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The introduction of improved varieties is one of the most powerful and cost-efficient means of enhancing crop productivity and farmers’ incomes. Efficiency in varietal development itself and in the process of matching varieties to production areas implies an understanding of plant responses to diverse environments and cropping systems in a target production zone. Multilocation testing remains the main tool for understanding varietal responses to environments, but the process is both time-consuming and expensive. The efficiency of this analytical process can be enhanced using recently developed statistical methods. This publication aims to support plant breeders by examining the opportunities offered by such methods. FAO hopes that this publication will be useful to a wide variety of persons interested in efficient, sustainable use of plant genetic resources, especially those focusing on the improvement of agriculture in food-deficit developing countries.

Following introductory remarks on the impact of genotype × environment interaction on agricultural production and plant breeding (Chapter 1), adaptation and yield stability concepts are discussed in relation to breeding and the utilization of crop varieties (Chapter 2). The potential usefulness of multi-environment yield trials is also examined (Chapters 2 and 3).

Techniques relating to analysis of variance (Chapter 4) and modelling of adaptation patterns (Chapter 5) are considered for optimizing variety recommendation and for defining the adaptation strategy and yield stability targets in breeding programmes. Attention is paid to limits and opportunities for the scaling-up of results from test sites to the target region. The application of selection theory to the analysis of multi-environment data as well as additional indications that may be obtained from adaptive traits are also considered (Chapter 6). Concepts and measures of yield stability and yield reliability, and their utilization for selection and recommendation of plant varieties, are highlighted in Chapter 7.

Information on useful software for data analysis is provided throughout the book with special emphasis on IRRISTAT, a freely-available software program developed by the International Rice Research Institute. The book also presents a case study (Chapter 8), in which a large multi-environment data set is used for exemplifying the different analytical procedures, as well as the IRRISTAT commands needed for the analysis.

Eric A. Kueneman
Crop and Grassland Service
Plant Protection Division

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