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Breeding scheme optimization

Optimal program sizes

What is an optimal program size?

The size of the breeding program is something that can increase the genetic gain by taking advantage of factors such as selection intensity or the among- and within-family variance.

These simulation reports demonstrate the trade-offs between of number of parents, crosses and progeny per cross, and provide practical advice on how to set the level of each. 

Contact: d.gemenet@cgiar.org

 

Choosing the right number of testers

What is the right number of testers?

Hybrid breeding aims to keep and increase the non-additive interactions in the final products while increasing the additive genetic value in a recurrent selection program.

The following simulation reports and retrospective analyses explore questions such as how many testers should be used to capture the general combining ability (GCA) that maximizes additive and non-additive effects.

Contact: d.gemenet@cgiar.org

 

Implementing hybrid breeding

Should we move to hybrid breeding?

Hybrid breeding aims to keep and increase the non-additive interactions in the final products while increasing the additive genetic value in a recurrent selection program.

The following simulation reports show how the hybrid genetic model applies to non-inbred crops and different ploidies. In addition, we provide practical advice for related questions related to testers, 3-way crosses, etc.

Contact: m.r.labroo@cgiar.org

 

Effects of reduced cycle time

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

 

Breeding scheme designer

 

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

Webinar: Enhancing and measuring Genetic Gain in crop breeding

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):

EiB breeding scheme optimization manuals

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. 

Identification key for agriculturally important plant-parasitic nematodes: a manual for nematology

Nematodes are diverse metazoans with an estimated one million species covering nearly all ecosystems in their roles as bacterivores, herbivores, parasites of animals and plants, and consumers of dissolved as well as particulate organic matter.

Their economic impact was estimated at a loss of $118 billion in 2001, half of that in rice and maize alone. Accuracy of species identification is therefore fundamental to our understanding and communication of the ecological role of any organism.

Linear selection indices in modern plant breeding

This book represents a compilation of work done in the area of “selection indices” in animal and plant breeding.

Selection indices were originally developed by Smith (1936) in plant breeding and by Hazel (1943) in animal breeding to address the selection of plants or animals scored for multiple traits.

In agriculture, the breeding worth (or net genetic merit) of a candidate for selection depends on several traits. For example, grain yield, disease resistance, and flowering time.

Sarah Hearne

 Toolbox

Sarah Hearne
Sarah Hearne’s work focuses on the interface between genetic resources and plant breeding and in the adaptation/development and use of tools to enhance the identification and transfer of useful native genetic variation from exotic germplasm to breeding germplasm. She leads the maize and informatics work of the Seeds of Discovery (SeeD) initiative at the International Maize and Wheat Improvement Centre (CIMMYT). Hearne is presently a Principal Scientist at CIMMYT. Previously, she was a Plant Molecular Geneticist/Physiologist at the International Institute of Tropical Agriculture (IITA). Hearne holds a doctoral degree on morphological, physiological and molecular interactions between maize and the parasitic angiosperm Striga hermonthica from the University of Sheffield – U.K.

Job title: 
Toolbox coordinator

Eduardo Covarrubias

Optimizing breeding schemes

Eduardo Covarrubias
As optimizing breeding schemes lead, Eduardo supports breeding programs to define processes, apply project management and quantitative genetics principles, and use computer simulations to optimize their breeding scheme. Eduardo studied crop sciences at the University of Chapingo, Mexico, and then gained his PhD in plant breeding with a specialization in quantitative genetics at the University of Wisconsin. Prior to joining EiB, Eduardo was the biometrics wheat lead at Bayer CropScience, now BSF, in Belgium.