Assessment of socio-economic factors that limits banana production and its mitigation strategies: a study of banana farmers in Sarawak - Teruki, Neilson; Alwie, Aryaty; Mokhtar, Suraya Hanim (Faculty of Agriculture and Food Sciences, Universiti Putra Malaysia Bintulu Sarawak Campus, 2019)
In Malaysia, the importance of banana is clearly indicated in the National Agro-Food Policy (2011 – 2020) where it is listed as one of the 15 fruit types prioritized for commercial cultivation. Banana ranked second in Malaysia in terms of production area, covering about 34,894.06 ha with a total annual production of 350,492.59 metric tonnes. Banana industry contributes significantly to country's socio-economic development in terms of improving livelihoods of smallholder farmers through incomes generation. In spite of ever growing global demand for banana fruit and Malaysia’s tropical climate and strategic geographical location, its contribution to the world’s banana market is quite low which is about 0.1% of the world production. Banana production has declined in the recent years. This trend has continued to date, and the information on the factor responsive for this decline is scanty. There is therefore need to conduct an assessment of the socio-economic factors influencing production of bananas in order to come up with mitigating measures to reverse the setback. Thus, this study is aimed at investigating factors influencing banana production in Malaysia with the specific objectives of identifying and determining the most influencing factors affecting the banana production in the study area. In order to attain these objectives, this study will be carried out in Sarawak, Malaysia. The primary data used for this study will be selected randomly from the list of the registered banana farmers obtained from DOA (Department of Agriculture) and IADA (Integrated Agricultural Development Area) Sarawak. Data collection will be using a well-structured close ended questionnaire via face-to face survey. The descriptive, exploratory factor analysis and multiple linear regression analysis will be used to analyse the data.