Factors Influencing Drip Irrigation Technology Uptake Among Small Scale Horticultural Farmers in Kenya, Exams of Agricultural policy

Download Factors Influencing Drip Irrigation Technology Uptake Among Small Scale Horticultural Farmers in Kenya and more Exams Agricultural policy in PDF only on Docsity! 1 FACTORS INFLUENCING DRIP IRRIGATION TECHNOLOGY UPTAKE AMONG SMALL SCALE HORTICULTURAL FARMERS latest updated Overview This chapter covers the 2 background information of the study, problem statement, objectives of the study, research hypotheses, and significance of the study. The last part in this chapter presents the theoretical scope and application of the study. Agriculture in Kenya In Kenya, as in many parts of the sub Saharan Africa, agriculture is the mainstay of the livelihood of her citizens. Over 75% of the population of Kenya relies heavily on subsistent farming and 52% of her entire workforce directly 5 the ASALs and intensively cultivated them. Cultivation in this fragile ecosystem has not been sustainable without external inputs such as water and nutrients, (Okumu, 2004). According to Okumu, between the mid- 1960s and the mid- 1980s, parastatal irrigation agencies were established and 6 irrigation infrastructure was installed in significant tracts of land. Besides installing infrastructure and providing support services, many agencies took on responsibility for purchasing inputs, selling outputs and organizing production processes, in fact taking on the character of „command-and control‟ operations, with smallholder farmers largely treated as laborers. According to National Irrigation Board Mid Term Plan (MTP) 2013-2017, to achieve vision 2030 for Kenya, Irrigation is 7 critical to increasing agricultural productivity. In this regard, incentives will be provided for farmers to invest in energy and water- efficient irrigation systems and technologies. Further the existing schemes need to be rehabilitated and expanded while new ones will be put place. Both the Kenya vision 2030 and the Second Medium Term Plan (MTP) 2013-2017 underscores the important role that irrigation is expected to play in improving agricultural productivity and meeting Kenya's food security needs. The MTP estimates that 10 farming technologies in citrus orchards (Sevier and Lee, 2004). Lapar and Ehui (2004) identified that small producers who have higher levels of education, higher incomes and access to credit are more likely to adopt dual-purpose forages in Philippine. According to Ogadaet al., (2014) the joint adoption of inorganic and improved maize varieties in Kenya was influenced by the use of manure, access to credit, distance to input markets, secure tenure, education and gender of the household head, cultivated area, drainage of the 11 plots, and expected yields. With respect to irrigation technologies, the literature distinguish mainly two stages of the adoption process. The first was related to the primary adoption in which the producer did not use previously any type of irrigation. The second was related with the change of an irrigation system for another; usually more efficient in the use of water. This second stage of adoption especially addressed in countries or regions with water resource scarcity problems and environmental degradation. 12 Techniques of irrigation vary across crops; common methods included surface irrigation (furrow or flood), overhead sprinklers, trickle irrigation (drip or buried), micro- sprinklers, Moneymaker pumps, and direct can watering (Kinyua, 2009). Research indicates that the kind of irrigation system used depends greatly on the type of farmer, size of farm, and range of operation, as well as the drought tolerance of particular plant standings (Uddin, Bokelmann, & Entsminger, 2014). 15 economic characteristics of the farmers, RoK (2015). The question of adoption and non adoption is important, however, intensity of adoption is actually the most important criterion in the adoption process. According to Rogers (1995), there are several factors affecting farmer‟s decision to adopt irrigation technologies. Extension creates awareness on existence of irrigation technology, the farmers assess whether the technologies are acceptable to them given their land sizes, crops grown, 16 education, experience, labour availability or demand, expected improvement in fertility, availability of credit facilities, input cost and other factors. According to Singh (2020)the decision to determine whether it is feasible and profitable for farmers to adopt and implement the irrigation technology on their farms may be instantaneous, that is they can adopt immediately in the same year when the technology is introduced or it can take several years depending on socio- economic factors such as 17 education, frequency of extension contact, technology input prices and literacy levels. Agricultural Irrigation Technology Reducing vulnerability to rainfall failure shocks and variability of production is extremely important for subsistence farmers. Fewer or less severe shocks mean the household is able to maintain proper consumption levels and is less likely to deplete savings or productive assets (tools and livestock) to cope with a shock. Reduced 20 sometimes a third crop planting season, thus increasing income for the farmer. In addition to increasing overall production, irrigation increases the