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© 2023 JETIR September 2023, Volume 10, Issue 9 www.jetir.org(ISSN-2349-5162)
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The nature and extent of adoption of climate-smart
agriculture technologies in Murang’a County, Kenya:
A case of Kiharu Constituency.
Eliud K. Bitok1; Dickson M. Nyariki1 and Dorothy A. Amwata1
MSc. Student, Professor, Associate Professor
Department of Agriculture
1Murang’a University of Technology; P.O. Box 75-10200, Murang’a, Kenya.
Abstract
Climate-smart farming, regenerative farming techniques and carbon farming are gaining popularity worldwide due to
their potential to improve food and nutrition security. Kenya’s agriculture is largely rain-fed and characterized by
unreliable rainfall and high temperatures affecting production, quality and pricing. While there is evidence of
opportunities presented by CSA supporting smallholders’ adaptation to climate change, the rate of adoption remains
low. The study, therefore, assessed the nature and extent of adoption of climate-smart agriculture (CSA) technologies
and innovations taking Kiharu Constituency as a case. About 50 households were sampled and data were collected
using questionnaires, interviews, observations and secondary sources. The descriptive analysis on collected data
revealed that on average 63.55% of the farmers were aware of the CSA technologies while only 55.10% of farmers
adopted them. The most adopted and utilized practices by more than 50% of the farmers include crop rotation,
intercropping, terracing, ridging/furrowing, resilient crop varieties, irrigation, agroforestry, building gabions, forage
conservation, and drought-tolerant animal breeds. The CSA technologies least adopted with less than 50% of the
farmers utilising them include minimum tillage, mulching and planting pits. Further research on methods of enhancing
the scalability of CSA technologies and innovations is vital for increasing awareness and uptake.
Keywords: Adoption; climate change; climate smart agriculture; food production; resilience
Introduction
Agriculture is an integral sector for global food security and economic development. It is a stimulus to economic
growth, accounting for one-third of the worldwide Gross Domestic Product (World Bank, 2019; Amwata, 2020).
Agriculture is one of the most effective weapons for ending extreme poverty, increasing shared prosperity, and feeding
the 9.7 billion people predicted to exist by 2050 according to the United Nations Department for Economic and Social
Affairs (2023). The growth in the sector is two to four times more effective than other sectors in generating income
among the poor. According to research done by the World Bank in 2016 studies, the sector earned a living for
approximately 65% of poor working adults in the world. Sustainable agriculture practices are thus gaining traction
around the world as people become more aware of the need to protect the environment while also ensuring food
security (Adebisi et al., 2022).
The current global trends in sustainable agriculture emphasises regenerative agricultural practices to promote soil
health and the use of technologies that build soil organic matter such as mulching, crop rotation and minimum tillage.
Climate-smart farming is also gaining traction, especially in efforts to withstand the stress of climate change, thus
reducing the risk of crop failure. Carbon farming is also a center of focus as it has been identified as a key area in the
generation of new and green revenue for the agricultural sector (FAO, 2016; World Bank, 2019).
Africa as a continent identifies agriculture as one of the key pillars in spurring socio-economic growth and
development. However, Africa's agricultural sector is confronted with some challenges, including low productivity
(Nyariki and Thirtle, 2000), limited market access, and climate change. In sub-Saharan Africa, agriculture accounts
for about 30% of Gross Domestic Product (GDP), and more than 60% of the working population are smallholder
farmers (Temple and Yearwood, 2016). In East Africa, Agriculture remains the backbone and the driving force for
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most economies accounting for greater percentages of their GDP contributors. Subsistence farming is practised by the
rural population, which is primarily made up of smallholder farmers, and agriculture is a way of life for many (Palmer
et al., 2023). Despite these sectoral challenges, there is growing interest in sustainable agriculture technologies and
innovations, which have potential to enhance food security in the region (Giller et al.,2021; Arora, 2019).
Agriculture in Kenya is largely rain-fed and therefore sensitive to climate change and climate variability which
hampers productivity (Amwata, 2020; Nyariki and Thirtle, 2000). Climate change is becoming a global concern
occasioned by rising temperatures, declining rainfall amounts and variations in frequency and intensity of extreme
climatic events such as drought thus affecting farming activities. Excessive rainfall and flooding significantly damage
farmers’ crops and pastures for livestock (Amwata and Nyariki, 2021). Furthermore, it has compromised food supply,
access, and consumption for Kenya's ever-growing population (Ochieng and Mathenge, 2016). The sector is the
backbone of the Kenyan economy, contributing approximately 33% of the GDP directly and 25% indirectly (ASTGS,
2018; FAO, 2020).
Climate change has driven farmers towards the adoption of sustainable agriculture practices in efforts to reduce severe
climatic risks in agriculture, sustainably increase productivity and enhance resilience to climatic stresses, reduce
greenhouse gas emissions, and protect the environment (Amwata et al., 2015; FAO, 2010; KCSAP, 2019). These
practices include climate-smart agriculture, carbon farming, and regenerative farming to enhance production amidst
the ever-changing climate.
