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Maize Yield Prediction — Uasin Gishu County, Kenya

IBM SkillsBuild Data Analytics Bootcamp

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Project Summary

This project predicts annual maize yield (t/ha) in Uasin Gishu County, Kenya using seasonal weather, soil, and seed management data from 2012–2023.

Key Findings

  • Rainfall timing matters more than total volume
  • Pre-planting conditions (Sep–Nov) shape the following harvest
  • Soil acidity (pH 5.7) explains the structural yield gap of ~6.5 t/ha

Model Performance

  • Algorithm: Random Forest + SVR
  • Validation: Leave-One-Out Cross-Validation (n=12)
  • LOO RMSE: 0.364 t/ha (10% of county average)
  • LOO R²: 0.304

Data Sources

  • Ministry of Agriculture & Livestock Development, Kenya
  • NASA POWER Climate Data
  • Lomurut (2014), Purdue University
  • CIMMYT / Tegemeo Institute

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Maize Yield Prediction — Uasin Gishu County, Kenya — Machine Learning Models with LOOCV RMSE 0.364 t/ha

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