reliability and consistency of production (Smit, 2003). Irrigation enables the farmer to control the available water throughout the growing season which boosts production and reduces exposure to water shortfalls or seasonal droughts. In arid and semi-arid areas where rainfall is inadequate, unreliable, or incorrectly timed, reducing the farmer‟s dependency on unsuitable 21 weather patterns is important for the best production. Irrigation technologies in Kenya dates back to some 400 years, longer than that of most countries in East and Southern Africa. Today, it is worth noting that Kenya is well ahead of other countries in the sub-region in utilizing low-cost technologies for small-scale irrigation, defined here as irrigation on small plots where farmers have the major controlling influence and using a level of technology which farmers can effectively operate and maintain (Carter, 1994). 22 Kenya has an estimated irrigation potential of 1.3 million ha and a drainage potential of 600,000 ha. Currently, 114,600 ha of irrigation and 30,000 ha of drainage have been developed. Of the available irrigation potential, 540,000 hectares can be developed with the available water resources, while the rest of the area will require water harvesting and storage. The developed irrigation potential can be categorized into the following three main types: smallholder schemes, 49,000 hectares, (43 per cent); 25 the study area there are not sufficient studies under-taken assessing the adoption decision of farmers. Given that the main driver for the promotion of drip irrigation in Kenya has been the provision of financial subsidies from the government. The present study focuses primarily on Subukia Sub County the evidence drawn upon and the conclusions drawn from the study expectantly is expected to have general applicability for other regions of the county as well. 26 General Objective The main purpose of this study was to analyze social, economic and institutional factors influencing adoption of drip irrigation technology among smallholder horticultural farmers in Subukia Sub County, Nakuru County, Kenya Specific Objectives The study addressed the following specific objectives; To determine the effect of social factors (age, gender, education level and farm experience and 27 family size) on adoption of drip irrigation technology among smallholder farmers in Subukia Sub County, Nakuru County, Kenya To determine the effect of economic factors (farm income, land size, and off farm income) on adoption of drip irrigation technology among smallholder farmers in Subukia Sub County, Nakuru County. To determine the effect of institutional factors (access to credit, availability of extension service, land tenure, extension services and frequency of extension visits) on adoption of 30 influence the adoption of drip irrigation technology among smallholder farmers in Subukia Sub County, Nakuru County. H03 : Institutional factors (access to credit, availability of extension service, frequency of extension visits, land tenure and source of extension knowledge) do not significantly influence the adoption of drip irrigation technology among smallholder farmers in Subukia Sub County, Nakuru County. Significance of the Study 31 Despite the benefits of irrigation, adoption of the technology has been very low in Africa. According to FAO only 6 percent of the cultivated land in Africa is irrigated, in contrast, 35 percent of the cultivated land in Asia is irrigated. In response to the potential benefits of irrigation and the low adoption rates in rural areas, especially in Africa, there are many organizations, governmental and non- governmental promoting small- scale irrigation technology. The irrigation projects implemented in developing 32 countries provide a wide variety of information, services and financial assistance; however, very little rigorous evaluation has been conducted on the actual factors influencing adoption among both participating and non- participating households. The findings provide useful insights that can inform the implementation of similar projects in Nakuru County and lessons to be learnt shared across similar initiatives in Kenya. 35 improve on the quality and reliability of data that were collected. Theoretical Scope and Application of the Study The current study is diffusion research and has focused on five areas: (1) the characteristics of an innovation which may influence its adoption; (2) the decision- making process that occurs when individuals consider adopting a new idea, product or practice in the current study drip irrigation; (3) the characteristics of individuals that make them likely to adopt 36 an innovation (drip irrigation); (4) the consequences for individuals and society for adopting an innovation; and (5) communication channels used in the adoption process. 37 CHAPTER TWO: LITERATURE REVIEW Overview This literature review summarizes research findings related to the application of drip irrigation for smallholder farming. Focusing in particular on, review of existing knowledge on theories of adoption, adoption of agricultural technologies among smallholder farmers, theoretical framework empirical literature review of models, summary of 40 on the other hand, focus on the individual adopters and a specific innovation or product rather than on large-scale change. The following are some of the theories that have been used in explaining technology adoption. 