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 (CycDesigN). For analysis of the examples, it provides online Genstat and SAS programs and a link to R programs.

Experimental Design and Analysis for Tree Improvement provides a set of practical procedures to follow when planning, designing and analysing tree improvement trials. Using many fully-worked examples, it outlines how to: design field, glasshouse and laboratory trials; efficiently collect data and construct electronic data files; pre-process data, screening for data quality and outliers; analyse data from single and across-site trials using either GenStat or SAS; and 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 conclusive results with the minimum expense. The techniques provided are applicable to the improvement of not only trees, but to crops in general. Building on the success of the first edition, this edition includes commercially-available software packages for design generation (CycDesigN) and data pre-processing and automated generation of programs for statistical analysis (DataPlus). For analysis, it provides both GenStat and SAS programs as generated by DataPlus.

Experimental planning and layout; Data collection and pre-processing; Experimental design; Analysis across sites; Variance components and genetics concepts; Incomplete block designs; analysis of gereralized lattice designs.

Experimental design is often overlooked in the literature of applied and mathematical statistics: statistics is taught and understood as merely a collection of methods for analyzing data. Consequently, experimenters seldom think about optimal design, including prerequisites such as the necessary sample size needed for a precise answer for an experi

Plant Breeding Reviews is an ongoing series presenting state-of-the art review articles on research in plant genetics, especially the breeding of commercially important crops. Articles perform the valuable function of collecting, comparing, and contrasting the primary journal literature in order to form an overview of the topic. This detailed analysis bridges the gap between the specialized researcher and the broader community of plant scientists.