Please use this identifier to cite or link to this item: http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/2253
Title: The Suitability of (MOAAS) for Small Scale Agro Enterprise Development in Sri Lanka
Authors: Fernando, W.H.R.E.
Hitinayake, H.M.G.S.B.
Widanapathirana, C.U.
Kotagama, H.B.
Keywords: Extension;Market oriented agricultural advisory services (MOAAS);Small scale farming community;Sri lanka;Peasant
Issue Date: 2019
Publisher: University of Jaffna
Abstract: One of the constraints associated with the general farming community of Sri Lanka is inability of farmers in adapting to the volatile market situations. Market oriented Agricultural Advisory Services (MOAAS) are knowledge based prediction systems that is successfully used in many countries as effective advisory services in strengthening the peasant farmer to identify and cater the market need, considering current market pattern with multiple approaches, focusing the development of overall production chain through securing new markets. This preliminary study intends to develop an operational tool using simple linear mathematical programming to predict commercial information to use it as supportive equipment for MOAAS to assess the use and suitability of MOAAS under practical farming operations based on a randomly selected small groups of small scale farmers from four areas of Sri Lanka. MOAAS was used to find the best crop animal combination with the lower and upper limits, reduced cost, allowable increase and decrease, practical alternative agricultural options. Farming activities were intensively studies to compare the commercial aspects of the venture before and after the programme was implemented and to evaluate the progress. It was concluded that the MOAAS programme offered promising results in cost reduction and increasing the average income per unit. The results show that the MOAAS programme can be continued with improvements suggested, expecting positive outcomes.
URI: http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/2253
ISSN: 2465-6143
Appears in Collections:ICDA 2016

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