Silva, J V and Ndour, A and Assefa, B and Desta, G and Mesfin, T and Ebrahim, M and Abera, W and Tamene, L and Nayak, H S and Sida, T S and Tesfaye, K (2026) Yield constraints in Ethiopia’s cereal production systems. Field Crops Research (TSI), 342. pp. 1-13. ISSN 0378-4290
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Context Cereals are of strategic importance for food and nutrition security in Ethiopia. Considerable yield gains have been reported in the country, yet farm yields remain well below their potential. Targeting technological solutions to current yield constraints can support efforts aiming to increase cereal productivity in a sustainable manner. Objective The objectives of this study were to quantify yield gaps for major cereals (tef, wheat and sorghum) and to identify the yield constraints under on-farm conditions across major production environments of Ethiopia. Methodology A large agronomic diagnostic survey with crop cut yield measurements was conducted for tef (n = 1131), wheat (n = 1721) and sorghum (n = 971) during the 2022 main (Meher) growing season. The survey was expanded with growing-season specific weather data, spatially predicted soil properties, and water-limited yields (Yw) simulated with crop models (or obtained from literature in the case of tef). Yield gaps were quantified as the difference between the water-limited yield and the measured actual yield. Field-specific yield constraints were identified with a machine learning approach, which explained 38–49% on the yield variability in independent test data. Model interpretation was done using SHAP plots and SHAP dependence plots for the most important predictors. Results Actual yields were on average 1.6 t ha−1 for tef, 3.4 t ha−1 for wheat, and 2.2 t ha−1 for sorghum, corresponding to a yield gap closure (defined as the ratio between actual and water-limited yields) of 47, 39 and 31% of Yw, respectively. Wheat yield gap closure was largest (50–60% of Yw) in North Shoa, which is indicative of increases in wheat productivity associated with increased fertilizer use, and lowest (20% of Yw) in North Wollo. The yield variability of the three crops was largely explained by biophysical conditions (e.g., average seasonal minimum and maximum temperature), except for sorghum for which plant population was one of the top predictors. Agronomic constraints for tef were mostly associated with sowing date, yet other important factors constraining tef yield variability (N fertilizer, seed rate, tillage and weed control) were not fully captured in our analysis. Agronomic constraints for wheat were largely associated with nutrient and disease management, and for sorghum with sub-optimal plant populations at harvest. Conclusion Variation in tef productivity was attributed to seasonal climatic conditions and agronomic management related to sowing dates. Nutrient and disease management remain important constraints to wheat yield, and there is scope for targeting interventions aiming to increase fertilizer rates and use efficiency across the country. Ensuring high plant populations during the cropping season, increasing fertilizer inputs and adopting practices that preserve soil moisture provide entry points to increase sorghum yields in the future. Significance Sustainable intensification strategies were identified for three major cereal crops in Ethiopia. Results provide disaggregated evidence of management by environment interactions driving yield variability and provide an entry point for integrated assessments of farm performance.
| Item Type: | Article |
|---|---|
| Divisions: | Research Program : East & Southern Africa |
| CRP: | UNSPECIFIED |
| Uncontrolled Keywords: | Food security, Sustainable intensification, Yield gaps, Random Forest, SHAP values |
| Subjects: | Others > Cereals Others > Sustainable Agriculture Others > Food Security Others > Ethiopia |
| Depositing User: | Mr Nagaraju T |
| Date Deposited: | 16 Apr 2026 08:40 |
| Last Modified: | 16 Apr 2026 08:40 |
| URI: | http://oar.icrisat.org/id/eprint/13599 |
| Official URL: | https://www.sciencedirect.com/science/article/pii/... |
| Projects: | UNSPECIFIED |
| Funders: | UNSPECIFIED |
| Acknowledgement: | This work was made possible through the OneCGIAR Initiative on Excellence in Agronomy (INV-005431). Accordingly, we thank the Bill and Melinda Gates Foundation and other funders supporting research through contributions to the CGIAR Trust Fund: https://www.cgiar.org/funders/. We also thank Robert Hijmans (UC-Davis) for the help retrieving the weather data, Hugo de Groot and Martin van Ittersum (WUR) for providing access to the water-limited yield data from www.yieldgap.org, and Andy McDonald (Cornell University) for stimulating discussions on the machine learning approach used in the analysis. Lastly, we are thankful to the researchers from different research centres, enumerators involved in the data collection and the hundreds of smallholders in Ethiopia who allowed us to conducted yield measurements in their fields and participated in the agronomic survey. |
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