What is the best selection method?
Selection methods for multiple traits aim to find the balance to increase the population means for multiple traits.
These simulation reports demonstrate the differences between classical methods such independent culling and selection indices, to support the practical implementation of indices.
Contact: g.covarrubias@cgiar.org
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
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
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
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.
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.
Maize hybrid seed provides farmers with varieties containing improved genetics, such as high yield potential and unique trait combinations to counter diseases and adverse growing conditions.
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.
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.
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.