Advertisement

Plant Breeding pp 535-572 | Cite as

Genotype-by-Environment Interaction in Crop Improvement

  • Manjit S. Kang
  • V. T. Prabhakaran
  • R. B. Mehra

Abstract

In this paper, we discuss the role of genotype by environment interactions (GEI) in crop improvement, especially the following: (1) Implications of GEI in crop improvement, (2) Nature and causes of GEI, (3) Approaches for studying GEI, and (4) Strategies for using GEI in crop improvement. Genetic, biochemical, and metabolic aspects of crop plant-environment interactions also are discussed. The take-home message in this paper is as follow: A lack of GEI could signal a lack of genetic diversity, which causes genetic vulnerability of a crop to disease epidemics, insect infestations, or other stresses. Such stresses provide opportunities for identifying and selecting genotypes.

Keywords

Quantitative Trait Locus Genetic Correlation Crop Improvement Best Linear Unbiased Prediction Mixed Model Equation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aastveit A. H. and Aastveit K. 1993. Effects of genotype-environment interactions on genetic correlations. Theor. Appl. Genet., 86: 1007–1013.CrossRefGoogle Scholar
  2. Aastveit A. H. and Mejza S. 1992. A selected bibliography on statistical methods for the analysis of genotype × environment interaction. Biuletyn Oceny Odmian, 25: 83–97.Google Scholar
  3. Allard R. W. 1960. Principles of Plant Breeding. John Wiley & Sons, New York.Google Scholar
  4. Allard R. W. and Bradshaw A. D. 1964. Implications of genotype-environment interactions in applied breeding. Crop Sci., 4: 503–508.CrossRefGoogle Scholar
  5. Annicchiarico P. 1997a. Additive main effects and multiplicative interaction (AMMI) analysis of genotype-location interaction in variety trials repeated over years. Theor. Appl. Genet., 94: 1072–1077.CrossRefGoogle Scholar
  6. Annicchiarico P. 1997b. STABS AS: a SAS computer programme for stability analysis. Ital. J. Agron., 1: 7–9.Google Scholar
  7. Annicchiarico P. 1999. Variety × location interaction and its implications on breeding lucerne: A case study. P. 35–43. In: Proc. XIII Eucarpia Medicago spp. germplasm. (eds. ) F. Veronesi and D. Rosellini, 13-16 Sep. 1999, Perugia, Italy.Google Scholar
  8. Annicchiarico P. and Mariani G. 1996. Prediction of adaptability and yield stability of durum wheat genotypes for yield response in normal and artificially drought-stressed conditions. Field Crops Res., 46: 71–80.CrossRefGoogle Scholar
  9. Annicchiarico P. and Perenzin M. 1994. Adaptation patterns and definition of macro-environments for selection and recommendation of common wheat genotypes in Italy. Plant Breeding, 113: 197–205.CrossRefGoogle Scholar
  10. Bajpai P. K. and Prabhakaran V. T. 2000. A new procedure for simultaneous selection for high yielding and stable crop genotypes. Indian J. Genet., 60: 141–152.Google Scholar
  11. Baker R. J. 1988. Tests for crossover genotype-environmental interactions. Can J. Plant Sci., 68: 405–410.CrossRefGoogle Scholar
  12. Baker R. J. 1990. Crossover genotype-environmental interaction in spring wheat, p. 42–51. In: Genotype-by-environment interaction and plant breeding. (ed. ) M. S. Kang, Louisiana State Univ. Agric. Center, Baton Rouge, LA.Google Scholar
  13. Balzarini M., Milligan S. B. and Kang M. S. 2001. Best linear unbiased prediction: A mixed model approach in multi-environmental trials, p. 353–364 In: Crop Improvement: New Challenges in the 21st Century. (ed. ) M. S. Kang, Food Products Press, Binghamton, NY.Google Scholar
  14. Barah B. C., Binswanger H. P., Rana B. S. and Rao N. G. P. 1981. The use of risk aversion in plant breeding: concept and application. Euphytica, 30: 451–458.CrossRefGoogle Scholar
  15. Baril C. P. 1992. Factor regression for interpreting genotype-environment interaction in bread-wheat trials. Theor. Appl. Genet., 83: 1022–1026.CrossRefGoogle Scholar
