The program for Varietal Intelligence for Seed Targeting and Adoption, ViSTA, ViSTA aims to enhance the readiness, quality, and targeted deployment of breakthrough cereal varieties in priority regions by generating and applying integrated varietal intelligence at scale, delivering regional proof points that accelerate adoption and impact for smallholder farmers.
ViSTA is a two-and-a-half-year program implemented by Resourced in partnership with national certification agencies and research institutions, including NASC, EIAR, ZARI, TOSCI and Breeding For Tomorrow. Through a regionalized partnership model, these institutions lead in-country implementation of varietal monitoring and seed system QA/QC strengthening, while Resourced provides overall coordination and technical leadership through a Centralized Function Technical Working Group. This structure ensures cross-country learning, harmonized methodologies, and alignment with global public goods priorities.
The program contributes to improved varietal readiness, seed quality assurance, and more precise targeting of breakthrough cereal varieties, ultimately accelerating adoption and impact for smallholder farmers. By regionalizing genotyping and AI-powered analytics, ViSTA strengthens institutional capacity, enhances data-driven decision-making, and supports more efficient varietal deployment pathways across participating countries.
To enhance the effectiveness, accountability, and impact of cereal seed systems in target regions of Africa by generating and applying high-integrity varietal intelligence through scalable genotyping, AI-powered analytics, and integrated monitoring innovations that strengthen seed quality assurance, varietal fidelity, and data-driven decision-making across the value chain.
Despite decades of investment in cereal crop improvement across sub Saharan Africa, varietal monitoring and seed quality systems remain underdeveloped. This limits the ability of producers, regulators, and policymakers to reliably track the adoption, performance, and integrity of improved varieties. As breeding pipelines become more diversified and context specific, it is increasingly difficult to generate timely, objective evidence on what farmers are planting, how varieties perform under real world conditions, and whether genetic gains translate into measurable impact.
Varietal identity can erode along the seed supply chain due to genetic drift, admixture, mislabeling, and weak quality assurance and quality control systems. Existing monitoring approaches often rely on farmer recall, expert opinion, or infrequent surveys. These methods are costly, retrospective, and insufficient for near real time decision making. The absence of integrated and scalable varietal intelligence systems constrains product lifecycle management, slows varietal turnover, and weakens accountability for breeding investments.
Resourced, in collaboration with national certification agencies, research institutions, and regional bodies, will conduct high quality and targeted research to address these constraints and strengthen efficient, transparent, and sustainable cereal seed systems across priority African geographies. Through the development of regional genetic reference libraries, scalable genotyping applications, AI enabled image analytics, and integrated monitoring tools, the program will build the technical and institutional capacity required to track varietal diffusion, safeguard genetic fidelity, and support data driven decision making from breeder pipelines to farmer fields.
Institutional Ownership and Financing
Long term impact depends on embedding genetic monitoring as a core seed system function from the outset. This requires sustained investment, shared financing models, and clear incentives for national certification agencies, research institutions, and seed companies to take ownership. Leadership sponsorship within national systems is essential so varietal monitoring is treated as an operational priority rather than an externally driven evaluation exercise.
Cost Effectiveness and Practical Design
While genotyping delivers accurate varietal identification, cost remains a barrier to routine use. Sustainability depends on improving affordability and identifying monitoring configurations that deliver credible results at lower cost. Systems must be right sized to balance rigor and feasibility, focusing on high value use cases such as resolving supply chain quality issues and verifying varietal performance to demonstrate clear returns on investment.
Capacity and Adaptive Support
Sustained results require building technical confidence and continuity of use. This includes maintaining strong regional genetic reference libraries, providing flexible technical support to national teams, and cultivating a practitioner oriented community of practice. By grounding implementation in partnership ownership, practical value, and ongoing capacity support, ViSTA can position varietal intelligence as a durable pillar of modern seed system management.
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Piloting regional genetic reference library (GRL) for rice in West Africa,
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Testing RGB-imagery based varietal identification for field deployment,
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Strengthening QA/QC practices through genotyped seed supply chain assessments, and
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Advancing AI-driven analytics for yield prediction, varietal monitoring, and secure data sharing
ViSTA Workplan Overview
ViSTA is structured around four interlinked components that together advance the next frontier of varietal intelligence. These components are delivered through coordinated scopes of work with national partners and CGIAR centers, supported by a centralized technical function led by Resourced to ensure methodological alignment, data harmonization, and cross country learning.
1. The program establishes Regional Genetic Reference Libraries to anchor varietal identification and seed system QA and QC. A West Africa rice reference library, led with NASC and regional partners, will provide the foundation for monitoring varietal uptake and performance. In parallel, a data governance framework for a regional maize reference library in Eastern and Southern Africa will be developed to enable secure, permissioned data sharing and future expansion.
2. ViSTA pilots RGB image based varietal identification models for rice and beans, led by IRRI and CIAT. Structured image libraries linked to genotyped materials will train AI models capable of identifying varieties in the field. These tools are designed to complement genotyping with lower cost, scalable options for routine monitoring.
3. The program implements seed system QA and QC assessments across Ethiopia, Nigeria, Tanzania, and Zambia. National partners will apply genotyping to track varietal integrity along the supply chain, identify points of deviation, and develop practical, cost effective protocols and manufacturing markers that can be embedded into routine seed system operations.
4. ViSTA advances integrated analytics for yield estimation by combining genotypic data, crop cut surveys, household interviews, and satellite imagery. Multi country analytics sprints will develop and validate spatially anchored methods that generate actionable insights on varietal adoption and productivity, strengthening evidence based decision making for breeding programs and policymakers.
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