Bio-economic evaluation and optimization of livestock intensification options in the Central Highlands of Vietnam
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Birnholz, Celine ; Bolliger, Adrian ; Khanh, Truong Tan ; Groot, Jeroen ; Paul, Birthe , 2017, "Bio-economic evaluation and optimization of livestock intensification options in the Central Highlands of Vietnam", doi:10.7910/DVN/LDLJ6D, Harvard Dataverse, V1, UNF:6:0/WsHVk+B0+f3EbIlix7yw==
Permanent link to cite or share this item: http://hdl.handle.net/10568/80920
Beef cattle have high market demand in Vietnam and the Dak Lak local government encourages the development of beef value chains. Household surveys were carried out in Cu Jut and Ea Kar districts and farming systems and production specialization were found to differ in each district. Ea Kar farmers were more specialized in livestock production while Cu Jut farmers were more focused on cash crop production. The FarmDESIGN bio-economic model allowed us to study two representative farms, one from Ea Kar and one from Cu Jut district. The Ea Kar farm had a more integrated livestock production system, providing manure to the fields that produced feed for the livestock. Both farms had high farm-level nitrogen balances due to high feed and fertilizer imports. The soil organic matter (SOM) balance in Cu Jut was negative (-48 kg/ha) because of its manure management strategy. On both farms, the residues were removed from the fields, providing no input to SOM and were fed to livestock (Ea Kar) or burnt (Cu Jut). Livestock intensification scenarios that were implemented for the Ea Kar case study farm showed two possible pathways – forage-based and grain-based cattle fattening. Both strategies could lead to higher operating profits (+35% for forage-based cattle fattening and +59% for grain-based cattle fattening) and lower labor demands if they were skillfully implemented for the latter scenario. However, grain-based fattening negatively affected SOM balance, in contrast to forage-based fattening. The optimization of the current Ea Kar farm with FarmDESIGN indicated that there are options to change the farm setup in order to increase profitability and reduce family labor demands. However there are some trade-offs to consider. If reducing environmental impact is a priority, there are alternative farm configurations that will produce lower greenhouse gas emissions while increasing SOM and increasing overall farm profitability. These should be assessed along with the farmers’ interests and priorities. Quantitative farm modeling of complex mixed farming systems can assess potential impact and support decision-making, targeting, prioritization and program design for sustainable intensification of livestock systems.
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