  16. Beavis W. D. and Keim P. 1996. Identification of quantitative trait loci that are affected by environment, pp. 123–149. In: Genotype-by-Environment Interaction, (eds. ) M. S. Kang and H. G. Gauch, Jr., CRC Press, Boca Raton, FL.CrossRefGoogle Scholar
  17. Becker H. C. 1981a. Correlations among some statistical measures of phenotypic stability. Euphytica, 30: 835–840.CrossRefGoogle Scholar
  18. Becker H. C. 1981b. Biometrical and empirical relations between different concepts of phenotypic stability, pp. 307–314. In: Quantitative Genetics and Breeding Methods, (ed. ) Gallais, A., Versailles; I. N. R. A.Google Scholar
  19. Becker H. C. and Leon J. 1988. Stability analysis in plant breeding. Plant Breeding, 101: 1–23.CrossRefGoogle Scholar
  20. Blum A. 1988. Plant Breeding for Stress Environments. CRC ress, Boca Raton, FL.Google Scholar
  21. Bol and G. J. 1997. Stability analysis for evaluating the influence of environment on chemical and biological control of white mold (Sclerotinia sclerotiorum) of bean. Biol. Control, 9: 7–14.CrossRefGoogle Scholar
  22. Bradshaw A. D. 1965. Evolutionary significance of phenotypic plasticity in plants. Adv. Genetics, 13: 115–155.CrossRefGoogle Scholar
  23. Bramel-Cox P. J. 1996. Breeding for reliability of performance across unpredictable environments. pp. 309–339. In: Genotype-by-environment interaction, (eds. ) M. S. Kang and H. G. Gauch, Jr. CRC Press, Boca Raton, FL.CrossRefGoogle Scholar
  24. Breese E. L. 1969. The measurement and significance of genotype-environment interactions in grasses. Heredity, 24: 27–44.CrossRefGoogle Scholar
  25. Bridges W. C. Jr. 1989. Analysis of a plant breeding experiment with heterogeneous variances using mixed model equations, pp 145–151. In: Applications of mixed models in agriculture and related disciplines. So. Coop. Series Bull. No. 343. Louisiana Agric. Exp. Stn., Baton Rouge, LA.Google Scholar
  26. Bucio Alanis L. 1966. Environmental and genotype-environmental components of variability. I. Inbred lines. Heredity, 21: 387–397.CrossRefGoogle Scholar
  27. Bucio Alanis L. and Hill J. 1966. Environmental and genotype-environmental components of variability. IL Heterozygotes. Heredity, 21: 399–405.CrossRefGoogle Scholar
  28. Bucio Alanis L., Perkins J. M. and Jinks J. L. 1969. Environmental and genotype-environmental components of variability. V. Segregating generations. Heredity, 24: 115–127.CrossRefGoogle Scholar
  29. Byth D. E., Eisemann R. L. and De Lacy I. H. 1976. Two-way pattern analysis of a large data set to evaluate genotypeic adaptation. Heredity, 37: 215–230.CrossRefGoogle Scholar
  30. Carter T. E. Jr., Burton J. W., Cappy J. J., Israel D. W. and Boerma H. R. 1983. Coefficients of variation, error variances, and resource allocation in soybean growth analysis experiments. Agron. J., 75: 691–696.CrossRefGoogle Scholar
  31. Ceccarelli S., Erskine W., Hamblin J. and Grando S. 1994. Genotype by environment interaction and international breeding programmes. Expl. Agric., 30: 177–187.CrossRefGoogle Scholar
  32. Charmet G., Balfourier F., Ravel C. and Denis J. B. 1993. Genotype × environment interactions in a core collection of French perennial ryegrass populations. Theor. Appl. Genet., 86: 731–736.CrossRefGoogle Scholar
  33. Clark R. B. and Duncan R. R. 1993. Selection of plants to tolerate soil salinity, acidity, and mineral deficiencies, p. 371–379. In: International Crop Science I., (eds. ) D. R. Bruxton, R. Shibles, R. A. Forsberg, B. L. Blad, K. H. Asay, G. M. Paulsen and R. F. Wilson, Crop Sci. Soc. America, Madison, WI.Google Scholar
  34. Comstock R. E. and Robinson H. F. 1952. Genetic parameters, their estimation and significance. Proceedings of the Sixth International Grassland Congress, 1: 284–91.Google Scholar
  35. Comstock R. E. and Moll R. H. 1963. Genotype-environment interactions. In: Statistical Genetics and Plant Breeding, (ed. ) W. D. Hanson and H. F. Robinson. National Academy of Sciences-National Research Council Publication 982, 164–96.Google Scholar
