Assessing and modelling farmers' decision-making on integrating aquaculture into agriculture in the Mekong Delta

被引:13
作者
Bosma, R. H.
Phong, Le Thanh
Kaymak, Uzay
Van den Berg, J.
Udo, H. M. J.
Van Mensvoort, M. E. F.
Tri, Le Quang
机构
[1] Univ Wageningen & Res Ctr, Fish Culture & Fisheries Grp, NL-6700 AH Wageningen, Netherlands
[2] Can Tho Univ, Coll Agr & Appl Biol, Can Tho, Vietnam
[3] Erasmus Univ, Dept Comp Sci, Rotterdam, Netherlands
[4] Univ Wageningen & Res Ctr, Anim Prod Syst Grp, NL-6700 AA Wageningen, Netherlands
[5] Univ Wageningen & Res Ctr, Lab Soil Sci & Geol, NL-6700 AA Wageningen, Netherlands
关键词
fish; fuzzy logic; motives; change; diversification;
D O I
10.1016/S1573-5214(06)80010-2
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Contrary to the global trend of specialization within agriculture, the rice-based Vietnamese production systems have diversified into integrated agriculture-aquaculture systems. Economic liberalization in 1986 resulted in an explosive increase in rice production and a rapid diversification. This paper describes the history and dynamics of these systems in the Mekong Delta, and the farmers' decision-making in this process. Subsequently, we use fuzzy logic to simulate farmers' decisions to opt for no aquaculture or one of four fish-production systems: waste-fed, pellet-fed, rice-fish, and ditch-dike, i.e., fish-fruit. In a reaction to changing market opportunities the farmers developed these systems either from the depressions left after building a homestead or after raising dikes to improve irrigation and drainage for rice and fruit trees. The decision-making was simulated in a two-level hierarchy decision-tree. The first layer handles the farmer's production preferences for rice, fruit or fish, with composed variables for land, water, labour, capital and market. The second layer simulates the choice between five options: no fish, and the four alternative fish-production systems. The model allowed a farmer to practise different aquaculture systems at the same time. The fuzzy model simulation predicted the frequency distribution of fish production systems fairly accurately, but performed poorly when classifying individual farmers. To improve the accuracy of the simulation, additional rules can be specified and more factors considered for each product by adding a third layer to the decision-tree and replacing the composed variables with fuzzy rules.
引用
收藏
页码:281 / 300
页数:20
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