41 Diffusion of Innovations Theory This theory traces the process by which a new idea or practice is communicated through certain channels over time among members of a social system. The model describes the factors that influence people's thoughts and actions and the process of adopting a new technology or idea. Rogers (1995), defines Diffusion of innovations (DOI) as the process “by which an innovation is communicated through certain channels over time among members of the 42 social system”. DOI is a theory of how, why, and at what rate new ideas and technology spread through cultures, operating at the individual and firm level. DOI theory sees innovations as being communicated through certain channels over time and within a particular social system (Rogers, 1995). Individuals are seen as possessing different degrees of willingness to adopt innovations, and thus it is generally observed that the portion of the population 45 through interactions with others. Thirdly, is 46 the decision stage where there is a drive to seek additional information and a decision is made. Fourthly, is the implementation stage as regular use is attempted more information is sought. The confirmation stage where continued use is justified or rejected based on the evidence of benefits. Rate of Adoption The rate of adoption is defined as the relative speed with which members of a social system adopt an innovation. Rogers 47 (1995) defines the rate of adoption as the relative speed with which an innovation is adopted by members of a social system. An innovation's rate of adoption in a system, usually measured as the number of members of the system that adopt the innovation in a given time period. It is usually measured by the length of time required for a certain percentage of the members of a social system to adopt an innovation, Sunding and Zilberman (2001). Within the rate of adoption there is a point at which an innovation reaches its critical 50 compatibility that an innovation has to be assimilated into an individual's life. Complexity or Simplicity: If the innovation is perceived as complicated or difficult to use, an individual is unlikely to adopt it. Trial ability: How easily an innovation may be experimented. If a user is able to test an innovation, the individual will be more likely to adopt it. Observability is the extent that an innovation is visible to others. An innovation that is more visible will drive communication among the individual's peers and personal 51 networks, and will in turn create more positive or negative reactions. Diffusion of Innovations Diffusion of innovation is a theory profound by Everett Rogers that seeks to explain how, why, and at what rate new ideas and technology spread. Rogers argues that diffusion is the process by which an innovation is communicated over time among the participants in a social system. For Rogers (2003), adoption is a decision of full use of an 52 innovation as the best course of action available and rejection is a decision not to adopt an innovation. Haider (2004) defines diffusion as the process in which an innovation is communicated thorough certain channels over time among the members of a social system. As expressed in this definition, innovation, communication channels, time, and social system are the four key components of the diffusion of innovations (Sahin, 2006). Therefore, this study was anchored on Diffusion of Innovations Theory. 55 occupation, and access to extension services. Haile et al., (2001) examined several smallholder drip irrigation systems using simple technology such as a bucket reservoir, valves, and water distributing pipelines, which they characterized as systems designed to maintain the benefits of drip irrigation while eliminating factors that discourage smallholders from adopting drip irrigation, such as the high cost of system inputs, complicated system operation, and system maintenance 56 requirements. They noted that the relatively low level of investment capital needed to implement a simple drip system is a major advantage for smallholders, estimating the initial investment for a drip irrigation system as between US$ 500 and US$ 3,000 per hectare. If properly managed, the increased crop value in terms of quality, quantity, and time saving would enable the farmer to recuperate this investment quickly. Nevertheless, the low initial investment required may still be 57 too expensive for poorer farmers, impeding adoption of the system, as most farmers would not risk their limited resources and fields. Given these initial investment costs, Haile et al., (2001) proposed that the government should support the introduction of these sustainable horticultural production technologies. While it is a disadvantage of the proposed simple system that water must be brought from a source and contained in a bucket or drum, small amounts of water can 60 a significant expenditure is required to purchase equipment, inadequate or unreliable supply of equipment, insufficient transportation or infrastructure, Uncertainty and risk associated with information about the technology as other major barriers to adoption of a new technology. Gareth et al., (2007) in a related study finding reinforced that micro parameters are crucially important to understanding agricultural technology