인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
ABSTRACT Post‐harvest fish losses (PHFL) significantly impact the aquaculture sector in Kenya, undermining food security and economic growth. This study investigated socio‐demographic factors and handling practices influencing PHFL in Kakamega County's cultured tilapia value chain. Data were collected from 94 value chain actors operating across multiple nodes, including farming, processing and retail stages from six sub‐counties using surveys and observations. Results revealed that 64% of participants were female, and 40.3% had completed high school, with only 26.6% holding valid food handler certificates. Household sizes mostly ranged from 4 to 9 members, and experience in the value chain varied, with 33% having 5–10 years of experience and 17% had over 21 years of experience. PHFL were significant across nodes, with farm gate losses highest in Butere (32%) and lowest in Likuyani (8.42%). Wholesale and retail losses were also notable, with Mumias East showing the highest overall losses. Regression analysis identified key predictors of PHFL, including poor sanitary conditions, lack of training, inadequate water quality and cooling practices, explaining 87.2% of the variance in PHFL. Experience negatively correlated with PHFL ( r = −0.354, p < 0.01), indicating that more experienced individuals incurred lower losses. Chi‐square tests showed significant associations between PHFL and factors like household size, occupation, training and sanitation but not gender, education or age. The findings highlight the need for targeted interventions, including training programmes, infrastructure improvements and adherence to food safety standards, to minimise PHFL, improve fish quality and enhance food and nutrition security in Kakamega County.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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