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Full Description
Students and researchers in plant breeding and molecular applications, and those interested in innovative biological research realized the need for comprehensive knowledge in Quantitative Genetics. Software packages have also grown concomitantly providing ready-made path to analysis of data generated. But users feel despondent as their knowledge is deficient to understand the logic or process steps in such software. They want more knowledge in Quantitative Genetics and seek quality books. This book aims to answer those needs. Its organization and coverage of content differ from the pattern in well-known books on the subject. The book is unique in its effort to carry along readers with no specific mathematical/ statistical background, especially those who specialize in Agriculture, Biology and related fields, to a high level of quality experimentation employing quantitative genetic tools. With an introduction explaining how contemporary developments in the fields of genetics, statistics and particularly probability theory blended to evolve the subject of quantitative genetics, the book provides practical details of probability distributions and their application in genetic investigations. Specifically designed plant breeding experiments are used to explain and interpret various mating designs and their specific utility. In the process, definition of additive effect and additive genetic variance are defined anew and the fallacy in their formulation found in illustrious treatises by Mather, Jinks and Falconer is corrected. In analyzing genetic variation, Fisher's average excess and effect of gene substitution are used probably for the first time in a book.
Contents
Introduction Basics of Probability Theory
Probability
Simple and Compound Events
Addition and Multiplication Laws
Conditional Event and Multiplication Law and Theorem of Probability
Multiplication Theorem
Partitioning of Sample Space
Bayes Theorem
Use of Matrix Theory in Solving Problems in the Field of Probability
Common Mating Systems Distributions
Expectations and Moments of a Variable
Discrete and Continuous Distributions
Analysis of Variance (ANOVA)
Fixed and Random Effects Model: Major Difference
t-test and Inferences
Duncan's Multiple Range Test (DMRT)
Appendix 3.6 Inference: Essential Basics
Important Concepts of Inference
Tests of Significance, Confidence Limit and Confidence Interval
Likelihood
Likelihood Ratio Quantitative Genetics: Genetic Analysis of Phenotypic Variation
Basics
QT and Genetic Values: Case of a Single Gene
Phenotypic and Genetic Variance
Alternate Formulation of Additive Genetic Variance and Interpretation of Additive Effect
Generation Means and Genetic Effects
Additive Genetic Variance and Natural Selection
Two Genes
QT Values in Two Genes
Genetic Effects and Variances
Various Types of Gene Interaction Inbreeding and Heterosis: Genotypic Frequencies Under Inbreeding
Li's Formulation of Inbreeding Coefficient
Additive Genetic Variance Under Inbreeding
Useful Relationships Involving Inbreeding
Heterosis
Inbreeding Depression
Breeding Value Genetic Divergence: Basics of Genetic Divergence
Numerical Example
Importance of Characters in Genetic Differentiation
Genetic Divergence and Heterosis
Implications of Genetic DivergenceHeterosis Hypothesis in Plant Breeding
Appendix 1: The process of obtaining linear combinations Y using
error variance-covariance matrix in Section 7.2 Mating Systems: Diallel Crosses
Covariance Between Relatives
Half-sibs and Full-sibs
Covariance of Half- and Full-sibs in the General Case
Diallel Crosses (Griffing's Approach)
Line x Tester Design
Partial Diallel Cross
Multiple Crosses
Diallel Crosses: Some General Observations
