Water Limited Yields & Optimum Maize Sowing Time & Variety Recommendation Summary for Kenya 

Background
Maize is part of a the diet for millions of people in Kenya. The crop is cultivated on about 1.5 million hectares of arable land. The average production is less than 2 t/ha, against a yield potential of even more than 10t/ha. The yield gap is attributed, to poor fertility management and climate risks (KALRO, 2024). This research therefore sought to enhance development of fertilizer recommendations and improve climate resilience. This was undertaken through simulation of potential water limited yields under different season types and varieties at scale for Kenya. 

Methodology
Kenya, has extreme agro-ecologies, with high maize potential in the Western Kenya, as opposed to the rest of the country. The CGIAR-Excellence in Agronomy (EiA) Initiative, sought to determine the water limited yields, optimum sowing dates and variety for Maize in Kenya, through use of the AgWise Water Limited Yield crop modelling platform. The AgWise modelling framework comprises of a variety of crop models, such as APSIM, DSSAT, WOFOST and Oryzae. This activity utilized the spatialized DSSAT 4.8 crop model, which was coupled with weather and soil from CHIRPS and AgERA5 and soil from ISRIC. DSSAT crop model spatialisation was enabled through of the DSSAT R-Package (Alderman, 2020). The model was calibrated based on a combination of field experimental data and expert feedback. Simulations based on 22-year historical data from, 2000, for 3 generic (short, medium and long), varieties over 916 weekly sowing dates. The simulation outputs were aggregated across different sowing dates, varieties and ENSO phases. This therefore enabled determination of the optimum sowing dates across different varieties and season types. The date with the highest median yield was referred to as the optimum sowing date, Specifically, season types were determined through classification of the season across the 3 ENSO phases. Determination of ENSO phases was undertaken through use of the Oceanic Niño Index (ONI), where an ONI value of greater and less than 0.5 OC, signifies an El Nino and La Nina respectively. ONI value between -0.5 and 0.5, signifies it is a neutral. 

Results
The analytics framework aggregated all the Maize yield data across different sowing dates, varieties and ENSO phases for Kenya. Specifically, early sowing around 2-March, led to high yields across all ENSO phases, compared to the rest of the sowing window. The impact of ENSO is significant even earlier in the season, as yields are low despite sowing early under the La Nina and Neutral, ENSO phases (Figure 1).


Figure 1: Maize yield response to varying sowing dates across different varieties and ENSO phases in Kenya. 

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Figure 2: Maize grain yield (a)-summaries, (b)- stability, across different sowing dates, varieties and ENSO phases for Kenya.

There is greater yield stability on cultivation of short and medium season varieties, despite the very low yields, compared to long seasoned varieties. There was high yield variability under the El Nino and Neutral conditions, compared to the La Nina conditions (Figure 2).



Figure 4: Mean yield distribution across different varieties and ENSO phases for Maize in Kenya.

El Nino caused slightly higher yields along the north western regions of Kenya, compared to La Nina and Neutral conditions. Pattern was also more notable for the short-seasoned varieties where La Nina and Neutral conditions, had very low yields as compared to under Nino (Figure 4).


Figure 5: Maize grain yield standard deviation across different varieties and ENSO phases for Kenya.

There is higher standard deviation, translating to lower yield stability, in the western parts of Kenya as opposed to the North and South. Nino had slightly higher variability compared to other phases across the different varieties (Figure 5). 

Figure 6: Optimum sowing dates across different varieties and ENSO phases for Maize in Kenya.

The earliest sowing dates (early March) are realized in mostly short and medium varieties, across all ENSO phases. Long seasoned varieties need proper timing across the different varieties and ESNO phases. Long seasoned varieties have slightly delayed optimum dates of Early April. Nino actually had the earliest sowing dates, especially in Short and Medium and less so in the long-seasoned variety (Figure 6).

Conclusion
Timing of sowing is critical across different ENSO phases and varieties in Kenya. The optimum sowing dates also vary by region and ENSO phase. There is less yield variability of dates under the different varieties. 

Additional information
The scripts used for simulations and analysis are available on .
The data used for DSSAT model calibration is publicly available.

Suggested citation
Chernet M, Mkuhlani S, Chimonyo VGP, Urfels A, Moreno P, Bendito EG, Sila A, llanos L, Degifie T, Seid JA, Abera W, Devare M. 2024. Water limited yields and optimum maize sowing time and variety recommendation summary for Kenya. CGIAR Excellence in Agronomy (EiA) Initiative. AgWise-Potential Yield. Use Case-Country Reports. 6pp.


Reference
KALRO, 2024. Maize production in Kenya. https://www.kalro.org/maize/

 NB: i-The outputs are constantly under revision
ii-The outputs should only be used to provide a general recommendation, due to the potential uncertainty from the use of gridded geo-spatial data sets. The recommendations therefore need to be used in consultation with local experts.



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