This cluster aims at learning from and supporting other clusters across all crops to improve the economic sustainability of RTB seed systems in providing quality seed of demanded varieties. This is done through the development of an evidence-based analytical procedure, which includes several standalone components:

(1) approaches and tools to speed up dissemination of improved varieties at large scale, including variety evaluation protocols, release approaches and studies on drivers for adoption;

(2) economic tools to estimate RTB seed supply & demand with a value chain perspective, which will generate critical information to implement profitable, gender responsive, and sustainable seed delivery business models for RTB seed systems;

(3) regulations and policies, including quality declared planting material (QDPM) guidelines and pest risk analysis to define thresholds values for seed-borne pests, to enable a more transparent environment for the development of RTB seed businesses, as well as to reduce yield losses caused by existing and emergent pests;

(4) decision support systems to help R&D partners to select the best multiplication techniques for producing seed, all the way from breeders seed through certified and farmers’ saved seed, based on criteria of efficiency, cost effectiveness and risk management;

(5) models, decision support systems and tools for managing seed degeneration, characterizing existing seed systems, including gender and social relations, and improving on-farm seed quality management to help researchers and practitioners understand formal and informal components of seed systems, in which seed interventions are planned and implemented; and

(6) innovative tools for knowledge sharing, such as communities of practice and ICTs for seed directories, variety catalogues, etc. These tools will be designed and tested in collaboration with stakeholders of crop-specific and system-oriented clusters, piggy-backing on existing interventions. Also, this cluster will add value to existing interventions, by collecting and analyzing critical data through existing M&E systems for formulating and answering key research questions.

A more detailed description of the cluster can be found in the Monitoring, Evaluation and Learning (MEL) platform: here.

Comments, questions? Contact Jorge Andrade-Piedra j.andrade@cgiar.org