and regression coefficients (Fig. 4) indicated that there was a positive relationship between yield potential and stability in this set of germplasm. Results confirmed a previous study by Worku et al. (2001) who reported positive correlation (r = 0.537) between yield potential and regression coefficients in East African maize cultivars.
Nonetheless, these results were different from the significant and negative relationship between yield potential and regression coefficients, which was reported in temperate maize (Tollenaar and Lee, 2002; Jansen and Cavalieri, 1983). The differences of results may be explained by the different sets of germplasm and the different test environments. Results from different regression analyses may not be comparable because the environmental index against which hybrid yields are regressed is dependent on the particular set of hybrids (Lin and Binns, 1986; Crossa, 1990). Non-parametric analyses in this study showed no significant relationship between yield potential and yield stability. However, both parametric and nonparametric methods identified hybrids which combined high yield potential and high yield stability indicating that high yield potential and high yield stability were not mutually exclusive. In other words there was no negative association between high yield potential and high yield stability, which has important implications for breeding.
Further evidence is provided by the hybrids B16/CML312, B19/CML395 and B18/CML442, which combined high yield potential (>100%) and high yield stability, which would be recommended for release across stress prone environments. These hybrids can also be used as sources in breeding new lines for yield stability. The hybrid B16/CML312, showed exceptional stability in combination with high yield potential. Apart from recommendation for release, this hybrid can be used as an elite breeding source for new stable lines. Although not tested in this study, previous studies by Lee et al. (2003) reported that stability was heritable and largely controlled by additive gene action. Thus, selection procedures can be used to develop inbred lines with high yield stability.
6.5 Conclusion
The objective of this study was to: (a) evaluate the level of yield stability; and (b) determine the relationship between yield stability and grain yield potential in a representative sample of Southern African maize base germplasm. Results showed that 85% of the 80 hybrids had average stability across the 10 environments. Eight percent displayed below average stability and were specifically adapted to high yielding environments. The hybrids CML395/A26, B17/CML312, B24/B16, B21/CML444 and CML312/A7 with high yield potential would be recommended for release in high yielding environments. Six percent exhibited above average stability and were specifically adapted to drought stress environments. The hybrids B20/CML488, B11/B24, A13/B21, B22/B18, CML312/A9 and ZS255, would be recommended for deployment only in low yielding environments to which they were specifically adapted. Parametric models showed a highly significant and positive relationship between yield stability and yield potential, while nonparametric models showed no significant relationship between yield potential and yield stability. In addition, the study identified some hybrids that displayed both high yield potential and high yield stability (B16/CML312, B19/CML395 and B18/CML442). The hybrid B16/CML312, which displayed high yield potential and high yield stability would be recommended for release in all environments. It can be concluded that high yield potential and high yield stability were not mutually exclusive in this set of germplasm, indicating that hybrids, which combine high, yield potential and high yield stability would be obtainable.
References
Agrobase. 2005. Agrobase Generation II. Agronomix Software Inc. Winnipeg, MB, Canada
Banziger, M., P.S. Setimela, D. Hodson, and B. Vivek. 2004. Breeding for improved drought tolerance in maize adapted to Southern Africa. “New directions for a diverse planet”. Proceedings of the 4th International Crop Science Congress, 26 September – 1 October 2004, Brisbane, Australia. Published on CDROM.
Web site www.cropscience.org.au
Beck, D.L., S.K. Vasal, and J. Crossa. 1990. Heterosis and combining ability of CIMMYT’s tropical early and intermediate maturity maize (Zea mays L.) germplasm. Maydica, 35: 279-85.
Bruce, W.B., Edmeades, G. O. and T. C. Barker. 2002. Molecular and physiological approaches to maize improvement for drought tolerance. Journal of Experimental Botany, 53: 13-25
CIMMYT, 1985. Managing trials and reporting data for CIMMYT International Maize Testing Program. Mexico, D.F. CIMMYT.
Comstock, R.E., and H.F. Robinson. 1948. The components of genetic variance in populations of bi-parental progenies and their use in estimating the average degree of dominance. Biometrics, 4: 254-266.
Comstock, R.E., and H.F. Robinson. 1952. Estimation of average dominance of genes. In: J.W. Gowen (Ed). Heterosis. Iowa State College Press, Ames. p.
494-516.
Cooper, M and I.H. Delacy. 1994. Relationships among analytical methods used to study genotypic variation and cultivar – by – environment interaction in plant breeding multi-environment experiments. Theoretical and Applied Genetics, 88: 561-572.
Cooper, M., Woodruff, D.R., Eisemann, R.L, Brennan, P.S and I.H Delacy. 1995. A selection strategy to accommodate cultivar x environment interaction for grain yield of wheat: managed – environments for selection among cultivars.
Theoretical and Applied Genetics, 90: 492 – 502.
Crossa, J. 1990. Statistical analyses of multilocation trials. Advances in Agronomy, 44: 55 85.
