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quantitative genetics msc agriculture 1 yr
- 1. Dr. Mayur (21878) 1 UNIT -1 Introduction, history and applications of Quantitative Genetics: Introduction Nature of quantitative traits and its inheritance Multiple factor hypothesis Principles of analysis of variance Manova, biplot analysis Comparison of means and variances for significance
- 3. Introduction 1. Biometrics 2. Biometrical Genetics 3. Quantitative Genetics 4. Population Genetics
- 4. Dr. Mayur (21878) 4 Biometrics 1. Statistical concepts and procedures to the study of biological problems 2. Also known as biometry and biostatistics.
- 5. Dr. Mayur (21878) 5 Biometrical Genetics 1. Statistical concepts and procedures to the study of genetical problems 2. Also known as statistical genetics or mathematical genetics. 3. Two branches: A. Quantitative Genetics B. Population Genetics
- 6. Dr. Mayur (21878) 6 1. Quantitative Genetics Study of polygenic or quantitative characters. Extension of Mendelian genetics Provides way and means to study polygenic variation Estimation based on means, variances and covariances. It deals with continuous variations. Help in better planning of crop improvement programmes. Fisher (1918) foundation of quantitative genetics
- 7. Dr. Mayur (21878) 7 2. Population Genetics Frequency of genes and genotypes in Mendelian population. Involves mathematical procedures. Deals with oligogenic variation. discontinuous variations. Estimation based on frequencies and ratio. Cannot be used for analysis of polygenic variations. Hardy and Weinberg (1908) foundation of population genetics
- 8. Dr. Mayur (21878) 8 Quiz Q1. Application of statistical concepts and procedure to study the biological problem is known as Q2. Application of statistical concepts and procedure to study the genetical problem is known as Q3. is a extension of Mendelian genetics. Q4. Quantitative genetics shows variations. Q5. .. Laid the foundation of Quantitative genetics. Q6. . Laid the foundation of Population genetics.
- 9. Dr. Mayur (21878) 9 Landmarks in the history of biometrical genetics
- 10. Dr. Mayur (21878) 10 Landmarks in the history of biometrical genetics
- 11. Dr. Mayur (21878) 11 Landmarks in the history of biometrical genetics
- 12. Dr. Mayur (21878) 12 Landmarks in the history of biometrical genetics
- 13. Dr. Mayur (21878) 13 Homework Q1. Define the following term A. Biometrics B. Population Genetics C. Quantitative Genetics D. Biometrical Genetics Q2. What are the major difference between population genetics and Quantitative genetics? Q3. Enlist any five qualitative and quantitative traits of your research crop. Q4. Give the landmarks in history of biometrical genetics (Any ten).
- 14. Dr. Mayur (21878) 14 History of Biometrical Genetics 1. General concepts and Experimental design: 2. Genetic Diversity: 3. Correlation, path and Discriminant Function: 4. Mating Design: 5. Stability analysis:
- 15. Dr. Mayur (21878) 15 Classification of Biometrical techniques Applications/Uses Biometrical techniques Assessment of variability 1. Measure of dispersion 2. Components of genetic variances 3. Metroglyph Analysis 4. D2 Statistics Selection of elite Genotypes 1. Correlation Analysis 2. Path Coefficient Analysis 3. Discriminant Function Analysis Choice of parents and Breeding Procedure 1. Diallel cross analysis 2. Partial Diallel Analysis 3. Line X Tester Analysis 4. Generation Mean Analysis Varietal Adaptibility 1. Stability Analysis
- 16. Dr. Mayur (21878) 16 Applications in crop improvement Assessment of polygenic variability Selection of elite genotypes Choice of parents and breeding procedure Study of varietal adaptation
- 17. Dr. Mayur (21878) 17 Assessment of polygenic variability 1. Effect of plant breeding programme depends on existence of genetic variability. 2. Genetic improvement in any characters depends on genetic variability. 3. Simple measure of variability-determines magnitude 4. Components of genetic variance-divide genetic variation in additive, dominance and epistasis.. Gene action. 5. Information about gene action--------- Breeding procedure. 6. D2 Statistics- genetically divergent parents hybridization programme. 7. Metroglyph analysis-phenotypic variability at a time.
- 18. Dr. Mayur (21878) 18 Selection of elite genotypes 1. Most important activity in all breeding programme. 2. Efficiency depends on extent of genetic variability and heritability. 3. Selection----high heritability. 4. Correlationmutual relationship among various traits. 5. Path analysis---Splits correlation into direct and indirect effects. 6. Discriminant function----identification of traits having high selection efficiency.
- 19. Dr. Mayur (21878) 19 Choice of parents and breeding procedure 1. Selection of parents---on phenotypic performance alonenot a sound procedure. 2. Selection of parents-------genetic values. 3. Three biometrical techniques---generation mean analysis, biparental cross analysis and triple test cross analysis. (Individual cross). 4. Diallel analysis, partial diallel analysis and line x tester analysis- several cross simultaneously.
- 20. Dr. Mayur (21878) 20 Study of varietal adaptation 1. Varietal adaptability to environmental fluctuaction--- stabilization. 2. Stability analysis identification of adaptable genotypes over changing environment. 3. Stable genotypesadjust phenotypic response.
- 21. Dr. Mayur (21878) 21 Multiple factor hypothesis Originally postulated by Yule (1906) but experimental evidence presented by Nilsson-Ehle (1908). Ex. (Homework) 1. Seed colour in wheat (Odd roll number) 2. Skin colour in Man (Even roll number) 3. Corolla length in tobacco (Nicotiana)
- 22. Dr. Mayur (21878) 22 Analysis of Variance (ANOVA) Analysis of variance (Abbreviated as ANOVA) Is a method for testing the hypothesis. Important tool of analysis in the hands of a researcher. Studies the significance of the difference in means by analyzing variance. ANOVA technique was first developed by Ronald A. Fisher (1923). For this technique Fisher is called the Father of Modern Statistics.
- 23. Dr. Mayur (21878) 23 Principles of analysis of variance to test for differences among the means of the populations by examining the amount of variation within each of these samples, relative to the amount of variation between samples
- 24. Dr. Mayur (21878) 24 Numerical-1 Four entries of mustard crop for the character plant height (cm) were put under Randomized Block Design (RBD) with three replications. Give the plan of experiment, analyze the data and interpret your result. Entries RI RII RIII Df 0.05 0.01 1 159 161 156 2 2.920 9.925 2 157 153 151 3 2.353 5.841 3 138 127 132 4 140 147 142
- 25. Dr. Mayur (21878) 25 MANOVA The obvious difference between ANOVA and MANOVA is the M, which stands for multivariate. The number of factor variables involved distinguish a one-way MANOVA from a two-way MANOVA. Extension of the ANOVA
- 26. Dr. Mayur (21878) 26 Biplot Analysis Biplots are exploratory graph used in statistics (two- variable). A biplot allows information on both samples and variables graphically.