[CROSSA, J. – GAUCH, H.G. – ZOBEL, R.W. 1990. Additive main effects and multiplicative interaction analysis of two international maize cultivar trials. In Crop Science, vol. 30, no. 3, pp. 493 – 500.]Search in Google Scholar
[FAO/IAEA MUTANT VARIETY DATABASE. 2019. FAO/IAEA Mutant Variety Database. Available at https://mvd.iaea.org/ (accessed January 10, 2019).]Search in Google Scholar
[FARSHADFAR, E. 2008. Incorporation of AMMI stability value and grain yield in a single non-parametric index (GSI) in bread wheat. In Pakistan Journal of Biological Science, vol. 11, no. 14, pp. 1791 – 1796.]Search in Google Scholar
[FRIEDT, W. 2011. Barley breeding history, progress, objectives, and technology. In ULLRICH, S.E. (Ed.) Barley: production, improvement, and uses. Wiley-Blackwel, pp. 160 – 186.]Search in Google Scholar
[GABRIEL, K.R. 1971. The biplot graphic of matrices with application to principal component analysis. In Biometrics, vol. 58, pp. 453 – 467.]Search in Google Scholar
[GAUCH, H.G. 1988. Model selection and validation for yield trials with interaction. In Biometrics, vol. 44, no. 3, pp. 705 – 715.]Search in Google Scholar
[GAUCH, H.G. 1992. Statistical analysis of regional yield trials: AMMI analysis of factorial designs. Amsterdam : Elsevier, 278 pp.]Search in Google Scholar
[GAUCH, H.G. 2006. Statistical analysis of yield trials by AMMI and GGE. In Crop Science, vol. 46, pp. 1488 – 1500.]Search in Google Scholar
[GAUCH, H.G. – ZOBEL, R.W. 1996. AMMI analysis of yield trials. In KANG, M. – GAUCH, H. (Eds.) Genotype by environment interaction. Boca Raton : CRC press, New York, pp. 85 – 122.]Search in Google Scholar
[GOCHEVA, M. 2014. Study of the productivity elements of spring barley using correlation and path-coefficients analysis. In Turkish Journal of Agricultural and Natural Sciences, vol. 2, pp. 1638 – 1641.]Search in Google Scholar
[HAGOS, H.G. – ABAY, F. 2013. AMMI and GGE biplot analysis of bread wheat genotypes in the northern part of Ethiopia. In Journal of Plant Breeding and Genetics, vol. 1, no. 1, pp. 12 – 18.]Search in Google Scholar
[JEBERSON, M.S. – KANT, L. – KISHORE, N. – RANA, V. – WALIA, D.P. ‒ SINGH, D. 2017. AMMI and GGE biplot analysis of yield stability and adaptability of elite Genotypes of bread wheat (Triticum aestivum L.) for northern hill zone of India international. In Journal of Bio-resource and Stress Management, vol. 8, no. 5, pp. 635 – 641.]Search in Google Scholar
[KILIC, H. 2014. Additive main effects and multiplicative interactions (AMMI) analysis of grain yield in barley genotypes across environments. In Tarım Bilimleri Dergisi, vol. 20, no. 4, pp. 337 – 344.]Search in Google Scholar
[MIHOVA, G. 2013. Winter barley breeding at Dobrodzha Agricultural Institute – Genegal Toshevo. In Scietific works of the Institute of Agriculture – Karnobat, vol. 2, no. 1, pp. 23 – 38 (Bg).]Search in Google Scholar
[MIRANDA, G.V. – SOUZA, L.V.D. – GUIMARÃES, L.J.M. – NAMORATO, H. – OLIVEIRA, L.R. – SOARES, M.O. 2009. Multivariate analyses of genotype x environment interaction of popcorn. In Pesquisa Agropecuária Brasileira, vol. 44, no. 1, pp. 45 – 50.]Search in Google Scholar
[MITROVIC, B. – STANISAVLJEVI, D. – TRESKI, S. – STOJAKOVIC, M. – IVANOVIC, M. – BEKAVAC, G. – RAJKOVIC, M. 2012. Evaluation of experimental maize hybrids tested in multi-location trials using AMMI and GGE biplot analyses. In Turkish Journal of Field Crops, vol. 17, pp. 35 – 40.]Search in Google Scholar
[MOHAMMADI, R. – ABDULAHI, A. – HAGHPARAST, R. – ARMION, M. 2007. Interpreting genotype-environment interactions for durum wheat grain yields using non-parametric methods. In Euphytica, vol. 157, pp. 239 – 251.]Search in Google Scholar