Crossa, J., Cornelius, P.L., Sayre K. and J.I.R. Ortiz-Monasterio. 1995. A shifted multiplicative model fusion method for Grouping Environments without Cultivar Rank Change. Crop Science, 35: 54 – 62.
Crossa, J., Gauch, H.G Jr., and R.W. Zobel. 1990. Additive main effects and multiplicative interaction Analysis of two International Maize cultivar trials.
Crop Science, 30: 493 – 500.
Crossa; J., Fox, P.N., Pfeiffer, W.H., Rajaram, S. and H.G. Jr. Gauch. 1991. AMMI adjustment for statistical analysis of an international wheat yield trial.
Theoretical and Applied Genetics, 81: 27 – 37.
Eberhart, S, A, and W.A. Russell. 1966. Stability parameters for comparing cultivars.
Crop Science, 6: 36 – 40.
Finlay, K.W. and G.N. Wilkinson. 1963. The analysis of adaptation in a plant breeding programme. Australian Journal of Agricultural Research, 14: 742-754.
Gevers, H.O and I.V Whythe. 1987. Patterns of heterosis in South African maize breeding material. In: Fourie, A.P and J.G Duplessis (Ed.) 1987. Proceedings
of the 7th South African Maize Breeding Symposium, 1986, p21 –26. Summer Grain Centre, Grain Crops Research Institute.
Hohls, T., Shanahan, P.E., Clarke, G.P and G.O Gevers. 1995. Cultivars X environment interactions in a 10x10 dialled cross of quality protein maize (Zea mays L.). Euphytica, 84: 209-218.
Huehn, M. 1990. Nonparametric measures of phenotypic stability. Part I: theory.
Euphytica, 47: 189-194.
Lee, E.A., T.K. Doerksen and L.W. Kannenberg. 2003. Genetic components of yield stability in Maize Breeding Populations. Crop Science, 43: 2018–2027.
Lin, C, S and M.R Binns. 1988. A superiority measure of cultivar performance for cultivar X location data. Canadian Journal of Plant Science, 68: 193-198.
Lin, C. S., M.R. Binns and L.P. Lefkovitch. 1986. Stability analysis: where do we stand? Crop Science, 26: 894-900.
Mickelson, H.R., Cordova, H., Pixley, K.V and M.S. Bjarnason 2001. Heterotic relationships among nine temperate and subtropical maize populations. Crop Science, 41: 1012 –1020.
Min, T.D and G.B. Saleh. 2003. Phenotypic stability of selected Tropical Maize Cultivars at four locations. Asian Journal of Plant Sciences, 2: 743–747.
Nassa, R. and M. Huhn. 1987. Studies of estimation of phenotypic stability: tests of significance for non-parametric measures of phenotypic stability. Biometrics, 43, 45-53.
Piepho, H.P. 1994. Partitioning cultivar-environmental interaction in regional yield trials via a generalised stability variance. Crop Science, 34,
Pingali, P.L. and S. Pandey. 2001. Meeting world maize needs: technological opportunities and priorities for the public sector. In: Pingali, P.L. (ed.) 2001.
CIMMYT 1999-2000 World Maize Facts and Trends. Meeting World Maize Needs: Technological Opportunities And Priorities For The Public Sector.
Mexico, D.F.: CIMMYT.
Richardson, C.J. 2005. The loss of property rights and the collapse of Zimbabwe.
Cato Journal, 25: pp35.
Rosen, S. and L. Scott. 1992. Famine grips sub-Saharan Africa. Agricultural Outlook, 191: 20-24.
Scapim, C. A., W.R. Oliveira, A.L. Braccini, C. D. Cruz, C.A.B, Andrade and M. C. G.
Vidigal. 2000. Yield stability in maize (Zea mays L.) and correlations among the parameters of the Eberhart and Russell, Lin and Binns and Huehn models. Genetics and Molecular Biology, 23: 387-393.
Tarig, M., Haq, M.I. Kiani, A.A. and N. Kamal. 2003. Phenotypic stability for Grain Yield in Maize Cultivars under varied rain fed environments. Asian Journal of Plant Sciences, 2, 80-82.
Tollenaar, M., E. A. Lee. 2002. Yield potential, yield stability and stress tolerance in maize. Field Crops Research, 75: 161-169.
Vargas, M., Crossa, J., Eeuwijk, F., Sayre, K.D. and M.P Reynolds. 2001.
Interpreting Treatment x Environment interaction in Agronomy Trials.
Agronomy Journal, 93, 949-960.
Worku, M., H. Zelleke, G.Taye, B. Tolessa, L. Wolde, W. Abera, A. Guta and H.
Tuna. 2001. Yield stability of maize (Zea mays L.) cultivars across locations.
Proceedings of seventh eastern and Southern Africa regional maize conference. 11 -15th February, 2001. p.199-142.