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( Jonathan Mbonge Munguti ),( Jeong Dae Kim ),( Erick Ochieng Ogello ) 한국수산과학회(구 한국수산학회) 2014 Fisheries and Aquatic Sciences Vol.17 No.1
The Kenyan aquaculture sector is broadly categorized into freshwater aquaculture and mariculture. Whereas freshwater aqua- culture has recorded significant progress over the last decade, the mariculture sector has yet to be fully exploited. The Kenyan aquaculture industry has seen slow growth for decades until recently, when the government-funded Economic Stimulus Program increased fish farming nationwide. Thus far, the program has facilitated the alleviation of poverty, spurred regional development, and led to increased commercial thinking among Kenyan fish farmers. Indeed, national aquaculture production grew from 1,000 MT/y in 2000 (equivalent to 1% of national fish production) to 12,000 MT/y, representing 7% of the national harvest, in 2010. The production is projected to hit 20,000 MT/y, representing 10% of total production and valued at USD 22.5 million over the next 5 years. The dominant aquaculture systems in Kenya include earthen and lined ponds, dams, and tanks distributed across the coun- try. The most commonly farmed fish species are Nile tilapia Oreochromis niloticus, which accounts for about 75% of production, followed by African catfish Clarias gariepinus, which contributes about 21% of aquaculture production. Other species include common carp Cyprinus carpio, rainbow trout Oncorhynchus mykiss, koi carp Cyprinus carpio carpio, and goldfish Carassius auratus. Recently, Kenyan researchers have begun culturing native fish species such as Labeo victorianus and Labeo cylindricus at the National Aquaculture Research Development and Training Centre in Sagana. Apart from limited knowledge of modern aquaculture technology, the Kenyan aquaculture sector still suffers from an inadequate supply of certified quality seed fish and feed, incomprehensive aquaculture policy, and low funding for research. Glaring opportunities in the Kenyan aquaculture industry include the production of live fish food, e.g., Artemia, daphnia and rotifers, marine fish and shellfish larviculture; seaweed farming; cage culture; integrated fish farming; culture of indigenous fish species; and investment in the fish feed industry.
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Munguti, Jonathan Mbonge,Kim, Jeong-Dae,Ogello, Erick Ochieng The Korean Society of Fisheries and Aquatic Scienc 2014 Fisheries and Aquatic Sciences Vol.17 No.1
The Kenyan aquaculture sector is broadly categorized into freshwater aquaculture and mariculture. Whereas freshwater aquaculture has recorded significant progress over the last decade, the mariculture sector has yet to be fully exploited. The Kenyan aquaculture industry has seen slow growth for decades until recently, when the government-funded Economic Stimulus Program increased fish farming nationwide. Thus far, the program has facilitated the alleviation of poverty, spurred regional development, and led to increased commercial thinking among Kenyan fish farmers. Indeed, national aquaculture production grew from 1,000 MT/y in 2000 (equivalent to 1% of national fish production) to 12,000 MT/y, representing 7% of the national harvest, in 2010. The production is projected to hit 20,000 MT/y, representing 10% of total production and valued at USD 22.5 million over the next 5 years. The dominant aquaculture systems in Kenya include earthen and lined ponds, dams, and tanks distributed across the country. The most commonly farmed fish species are Nile tilapia Oreochromis niloticus, which accounts for about 75% of production, followed by African catfish Clarias gariepinus, which contributes about 21% of aquaculture production. Other species include common carp Cyprinus carpio, rainbow trout Oncorhynchus mykiss, koi carp Cyprinus carpio carpio, and goldfish Carassius auratus. Recently, Kenyan researchers have begun culturing native fish species such as Labeo victorianus and Labeo cylindricus at the National Aquaculture Research Development and Training Centre in Sagana. Apart from limited knowledge of modern aquaculture technology, the Kenyan aquaculture sector still suffers from an inadequate supply of certified quality seed fish and feed, incomprehensive aquaculture policy, and low funding for research. Glaring opportunities in the Kenyan aquaculture industry include the production of live fish food, e.g., Artemia, daphnia and rotifers, marine fish and shellfish larviculture; seaweed farming; cage culture; integrated fish farming; culture of indigenous fish species; and investment in the fish feed industry.
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Jimmy Brian Mboya,Kevin Odhiambo Obiero,Maureen Jepkorir Cheserek,Kevin Okoth Ouko,Erick Ochieng Ogello,Nicholas Otieno Outa,Elizabeth Akinyi Nyauchi,Domitila Ndinda Kyule,Jonathan Mbonge Munguti 한국수산과학회 2023 Fisheries and Aquatic Sciences Vol.26 No.2
Improved fish post-harvest technologies (IFPT) have been promoted as more efficient methods of fish processing, preservation, and value addition than the traditional methods prevalent in developing countries. The adoption rates, however, do not appear to be convincing. The purpose of this study was to determine the socio-demographic and psychological factors that influence intention of Kenyan farmed fish traders to use IFPT. The technology acceptance model (TAM) was used to properly explain the impact of TAM constructs such as perceived usefulness (PU), perceived ease of use (PEOU), and attitude (ATT), as well as socio-demographic factors such as gender, age, education level and fish trading experience on traders’ intention to use the technologies. A cross-sectional survey was conducted to collect data using a semi-structured questionnaire from 146 traders in Busia, Siaya and Kakamega counties. At a significance level of p = 0.05, a linear regression model was used to examine the socio-demographic and psychological determinants of the traders’ behavioral intention to use the improved technologies. The regression analysis revealed that PU (β = 0.443; p = 0.000), PEOU (β = 0.364; p = 0.000) and ATT (β = 0.615; p = 0.000) influence traders’ intention to use IFPT, with ATT having the highest influence on intention. However, the traders’ socio-demographic characteristics have no effect on their intention to use the technologies, as the coefficients for gender (β = 0.148; p = 0.096), age (β = 0.016; p = 0.882), level of education (β = –0.135; p = 0.141) and fish trading experience (β = 0.017; p = 0.869) are all insignificant. These findings show that the traders intend to use IFPT and will use them when it is in their best economic interests.
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