  36. Cooper M. and De Lacy LH. 1994. Relationships among analytical methods used to study genotypic variation and genotyp-by-environment interaction in plant breeding multi-environment experiments. Theor. Appl. Genet., 88: 561–572.CrossRefGoogle Scholar
  37. Cooper M. and Hammer G. L. 1996. Plant adaptation and crop improvement. CAB International, Wallingford, U. K., ICRISAT, Patancheru, India, and IRRI, Manila, Philippines.Google Scholar
  38. Cornelius P. L., Crossa J. and Seyedsadr M. S. 1996. Statistical tests and estimates of multiplicative models for GE interaction, p. 199–234. In: Genotype-by-environment interaction, (eds. ) M. S. Kang and H. G. Gauch Jr., CRC Press, Boca Raton, FL.Google Scholar
  39. Cornelius P. L., Seyedsadr M. S. and Crossa J. 1992. Using the shifted multiplicative model to search for “separability” in crop vcultivars trials. Theor. Appl. Genet., 84: 161–172.CrossRefGoogle Scholar
  40. Crispeels M. J. 1994. Introduction to’ signal transduction in plants: A collection of updates. ’ Am. Soc. Plant Physiologists, Rockville, MD.Google Scholar
  41. Crossa J. and Cornelius P. L. 2000. Modelos lineales-bilineales para el analisis de ensayos de genotipos en ambientes multiples. p. 61–88. In: Simposium interaccion genotipo × ambiente. (eds. ) F. Zavala Garcia and N. E. Treviqo Hernandez, SOMEFI-CSSA-UG, Irapuato, Gto, Mexico.Google Scholar
  42. Crossa J., Cornelius P. L. and Seyedsadr M. S. 1996. Using the shifted multiplicative model cluster methods for crossover GE interaction, p. 175–198. In: Genotype-by-environment interaction, (eds. ) M. S. Kang and H. G. Gauch, Jr., CRC Press, Boca Raton, FL.Google Scholar
  43. Dashiell K. E., Ariyo O. J. and Bello L. 1994. Genotype × environment interaction and simultaneous selection for high yield and stability in soybeans (Glycine max (L. ) Merr. ). Ann. Appl. Biol., 124: 133–139.CrossRefGoogle Scholar
  44. De Lacy I. H., Cooper M. and Basford K. E. 1996. Relationships among analytical methods used to study genotype-by-environment interactions and evaluation of their impact on response to selection, p. 51–84. In: Genotype-by-environment interaction. (eds. ) M. S. Kang and H. G. Gauch, Jr., CRC Press, Boca Raton, FL.Google Scholar
  45. Denis J. B. 1988. Two-way analysis using covariates. Statistics, 19: 123–132.CrossRefGoogle Scholar
  46. Dickerson G. E. 1962. Implications of genetic-environmental interaction in animal breeding. Animal Prod., 4: 47–64.CrossRefGoogle Scholar
  47. Digby P. G. N. 1979. Modofied joint regression analysis for incomplete variety × environment data. J. agric. Sci., Camb., 93: 81–86.CrossRefGoogle Scholar
  48. Dutilleul P. and Carriere Y. 1998. Among-environment heteroscedasticity and the estimation and testing of genetic correlation. Heredity, 80: 403–413.CrossRefGoogle Scholar
  49. Duvick D. N. 1996. Plant breeding, an evolutionary concept. Crop Sci,. 36: 539–548.CrossRefGoogle Scholar
  50. Dyke G. V., Lane P. W. and Jenkyn J. F. 1995. Sensitivity (stability) analysis of multiple variety trials, with special reference to data expressed as proportions or percentages. Expl. Agric., 31: 75–87.CrossRefGoogle Scholar
  51. Eberhart S. A. and Russell W. A. 1966. Stability parameters for comparing varieties. Crop Sci., 6: 36–40.CrossRefGoogle Scholar
  52. Eberhart S. A. and Russell W. A. 1969. Yield stability for a 10-line diallel of single-cross and double cross maize hybrids. Crop Sci., 9: 357–361.CrossRefGoogle Scholar
  53. Eisemann R. L., Cooper M. and Woodruff D. R. 1990. Beyond the analytical methodology, better interpretation and exploitation of GE interaction in plant breeding, pp. 108–117. In: Genotype-by-environment interaction and plant breeding, (ed. ) M. S. Kang, Louisiana State Univ. Agric. Center, Baton Rouge, LA.Google Scholar
  54. Epstein E. 1972. Mineral nutrition of plants: principles and perspectives. John Wiley, New York.Google Scholar
