Random forest machine learning for maize yield and agronomic efficiency prediction in Ghana
Most Cited Paper
in Crop Yield and Soil Fertility
18 Months Post-Publication
Class of 2026
“Random forest machine learning for maize yield and agronomic efficiency prediction in Ghana”
A research intelligence initiative by Pepkio
pri.pepkio.com/top-papers/crop-yield-and-soil-fertility/2026/
Topics
Random forest · Maize yield prediction · Agronomic efficiency · nutrient use efficiency · fertilizer application · soil variables · climate variables · nested cross-validation · model efficiency coefficient · prediction interval coverage probability · AE-N · AE-P · AE-K · georeferenced treatment plots · field trials · temperature · rainfall · Sub-Saharan Africa · Ghana
Share
Cite this ranking
Pepkio Research Index (PRI). Topics and Trends in Most Cited Crop Yield and Soil Fertility Papers, Class of 2026. https://pri.pepkio.com/top-papers/crop-yield-and-soil-fertility/2026. Accessed 2026-07-20. Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459