Multi-model approach for assessing the sunflower food value chain in Tanzania. (January 2018)

• Record Type: Journal Article
• Authors: Vilvert, Elisa; Lana, Marcos; Zander, Peter; Sieber, Stefan
• Is Part Of: Agricultural systems. Volume 159(2018)
• Page Start: 103
• Page End: 110
• Publication Date: 2018-01
• Subjects: Sunflower -- Food value chain -- Modelling -- Tanzania -- Food security; Agricultural systems -- Periodicals; Agriculture -- Environmental aspects -- Periodicals; 338.16
• DOI: 10.1016/j.agsy.2017.10.014
• Languages: English
• ISSNs: 0308-521X

Abstract

Abstract: Sunflower is one of the major oilseeds produced in Tanzania, but due to insufficient domestic production more than half of the country's demand is imported. The improvement of the sunflower food value chain (FVC) understanding is important to ensure an increase in the production, availability, and quality of edible oil. In order to analyse causes and propose solutions to increase the production of sunflower oil, a conceptual framework that proposes the combined use of different models to provide insights about the sunflower FVC was developed. This research focus on the identification of agricultural models that can provide a better understanding of the sunflower FVC in Tanzania, especially within the context of food security improvement. A FVC scheme was designed considering the main steps of sunflower production. Thereafter, relevant models were selected and placed along each step of the FVC. As result, the sunflower FVC model in Tanzania is organized in five steps, namely (1) natural resources; (2) crop production; (3) oil processing; (4) trade; and (5) consumption. Step 1 uses environmental indicators to analyse soil parameters on soil-water models (SWAT, LPJmL, APSIM or CroSyst), with outputs providing data for step 2 of the FVC. In the production step, data from step 1, together with other inputs, is used to run crop models (DSSAT, HERMES, MONICA, STICS, EPIC or AquaCrop) that analyse the impact on sunflower yields. Thereafter, outputs from crop models serve as input for bio-economic farm models (FSSIM or MODAM) to estimate production costs and farm income by optimizing resource allocation planning for step 2. In addition, outputs from crop models are used as inputs for macro-economic models (GTAP, MAGNET or MagPie) by adjusting supply functions and environmental impacts within steps 3, 4, and 5. These models simulate supply and demand, including the processing of products to determine prices and trade volumes at market equilibrium. In turn, these data is used by bio-economic farm models to assess sunflower returns for different farm types and agro-environmental conditions. Due to the large variety of models, it is possible to assess significant parts of the FVC, reducing the need to make assumptions, while improving the understanding of the FVC. Highlights: A framework linking models along the Tanzanian sunflower FVC is proposed. The combination of models makes possible the assessment of the food value chain. A model-based analysis contributes to improve the understanding of sunflower chain. The FVC improvement will ensure an increase in production and availability of oil.