Abstract
Three new concepts of genotype wide adaptation levels I, II and III are presented and shown to the adequate describing quantitatively by measures such as superiority measure, Pi, Eskridge’s yield reliability measure, Ri and Eskridge’s yield reliability function, Ri(d). These indices have been called quantitative measures of genotype wide adaptation levels I, II and III, respectively. Relationships (consistency) between the three measures were studied using data for grain yield of winter wheat advanced lines from 15 preliminary multi-environment trials carried out across Polish test locations in the years 1993–2007. The quantitative measures are simple to interpret and useful quantitative characteristics of genotype wide adaptation levels I, II and III. High Spearman rank correlation coefficients were found between each of the pairs of the quantitative measures of genotype wide adaptation levels I, II and III within all sets of winter wheat genotypes. Then, for evaluating wheat genotype wide adaptation level in each aspect only one of the considered measures could be sufficient. The studies delivered new results on the usefulness of quantitative measures of genotype wide adaptation level for winter wheat. These findings indicate that those measures could be also useful for comparative evaluation of genotype wide adaptation level in other crops.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Annicchiarico, P. 2002. Genotype-environment interactions: challenges and opportunities for plant breeding and cultivar recommendations. FAO Plant Production and Protection Paper No. 174. Food and Agriculture Organization, Rome.
Baxevanos, D., Goulas, C., Tzortzios, S., Mavromatis, A. 2008. Interrelationship among and repeatability of seven stability indices estimated from commercial cotton (Gossypium hirsutum L.) variety evaluation trials in three Mediterranean countries. Euphytica 161:371–382.
Becker, H.C., Leon, J. 1988. Stability analysis in plant breeding. Plant Breeding 101:1–23.
Blanche, S.B., Utomo, H.S., Wenefrida, I., Myers, G.O. 2009. Genotype × environment interactions of hybrid and varietal rice cultivars for grain yield and milling quality. Crop Sci. 49:2011–2018.
Braun, H.J., Rajaram, S., van Ginkel, M. 1996. CIMMYT’s approach to breeding for wide adaptation. Euphytica 92:175–183.
Calimski, T., Czajka, S., Kaczmarek, Z. 1997. A multivariate approach to analysing genotype-environment interactions. In: Krajewski, P., Kaczmarek, Z (eds), Advances in Biometrical Genetics, Poznam, pp. 3–14.
Ceccarelli, S. 1989. Wide adaptation: How wide? Euphytica 40:197–205.
Cooper, M. 1999. Concepts and strategies for plant adaptation research in rainfed lowland rice. Field Crops Res. 64:13–34.
Cooper, M., Byth, D.E. 1996. Understanding plant adaptation to achieve systematic applied crop improvement — a fundamental challenge. In: Cooper, M., Hammer, G.L. (eds), Plant Adaptation, Crop Improvement. CAB International/International Rice Research Institute (IRRI)/International Crops Research Institute for Semi Arid Tropics (CRISAT), Wallingford, UK/Los Banos, Laguna, Philippines/Hyderabad, India, pp. 5–24.
Duarte, J.B., Zimmermann, M.J. 1995. Correlation among yield stability parameters in common bean. Crop Sci. 35:905–912.
Eskridge, K.M. 1990. Selection of stable cultivars using a safety-first rule. Crop Sci. 30:369–374.
Eskridge, K.M., Byrne, P.F., Crossa, J. 1991. Selection of stable cultivars by minimizing the probability of disaster. Field Crops Res. 27:169–181.
Eskridge, K.M., Mumm, R.F. 1992. Choosing plant cultivars based on the probability of outperforming a check. Theor. Appl. Genet. 84:494–500.
Eskridge, K.M., Smith, O.S., Byrne, P.F. 1993. Comparing test cultivars using reliability functions of test-check differences from on-farm trials. Theor. Appl. Genet. 87:60–64.
Flores F., Moreno, M.T., Cubero, J.I. 1998. A comparison of univariate and multivariate methods to analyze G×E interaction. Field Crops Res. 56:271–286.
Gauch, H.G., Piepho, H.P., Annicchiarico, P. 2008. Statistical analysis of yield trials by AMMI and GGE: Further considerations. Crop Sci. 48:866–889.