Climate Smart Agriculture (CSA) is an integration of traditional and innovative technologies and practices aimed at
achieving climate-resilient food production systems to address food security concerns of the ever-growing human
population (KCSAP, 2019). Climate resilient agricultural practices and technologies such as crop rotation, minimum
tillage, Zai pits, irrigation, and mixed cropping have been found to help increase crop yields, water, and nutrient use
efficiency and reduce GHG emissions (Belay et al., 2023; Khatri-Chhetri et al., 2023). Further, the use of stress-
tolerant seeds, irrigation, rainwater harvesting, extension officer-farmer linkages, and crop/livestock insurance have
enhanced farmers ‘resilience to climate change and variability (Khatri-Chhetri et al., 2023). These technologies and
practices can be implemented singly or in combination. This study therefore focused on the assessment of the nature
and extent of adoption of climate-smart agricultural technologies among farmers in the study area.
1. Literature Review and Theoretical Framework
The chapter describes the concept of agricultural productivity, climate-smart agriculture, policy interventions on CSA
technologies and innovations, CSA technologies practiced in the study area, factors influencing the choice of CSA,
challenges and opportunities, and the theoretical framework.
2.1 Literature review
The study’s literature review is as presented below.
2.1.1 Concept of agricultural productivity
Agricultural productivity is defined as "output per unit of input" or "output per unit of land area". Increase in
productivity i.e., crop productivity, livestock productivity, and fisheries is often considered to be the result of effective
and efficient utilization of both physical and several non-physical factors of production (Dharmasiri, 2012).
Productivity is critical in emphasizing the structure and challenges affecting agricultural production, prompting
policymakers to propose appropriate policies. This concept is generally considered from two close interactions of both
productivities of land and infrastructure and other factors engaged in agriculture to ensure optimal agricultural
productivity is achieved (Dharmasiri, 2012).
Land is a fixed factor of production whose value is determined by the output per unit area of land. Producing
agricultural goods requires a significant amount of labour and productivity is an important factor in this regard. It is
evaluated by computing the labour input in terms of man-hours worked and the number of workers engaged in
production vs. output. Training and increased incentives or compensation could boost agricultural labour productivity.
Capital is also a very essential factor of production in agricultural productivity playing a vital role in providing a
means of acquiring inputs such as seeds, fertilizers, pesticides, and irrigation equipment among others to be used in
agricultural production (Singh and Raghubanshi, 2019). Entrepreneurship combines all the factors of production i.e.,
land, labour, and capital in production to earn a profit. Agricultural productivity heavily relies on these factors of
production to ensure efficiency in food production.
2.1.2 Concept of Climate Smart Agriculture
Climate-smart agriculture is a comprehensive approach that guides actions and implementation of agricultural
technologies and innovations to effectively and efficiently support development as well as guarantee food safety in
the face of climate change (FAO, 2019). It refers to both on and off-farm mutually integrated agricultural strategies
that incorporate technologies, policies, institutions, and investment to support agricultural production and ensure food
safety amidst the threat of climate change (FAO, 2020). CSA champions three main objectives:
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i) Sustainable increase in agricultural production and incomes
CSA focuses on increasing agricultural production and income, particularly from crops, livestock, and fish while
minimizing environmental impact. Sustainable intensification of agricultural production systems requires efficient
utilization of water, soils, and other natural resources, while also providing farmers with the necessary income to
maintain investment levels in more resilient and productive food systems.
ii) Adapting and building resilience to climate change
The goal of CSA is to reduce farmers' vulnerability to short-term production and business risks while also increasing
their capacity to embrace changes to farming operations and the long-term impacts of climate variability.
iii) Reducing greenhouse gas emissions
Climate-smart agriculture plays a major role in building resilience. Several agricultural practices and technologies
contribute to both adaptation and mitigation goals, for example, farmers use reforestation programs to reduce land
degradation while mitigating climate change impacts. Reforestation and afforestation result in increased production
due to the influence of the microclimate. Practices that sustainably promote forest management can benefit local
communities in a variety of ways. Improved land management has increased fodder production for livestock and
additional income to farmers. Other benefits of reforestation include reduced land degradation and soil erosion, as
well as improved water infiltration.
Conservation agriculture is a good climate-smart approach practice that aims to boost smallholder farms' production
and profitability while also increasing their resilience to climate change. It is based on minimum soil disturbance,
maintaining good rotations, intercropping, and relay cropping principles. These conservation agriculture practices
contribute largely to saving the cost of production and promoting agricultural diversification.
2.1.3 Policy interventions on Climate Smart Agricultural technologies and innovations
CSA refers to both on and off-farm mutually integrated agricultural strategies that incorporate technologies, policies,
institutions, and investment to support agricultural production and ensure food safety amidst the threat of climate
change (FAO, 2020). The goal of CSA is to ensure a long-term increase in agricultural productivity and income
generation, enhancing adaptation and resilience to climate change, and, where possible, reduction and/or elimination
of greenhouse gas emissions.
