Publication Date: 2025/01/08
Abstract: This paper mainly aims to capture and assess projects and initiatives that have led or are leading innovative actions or good practices that can be replicated or scaled up in Sudan. Methods used mainly desk review, interviews using convenient sampling method with a number of experts charged of different occupation in academia, research centres, line ministries and freelance experts. Assessment was covered selected projects of innovative actions and good ecological and /or socioeconomic practices implemented by development partners. Focusing was on four crosscutting accelerators: which is technology, innovation, data, and complements (governance, human capital and institutions). The secondary and primary data collected were subjected to screening, sorting out and thematic analysis. Main findings of good practices adopted include; ecosystems-based adaptation (EbA) to reduce vulnerability and build resilience to climate change, adaptive technology like zero tillage, improve crop management practices etc., promotion of inclusive high- potential value chains, that allow resilient models for smallholder producers and other herewith described good practices. It is recommended that the local authorized and concerned partners to; support and scale up and replicate action needed to form consultative natural resource forum develops innovative tools for EbA, to alleviate vulnerability and build resilience to climate change; monitoring, reporting, and verification (MRV) system in sectors; establish Regional Observatory Centre; adoption of social protection system; land governance, support tenure rights and land ownership, The technologies judged as most appropriate by producers to be incorporated into on-farm demonstrations and strengthening the research and to be linked to development.
Keywords: Innovative Actions, Good Practices, Accelerators, Scale Up, Replication.
DOI: https://doi.org/10.5281/zenodo.14613778
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT25JAN079.pdf
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