Vincent LogahSenior author
- Kwame Nkrumah University of Science and Technology (GH)

Fields

Assignment is probabilistic — a work belongs to several fields in proportions.

Climate change impacts on agriculturelevel 3 · 0.21
Smart Agriculture and AIlevel 3 · 0.18
Crop Yield and Soil Fertilitylevel 3 · 0.14

Sources

Several sources describing one work is the point — it means the record rests on more than one authority.

openalexseen September 9, 2026
2025 · Agronomy Journal · 1 citations
https://openalex.org/W4415621301

Modeling maize yield and agronomic efficiency using machine learning models: A comparative analysis · Sankore