The practices and innovations including policy interventions are some of the government interventions to reduce the
adverse impacts on agricultural production. These practices are sector-specific though they link up mutually to
improve agricultural production. Furthermore, the Kenya Climate-Smart Agriculture Implementation Framework,
2018-2027 (KCSAIF) is one of the policy frameworks developed to guide mainstreaming Climate-Smart Agriculture
in agriculture and other related sectors. The Framework seeks to achieve climate-resilient and low-carbon-growth
agriculture that guarantees food safety and contributes to Kenya Vision 2030 development goals and SDGs 1, 2, and
13. It enables stakeholders to identify agricultural strategies and innovations that are appropriate for their local
conditions while also taking into account the social, economic, and environmental impact on the area of application.
It aids in the identification of barriers to farmer adoption as well as appropriate solutions in the formulation of policies,
strategies, activities, and incentive programs (FAO, 2019).
2.1.4 CSA practices and innovations practiced by farmers in the study area
Kenya's Ministry of Agriculture, Livestock, and Fisheries has launched over eleven CSA-related initiatives since
2001, the vast majority of which have been implemented in ASALs. CSA technologies and innovations help farmers
build more resilience to the ever-changing climate. Farmers in Kiharu have been trained on the importance of
incorporating agroforestry systems to reduce livestock feed costs and farmers' reliance on rangelands. The program
also assists farmers in improving livestock management thus increasing production. Changing livestock production
techniques help farmers produce more and higher-quality animals, reduce their reliance on degraded rangelands, and
make better use of water for their livestock. The County Government of Murang’a has established Murang’a County
Creameries with several cooling plants at different designated points within the County. The plant has been collecting
milk from about 43,000 dairy farmers affiliated with about thirty-six (36) dairy cooperative societies spread all over
the County since its formation in 2014.
Farmers have adopted water harvesting and supplemental irrigation technologies championed by the County allowing
them to utilize rainwater, groundwater, and surface water which continues to be scarce and less reliable. Drought-
tolerant and insect-resistant crop varieties aid farmers in increasing production.
Minimum tillage is also one of the CSA practices recommended for farmers in Kiharu to enhance climate resilience
by reducing risks due to erratic rainfall. It implies minimum soil disturbance and encourages soil coverage through
practices such as mulching to avoid nutrient and carbon losses, soil erosion, and contaminant accumulation in the soil.
This contributes to improved soil structure, soil fertility, carbon sequestration, and soil water-holding capacity
(Sapkota et al., 2015).
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Site-specific nutrient management is among the CSA practices aimed at managing crop nutrients through maximizing
the use of organic fertilizers and optimizing the use of chemical fertilizers, thereby enhancing resource use efficiency
and lowering agricultural GHG emissions.
Furthermore, farmers have been sensitized on the adoption of seeds of stress-tolerant varieties such as rice varieties
that are submergence tolerant, while other varieties are heat, temperature, and/or drought tolerant. Farmers' adaptation
to climate risks such as drought, flood, heat, and temperature stress has increased due to their efficiency. Farmers have
also been encouraged to use improved crop production techniques, such as higher-yielding and shorter-duration
varieties, or those with resistance to specific climate shocks as well as improved crop nutrient management, farm
diversification and intercropping, crop rotation, and increased cultivation of perennial crops.
Protected cultivation is one of the major practices that farmers are advised to undertake. Protected cultivation is a
process of cultivating crops in a controlled environment in which temperature, light, humidity, and other factors can
be adjusted to meet crop requirements. Kiharu farmers could tap the benefits from such cultivation, which includes
forced ventilated greenhouses, naturally ventilated poly houses, insect-proof net houses, shade net houses, plastic
tunnel and mulching, raised beds, trellising, and drip irrigation, in addition to crop health management. These practices
can be used alone or in combination to provide optimal conditions for saving plants from harsh weather and extending
the duration of cultivation or off-season crop production. Drip irrigation in raised beds covered with mulch films not
only eliminates weeds but also keeps moisture in the soil for a longer period by minimizing evaporation losses.
In addition, other CSA interventions include post-harvest technologies and services. The agricultural sector suffers
from high levels of post-harvest losses, particularly for harvested crops, due to ineffective value-chain arrangements
and scarcity of post-harvest facilities. Farmers have been encouraged to use techniques and technologies aimed at
reducing energy losses and increasing energy efficiency, such as the use of renewable energy applications such as
solar panels biogas, and improved Jikos.
2.1.5 Choice of CSA practices and innovations among farmers in Murang’a
Climate-smart agriculture (CSA) employs a variety of agricultural technologies and innovations to increase
sustainable productivity, improve resource-use efficiency, minimize risk and threat to climate variability, and decrease
GHG emissions to the atmosphere. However, in practice, farmers' choices to adopt CSA practices and innovations are
typically influenced by the benefits associated with these practices (Neufeldt et al., 2013).
