An overview of statistical methods to detect and understand genotype-by-environment interaction and QTL-by-environment interaction
Author:
Affiliation:
1. CAST, Faculty of Natural Sciences , University of Tampere , Finland
2. Department of Statistics , Federal University of Bahia , Salvador , Brazil
Abstract
Publisher
Walter de Gruyter GmbH
Link
https://www.sciendo.com/pdf/10.2478/bile-2018-0009
Reference68 articles.
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3. Arciniegas-Alarcón S., García-Peña M., Krzanowski W.J., Dias C.T.S. (2014): An alternative methodology for imputing missing data in trials with genotype-by-environment interaction: some new aspects. Biometrical Letters 51: 75-88.10.2478/bile-2014-0006
4. Arciniegas-Alarcón S., Peña M.G., Dias C.T.S., Krzanowski W.J. (2010): An alternative methodology for imputing missing data in trials with genotype-by-environment interaction. Biometrical Letters 47: 1-14.
5. Annicchiarico P. (2009): Coping with and exploiting genotype-by-environment interactions. In: Ceccarelli, S., E.P., G. & Weltzien, E. (eds.) Plant breeding and farmer participation. Rome: FAO.
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