[MOHAMMADI, R. – NADER MAHMOODI, K. 2008. Stability analysis of grain yield in barley (Hordeum vulgare L.). In International Journal of Plant Breeding, vol. 2, no. 2, pp. 74 – 78.]Search in Google Scholar
[PRŽULJ, N. – MIROSAVLJEVIĆ, M. – ČANAK, P. – ZORIĆ, M. – BOĆANSKI, J. 2015. Evaluation of spring barley performance by biplot analysis. In Cereal research communications, vol. 43, no. 4, pp. 692 – 703.]Search in Google Scholar
[PRŽULJ, N. – MOMČILOVIĆ, V. – SIMIĆ, J. – MIROSAVLJEVIĆ, M. 2014. Effect of growing season and variety on quality of spring two-rowed barley. In Genetika, vol. 46, pp. 59 – 73.]Search in Google Scholar
[PURCHASE, J.L. – HATTING, H. – VAN DEVENTER, C.S. 2000. Genotype × environment interaction of winter wheat (Triticum aestivum L.) in South Africa: II. Stability analysis of yield performance. In South African Journal of Plant and Soil, vol. 17, pp. 101 – 107.]Search in Google Scholar
[RAD, N.M. – KADIR, M.A. – RAFII, M.Y. – JAAFAR, H.Z. – NAGHAVI, M.R. – AHMADI, F. 2013. Genotype × environment interaction by AMMI and GGE biplot analysis in three consecutive generations of wheat (Triticum aestivum) under normal and drought stress conditions. In Australian Journal of Crop Science, vol. 7, pp. 956 – 961.]Search in Google Scholar
[VAEZI, B. – POUR-ABOUGHADAREH, A. – MOHAMMADI, R. – ARMION, M. – MEHRABAN, A. – HOSSEIN-POUR, T. – DORII, M. 2017. GGE biplot and AMMI analysis of barley yield performance in Iran. In Cereal Research Communications, vol. 45, no. 3, pp. 500 – 511.]Search in Google Scholar
[VALCHEVA, D. – VULCHEV, D. – POPOVA, T. – DIMOVA, D. – OZTURK, I. – KAYA, R. 2013. Productive abilities of Bulgarian and introduced varieties and lines barley in Southeast Bulgaria conditions. In Scientific works of the Institute of Agriculture – Karnobat, vol. 2, no. 1, pp. 39 – 48 (Bg).]Search in Google Scholar
[VOLTAS, J. – VAN EEUWIJK, F.A. – IGARTUA, E. – GARCIA DEL MORAL, L.F. – MOLINA-CANO, J.L. – ROMAGOSA, I. 2002. Genotype by environment interaction and adaptation in barley breeding: basic concepts and methods of analysis. In SLAFER, G.A. – MOLINACANO, J.L. – SAVIN, R. – ARAUS, J.L. – ROMAGOSA, I. (Eds.) Barley science: recent advances from molecular biology to agronomy of yield and quality. New York, Food Product Press, pp. 205 – 241. ISBN 1-56022-909-8.]Search in Google Scholar
[YAN, W. 2001. GGE biplot – a windows application for graphical analysis of multi-environment trial data and other types of two way data. In Agronomy Journal, vol. 93, pp. 1111 – 1118.]Search in Google Scholar
[YAN, W. – HUNT, L.A. – SHENG, Q. – SZLAVNICS, Z. 2000. Cultivar evaluation and mega environment investigation based on the GGE biplot. In Crop Science, vol. 40, pp. 597 – 605.]Search in Google Scholar
[YAN, W. – KANG, M. S. 2003. GGE biplot analysis: a graphical tool for breeders. In KANG M.S. (Ed.) Geneticists, and Agronomist. CRC Press, Boca Raton, FL. pp. 63 – 88.]Search in Google Scholar
[YAN, W. – RAJCAN, I. 2002. Biplot analysis of test sites and trait relations of soybean in Ontario. In Crop Science, vol. 42, pp. 11 – 20.]Search in Google Scholar
[YAN, W. – TINKER, N. A. 2006. Biplot analysis of multi-environment trial data: principles and applications. In Canadian Journal of Plant Science, vol. 86, pp. 623 – 645.]Search in Google Scholar
[ZOBEL, R.W. – WRIGHT, M.J. – GAUCH, H.G. 1988. Statistical analysis of a yield trial. In Agronomy Journal, vol. 80, pp. 388 – 393.]Search in Google Scholar
