Experimental Design and Analysis for Tree Improvement provides a set of practical procedures to follow when planning, designing and analysing tree improvement trials. Using examples, it outlines how to:
- design field, glasshouse and laboratory trials
- efficiently collect and construct electronic data files
- pre-process data, screening for data quality and outliers
- analyse data from single and across-site trials
- interpret the results from statistical analyses.
The authors address the many practical issues often faced in forest tree improvement trials and describe techniques that will give meaningful results. The techniques provided are applicable to the improvement of not only trees, but to crops in general.
This fully revised third edition includes the construction of p-rep and spatial designs using the commercially available software package for design generation (Cyc Desig N). For analysis of the examples, it provides online Genstat and SAS programs and a link to R programs.
Table des matières
Acknowledgments
Preface to the third edition
Chapter 1: Introduction
1.1 Overview
1.2 Outline
1.3 Software
1.4 Summary
Chapter 2: Experimental planning and layout
2.1 Introduction
2.2 Experimental objectives
2.3 Sampling strategies
2.4 Allocation of resources
2.5 Strata
2.6 Analysis of variance
Chapter 3: Data collection and pre-processing
3.1 Introduction
3.2 Pre-processing using Genstat
3.3 Pre-processing using Excel
Chapter 4: Experimental design
4.1 Introduction
4.2 Simple designs
4.3 Factorial designs
4.4 Split-plot designs
Chapter 5: Analysis across sites
5.1 Introduction
5.2 Complete two-way tables
5.3 Incomplete two-way tables
5.4 Joint regression analysis with complete two-way tables
5.5 Joint regression analysis with incomplete two-way tables
Chapter 6: Variance components and genetics concepts
6.1 Introduction
6.2 Variance components
6.3 Genetics concepts
6.4 Heritability
6.5 Heritability from provenance/progeny trials
6.6 Genetic correlation
6.7 Selecting superior treatments – BLUEs versus BLUPs
Chapter 7: Incomplete block designs
7.1 Introduction
7.2 Need for incomplete block designs
7.3 Choice of incomplete block designs
7.4 Generalised lattice designs and alpha designs
7.5 Extra blocking structures
7.6 Spatial enhancements
7.7 Partially replicated designs
7.8 Using Cyc Desig N
Chapter 8: Analysis of generalised lattice designs
8.1 Introduction
8.2 Fixed-effects model
8.3 Mixed-effects model
8.4 Nested treatment structure
8.5 Treatments as random effects
8.6 Summary of analysis options
Appendix A: Introduction to Genstat
Glossary
References
Index
A propos de l’auteur
Dr Colin Matheson is an internationally recognised forest geneticist with many decades of experience in research, data analysis and implementation of results into novel tree breeding and improvement programs for many species.
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