adoption and can best be statistically assessed using micro- level data. 61 The same study also supports the findings that heterogeneity of asset quality is critical in the general study of technology adoption. Hochman et al., (1978) in their theoretical research identified three broad classes of factors affecting irrigation technology choices; economic variables, environmental characteristics and institutional variables. One of the major contributions of the past studies of 62 agricultural technology adoption to the general adoption literature is that they emphasize the role of heterogeneity of asset quality in the adoption process. Heterogeneity is a crucial element of the threshold model of diffusion (Davies et al., 2010), but many of the early threshold models focus exclusively on variations in wealth or related factors such as farm size. The agricultural technology problem highlights the importance of differences in physical or geographical 65 models as some extension methodologies that share common features; all being top- down, centre outwards, control oriented and intended to standardize and regulate behavior. The study concluded that in practice none could fit or serve local complex, diverse, dynamic and unpredictable conditions. They concluded that farmers do not think of adoption or non-adoption as scientists do, but select elements from the technological complexes to suit their constantly changing circumstances. 66 Demographic Characteristics and Adoption of Drip Irrigation Technology Age is factor thought to affect adoption. Age is said to be a primary latent characteristic in adoption decisions. However, there is contention on the direction of the effect of age on adoption. Age was found to positively influence adoption of sorghum in Burkina Faso (Adesiina and Baidu-Forson, 2009), IPM on peanuts in Georgia (McNamara, Wetzstein and Douce, 2011) and chemical control of rice stink bug in 67 Texas (Kongola, 2018). The effect is thought to stem from accumulated knowledge and experience of farming systems obtained from years of observation and experimenting with various technologies. In addition, since adoption pay- offs occur over a long period of time, while costs occur in the earlier phases, age of the farmer can have a profound effect on technology adoption. However, age has also been found to be either negatively correlated with adoption, or not significant in farmers‟ adoption decisions. In 70 income-enhancing technology. As a matter of fact, it is expected that the old that do adopt a technology do so at a slow pace because of their tendency to adapt less swiftly to a new phenomenon (Christensen et al., 2018). Studies in some areas have shown that smallholder farmers do not adopt all components of “packaged” technologies (Nguluuet al., 2006). When exposed to innovations, smallholder farmers only take those components that they perceive as useful and 71 economically within their reach (Nguluuet al., 2012). Those that require a substantial cash outlay are not taken up easily (Ockwellet al., 2010). There are also technologies that do not require high investment costs and still exhibit low adoption. Rukandema (2004) and Muhammad and Parton (2012) have described other socio- economic factors such as farmers‟ innovativeness, age, off-farm income, risk and uncertainty that may result in low technology uptake. Lack of awareness of improved practices is another reason, 72 particularly in remote areas (Nguluu et al., 2014). Studies that have sought to establish the effect of education on adoption in most cases relate it to years of formal schooling (Christensen et al., 2018), Feder and Slade, 2008). Generally, education is thought to create a favorable mental attitude for the acceptance of new practices especially of information- intensive and management- intensive practices (Waller et al., 2008; Caswell et al., 2011). IPM is frequently stated to be a complex technology (Pimentel, 75 system. For IPM, the relevance of education comes to play in a number of ways. First, effective IPM requires regular field monitoring of pests conditions to identify the critical periods for application of a pesticide or other control measures (Haider& Kreps, 2004).). Farmers‟ knowledge of insect life cycles is also crucial when precision is required about the best stage of the life cycle of a particular control strategy. In addition, knowledge of the possible dangers from improper use of particular practices may direct farmers to the safest 76 application procedure regarding a given control strategy especially where chemicals are involved. In recent studies reviewed, including Daku (2012) and Doss and Morris (2011), education positively affected IPM adoption. A study on IPM practices on potatoes identified level of education as one of the major factors that positively affected the observed level of IPM practices with Ohio potato growers (Waller et al, 2008). However, in adoption of IPM insect sweep nets in Texas, 77 higher education was negatively related to adoption Gender issues in agricultural production and technology adoption have been investigated for a long time. Most show mixed evidence regarding the different roles men and women play in technology adoption. In the most recent studies, Doss and Morris (2011) in their study on factors influencing improved maize technology adoption in Ghana and