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. 2021 Jul 16;7(7):e07597.
doi: 10.1016/j.heliyon.2021.e07597. eCollection 2021 Jul.

Value chain analysis of wheat in Duna district, Hadiya zone, Southern Ethiopia

Assefa Ayele  1 , Tessema Erchafo  2 , Alemayehu Bashe  3 , Seyfu Tesfayohannes  3
Affiliations

Value chain analysis of wheat in Duna district, Hadiya zone, Southern Ethiopia

Assefa Ayele et al. Heliyon. .

Abstract

Wheat is a source of food and income for Ethiopian farmers in general, and the Duna district in particular. Despite the district's high wheat production potential, a number of constraints impede the wheat sector's and value chain's development. This study, thus, analyzed the wheat value chain in Duna district, Hadiya zone, Southern Ethiopia. Descriptive statistics, marketing margin, and a multiple linear regression model were used to analyze data from 149 respondents. The result showed that the actors in the wheat value chain have a shaky relationship. According to the findings, flour wholesalers had the highest market margin (18.36%), followed by flour processors (17.70%). The estimated multiple linear regression result revealed that wheat supply is influenced by the quantity of wheat produced, household education level, farming experience, frequency of extension contact, and lagged market price. Furthermore, wheat producers identified climate variability and low wheat prices as the top two problems in wheat production and wheat marketing, respectively. Hence, the government and other concerned bodies should focus on productivity increasing technologies in the study area in order to boost productivity and thus increase wheat market supply. In addition, to solve the marketing problem, the promotion of value-added practices and the formation of wheat cooperatives are suggested.

Keywords: Ethiopia; Market margin; Multiple linear regression; Value chain; Wheat.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
The wheat value chain map in Duna district. Source: Authors computation from the own survey data (2017).
Figure 2
Figure 2
Most important constraints in wheat production in the study area. Source: Authors computation from the own survey data (2017).
Figure 3
Figure 3
Most important constraints in wheat marketing. Source: Authors computation from the own survey data (2017).
See this image and copyright information in PMC

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