  55. Epstein E. 1976. Genetic potential for solving problems of soil mineral stress: Adaptation of crops to salinity, p. 73–82. In: Plant adaptation to mineral stress in problem soils, (ed. ) Wright M. L., Cornell University Agricultural Experiment station, Ithaca, NY.Google Scholar
  56. Eskridge K. M. 1996. Analysis of multiple environment trials using the probability of outperforming a check, p. 273–307. In: Genotype-by-environment interaction, (eds. ) Kang M. S. and Gauch H. G. Jr., CRC Press, Boca Raton, FL.CrossRefGoogle Scholar
  57. Evans L. T. 1993. Crop evolution, adaptation and yield. Cambridge University Press, New York.Google Scholar
  58. Falconer D. S. 1952. Selection for large and small size in mice. J. Genet., 51: 470–501.CrossRefGoogle Scholar
  59. Falconer D. S. 1981. Introduction to quantitative genetics. Second edition. The Longman Press, London.Google Scholar
  60. Finlay K. W. and Wilkinson G. N. 1963. The analysis of adaptation in a plant breeding programme. Aust. J. Agr. Res., 14: 742–754.CrossRefGoogle Scholar
  61. Fisher R. A. 1926. The arrangement of field experiments. Journal of the Ministry of Agriculture, 33: 403–13.Google Scholar
  62. Fisher R. A. and Mackknzie W. A. 1923. Studies in crop variation, II. The manurial response of different potato variations. Journal of Agricultural Science, Cambridge. 13: 311–20.CrossRefGoogle Scholar
  63. Francis T. R. and Kannenberg L. W. 1978. Yield stability studies in short-season maize. I A descriptive method for grouping genotypes. Can. J. Plant Sci., 58: 1029–1034.CrossRefGoogle Scholar
  64. Freeman G. H. 1973. Statistical methods for the analysis of genotypes-environment interactions. Heredity, 31: 339–354.PubMedCrossRefGoogle Scholar
  65. Freeman G. H. 1975. Analysis of interactions in incomplete two-way tables. Applied Statistics, 24: 46–55.CrossRefGoogle Scholar
  66. Freeman G. H. and Perkins J. M. 1971. Environmental and genotype environmental components of variability. VIII. Relations between genotypes grown in different environments and measurement of these environments. Heredity, 27: 15–23.CrossRefGoogle Scholar
  67. Fripp Y. J. 1972. Genotype-environmental interactions in Schizophyllum commune. II. Assessing the environment. Heredity, 28: 223–238.CrossRefGoogle Scholar
  68. Fripp Y. J. and Caten C. E. 1971. Genotype-environment interactions in Schirophyllum commune, I. Analysis and character. Heredity, 27: 393–407.PubMedCrossRefGoogle Scholar
  69. Fripp Y. J. and Caten C. E. 1973. Genotype-environment interactions in Schizophyllum commune. III. The relationship between mean expression and sensitivity to change in environment. Heredity, 30: 341–349.PubMedCrossRefGoogle Scholar
  70. Gabriel K. R. 1978. Least squares approximation of matrices by additive and multiplicative models. J. R. Stat. Soc. Ser. B., 40: 186–196.Google Scholar
  71. Gail M. and Simon R. 1985. Testing for qualitative interactions between treatment effects and patient subsets. Biometrics, 41: 361–372.PubMedCrossRefGoogle Scholar
  72. Gauch H. G. Jr. 1988 Model selection and validation of yield trials with interaction. Biometrics, 44: 705-7151988 Model selection and validation of yield trials with interaction. Biometrics, 44: 705–715CrossRefGoogle Scholar
  73. Gauch H. G. Jr. 1992. Statistical analysis of regional yield trials: AMM1 analysis of factorial designs. Elsevier, Amsterdam.Google Scholar
  74. Gauch H. G. and Zobel R. W. 1990. Imputing missing yield trial data. Theor. Appl. Genet., 70: 753–761.Google Scholar
  75. Gauch H. G. Jr. and Zobel R. W. 1996. AMMI analysis of yield trials, p. 85–122. In: Genotype-by-environment interaction, (eds. ) M. S. Kang and H. G. Gauch, Jr., CRC Press, Boca Raton, FL.CrossRefGoogle Scholar
  76. Gimelfarb A. 1994. Additive-multiplicative approximation of genotype-environment interaction. Genetics, 138: 1339–1349.PubMedGoogle Scholar
