Enhancing response farming for improved strategic and tactical agronomic adaptation to seasonal rainfall variability under the semi-arid conditions of Ethiopia
Date
2013
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Sokoine University of Agriculture, Morogoro, TZ
Abstract
The research developed a strategic predictor capable of advanced prediction of rainfall parameters by a lead time of two to three months, a marked improvement over previous forecasting. Using the amount of off-season and cumulative early-season rainfall, seventeen prediction models that can facilitate in-season tactical response farming (RF) were developed. Predictive capacity is crucial for rainfall variability and farming conditions in the drylands of Ethiopia. An increased maize grain yield by 70% was achieved from enhanced RF (ERF) forecasts which guided maize production strategy, and was tested at 55 sites during the 2010-11 seasons.
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Keywords
RAINFALL VARIABILITY, ETHIOPIA, ARID ZONE, MAIZE, FARMING SYSTEMS, SOUTH OF SAHARA, AGROECOLOGY, PLANTING DATE, AGRONOMY, RAINFALL, FORECASTING TECHNIQUES