Home Research PapersIt et al. (2010) financial capital appears to be

It et al. (2010) financial capital appears to be

It
is indubitable that, for every country in the world, agriculture is an
indispensable sector that accelerates economic growth and development. Socio-economic
and institutional factors play an important role in the adoption of new
technology by the farmers. According to Babatunde et al. (2010) financial
capital appears to be the most limiting factor
for farming, so that cash income from off-farm activities can help to expand
farm production. Schneider and Gugerty (2011) conceive that real income
changes, employment generation, rural non-farm multiplier and food price
effects are some of the significant changes that increased agricultural
production and thereby reduce poverty. As per the Rio + 20 conferences,
smallholder farmers and smallholder agricultural production are pertinent to
meet Millennium Development Goals (MDGs) particularly reducing hunger and
poverty (Vargas-Lundius, 2012). Byerlee et al. (2005) posited that if there is
higher agricultural
production and growth per worker where there is abundant labor force, poverty
reduction rate
would be high. In the same line of reference, production and productivity
increment, therefore, will increase or at least bring a positive change in the
income of smallholder farmers; increase linkages between rural and urban production
requirements and reduce poverty. Similarly, the finding by Jayne et al. (2010)
in Kenya, Malawi, Zambia, and
Mozambique tell that, abundant maize production has had increased the income of
smallholder farmers and poverty has been reduced. According to
Kende-Robb (2013) in Kenya; Diao and Pratt (2007) and Samuel (2006) in
Ethiopia purport
that, agriculture has reduced poverty twice as fast as other sectors.

Gender
is one of the significant determinants of agricultural production since
male-headed and female-headed households could not have the same capability and
endurance in
enhancing agricultural production; where the male-headed are stronger (Nyanga
et al., 2012). In Kenya, Ekbom et al. (2012) found that female-headed
households are inefficient and unproductive compared with their counter parts.
According to Malek and Usami (2010) male-headed households expend more on external
inputs at their farm. Male-headed households are better off to get agricultural
information and to take risks (Abay and Assefa, 2004). Adebiyi and Okunlola
(2013) reported that, in Nigeria, unlike their counter parts, females more
engage in off-farm activities like in selling agricultural products, storing
and packing them out. This indicates that, male did pay attention for their
farm work and do better adopt farm rehabilitation techniques, inputs for
sufficient production. Lugandu (2013) reported that in Tanzania, male-headed
households has had adopted conservation agricultural technologies as compared
with female-headed. This does not mean that female-headed households are
reluctant to adopt agricultural technologies, but their decision is being challenged
or influenced by their family members or beyond. In the same reference of line,
Uwagboe et al. (2012) agreed that different social and institutional factors
did hold back female-headed households in practicing integrated pest management
technologies where their effort in agricultural production is being
compromised. In Ethiopia, work division culture makes female-headed households
less effective in production; like taking perishable products to the market
unlike males (Tewodaj et al., 2009).

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Level
of education and age of farmers also among the key factors those affects
adoption of new innovative technologies. Education is the key factor that
determines agricultural production in adopting inputs in general and management
practices (Uwagboe et al., 2012). Researchers like Shumet (2011); Chiputwa et
al. (2011); Askal (2010);
Anyanwu (2009) reported that educated farmers have a better access for
agricultural information that is pertinent for decision making on what and when
to produce; to adopt and use inputs efficiently thereby increase production.
Thierfelder and Wall (2011) inferred that education as a source of knowledge
has had resulted in adoption of the new techniques.  Abay and Assefa, 2004 reported that younger
farmers are risk takers for what they adopt and for yield uncertainties.
Whatever other reasons might be, in Kenya, Ekbom et al. (2012) found that older
farmers with better accumulated experience are more efficient than younger
farmers.

Institutional
factors are crucial for increasing agricultural production and food sufficiency
by solving liquidity problem, making accessible agricultural inputs,
consultancy services and the like. These could include credit, extension
functionaries, and agricultural cooperatives. Smallholder farmers are lacking
in access of agricultural production techniques and inputs due to credit
rationing or liquidity constraint as a result agricultural production become
liable to dwindle explained by Anyanwu (2011). Adebiyi and Okunlola (2013)
explained that credit is worth enough for farmers in such a way that credit
availability turns off the cash limitation and allow farmers to purchase inputs
on time and produce stable production.

Among
the other stakeholders, extension service being activated by department of
agriculture is paramount importance for enhancing agricultural production.
Department of agriculture is the closest stakeholder to farmers and plays key
role in instigating farmers to use agricultural inputs. Genius et al. (2013)
concluded that the role of department of agriculture is transferring
information to farmers and thereby shaping their activities. Genius et al.
(2013) further argued that extension services and farmer-farmer contact are
basic points that determine technology adoption and diffusion; and both are
mutually supportive. Kizito and Steve (2009) explained about adoption of
conservation farming in Zimbabwe, following promotional efforts were being made
by extension agencies aiming to improve food security among vulnerable farmers.
The technologies were adopted by all groups of farmers including elderly
farmers. The Tobit model results show that extension access, NGO support,
increased plot size and agro-ecological location significantly influences the
intensity of adopting different components of conservation farming. Active
support by both NGOs and government made changes through the supply of seed,
fertilizer, and training increased the likelihood of conservation farming
adoption. The well-being of the farming society depends on proper adoption and
use of innovative new technologies such as conservation agriculture etc. 

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