Iwamska, M., Mbdry, W., Drzazga, T., Rajfura, A. 2008. Assessment of wide adaptation degree of winter wheat cultivars by statistical measures using yield data from preregistration trials. Biul. IHAR 250:67–86. (in Polish)
Joshi, K.D., Musa, A.M., Johansen, C., Gyawali, S., Harris, D., Witcombe, J.R. 2007. Highly client-oriented breeding, using local preferences and selection, produces widely adapted rice cultivars. Field Crops Res. 100:107–116.
Kang, M.S. 1998. Using genotype-by environment interaction for crop cultivar development. Adv. Agron. 62:199–253.
Kang, M.S., Pham, H.N. 1991. Simultaneous selection for high and stable crop genotypes. Agron. J. 83:161–165.
Lin, C.S., Binns, M.R. 1988. A superiority measure of cultivar performance for cultivar × location data. Can. J. Plant Sci. 68:193–198.
Mbdry, W. 2003. Yield-stability statistic for selecting widely adapted genotypes of spring wheat and oat. J. New Seeds 5:43–56.
Mbdry, W., Kang, M.S. 2005. Scheffé-Calimski and Shukla models: Their interpretation and usefulness in stability and adaptation analyses. J. Crop Improv. 14:325–369.
Moghaddam, M.J., Pourdad, S.S. 2009. Comparison of parametric and non-parametric methods for analysing genotype environment interactions in safflower (Carthamus tinctorius L.). J. Agric. Sci. 147:601–612.
Mohammadi, R., Amri, A. 2008. Comparison of parametric and nonparametric methods for selecting stable and adapted durum wheat genotypes in variable environments. Euphytica 159:419–432.
Möhring, J., Piepho, H.P. 2009. Comparison of weighting in two-stage analysis of plant breeding trials. Crop Sci. 49:1977–1988.
Piepho, H.P. 1995. Assessing cultivar adaptability by multiple comparison with the best. Agron. J. 87:1225–1227.
Piepho, H.P. 1998. Methods for comparing the yield stability of cropping systems — A review. J. Agron. Crop Sci. 180:193–213.
Piepho, H.P., Möhring, J. 2005. Best linear unbiased prediction of cultivar effects for subdivided target regions. Crop Sci. 45:1151–1159.
Sabaghnia, N., Dehghani, H., Sabaghpour, S.H. 2006. Nonparametric methods for interpreting genotype × environment interaction of lentil genotypes. Crop Sci. 46:1100–1106.
Sabaghnia, N., Sabaghpour, S.H., Dehghani, H. 2008. The use of an AMMI model and its parameters to analyse yield stability in multi-environment trials. J. Agric. Sci. 146:571–581.
SAS Institute Inc. 2004. SAS OnlineDoc® 9.1.3 Cary, USA.
Scapim, C.A., Pacheco, C.A., Amaral, A.T., Vieira, R.A., Pinto, R.J., Conrado, T.V. 2010. Correlations between the stability and adaptability statistics of popcorn cultivars. Euphytica 174:209–218.
Solomon, K.F., Smit, H.A., Malan, E., Du Toit, W.J. 2007. Comparison study using rank based nonparametric stability statistics of durum wheat. World J. Agric. Sci. 3:444–450.
Shukla, G.K. 1972. Some aspects of partitioning genotype-environmental components of variability. Heredity 28:237–245.
St-Pierre, C.A., Klinck, H.R., Gauthier, F.M. 1967. Early generation selection under different environments as it influences adaptation of barley. Can. J. Plant Sci. 47:507–517.
Yan, W., Kang, M.S. 2003. GGE Biplot Analysis: A graphical tool for breeders, geneticists, and agronomists. CRC Press. Boca Raton, FL, USA.
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by A. Goyal and J. Johnson
Rights and permissions
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
About this article
Cite this article
Mądry, W., Iwańska, M. Measures of genotype wide adaptation level and their relationships in winter wheat. CEREAL RESEARCH COMMUNICATIONS 40, 592–601 (2012). https://doi.org/10.1556/CRC.40.2012.0013
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1556/CRC.40.2012.0013