Strengthening Public Breeding Pipelines by Emphasizing Quantitative Genetics Principles and Open Source Data Management

From
CGIAR Excellence in Breeding Platform (EiB)
Published on
26.07.21
Impact Area
Big data, Food security
Funders
Australia, Gates Foundation, Germany, United Kingdom, United States of America

This opinion piece published in Frontiers in Plant Science briefly presents the breeder’s equation and highlights the terms that can be manipulated to increase genetic gain per time and per dollar invested. The authors also present some guidelines recommended by the Excellence in Breeding (EiB) Platform to optimize the selection response in a classical breeding scheme to create an aggressive pipeline with high genetic gains. They then discuss how genome-assisted prediction methods (genomic selection, GS) can be used for further optimization across all breeder’s equation terms. Opinion piece by Giovanny Covarrubias-Pazaran (Excellence in Breeding, EiB), Johannes W. R. Martini (CIMMYT), Michael Quinn (EiB) and Gary Atlin (Bill and Melinda Gates Foundation).

The strategic goals of the CGIAR, which serves small-scale agricultural producers in the developing world, include the increase of nutrition and food security, the reduction of poverty, and the reduction of the “environmental footprint” of agricultural production systems. For each of these goals, progress can be made by breeding new crop varieties with increased productivity, stress resilience, nutritional value, and reduced requirement for fertilizer or agrochemicals.