Some CSA practices and innovations such as crop rotation and mixed cropping have been widely practiced over the
years by farmers in Kenya with minimal knowledge of the benefits it brings in efforts to transform the agricultural
sector amidst climate change concerns. Recent years have seen the promotion of relatively newer practices such as
minimum tillage, laser land leveling, and site-specific nutrient management to combat the effects of climate change
and build resilience to improve agricultural production. Despite the benefits of CSA, as well as ongoing support from
national and international agricultural institutions such as FAO, farmer adoption remains varied and low (Palanisami
et al., 2015).
As a result, the purpose of this research is to identify factors influencing the adoption of CSA and the extent of
adoption by farmers. With this context in mind, the study focuses on major CSA technologies and innovations such
as the use of seeds of stress-tolerant varieties, minimum tillage, Livestock breeding, Ecosystem-based Fisheries, Site-
specific nutrient management, and laser land leveling, mixed cropping, crop diversification and supplemental
irrigation among other soil conservation measures.
The decision to adopt a technology has been associated with earlier technologies adopted by farmers. The influence
of various factors on the adoption decision can either be underestimated or overestimated due to technology
interdependence (Kassie et al., 2013). A farmer is more likely to adopt a specific CSA technology or innovation
especially if the benefit outweighs the cost of non-adoption.
When there are market imperfections and institutional failures, household characteristics like age, gender, and income
levels frequently influence technology adoption decisions (Amwata and Mutavi, 2018; Sahin, 2006: Amwata and
Nyariki, 2023). Adopting farm technology is usually part of a larger household strategy to improve livelihood.
Markets, institutional services, and training, as well as access to markets and other institutional services, all have a
significant impact on CSA adoption via transaction costs. Market access by farmers traveling several kilometers to
the village markets is a bigger challenge, while access to institutional services is proxied by the distance to the nearest
agricultural extension officer and is critical in increasing adoption and innovation (Zougmoré et al., 2016).
Adoption is dependent on ease of access to information and regular training. Farmers in India whose adoption of CSA
was pegged on access to information achieved approximately 12% higher net returns per hectare (Aryal et al., 2018).
Farmers obtain information by relying on these sources; farmer-to-farmer communication, public extension service
or research centers, and information and communication technology, but they primarily rely on one of these sources.
Training in these areas also influences farmers' willingness to adopt technologies such as soil-water management,
minimum tillage, and crop diversification.
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Economic and social capital is also another factor that influences the adoption behaviour of CSA practices and
innovations. Practices such as the adoption of biogas technology require huge capital requirements which is a
challenge for most farmers. In this study, economic capital is defined as land ownership, livestock ownership, and
household labour endowment, whereas social capital is defined as membership in village institutions such as farm
cooperatives (Bryan et al., 2013; FAO, 2015).
Better organization and allocation of various forms of capital would improve efficiency, which is critical for the
adoption and diffusion of interventions in the farming system to achieve the desired impact (Mutoko, 2014).
2.1.6 Challenges and opportunities
Historically, Murang’a County, and specifically Kiharu is known for its vast growth driven by agricultural activities.
Farming is mainly practiced by small-scale farmers with coffee, tea, and horticultural products being the major crops
grown for export. Another common practice in almost every homestead is dairy farming. Until 1989, when global
prices fell, coffee farming was the main source of income for farmers in Murang'a County (Nyoike, 2015). Due to this
decline in prices in the international markets, farmers have been sensitized to diversify their agricultural production
and tap the potential of the land. Farmers have switched to growing other crops including avocados which fetch good
prices in the international markets. Livestock production and Fish farming have not been left out though practiced on
a small scale.
Additionally, farmers have faced the challenge of low production in the wake of the changing rainfall regimes and
increasingly high temperatures. Climate change remains a major issue in the region and farmers are working hard to
build resilience to the impacts of climate change variability. Other challenges faced by farmers include; inadequate
agricultural information, pests and diseases, poor infrastructure i.e., roads and water, increased cost of inputs, soil
nutrient deterioration, and use of obsolete technologies in production among others (Mutombo and Musarandega,
2023).
The County government has launched a program in which over 8,000 farmers received drought-resistant seeds to
increase food production through the use of modern farming technology (Nyoike, 2015).
Furthermore, despite all of the interventions by national and county governments to ensure the supply of subsidized
agricultural inputs, adequate extension knowledge, tools, techniques, and institutions that lower their risk of investing
(crop and animal insurance), there is still little evidence of climate-smart agricultural technologies and innovations
being adopted. The Kenya Vision 2030 envisages a food-secure nation. The government has invested in climate-smart
agriculture to boost agricultural production and expects an improvement in the sector. As a result, the focus of this
research is to assess the nature and extent of adoption of CSA technologies and innovations thus informing on better
approaches to enhancing the scalability in Kiharu Constituency, Murang'a County.
