Items related to Quantitative Genetics in Maize Breeding
Synopsis
Preface 1 Introduction 1.1 Quantitative Genetics 1.2 Population Improvement: What do we mean by Recurrent Selection? 1.3 Inbred Line Development 1.4 Conclusions 1.5 References 2 Means and Variances 2.1 Genetically Narrow- vs. Broad-Based Reference Populations 2.2 Hardy-Weinberg Equilibrium 2.3 Means of Non-inbred Populations and Derived Families 2.4 Means of Inbred Populations and Derived Families 2.5 Mean of a Cross between Two Populations 2.6 Average Effect 2.7 Breeding Value 2.8 Genetic Variance 2.9 Means and Variances in Backcross Populations 2.10 Heritability, Genetic Gain, and Usefulness Concepts 2.11 Generation Mean Analysis 2.12 References 3 Resemblance Between Relatives 3.1 Introduction 3.2 Theoretical Basis of Covariance 3.3 Covariance Between Relatives as a Linear Function of Genetic Variances 3.4 References 4 Hereditary Variance: Mating Designs 4.1 Bi-parental Progenies 4.2 Pure Line Progenies (Analysis in self-pollinated crops) 4.3 Parent-Offspring Regressions 4.4 Design I 4.5 Design II 4.6 Design III 4.7 Diallel Methods: The Gardner-Eberhart Analysis II Special Case 4.8 Triple Testcross 4.9 Triallel and Quadrallel 4.10 Inbred Lines 4.11 Selection Experiments 4.12 More on F2 Populations (Special Case of p = q = 0.5) 4.13 Epistasis 4.14 References 5 Hereditary Variance: Experimental Estimates 5.1 Experimental Results 5.2 Iowa Stiff Stalk Synthetic (BSSS) 5.3 Selection Experiments vs. Mating Designs for Prediction 5.4 Epistasis Variance and Effects 5.5 Correlations among Traits and Indirect Selection 5.6 References 6 Selection: Theory 6.1 Selection among Populations 6.2 Selection of Genotypes within Populations 6.3 Intra-population Improvement: Qualitative Traits 6.4 Intra-population Improvement: Quantitative Traits 6.5 Comparing Breeding Methods 6.6 Increasing Gain from Selection 6.7 Correlation among Traits and Correlated Response to Selection 6.8 Multi-Trait Selection 6.9 References 7 Selection: Experimental Results 7.1 Measuring Changes from Selection 7.2 Improvement from Intra-population Selection 7.3 Improvement from Inter-population Selection 7.4 General Effects of Selection 7.5 Factors Affecting Efficiency of Selection 7.6 References 8 Testers and Combining Ability 8.1 Theory 8.2 Correlations between Lines and Hybrids 8.3 Visual Selection 8.4 Genetic Diversity 8.5 Testing Stage 8.6 General vs. Specific Combining Ability 8.7 References 9 Inbreeding 9.1 The Need for Maize Artificial Pollination 9.2 Early Reports of Inbreeding 9.3 Inbreeding Systems 9.4 Inbreeding due to Small Population Size 9.5 Estimates of Inbreeding Depression 9.6 Frequency of Useful Lines 9.7 Types of Hybrids Produced from Inbred Lines 9.8 Heterozygosity and Performance 9.9 References 10 Heterosis 10.1 Introduction and Major Achievements 10.2 Empirical Evidence 10.3 Genetic Basis 10.4 Biometrical Concept 10.5 Heterosis and Prediction Methods across Genotypes 10.6 Components of Heterosis in Intervarietal Diallel Crosses 10.7 Conclusions 10.8 References 11 Germplasm 11.1 Origin of Maize 11.2 Classification of Maize Germplasm 11.3 Races of Maize in the Western Hemisphere 11.4 European Races of Maize 11.5 U.S. Corn Belt Germplasm 11.6 Germplasm Preservation 11.7 Potential and Use of Exotic Germplasm 11.8 References 12 Breeding Plans 12.1 Choice of Germplasm 12.2 Recurrent Selection and Germplasm Improvement 12.3 Integrating Recurrent Selection with Cultivar development 12.4 Intra-population Genetic Improvement 12.5 Inter-population Genetic Improvement 12.6 Additional Considerations for Germplasm Improvement 12.7 Additional Considerations for Inbred Line Development 12.8 References Index
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From the Back Cover