Akudugu, Guo&Dadzie (2012) (2010) studying coffee production in Papua New Guinea show 80 inputs (e.g. seeds, fertilizers, labor) (Muzari, Gatsi & Muvhunzi, 2012)). In addition, cash proceeds from crop sales, and income obtained from the sale of livestock and livestock products, also provide cash for the purchase of inputs in crop farming (Muzari, Gatsi & Muvhunzi, 2012). Higher levels of income from each of the above sources will lead to higher rates of adoption of yield-raising technology. Labor bottlenecks, resulting from higher labor requirements that new technologies often introduce, and seasonal peaks 81 that may overlap with other agricultural activities, are important constraints to technology adoption. Acquisition of information about a new technology demystifies it and makes it more available to farmers. Information reduces the uncertainty about a technology‟s performance hence may change individual‟s assessment from purely subjective to objective over time (Caswell et al., 2011). Exposure to information about new technologies as such 82 significantly affects farmers‟ choices about it. Feder and Slade (2004) indicate how, provided a particular technology, increased information induces its adoption. However, in the case where experience within the general population about a specific technology is limited, more information induces negative attitudes towards its adoption, probably because more information exposes an even bigger information vacuum hence increasing the risk associated with it. 85 to adopt some technologies. A wide range of economic, social, physical, technical and institutional aspects of farming influence the adoption of agricultural production technologies. In a review of adoption of agro forestry technologies, Pattanayaket al., (2002) established that there were five basic categories of determinants of adoption. These were farmer preferences, resource endowments, market incentives, biophysical factors and risk and uncertainty. Farmer preferences include risk tolerance, conservation attitude 86 and intra-household homogeneity. But since these are difficult to model, proxies such as age, gender, education and social status are used instead. Resource endowments include assets which a household has such as land, labour, livestock and earnings. Several authors identified a positive impact of the educational level of the household head on irrigation adoption (Barseet al., 2010; Vaezi and Daran, 2012; Shahzadi, 2013; Singh et al., 2015). Barseet al., (2010) found 87 that the high level of education of orange producers in India influenced positively the adoption of drip irrigation. 90 Kumar (2012) identified that the experience in farming (proxied by the age of the producer) have a positive impact on drip irrigation adoption in India. Experience improves the awareness concerning the positive effects generated by the adoption and encourages the decision towards adoption. However, according to Kiruthika (2014) the years of experience of sugarcane producers in India have a negative impact on drip irrigation adoption. Younger producers are more likely to be less risk averse than older 91 producers and hence more likely to became adopters. Joshi (2004) found positive and significant correlation between education of the farmers and their adoption level. He also reported positive and significant correlation between scientific orientation and adoption level. Gupta et al., (2010) revealed that there was significant improvement in yield, quality, water and fertilizer use 92 efficiencies of capsicum under drip irrigation and fertigation. However, the combined effect of drip irrigation and fertigation was found superior than their individual effects. Kumar (2012) found that drip method of irrigation is found to have a significant impact on resources saving, cost of cultivation, yield of crops and farm profitability. The adoption of drip irrigation is significantly influenced by experience, farm size, proportion of wider spaced crops and participation in non- farm income activities. The policies should focus on 95 factors to explain the patterns and level of adoption. For example, Oladele (2005) highlights that some studies have shown strong and positive correlation between farming size and adoption while others have shown a positive and significant association between age, farming experience, training received, social- economic status, economic motivation, 96 innovativeness, information source and adoption. Other studies have however shown household size not significantly related to adoption. There exist vast literatures on factors that determine agricultural technology adoption. According to (Loevinsohn et al., (2013), farmers‟ decisions about whether and how to adopt new technology are conditioned by the dynamic interaction between characteristics of the technology itself and the array of conditions and circumstances. 97 Diffusion itself results from a series of individual decisions to begin using the new technology, decisions which are often the result of a comparison of the uncertain benefits of the new invention with the uncertain costs of adopting it (Hall and Khan, 2002). An understanding of the factors influencing this choice is essential both for economists studying the determinants of growth and for the generators and disseminators of such technologies (Hall and Khan, 2002).