2.2 Theoretical framework
Several theoretical models have been proposed by researchers to explain awareness and adoption of CSA technologies
and innovations. Mainstreaming of these technologies and innovations is aimed at increasing farmers' agricultural
production, enhancing resilience to climate change, and reducing greenhouse gas emissions. The study used the
innovation-diffusion theory to explain the nature and extent of the adoption of CSA technologies and innovations.
The innovation-diffusion theory was developed by E.M. Rogers in 1962 as one of the theories that influences the
adoption of CSA practices and innovations. The theory focuses on the empirical observation of significant differences
in land and labour productivity among farmers. In addition, the theory aids in the dissemination of technologies that
prove more reliable to farmers in terms of productivity in the face of climate change (Sahin, 2006).
The innovation-diffusion model explains the determinants of technology adoption (Sahin, 2006), with information
access being a key determinant in enabling farmers to gain knowledge of an innovation/practice, informing their
choices to adopt or reject it. The adoption perception model explains how farmers' adoption behaviour is influenced
by the perceived attributes of the technology. According to the economic constraints model, inputs such as land,
labour, and credit availability limit production flexibility and influence technology adoption (Mujeyi and Mudhara,
2020). This theory, therefore, created an understanding of how awareness and extent of adoption of CSA technologies
and innovations could be achieved and factors that could enhance technology adoption.
2. Methodology
3.1 Study area
The study was conducted in Kiharu Constituency, Murang’a County, Kenya, historically. Murang’a County lies
between latitudes 0o 34’ South and 1o 7’ South and longitudes 36o East and 37o 27’ East and has seven sub-counties
namely: Kiharu, Gatanga, Kigumo, Kandara, Mathioya, Kangema, and Maragwa (KNBS, 2019) as shown in Figure
2.1. The county is spatially expansive, spanning from an alpine zone defined by a tropical forest called the Aberdare
Forest to semi-arid zones bordering Machakos and Embu Counties. The altitude ranges from 914 meters ASL in the
lowlands East and 3,354 meters ASL in the highlands west along the slopes of the Aberdare Ranges. Most parts of
the county have dissected terrain characterized by valleys and ridges which makes the zones prone to landslides and
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erosions. Kiharu has witnessed landslides in areas around Githambo, Inoi, Gitugi, Kairo, and Mioro villages and areas
around Kiambuthia Secondary School leading to the destruction of crops and livestock farming activities.
Figure 2.1: Map of Murang’a County. Source: Muranga.go.ke
The county is divided into three major climate areas. The western section, which includes Mathioya, Kangema,
Gatanga, and the higher parts of Kigumo and Kandara, has an equatorial climate. Due to the influence of the Aberdares
and Mt. Kenya, this region is often wet and humid. The central region has a subtropical climate, but the eastern region,
which includes the lower parts of the Kigumo, Kandara, Kiharu, and Maragua constituencies, has arid weather and
receives less rain. The highest prospective locations receive an average yearly rainfall of 1400mm to 1600mm. Low
potential receives less than 900mm of rain each year. Rainfall in high and medium potential locations is consistent
and evenly distributed throughout the year, and is sufficient for agricultural production (MCIDP 2022-2023).
The highest annual temperatures in the eastern lower parts range between 26° C and 30° C, while the minimum annual
temperatures range between 14°C and 18°C (MCIDP 2022-2023). Variations in altitude, rainfall, and temperature
between the highland and lowland, as well as changes in the underlying geology of both volcanic and basement system
rocks, result in a wide range of soil types. Highland areas feature rich brown loamy soils that are ideal for growing
tea, Coffee, maize, and dairy farming whereas the lower-lying soils are generally black cotton clay with seasonal
impended drainage (GoK, 2010).
Kiharu comprises arid and semi-arid lands which have been utilized for various economic activities. Since the early
1980s, it has been well-known for the commercial production of tea and coffee for the export market. The rainy season
lasts from March until May. The month of April has the most rainfall, and rainfall is extremely reliable during this
month. The short rains are received during October and November as shown in Figure 2.2 (GoK, 2010).
Figure 2. 2: Murang’a rainfall levels on monthly basis. Source: climate-data.org
3.2 Sampling and data collection
A random sampling method was used to sample 50 farmers from the study area. Quantitative and qualitative
information was obtained using different data collection methods such as questionnaires, key informant interviews,
focus group discussions, and secondary data collection. A total of fifty (50) copies of structured questionnaires were
distributed to the farmers during the research. Forty-nine (49) questionnaires were properly completed and returned,
while one questionnaire was not returned. According to Lund (2023), a response rate of approximately 60% for
research is appropriate and helps reduce the problem of coverage error in the administration of questionnaires. Based
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on the findings, the study response rate was 98% which was higher than the recommended minimum of 60%, hence
adequate for the study.
The study used a nominal scale (yes or no) to determine the nature and familiarity level of the CSA technologies and
innovations adopted in the study area and subjected the data to descriptive and inferential analysis.
3.3 Data analysis
Descriptive statistics such as measures of central tendency, standard deviation and mean were computed. The
generalized findings were then presented using tables.
