| dc.description.abstract | Rainfall variability has led to detrimental influence on food crop production in different parts
of the world. Many countries experience cases of reduced crop production thus lowering food
security. Kenya being an agricultural country, has been affected by variation of rainfall leading
to reduced food production. Nyando Sub-County has experienced incidences of rainfall
variability which has affected crops that are rain-fed. Despite the fact that studies have been
conducted on the effect of rainfall variability on food crop production, there was pending need
to provide detailed information on how rain had affected maize, beans, and African nightshade.
The data used in this study was for the past 10 years (2013 -2022) because it is within this
period that the study area received fluctuating rainfall in terms of magnitude, duration and
timing which affected production of maize, beans and African nightshade. The crops are the
staples within the study area but their production was perceived to decline over the same period.
Therefore, the purpose of the study was to assess the effect of rainfall variability on selected
food crops production. The specific objectives of this study were: to examine the effect of
duration of rainfall on maize, beans and African nightshade production; to establish the effect
of magnitude of rainfall on maize, beans and African nightshade production; to assess the effect
of timing of rainfall on maize, beans and African nightshade production in Nyando Sub County.
A Quasi-longitudinal research design was adopted. The study was conducted in five wards in
the sub-county namely; Ahero, Awasi, Kobura, East Kano and Kabonyo. A sample size of 384
household heads was selected using Fischer’s formula from a target population of 24,866
households. The household heads’ selection was done through simple random sampling for
Questionnaire administration. Primary data collection methods were Observation,
Photography, Key informant interview and Focus Group Discussions. Literature from KMD
and Sub County and County Agricultural offices provided secondary data. Qualitative data was
analyzed through themes. Quantitative data was analyzed using descriptive statistics such as
means, percentages and standard deviation. Simple regression analysis was conducted to
determine the effect of rainfall duration, magnitude and timing on yields of maize, beans and
African nightshade. The regression model was found linear and significant; Rainfall duration
and maize yield was [F (383) =25.63, P < .001, R2 = .65], Beans yield [F (383) =20.42, P <
.001, R2 = .47], and African nightshade Yield [F (383) =19.41, P < .001, R2 = .38]. This is
because both beans and the African nightshade are cover crops which are susceptible to floods.
Rainfall magnitude and maize yield showed [F (383) =11.45, P < .001, R2 =.44], Beans yield
[F (383) =16.08, P < .001, R2 = .37], and African nightshade Yield [F (383) =8.73, P < .001,
R2 = .34]. This was so because the mean rainfall volume was not enough for maximum maize
yield. The reduction in both beans and nightshade yields was possibly due to extreme
fluctuations in rainfall volumes during short rains seasons. Rainfall timing and maize yield [F
(383) =13.68, P < .001, R2 =.44], beans yield [F (383) =21.24, P < .001, R2= .38], and African
Nightshade Yield [F (383) =14.45, P < .059, R2 =34]. Poor timing affected maize yields in
short rains timing. Similarly, the depreciation in both beans and African nightshade yields was
possibly due to rainfall unpredictability which is common during short rains. However, correct
rainfall timing resulted in the increase in the African nightshade yields. The findings were
fundamental to the farmers as they advised on the importance of timing of rainfall enable them
prepare adequately for onset of long and short rains to realize best crop yields. The findings
showed that rainfall variability affected the production of the three crops hence the need to
minimize absolute reliance on rain-fed farming, adopt smart farming and use hybrid seeds that
mature faster. Meteorological data interpretations should be availed to farmers for timely
planting | en_US |
