SRE: A Practical Tool for Estimating Seed Requirements for Vegetatively Propagated Crops Key highlights • We developed a Seed Requirement Estimation (SRE) Tool for practical, data-driven VPC (sweetpotato, cassava, yam) seed production planning by National Agricultural Research Institutes, commercial seed producers, policymakers, NGOs, and humanitarian organizations—reducing losses and de-risking investments. • Proven application in Uganda, Tanzania, Kenya, and Nigeria across sweetpotato, cassava, and yam. • Data-driven, editable assumptions validated with stakeholders (adoption rates, area projections, replacement intervals, purchase share, seeding rates, multiplication/wastage), enabling dynamic, scenario-based planning and rapid multiplication options. • Accessible online via TAAT e-catalogue. What was the problem? For vegetatively propagated crops (VPCs) such as sweetpotato, cassava, and yam, a consistent and timely supply of quality seed is critical for improved crop production. Efficient seed production planning, especially from the supply side, is therefore essential. In Sub-Saharan Africa, Early Generation Seed (EGS) production for VPCs is predominantly managed by the public sector, although a small number of private actors are also involved. Further along the chain, certified and Quality Declared Seed (QDS) classes are typically produced by Commercial Seed Producers (CSPs), many of whom operate as farmer-led enterprises. Both public institutions and farmer-led seed enterprises face significant challenges in accurately forecasting seed demand. This is largely due to the absence of reliable data on factors such as adoption rates, seed replacement behavior, and market segmentation. As a result, seed production is often either under- or over-supplied, leading to inefficiencies and economic losses. While academic models for demand estimation exist, they are generally not practical for the seasonal, real-time decision-making required by seed actors. A user-friendly, data-driven, and dynamic tool was therefore needed—one that accommodates flexible entry and exit points along the seed chain and supports tailored multiplication calendars. Such a tool would improve forecasting, enhance efficiency, reduce losses, and support the development of a more market- responsive and scalable seed system. What objectives did we set? The primary objective was to develop a practical, automated gender responsive tool to support National Agricultural Research Institutes (NARIs) and commercial seed producers in planning timely and accurate seed production for vegetatively propagated crops. Figure 1: Seed Requirement Estimation (SRE) tool for National-Level Figure 2: Seed Requirement Estimation (SRE) tool for Enterprise-Level Where did we work? To date, the tool has been applied in: • Uganda – for sweetpotato and cassava • Tanzania – for sweetpotato and cassava • Kenya – for sweetpotato • Nigeria – for sweetpotato, yam, and cassava How did we make it happen? The tool, officially named the Seed Requirement Estimation (SRE) Tool, was developed by scientists at the International Potato Center (CIP) with input from a diverse group of experts representing research and academic institutions, national agricultural research systems, NGOs, private sector entities, and humanitarian organizations. The tool offers two levels of estimation to meet the needs of both national policymakers and individual seed producers: 1. National-Level Estimation (Figure 1): This level estimates the total national requirement for Certified and Quality Declared Seed (QDS) based on adoption rates, seed replacement cycle, area under improved varieties, and purchase behavior. It helps assess the potential market size and guides strategic planning at the country level. 2. Enterprise-Level (Individual) Estimation: Based on series of assumptions, this level conducts backward calculations from the national requirement for Certified seed or QDS to determine the volume of seed required at each preceding stage—certified, basic, pre-basic, and tissue culture. Crucially, the tool allows seed producers to choose flexible entry and exit points in the seed value chain depending on their business model. Whether a producer starts at the TC level and exits at pre-basic, or begins at basic and goes up to QDS, the tool customizes the seed multiplication calendar and land resource needs accordingly. This flexibility empowers both public and private actors to design seed production strategies tailored to their capacity, goals, and market opportunities. It supports operational decision-making by early generation seed producers and seed entrepreneurs. The assumptions used in the tool were validated through several rounds of stakeholder meetings in-person or online. However, the user can make explicit assumptions for the following parameters to determine the seed requirement: 1. Estimated adoption rate of improved varieties by farmers in the field. This country-specific information can be obtained through secondary data (i.e., FAO, household surveys, literature review), stakeholder meetings, expert opinions, ICT platforms. This step should be completed by crop specialists and research and development experts. 2. The area under improved varieties is projected based on the estimated adoption rate and forecasting models. The forecasting models are based on historical trends (FAO data) and then adjusted for seasonal effects. The linear projection model is used for projecting area under crop. 3. The seed replacement rate (the number of seasons after which farmers repurchase new seed of the variety that they are using). This information is obtained from survey reports or expert opinion. 4. Proportion of purchased seed. When a farmer is planting a plot s/he may not purchase all the seed planted. A combination of own saved seed planted in a small area, then extended by taking cuttings from the initial plot and with purchased seed may be used. This will be estimated based on survey data or expert opinion. Key Contact Persons: Srini Rajendran (Srini.rajendran@cgiar.org) Kwame Ogero (k.ogero@cgiar.org) Martin Ogwal (m.ogwal@mt.co.ug) CIP thanks all donors and organizations that globally support its work through their contributions to the CGIAR Trust Fund. https://www.cgiar.org/funders/ © 2025. This publication is copyrighted by the International Potato Center (CIP). It is licensed for use under the Creative Commons Attribution 4.0 International License 5. The seeding rate (amount of seed/plant population per ha) . 6. The multiplication rate, number of harvests, seasons, and wastage is accounted for at each stage of production, and then through the seed value chain. The tool focuses on rapid multiplication technologies using short cuttings and close spacing on seed beds. However, rapid multiplication technologies differ crop-wise. What did we achieve? Originally conceptualized during the Sweetpotato Action for Security and Health in Africa (SASHA) project in 2017, the tool was further improved and expanded under the Sweetpotato Genetic Advances and Innovative Seed Systems (SweetGAINS) project (2019–2021). It has since been validated across multiple crops and countries through The Program for Seed System Innovation for Vegetatively Propagated Crops in Africa (PROSSIVA) and the CGIAR’s Seed Equal Initiative (now known as Inclusive Delivery). The tool is currently hosted by CIP’s partner MOOD Technologies in Uganda and can be accessed online via https:// mt.co.ug/bid_tools. Users are required to register to gain access. The tool has been validated and applied in Kenya, Tanzania, Uganda, and Nigeria. The users of this tool are able to plan their seed production efficiently. Beyond research and seed producers, the tool has also proven valuable for policymakers, NGOs, and humanitarian organizations. It helps them anticipate seed demand, allocate resources more effectively, reduce supply imbalances, and de-risk investments—ensuring a more resilient and market-responsive seed system. Figure 2: Basic seed production using Sandponic technique in TARI, Tanzania Key lessons learned • Assumptions must be frequently updated using new data and expert consultations. • Demand forecasting must be dynamic—accounting for shocks, trends, and seasonal effects. • The interface must remain simple, intuitive, and adaptable for both public sector planners and private seed businesses. • Potential for including more crops but requires more consultation with crop experts before they are incorporated into the tool. However, the tool can accommodate more VPCs. https://mt.co.ug/bid_tools https://mt.co.ug/bid_tools