3. Results and discussion
The objective of the study was to establish the nature and extent of the adoption of CSA technologies and innovations
by the farmers in the study area. The farmers were identified and asked to provide information about the nature and
extent of the adoption of all 15 selected CSA technologies and innovations.
4.1 Nature of CSA Technologies and Innovation
The CSA technologies were examined in order to determine their nature and familiarity level among the farmers in
the study area.
4.1.1 Classification of CSA Technologies and Innovations
To begin with, the technologies were classified into five (5) categories of CSA based on FAO classification. The 15
CSA technologies and innovations were classified as shown in Table 4.1.
Table 4. 1: Classification of CSA Technologies and Innovations
Classification
CSA Technologies and innovations
Livestock management
technologies
Animal insurance
Drought tolerant animal breeds
Forage conservation
Conservation agriculture
Crop rotation
Minimum tillage
Intercropping
Agroforestry
Soil and water conservation
Terracing
Mulching
Irrigation
Ridging/furrowing
Planting pits (Zai)
Building of gabions
Resilient crop varieties
Stress tolerant crops and varieties
Cropland management
Crop insurance
4.1.2 Farmers familiarity with selected CSA Technologies and Innovation
Furthermore, in order to determine the nature and familiarity level of the CSA technologies and innovations
implemented, the study used a nominal scale (yes or no) as a question. The results are presented in Table 4.2.
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Table 4. 2: Farmers familiarity with selected CSA Technologies and Innovation
Classification of
CSA Technologies
and Innovation
CSA
Technologies
and
Innovation
Yes
No
Mean
Standar
d dev.
Livestock
Management
Technologies and
Innovations
Animal
insurance
26 (53.1)
23 (46.9)
1.47
0.50
Drought
tolerant animal
breeds
28 (57.1)
21 (42.9)
1.43
0.50
Forage
conservation
32 (65.3)
17 (34.7)
1.35
0.48
Conservation
Agriculture
Technologies and
Innovations
Crop Rotation
47 (95.9)
2 (4.1)
1.04
0.20
Minimum
Tillage
24 (49.0)
25 (51.0)
1.51
0.51
Intercropping
49 (100.0)
0 (0.0)
1.00
0.00
Agroforestry
27 (55.1)
22 (44.9)
1.45
0.50
Soil and water
Conservation
Technologies and
Innovations
Terracing
40 (81.6)
9 (18.4)
1.18
0.39
Ridging/
furrowing
31 (63.3)
18 (36.7)
1.37
0.49
Mulching
31 (63.3)
18 (36.7)
1.37
0.49
Irrigation
30 (61.2)
19 (38.8)
1.39
0.49
Planting pits
(Zai)
31 (63.3)
18 (36.7)
1.37
0.49
Building of
gabions
21 (42.9)
28 (57.1)
1.57
0.50
Resilient crop
varieties
Stress tolerant
crops and
varieties
24 (49.0)
25 (51.0)
1.51
0.51
Soil and crop land
management
Crop insurance
26 (53.1)
23 (46.9)
1.47
0.50
As indicated in Table 4.2, the nature and familiarity of the farmers with various CSA technologies and innovations
varied. Crop rotation, intercropping, terracing, ridging/furrowing, mulching, crop insurance, irrigation, agroforestry,
planting pits, animal insurance, forage conservation, and drought-tolerant animal breeds were among the technologies
and innovations that received greater than 50% understanding.
In comparison to the other technologies under investigation, most farmers were aware of crop rotation, intercropping,
and terracing practices. Crop rotation and intercropping are the most prevalent farming practices utilized by most
farmers, based on the farmers’ knowledge of them. Furthermore, given the geography of the study area, farmers were
more experienced with terracing as a CSA practice, mostly used to prevent run-off downstream during torrential
downpours, which could result in crop and livestock damage (Nyoike, 2015).
Minimum tillage, stress-tolerant crops and cultivars, and erecting gabions, on the other hand, received less than a 50%
familiarity score as CSA technology. Surprisingly, all farmers identified intercropping as a CSA technology. The
mean and standard deviation were 1.00 and 0.00 respectively.
According to Nyoike (2015), the study area is prone to landslides, which frequently result in crop destruction,
including settlement in areas around Githambo and Inoi villages, Gitugi, Kairo, Mioro, and regions around Kiambuthia
Secondary School. Crop destruction has consequences for pasture and other supplementary feeds for animals, and as
a result of all these factors, terracing as a CSA technology is becoming more popular among farmers in the study area.
4.1.3 Sources of information
Farmers' access to information on the best agricultural activities is key to enhancing agricultural productivity. The
study revealed that farmers' awareness was contributed by exposure to agricultural technologies and innovations
through attending agricultural shows and exhibitions, field training, online platforms (google, YouTube, etc.),
television, and reading literature such as books. The results were as shown in Figure 4.1.
