Enhancing response farming for improved strategic and tactical agronomic adaptation to seasonal rainfall variability under the semi-arid conditions of Ethiopia
Loading...
Date
2013
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Sokoine University of Agriculture
Abstract
Rainfall variability in the drylands of Ethiopia greatly impacts on agricultural
planning, performance, food security, livelihoods of the people and the national
agronomic planning and tactical management of in-season risks are necessary. A
study based on thirty two years of climatic data for Melkassa and Adami-Tulu
research centres was conducted with objective of improving strategic and tactical
response farming (RF). Applying a multi-factor onset definition approach that
accounts climate, soil and crop types, and farmers’ perceptions of onset and the
principles of RF, April was found to be the most risk-wise acceptable time ofseason
onset for planting of a 150-day maize crop. However, simulation modelling
accepting April onset revealed 63% and 41% crop failure at Melkassa and Adami
Tulu respectively. Thus, predictive capacity was found crucial because April onset
enabled flexible combination production ofmaize varieties maturing in 150, 120 and
90 days. Regression analyses revealed the first effective rainfall date (FRD) to be the
89% for Melkassa and 95% for Adami Tulu), and a good indicator of the duration of next season (Melkassa: R2 = 71%,
= 68%). The R2 for both are statistically significant at 1%
probability (P<0.001). The
advanced prediction of both rainfall parameters by a lead time of two to three
months, markedly improving Stewart’s RF. The date of onset was also found to be a
useful predictor ofseason duration (Melkassa: R2 =
best predictor of the date of onset (R2 =
new agronomically useful strategic predictor (FRD)
86%, P<0.001; Adami-Tulu: R2
Adami-Tulu: R2
= 71%, P<0.001). Using the amount of off-season and cumulative early season
economy. Therefore, rainfall prediction models that can facilitate strategic
iii
rainfall, seventeen prediction models that can facilitate in-season tactical RF were
developed. An increased in maize grain yield by 70% was achieved from enhanced
RF (ERF) forecasts guided maize production strategy that were tested at 55 sites
during 2010-11 seasons. The overall findings suggest that strategic agronomic
planning of farm operations and tactical management of in-season risks should be
guided by ERF forecasts. Research
recommended for similar dryland agro-ecologies in other areas.
on the feasibility of ERF
Description
Keywords
Enhancing responsible farming, Tactical agronomic, Seasonal rainfall