Statistical Analysis of Regional Yield Trials: AMMI Analysis of Factorial Designs
Language: English
Published by Elsevier Science and Technology, GB, 1992
- Hardcover
- New

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AbeBooks seller since June 11, 2025
Condition: New
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Add to basketItem description from seller
During the last few years, many journal articles have shown the usefulness of the Additive Main Effects and Multiplicative Interaction (AMMI) model for analyzing regional yield trials. AMMI helps agronomists and breeders in several ways: to understand or model complex data sets, especially the interactions; to estimate yields more accurately, even with less data; to make better selections; and to design more efficient yield-trial experiments.This book is the first systematic treatment of these topics, collecting concepts from the scattered literature and also presenting many new results. Although agricultural applications are emphasized here, AMMI is applicable to two-way data tables containing one kind of data, either replicated or not, so AMMI appears in many areas of science and technology.The volume's first seven chapters review the agricultural and statistical principles and the final chapter indicates the difference that AMMI can make for agricultural research and world food supplies. This book will be of great value to agricultural scientists throughout the world, enabling them to learn more from their data and thereby make greater progress.…
Seller Inventory # LU-9780444892409
- Title
- Statistical Analysis of Regional Yield Trials: AMMI Analysis of Factorial Designs
- Author
- H.G. Gauch Jr.
- Publisher
- Elsevier Science and Technology, GB
- Publication year
- 1992
- Condition
- New
- Binding
- Hardback
- Language
- English
- ISBN 10
- 0444892400
- ISBN 13
- 9780444892409
- Item weight
- 680 grams
This book is the first systematic treatment of these topics, collecting concepts from the scattered literature and also presenting many new results. Although agricultural applications are emphasized here, AMMI is applicable to two-way data tables containing one kind of data, either replicated or not, so AMMI appears in many areas of science and technology.
The volume's first seven chapters review the agricultural and statistical principles and the final chapter indicates the difference that AMMI can make for agricultural research and world food supplies. This book will be of great value to agricultural scientists throughout the world, enabling them to learn more from their data and thereby make greater progress.
"Synopsis" may belong to another edition of this title.
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