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Figure 4. 1: Sources of information vis-a-vis percentage of farmers
Based on the results in Figure 4.1. the study established that awareness of CSA technologies and innovations was
largely contributed through field training (51%). Training facilitates knowledge transfer through observation and
practical hence most appreciated by farmers. On the contrary, awareness through television (16%) and online
platforms (18%) were minimal perhaps because farmers devote much of their time to the farm and less time is left to
watch television programmes and browse.
Murang’a County has a Farmers Agricultural Training Center - Mariira Farm based in Kigumo. This facility offers
training and conducts agricultural shows and exhibitions annually to facilitate the dissemination of best farming
practices across agriculture sub-sectors such as crops, livestock, fisheries, and apiary among others (MCIDP 2022-
2027). The study revealed that field training, extension farmer advice, and agricultural shows and exhibitions were
the main enablers to increased awareness and eventually adoption of the CSA technologies and innovations.
4.2 Extent of Adoption of CSA Technologies and Innovation
An analysis was carried out to establish the level of adoption of the various CSA technologies and innovations and
their influence on agricultural production. The study adopted the nominal scale (yes or no) by way of question to
determine the extent of adoption and usage of the CSA technologies and innovations deployed. The results are
presented in Table 4.3. Table 4. 3: Extent of Adoption of CSA Technologies and Innovation
Classification of CSA
Technologies and
Innovation
CSA Technologies
and Innovation
Yes
No
Mean
Standard
dev.
Livestock Management
Technologies and Innovations
Animal insurance
0 (0.0)
49 (100.0)
2.00
0.00
Drought tolerant
animal breeds
26 (53.1)
23 (46.9)
1.47
0.50
Forage conservation
32 (65.3)
17 (34.7)
1.35
0.48
Conservation Agriculture
Technologies and Innovations
Crop Rotation
36 (73.5)
13 (26.5)
1.27
0.45
Minimum Tillage
20 (40.8)
29 (59.2)
1.59
0.50
Intercropping
35 (71.4)
14 (28.6)
1.29
0.46
Agroforestry
25 (51.0)
24 (49.0)
1.49
0.51
Soil and water Conservation
Technologies and Innovations
Terracing
45 (91.8)
4 (8.2)
1.08
0.28
Ridging/ furrowing
32 (65.3)
17 (34.7)
1.35
0.48
Mulching
22 (44.9)
27 (55.1)
1.55
0.50
Irrigation
25 (51.0)
24 (49.0)
1.49
0.51
Planting pits (Zai)
9 (18.4)
40 (81.6)
1.18
0.39
Building of gabions
29 (59.2)
20 (40.8)
1.41
0.50
Resilient crop varieties
Stress tolerant crops
and varieties
25 (51.0)
24 (49.0)
1.49
0.51
Soil and crop land
management
Crop insurance
0 (0.0)
49 (100.0)
2.00
0.00
As shown in Table 4.3, terracing had the highest percentage of adopters, accounting for 91.8%. These findings
correspond to those of Nyoike (2015), who discovered that given the geography of the study area, farmers were more
experienced with terracing to manage the steep terrain and reduce run-off downstream during torrential downpours,
which could result in crop and livestock loss (Nyoike, 2015).
0
10
20
30
40
50
60
Agricultural shows Extension farmers
advise Field trainings online Television Books
Sources of information vis-a-vis percentage of farmers
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Furthermore, crop rotation, intercropping, terracing, ridging/furrowing, stress-tolerant crops and varieties, irrigation,
agroforestry, planting pits, building gabions, forage conservation, and drought-tolerant animal breeds were among the
highly adopted technologies and innovations that received greater than 50% adoption.
On the other hand, minimum tillage, mulching and planting pits (Zai) received less than a 50% adoption rate among
the farmers. Crop and animal insurance registered zero adoption, with a mean and standard deviation of 2 and 0
respectively. Crop and animal insurance reported zero adoption since most farmers lacked information on risk
management plans for their agricultural production.
Based on the findings, on average, 63.55% of farmers were aware of the existence of CSA technologies. This
awareness was attributed to the cascading of CSA technologies and innovations through the Kenya Climate Smart
Agriculture Implementation Framework (KCSAP). The framework is aimed at upscaling, mainstreaming, and
strengthening CSA and seed systems. It supports the generation and dissemination of improved agricultural
technologies, innovations, and management practices.
Besides, 55.10% of the farmers adopted the technologies and innovations studied. Adoption rates varied as determined
by the various socio-economic characteristics of household heads. Of the technologies studied, two technologies, i.e.,
animal and crop insurance had zero adoption while 13 technologies showed varied adoptions. The minimal adoption
rates may have been contributed to the high costs involved and inadequate knowledge of the importance to the farmers.
Adoption based on classification of CSA technologies and innovations
The study further conducted an analysis of the adoption (%) based on the FAO classification of technologies and
innovations to better understand the trends of adoption. The results are as presented in Figure 4.2.
Figure 4. 2: Adoption based on classification
The analysis revealed that on average, Livestock Management (59.2%), conservation agriculture (59.2%), and soil
and water conservation (55.1%) technologies and innovations were highly adopted by the farmers in the study area.
