- citations in SCIndeks: [1]
- citations in CrossRef:0
- citations in Google Scholar:[
 ]
- visits in previous 30 days:10
- full-text downloads in 30 days:8
|
|
|
2013, vol. 50, iss. 2, pp. 28-35
|
|
Identification of the most desirable maize testing environments in northern Serbia
Identifikacija najpoželjnijih lokaliteta za testiranje hibrida kukuruza u severnoj Srbiji
Project: Improvement of Maize and Sorghum Production Under Stress Conditions (MESTD - 31073)
Abstract
One of the final stages in the process of maize breeding is testing the potential hybrids in pre-registration multi-location trials. The aim of this study was to evaluate six locations (Pančevo, Sremska Mitrovica, Ruma, Srbobran, Rimski Šančevi and Sombor) in the northern Serbia for testing yields of maize seed hybrid by GGE (Genotype and Genotype by Environment Interaction) biplot method in the period from 2007 to 2011. This study comprised 24 maize hybrids tested across 6 environments. Different sets of hybrid were used every year. Hybrids served as 'a random' factor for the evaluation of locations. The ANOVA indicated significant effects of genotypes (G) and environments (E) every year, while their interaction (GE) was significant in 2007, 2009 and 2011. On average, the SO location provided the smallest amount of information and therefore can be excluded from further trials and analysis. The sites SM and RU were the most similar locations and only one of these two locations should be included in further trials. The location RŠ presented the smallest repeatability. For analysis that is more detailed it is necessary to include more locations in trials and analysis.
Sažetak
Jedna od krajnjih faza u procesu oplemenjivanja kukuruza je testiranje potencijalnih hibrida u više-lokacijskim pretkomisijskim ogledima. Cilj ovog istraživanja bila je procena šest lokaliteta (Pančevo, Sremska Mitrovica, Ruma, Srbobran, Rimski Šančevi i Sombor) u severnoj Srbiji za testiranje prinosa zrna hibrida kukuruza GGE biplot metodom u periodu od 2007 do 2011. god. Ovo istraživanje je obuhvatilo 24 hibrida kukuruza testirana na šest lokaliteta. Različiti setovi hibrida su korišćeni svake godine. Hibridi su služili kao 'random' faktor za procenu test lokaliteta. ANOVA test je pokazao značajne efekte genotipa (G) i životne sredine (E) svake godine, dok je njihova interakcija (GE) bila značajna u 2007, 2009. i 2011. U proseku, lokalitet SO je pružio najmanje informacija, pa se stoga može isključiti iz daljih ogleda i analiza. Lokaliteti SM i RU su bili najsličniji, tako da samo jedan od njih treba da se uključi u dalja testiranja. Lokalitet RŠ je imao najmanju ponovljivost. Takođe trebalo bi uključiti, druge, do sada nekorišćene lokalitete u budućim višelokacijskim ogledima.
|
|
|
|
References
|
|
1 
|
Balestre, M., de Souza, C.J., von Garcia, P.R., de Lunzzo, O.R., Valente, M.P.J. (2009) Yield stability and adaptability of maize hybrids based on GGE biplot analysis characteristics. Crop Breed. Appl. Biotechnol, 9: 219-228
|
|
2  
|
Crossa, J. (1990) Statistical analyses of multilocation trials. Adv. Agron., 45: 55-85
|
|
38
|
Eberhart, S.A., Russell, W.A. (1966) Stability parameters for comparing varieties. Crop Sci., 6: 36-40
|
|
1
|
Fan, X., Kang, M.S., Chen, H., Zhang, Y., Tan, J., Xu, C. (2007) Yield Stability of Maize Hybrids Evaluated in Multi-Environment Trials in Yunnan, China. Agronomy Journal, 99(1): 220-228
|
|
|
FAOSTAT (2011) Food and Agriculture Organization of the United Nations, FAOSTAT database. http://faostat.fao.org/site/567/DesktopDefault.aspx?PageID=567#ancor
|
|
3
|
Gabriel, K.R. (1971) The biplot graphic display of matrices with application to principal component analysis. Biometrika, 58(3): 453-467
|
|
12
|
Gauch, H.G., Zobel, R.W. (1996) AMMI analysis of yield trials. in: Kang M.S.; Gauch H.G. [ed.] Genotype by Environment Interactions, Boca Rataon, Florida, USA: CRS Press, 85-122
|
|
10
|
Gauch, H.G., Zobel, R.W. (1997) Identifying mega-environments and targeting genotypes. Crop Sci., 37: 311-326
|
|
7
|
Kang, M.S. (2004) Breeding: Genotype-by-environment interaction. in: Goodman R.M. [ed.] Encyclopedia of Plant and Crop Science, New York: Marcel Decker, 218-221
|
|
|
Kaya, Y., Akcura, M., Taner, S. (2006) GGE-Biplot analysis of multi-environment yield trials in bread wheat. Turk J. Agric, 30: 325-337
|
|
|
Mitrović, B., Stanisavljević, D., Treskić, S., Stojaković, M., Bekavac, G., Nastasić, A., Ivanović, M. (2011) GGE biplot analiza multilokacijskih ogleda NS hibrida kukuruza. Ratarstvo i povrtarstvo, vol. 48, br. 1, str. 77-82
|
|
2
|
R Development Core Team (2011) A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing, www.R-project.org
|
|
2
|
Samonte, S.O.P.B., Wilson, L.T., Mcclung, A.M., Medley, J.C. (2005) Targeting cultivars onto rize growing environments using AMMI and SREG GGE biplot analysis. Crop Sci., 45(6): 2414-2424
|
|
2
|
Stojaković, M., Ivanović, M., Jocković, Đ., Bekavac, G., Purar, B., Nastasić, A., Stanisavljević, D., Mitrović, B., Treskić, S., Laišić, R. (2010) NS hibridi kukuruza u proizvodnim rejonima Srbije. Ratarstvo i povrtarstvo, vol. 47, br. 1, str. 93-102
|
|
|
Yan, W. (2002) Singular-value partitioning in biplot analysis of multienvironment trial data. Agron. J., 94: 990-996
|
|
1
|
Yan, W., Hunt, L.A., Sheng, Q., Szlavnics, Z. (2000) Cultivar evaluation and megaenvironment investigation based on the GGE biplot. Crop Sci., 40: 597-605
|
|
2
|
Yan, W., Cornelius, P.L., Crossa, J., Hunt, L.A. (2001) Two types GGE biplots for analyzing multi-environment trial data. Crop Sci., 41: 656-663
|
|
|
Yan, W., Frégeau-Reid, J., Pageau, D., Martin, R., Mitchell-Fetch, J., Etienne, M., Rowsell, J., Scott, P., Price, M., de Haan, B., Cummiskey, A., Lajeunesse, J., Durand, J., Sparry, E. (2010) Identifying essential test-locations for oat breeding in eastern Canada. Crop Sci., 50: 504-515
|
|
4
|
Yan, W., Tinker, N.A. (2006) Biplot analysis of multi-environment trial data: Principles and applications. Can. J. Plant Sci., 86(3): 623-645
|
|
|
|
|