Comparing productivity of rice under system of rice intensification and conventional flooding: A switching regression approach

Rice (Oryza sativa L.) is one of the most important food
crops for more than 50% of the world population (Atera et
al., 2018). Globally, about 160 million hectares are
estimated to be under rice production with an annual
production of approximately 500 million metric tons
(Kirby et al., 2017). The demand for rice has increased
steadily over the years, thus playing a major role in many
countries in terms of strategic food security planning
policies.In recent years, rice crop yield has slowed
considerably therefore failing to keep up with the
population growth thus leading to shortages and higher
prices that have adversely affected smallholder rice

farmers (Denkyirah, 2015; Lee and Kobayashi, 2017)
Paddy rice is one of the commodities whose demand is
rapidly increasing in Sub-Saharan Africa as a result of
increased urbanization, growing importance of the crop
and the challenges of attaining food security (Amos,
2014). Therefore the consumption of rice is expected to
increase tremendously (Kirby et al., 2017). The current
paddy rice production in Kenya is estimated at 150,000
metric tons. The output meets only about 20% of the
total demand (Omondi and Shikuku, 2013). The gap
between production and consumption is filled by
importation to meet the domestic demands (Ndirangu,
2015). For Kenya to attain self-sufficiency in rice
production, the domestic production must increase at the
rate of 9.3% per year (Amos, 2014). To achieve selfsufficiency in rice production, innovative practices that
reduce water use need to be put in place to enhance
sustainable rice farming.
Various methods have been used to reduce water
usage in rice production (Denkyirah, 2015). One of the
most tried methods was the Green Revolution in Asia,
which involved a series of research and technology
transfer initiatives (Kassam et al., 2011). This innovation
involved the development of high yielding varieties of
cereal grains and modernization of farmland
management techniques (Rahman, 2017). The Green
Revolution was very effective and successful in Asia
whereby many farmers were able to adopt the technology
(Thakur et al., 2015). However, the innovation was not
able to help many African countries farmers due to limited
infrastructure and financial constraints (Ndiiri et al.,
2013). The other innovation is the System of Rice
Intensification (SRI). From the farmers’ perspective, SRI
is the use of existing assets differently yet increasing the
outputs and reducing water use while maintaining the
quality of the grain (Katambara et al., 2013). It can be
inferred from Stoop (2003) that SRI is a concept on the
manipulation of agronomic practices to attain higher rice
yields with the use of minimal resources such as
agrochemicals, seeds, and water (without continuous
flooding in SRI as compared to traditional methods). The
SRI is gaining popularity in all rice-growing areas of the
world and that farmers can grow more rice with less
water (Karki, 2010).
The key components of SRI include: water
management, practiced by keeping the soil drained and
saturated rather during the vegetative growth period.
Furthermore, it includes flooding and drying of the fields
for alternating periods of 3-6 days each (Namara et al.,
2003). The second component is the planting method
which involves spacing configurations and age of
seedlings. In SRI, seedlings are transplanted 8-15 days
after germination (Thura, 2010). Some studies suggest a
line spacing of 30 cm × 30 cm. The spacing could be
based on the local edaphic conditions but it has to
facilitate weeding (Uphoff and Thiyagarajan, 2005). The
third component is weed control which is best done ten
days after transplanting and then weeding every ten days
until canopy closure (Uphoff and Thiyagarajan, 2005).
The fourth component entails soil fertility management.
Most farmers use compost or organic manure but the
amount applied varies in terms of its availability and also
because there is no fixed recommended rate to follow
(Ndiiri et al., 2013). The traditional method of rice
growing involves continuous flooding during the
vegetative growth with draining of the water during the
grain ripening stage, which is a common practice in all
rice-growing schemes in Kenya (Omwenga et al., 2014).
The Conventional Flooding (CF) method is thus
associated with higher water demand and occasioned by
high losses through percolation, seepage, and
evaporation (Paredes et al., 2017).
There exist various socioeconomic factors that
influence the level of rice productivity in the two systems
of rice farming in Sub-Saharan Africa, Kenya included.
Many empirical studies have investigated the issue of
crop productivity and profitability (Denkyirah, 2015).
However, alternative production practices such as SRI
and CF have not yet been fully investigated especially on
productivity and profitability of rice. Previous studies on
SRI in Mwea Irrigation Scheme include (Ndiiri et al.,
2013). Authors such as Ndirangu (2015) focused on the
constraints and the returns associated with SRI.
Additionally, their studies focused on the perceptions of
SRI. On profitability, authors such as Denkyirah (2015)
focused on cash flow projections for SRI for a period of
five years using the Benefit Cost Ratio (BCR) and Net
Present Value (NPV) approaches. However the study did
not focus on the use of other approaches in determining
profitability. In Ghana, the application of gross margin
approaches was done for paddy production (Bwala and
John, 2018). However the study did not make a
comparison of rice practices instead it focused costs and
returns thus creating a research gap.
There is a need to understand what to increase or
decrease in productivity of rice among smallholder
farmers. Therefore the main objective of this study was to
compare the productivity of rice under SRI and CF.
Against this background, this study came in hardy to
provide research-based information on determinants of
rice productivity under SRI and Convectional flooding in
Mwea irrigation scheme, Kenya. From these studies, little
has been done or investigated on productivity of rice
using the SRI and CF methods of crop establishment in
Mwea Irrigation Scheme. ESRM have been applied to
examine the impacts of technology adoption on farm
outcomes when self-selection is an issue. The model
accounts for selection bias making it the most appropriate
in analyzing the productivity of rice under SRI and CF.
This, therefore, provides a strong case of argument of
using SRI to generate information on rice productivity
with a view of driving policy recommendations and filling
the information gap in Kenya.

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