Accesso libero

Genotype by Environment Interaction for Grain Yield of Barley Mutant Lines

INFORMAZIONI SU QUESTO ARTICOLO

Cita

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 – 500.10.2135/cropsci1990.0011183X003000030003xSearch 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 – 1796.10.3923/pjbs.2008.1791.1796Search 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 – 186.10.1002/9780470958636.ch8Search in Google Scholar

GABRIEL, K.R. 1971. The biplot graphic of matrices with application to principal component analysis. In Biometrics, vol. 58, pp. 453 – 467.10.1093/biomet/58.3.453Search in Google Scholar

GAUCH, H.G. 1988. Model selection and validation for yield trials with interaction. In Biometrics, vol. 44, no. 3, pp. 705 – 715.10.2307/2531585Search 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 – 1500.10.2135/cropsci2005.07-0193Search 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 – 122.10.1201/9781420049374.ch4Search 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 – 641.10.23910/IJBSM/2017.8.5.1838Search 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 – 344.10.1501/Tarimbil_0000001292Search 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 – 50.10.1590/S0100-204X2009000100007Search 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 – 251.10.1007/s10681-007-9417-3Search 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 – 703.10.1556/0806.43.2015.018Search 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 – 73.10.2298/GENSR1401059PSearch 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 – 107.10.1080/02571862.2000.10634878Search 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 – 511.10.1556/0806.45.2017.019Search 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 – 1118.10.2134/agronj2001.9351111xSearch 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 – 605.10.2135/cropsci2000.403597xSearch 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 – 88.10.1201/9781420040371-5Search 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 – 20.10.2135/cropsci2002.1100Search 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 – 645.10.4141/P05-169Search 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 – 393.10.2134/agronj1988.00021962008000030002xSearch in Google Scholar

eISSN:
1338-4376
Lingua:
Inglese
Frequenza di pubblicazione:
4 volte all'anno
Argomenti della rivista:
Life Sciences, Plant Science, Ecology, other