How to implement genomic selection?
Using genome-assisted prediction to increase accuracy, manage diversity, intensity or reduce cycle time is normally referred as genomic selection (GS).
The following simulation reports provide practical recommendations for a successful implementation of these methodologies.
Contact: g.covarrubias@cgiar.org
Breeding programs rely on accurate selections to move population means along time. Understanding the best experimental design across environments is pivotal to achieve this goal.
These simulation reports and retrospective analyses demonstrate practical recommendations on the proper experimental design.
Contact: c.werner@cgiar.org
What is the effect of reducing cycle time?
Breeding programs aim to increase productivity of varieties in farmers fields. EiB proposes a fast and accurate population improvement approach as a strategy to release such improved varieties at a faster rate.
These simulation reports show the impact of reducing the cycle time in the short and long-term genetic gain and improve variety release.
Contact: g.covarrubias@cgiar.org
The Breeding Scheme Designer is a tool to explore trade offs between different evaluations strategies in breeding programs using stochastic simulation. Comparisons of different scenarios with respect to genetic gain and genetic gain per dollar invested are enabled.
Version 1. Excel format
By adopting best practices and established modern tools, NARS (national agricultural research systems) are making data-driven decisions to boost genetic improvement. And they are measuring this progress through tracking and setting goals around “genetic gain.”
In this Story of Excellence, Busiso Olga Mavankeni (DR&SS), Ronika Mukaro (DR&SS), Lubasi Sinyinda (ZARI), and Samson Ojok (NARO) discuss how they quantified the cost of their breeding operations. Using the University of Queensland tool, this data supports planning, optimization and improved cost control.
Driving Genetic Gain through selection is at the core of every successful plant breeding program. In this webinar targeting national breeding programs in Africa, EiB will explain the concepts behind genetic gain; introduce tools and approaches to measure genetic gain; provide real examples from a national program in East Africa.
Organized by: CGIAR Excellence in Breeding (EiB), Accelerating Genetic Gains (AGG), along with partners MAIZE, CIMMYT and more
Powerpoint slides (PDF links):
In order to deliver higher rates of genetic gain and variety turnover, breeding programs targeting low- to middle-income countries must adopt standard best practices in breeding scheme design in order to enable a continuous process of optimization to deliver on breeding targets (product profiles).
The CGIAR Excellence in Breeding Platform has developed this series of practical and conceptual manuals to set a common terminology and conceptual framework to visualize the main steps in a breeding process.
By Jerome Bossuet
From 10-12 September, members of the Global Maize Program at the International Maize and Wheat Improvement Center (CIMMYT) team met with breeders, seed system specialists, research associates, technicians and enabling technology leads from Kenya and Zimbabwe for a costing workshop.
The “Breeding Costing Tool” is software made freely available from the Queensland Alliance for Agriculture and Food Innovation and the University of Queensland in Australia.
It is a powerful solution for allowing users to “estimate the cost of crop breeding and its associated research activities and to help breeders make decisions about resource allocation.