首页|Identifying low risk and profitable crop management practices for irrigated Teff production in northwestern Ethiopia
Identifying low risk and profitable crop management practices for irrigated Teff production in northwestern Ethiopia
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NSTL
Elsevier
? 2022 The AuthorsTeff (Eragrostis tef (Zucc.) Trotter) is one of the most important staple crops in Ethiopia. However, the optimal agronomic practices of the crop under irrigation remain unclear. The objectives of this study were to evaluate the Cropping System Model (CSM)-NWheat-Teff and to determine the optimum planting date, nitrogen (N) application rate, and irrigation threshold in northwestern Ethiopia. The model was calibrated and evaluated using published data from field experiments conducted from 1996 to 1998 in the Adet and Bichena districts and from 2001 to 2003 in the Dangila district. The model was then used to simulate different planting dates (Jan 1, Jan 15, Feb 1, Feb 15, Mar 1), N rates (0, 20, 40, 60, 80 kg ha?1), and irrigations (irrigation when required/automated, 50% and 25% available soil moisture thresholds) levels for Adet, Bichena and Dangila using historical weather data (1983–2020). The model was able to simulate teff phenology and yield adequately as indicated by low root mean square error (RMSE) and a high index of agreement (d) for both the calibration and evaluation datasets. Grain and straw yield increased with increasing N, but the rate of increment was higher under irrigation when required (automated) compared to 50% and 25% thresholds. Late planting (March 1) at Adet and early planting (January 1 and February 15) at Bichena and Dangila resulted in the highest profit with a minimum variability in output. The combined use of 80 kg N ha?1 and irrigation when required gave the most profitable option with low risk of irrigated teff production at the three sites studied. This study showed that the new CSM-NWheat-Teff model can be used to optimize agronomic practices for irrigated teff production systems in Ethiopia. Further research is needed to improve model performance in predicting teff yield for contrasting biophysical and socio-economical environments.
NSTL
Elsevier