Handbook of Plant Breeding Arnel R. Hallauer · Marcelo J. Carena · J.B. Miranda Filho Quantitative Genetics in Maize Breeding Public investment in maize breeding from 1865 to 1996 was $3 billion (Crosbie et al., 2004) and the return on investment was $260 billion as a consequence of applied maize breeding, even without full understanding of the genetic basis of heterosis. Quantitative genetics has allowed the integration of prebreeding with cultivar development by characterizing populations genetically, adapting them to places never thought of (e.g., tropical to short seasons), improving them by all sorts of intra and inter population recurrent selection methods, extracting lines with more prob ability of success, and exploiting inbreeding and heterosis. Quantitative Genetics in Maize Breeding aims to increase awareness of the relative value and impact of maize breeding for food, feed, and fuel security. Without breeding programs continuously developing improved germplasm, no technology can develop improved cultivars. This volume presents principles and data that can be applied to maximize genetic im provement of germplasm and develop superior genotypes in different crops. This is a unique and permanent contribution to breeders, geneti cists, students, policy makers, and land grant institutions still promoting quality research in applied plant breeding as opposed to promoting grant monies and indirect costs at any short term cost. The book is dedicated to those who envision the development of the next generation of cultivars with less need of water and inputs, with better nutrition; and with higher percentages of exotic germplasm as well as those that pursue independent research goals before searching for funding. Arnel R. Hallauer is C. F. Curtiss Distinguished Professor in Agriculture (Emeritus) at Iowa State University (ISU). Dr. Hallauer has led maize breeding research for mid season maturity at ISU since 1958. His work has had a worldwide impact on plant breeding programs, industry, and students and was named a member of the National Academy of Sciences. Hallauer is a native of Kansas, USA. M.J. Carena is professor of plant sciences at North Dakota State University (NDSU). Dr. Carena has led maize breeding research for short season maturity at NDSU since 1999. This program is currently one the of the few public U.S. programs left integrating pre breeding with cultivar development and training in applied maize breeding. He teaches Quantitative Genetics and Crop Breeding Techniques at NDSU. Carena is a native of Buenos Aires, Argentina. http://www.ag.ndsu.nodak.edu/plantsci/faculty/Carena.htm J. B. Miranda Filho is full professor in the Department of Genetics, Escola Superior de Agricultura Luiz de Queiroz University of São Paulo located at Piracicaba, Brazil. His research interests have emphasized development of quantitative genetic theory and its application to maize breeding. Miranda Filho is native of Pirassununga, São Paulo, Brazil. life sciences
About the Author
Arnel R. Hallauer is C. F. Curtiss Distinguished Professor in Agriculture (Emeritus) at Iowa State University (ISU). Dr. Hallauer has led maize-breeding research for mid-season maturity at ISU since 1958. His work has had a worldwide impact on plant-breeding programs, industry, and students and was named a member of the National Academy of Sciences. Hallauer is a native of Kansas, USA. José B. Miranda Filho is full-professor in the Department of Genetics, Escola Superior de Agricultura Luiz de Queiroz - University of São Paulo located at Piracicaba, Brazil. His research interests have emphasized development of quantitative genetic theory and its application to maize breeding. Miranda Filho is native of Pirassununga, São Paulo, Brazil. M.J. Carena is professor of plant sciences at North Dakota State University (NDSU). Dr. Carena has led maize-breeding research for short-season maturity at NDSU since 1999. This program is currently one the of the few public U.S. programs left integrating pre-breeding with cultivar development and training in applied maize breeding. He teaches Quantitative Genetics and Crop Breeding Techniques at NDSU. Carena is a native of Buenos Aires, Argentina. http://www.ag.ndsu.nodak.edu/plantsci/faculty/Carena.htm
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