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Adding Value to Field-Based Agronomic Research through Climate Risk Assessment: A Case Study of Maize Production in Kitale, Kenya

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Field Value
 
Relation http://oar.icrisat.org/43/
http://dx.doi.org/10.1017/S0014479710000773
 
Title Adding Value to Field-Based Agronomic
Research through Climate Risk Assessment:
A Case Study of Maize Production
in Kitale, Kenya
 
Creator Dixit, P N
Cooper, P J M
Dimes, J
Rao, K P C
 
Subject Maize
Climate change
 
Description In sub-Saharan Africa (SSA), rainfed agriculture is the dominant source of food production. Over the past
50 years much agronomic crop research has been undertaken, and the results of such work are used in
formulating recommendations for farmers. However, since rainfall is highly variable across seasons the
outcomes of such research will depend upon the rainfall characteristics of the seasons during which the
work was undertaken. A major constraint that is faced by such research is the length of time for which
studies could be continued, typically ranging between three and five years. This begs the question as to
what extent the research was able to ‘sample’ the natural longer-term season-to-season rainfall variability.
Without knowledge of the full implications of weather variability on the performance of innovations being
recommended, farmers cannot be properly advised about the possible weather-induced risks that they
may face over time. To overcome this constraint, crop growth simulation models such as the Agricultural
Production Systems Simulator (APSIM) can be used as an integral part of field-based agronomic studies.
When driven by long-term daily weather data (30+ years), such models can provide weather-induced risk
estimates for a wide range of crop, soil and water management innovations for the major rainfed crops of
SSA.Where access to long-term weather data is not possible, weather generators such as MarkSim can be
used. This study demonstrates the value of such tools in climate risk analyses and assesses the value of the
outputs in the context of a high potential maize production area in Kenya. MarkSim generated weather
data is shown to provide a satisfactory approximation of recorded weather data at hand, and the output of
50 years of APSIM simulations demonstrate maize yield responses to plant population, weed control and
nitrogen (N) fertilizer use that correspond well with results reported in the literature.Weather-induced risk
is shown to have important effects on the rates of return ($ per $ invested) to N-fertilizer use which, across
seasons and rates of N-application, ranged from 1.1 to 6.2. Similarly, rates of return to weed control and
to planting at contrasting populations were also affected by seasonal variations in weather, but were always
so high as to not constitute a risk for small-scale farmers. An analysis investigating the relative importance
of temperature, radiation and water availability in contributing to weather-induced risk at different maize
growth stages corresponded well with crop physiological studies reported in the literature.
 
Publisher Cambridge University Press
 
Date 2011
 
Type Article
PeerReviewed
 
Format application/pdf
 
Language en
 
Rights —
 
Identifier http://oar.icrisat.org/43/1/ADDING_VALUE_TO_FIELD-BASED_AGRONOMIC_RESEARCH_THROUGH_CLIMATE_RISK_ASSESSMENT_%282%29.pdf
Dixit, P N and Cooper, P J M and Dimes, J and Rao, K P C (2011) Adding Value to Field-Based Agronomic Research through Climate Risk Assessment: A Case Study of Maize Production in Kitale, Kenya. Experimental Agriculture, 47 (2). pp. 317-338.