Chapter 1. General introduction

We describe the main characteristics of two approaches to the linear selection indices theory. The first approach is called standard linear selection indices whereas the second of them is called eigen selection index methods. In the first approach, the economic weights are fixed and known, whereas in the second approach the economic weights are fixed but unknown. This is the main difference between both approaches and implies that the eigen selection index methods include to the standard linear selection indices because they do not require that the economic weights be known. Both types of indices predict the net genetic merit and maximize the selection response, and they give the breeder an objective criterion to select individuals as parents for the next selection cycle. In addition, in the prediction they can use phenotypic, markers, and genomic information. In both approaches, the indices can be unrestricted, null restricted or predetermined proportional gains and can be used in the context of single-stage or multistage breeding selection schemes. We describe the main characteristics of the two approaches to the linear selection indices theory and we finish this chapter describing the Lagrange multiplier method, which is the main tool to maximize the selection index responses.

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Bibliographic Details
Main Authors: Ceron Rojas, J.J., Crossa, J.
Format: Book Chapter biblioteca
Language:English
Published: Springer 2018
Subjects:AGRICULTURAL SCIENCES AND BIOTECHNOLOGY, LINEAR MODELS, PHENOTYPIC VARIATION, GENETIC GAIN, SELECTION CRITERIA,
Online Access:https://hdl.handle.net/10883/19800
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Summary:We describe the main characteristics of two approaches to the linear selection indices theory. The first approach is called standard linear selection indices whereas the second of them is called eigen selection index methods. In the first approach, the economic weights are fixed and known, whereas in the second approach the economic weights are fixed but unknown. This is the main difference between both approaches and implies that the eigen selection index methods include to the standard linear selection indices because they do not require that the economic weights be known. Both types of indices predict the net genetic merit and maximize the selection response, and they give the breeder an objective criterion to select individuals as parents for the next selection cycle. In addition, in the prediction they can use phenotypic, markers, and genomic information. In both approaches, the indices can be unrestricted, null restricted or predetermined proportional gains and can be used in the context of single-stage or multistage breeding selection schemes. We describe the main characteristics of the two approaches to the linear selection indices theory and we finish this chapter describing the Lagrange multiplier method, which is the main tool to maximize the selection index responses.