Agropastoralis Scientia
Volume 2, Numéro 2, Pages 235-250
2026-05-07
Sustainable Sheep Production In Algeria: Mapping Challenges And Opportunities Across The Value Chain
Authors : Moula Nassim . Djebala Salem .
Abstract
The sustainable development of the sheep sector in Algeria is crucial for rural livelihoods, food security, and ecosystem resilience. This study assesses the sector’s sustainability using an integrated “One Health” and “value chain” framework combining economic, social, and environmental dimensions. Based on a multi-criteria analysis (Analytic Hierarchy Process, AHP), three development scenarios were evaluated: (1) the Business-as-usual model, (2) the Cooperative structure model, and (3) the Smart, traceable sector model. Primary data were collected from 200 farmers across three representative agro-ecological regions (High Plateaus, Aurès Mountains, and Southern Steppe zone) through structured surveys, 30 semi-structured interviews, and 3 regional focus groups. Complementary data from official statistics (MADR, 2023) and FAO reports (2022–2024) were analyzed using SPSS and thematic coding. Results show that the Smart, traceable sector scenario achieved the highest overall sustainability score (3.75/5), followed closely by the Cooperative structure model (3.70/5). Quantitatively, the analysis indicates that cooperative organization could increase average carcass yield by +12%, reduce post-weaning mortality by –8%, and improve farmers’ income stability by +15% compared to the baseline scenario. These findings highlight the potential of digital innovation, collective organization, and coordinated governance to improve efficiency, resilience, and equity throughout the value chain. Policy recommendations emphasize the establishment of regional cooperatives, national traceability systems, and integrated livestock management platforms to ensure a more sustainable and inclusive future for Algeria’s sheep sector.
Keywords
Sustainable livestock systems; Sheep value chain; Agricultural innovation; Smart farming; Multi-criteria analysis; One Health
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