However, soil and cropland management technologies were the least adopted by farmers. Farmers have not realized
the importance of crop insurance as a CSA technology to help mitigate the impacts of crop failure as a result of
flooding and landslides due to heavy rainfall or fluctuation of temperatures and increased pests and disease prevalence.
Factors influencing adoption of CSA technologies and innovations
According to the findings, the adoption of CSA technologies varied depending on the socio-economic characteristics
of the farmers. These findings agreed with the study by Kurgat et al. (2020) on the adoption of climate-smart
agriculture technologies in Tanzania. The researchers found that the adoption of CSA technologies was heavily
dependent on the demographic characteristics of the farmers involved in the study sample. A multivariate probit model
was used to evaluate the determinants of adoption and assess the synergies and trade-offs between five (5) CSA
technologies (crop and livestock diversity, irrigation, chemical fertilizer application, and agroforestry). Household
demographic characteristics such as age, gender, literacy levels, and occupation impact the study's choices regarding
the adaptation of the different CSA technologies under consideration.
Source of information
Adoption is dependent on access to information and training received by farmers. Sapkota et al. (2018) found that
farmers who use modern information and communication technology to get farm-related information had greater rice,
wheat, and maize crop yields. Training and information access improve CSA uptake significantly. Farmers learned of
the various CSA technologies and innovation methods from a variety of sources. Based on the findings, training,
extension advice, and attendance to agricultural shows and exhibitions improved farmers' access to information hence
enhancing adoption.
0
20
40
60
80
100
120
Livestock
Management
Technologies and
Innovations
Conservation
Agriculture
Technologies and
Innovations
Soil and water
Conservation
Technologies and
Innovations
Resilient crop varieties Soil and crop land
management
% Adoption based on classification
Adoption(%) Non- adoption(%)
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Gender of the farmers
Gender plays a crucial role in influencing the adoption of CSA technologies and innovations. The distribution of
gender by respondents showed that a majority were male at 63% while the remaining 37% were female. There were
more male respondents than females who took part in the study. The former is perceived to participate more in
agricultural production activities than women because they have better access to resources and services such as land,
finances, training, inputs, and equipment. However, in some circumstances, while men may have greater access to
resources, women conduct the actual farming activities (Begho et al., 2022).
The findings are consistent with those of Maka et al. (2021), who conducted a study on the appraisal of climate-smart
agriculture (CSA) practices among South African extension practitioners. According to the researcher, male
participation in farming was higher, accounting for 56.2%, followed by female participation at 43.5%.
Literacy levels of the farmers
The findings of the study revealed that household heads i.e., those with at least a primary education level were more
likely to understand and adopt the technologies and innovations. These farmers had non-farm income and a greater
capacity to access, acquire, absorb, and adopt new technology and process new information (Aryal et al., 2018).
Age of the farmers
Farmers over the age of 55 have more exposure and experience in farming, have amassed more assets, and have
established broad social networks, making them more likely to embrace technologies. However, their old age was
associated with low energy, short-term investment plans, and more risk-averse resulting in lower adoption levels
(Mutombo and Musarandega, 2023).
Middle-aged farmers between the ages of 36 and 45 were energetic, full of resources, and thus easily adopted CSA
technologies, whereas those under the age of 35 had schooling and knowledge but fewer assets such as land and capital
under their control to do farming, resulting in minimal adoption.
There exist gaps in policy and extension planning programs that can help to enlighten farmers on the adoption of
animal and crop insurance and its importance as CSA. Inadequate levels of education, lack of access to information,
and pressures on financial resources for some farmers reduce the rate of adoption of these technologies, especially
those that require significant investment (Singh et al., 2023; Kurgat et al., 2020).
4. Conclusions and policy recommendations
Climate change continues to pose a direct and indirect threat to agricultural systems through linkages with other
sectors of the economy hence a global concern. Climate-smart agriculture strategies have been suggested as a viable
strategy for increasing agricultural production and incomes and enhancing food security and dietary diversity by
preparing farmers to avert the negative impacts of climate change. The study concluded that boosting agricultural
production in the face of climate change may be accomplished through CSA to end hunger, eradicate poverty, and
enhance food security.
Generally, the four socio-economic characteristics, i.e., age, gender, level of education, and occupation greatly
influenced the adoption of CSA technologies. However, CSA technologies and awareness did not translate to adoption
and therefore the need to put in place initiatives to promote uptake. Concerted efforts are required from the National
Government, Murang’a County Government, and development partners to strengthen awareness and adoption through
capacity building and climate financing programmes. Enhancing access to inputs such as climate-resilient seeds and
animal breeds, fertilizers, and other inputs through subsidy initiatives at close proximities to farmers will lessen the
difficulty of unavailability during peak seasons. Strengthening capacity building through extension services to farmers
and climate change financing will play a key role in creating awareness and uptake of these promising technologies
and spur more innovations, thus helping production. Future research can also be conducted along with improved
techniques in strengthening the scalability of CSA technologies and innovations.
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