  77. Glaz B. and Dean J. L. 1988. Statistical error rates and their implications in sugarcane clone trials. Agron. J., 80: 560–562.CrossRefGoogle Scholar
  78. Glaz B., Miller J. D. and Kang M. S. 1985. Evaluation of cultivar-testing locations in sugarcane. Theor. Appl. Genet., 71: 22–25.CrossRefGoogle Scholar
  79. Gorman D. P., Kang M. S. and Milam M. R. 1989. Contribution of weather variables to genotype × environment interaction in grain sorghum. Plant Breeding, 103: 299–303.CrossRefGoogle Scholar
  80. Gravois K. A., Moldenhauer K. A. K. and Rohman P. C. 1990. GEI interaction for rice yield and identification of stable, high-yielding genotypes. p. 181–188. In: Genotype-by-environment interaction and plant breeding. (ed. ) M. S. Kang, Louisiana State Univ. Agric. Center, Baton Rouge, LA.Google Scholar
  81. Gurganus M. J., Fry J. D., Nuzhdin S. V., Pasyukova E. G., Lyman R. F. and Mackay T. F. C. 1998. Genotype-environment interaction at quantitative trait loci affecting sensory bristle number in Drosophila melanogaster. Genetics, 149: 1883–1898.PubMedGoogle Scholar
  82. Gutierrez J. C, Lopez M. and El-Zik K. M. 1994. AMMI (additive main effects and multiplicative interactions analysis): A tool to determine adaptability of upland cotton genotypes in Spain. Cotton Improve. Conf. Beltwide Cotton Conf. Proceedings Vol. 2 (1994): 688–689.Google Scholar
  83. Hanson C. H., Robinson H. F. and Comstock R. E. 1956. Biometrical studies of yield in segregating populations of Korean Lespedeza. Agronomy Journal, 48: 268–72.CrossRefGoogle Scholar
  84. Hanson W. D. 1970. Genotypic stability. Theor. Appl. Genet., 48: 226–231.Google Scholar
  85. Hardwick R. C. and Wood J. T. 1972. Regression methods for studying gnotype environment interactions. J. Agric. Sci. Camb., 85: 477–493.Google Scholar
  86. Harville D. A. 1977. Maximum-likelihood approaches to variance component estimation and to related problems. J. Amer. Stat. Assoc., 72: 320–340.CrossRefGoogle Scholar
  87. Hayes P. M., Liu B. H., Knapp S. J., Chen F., Jones B., Blake T., Franckowviak J., Rasmusson D., Sorrells M., Ullrich S. E., Wesenberg D. and Kleinhofs A. 1993. Quantitative trait locus effects and environmental interaction in North American barley germplasm. Theor. Appl. Genet., 87: 392–401.CrossRefGoogle Scholar
  88. Henderson C. R. 1975. Best linear unbiased estimation and prediction under a selection model. Biometrics, 31: 423–447.PubMedCrossRefGoogle Scholar
  89. Higley L. G., Browde J. A. and Higley P. M. 1993. Moving toward new understandings of biotic stress and stress interactions, p. 749–754. In: International crop science, (eds. ) I. D. R. Bruxton, R. Shibles, R. A. Forsberg, B. L. Blad, K. H. Asay, G. M. Paulsen, and R. F. Wilson, Crop Sci. Soc. America, Madison, WI.Google Scholar
  90. Hill J. 1975. Genotype-environment interaction — a challenge for plant breeding. J. Agric. Sci., Camb., 85: 477–493.CrossRefGoogle Scholar
  91. Hill J. and Perkins J. M. 1969. The environmental induction of heritable changes in Nicotiana rustica. Effects of gentoype-environmental interactions. Genetics, 61: 661–675.PubMedGoogle Scholar
  92. Hill R. R. Jr. and Rosenberger J. L. 1985. Methods for combining data from germplasm evaluation trials. Crop Sci., 25: 467–470.CrossRefGoogle Scholar
  93. Hühn M. 1979. Beitrage zur Erfassung der phanotypischen Stabilitat. I. Vorschlag eingier auf Ranginformationen beruhenden Stabilitats parameter. EDP in Medizin und Biologie., 10: 112–117.Google Scholar
  94. Hühn M. 1990a. Nonparametric measures of phenotypic stability. Part 1: Theory. Euphytica, 47: 189–194.Google Scholar
  95. Hühn M. 1990b. Nonparametric measures of phenotypic stability. Part 2: Application. Euphytica, 47: 195–201.Google Scholar
  96. Hühn M. 1996. Nonparametric analysis of genotype × environment interactions by ranks, p. 235–271. In: Genotype-by-environment interaction, (eds. ) M. S. Kang and H. G. Gauch, Jr., CRC Press, Boca Raton, FL.CrossRefGoogle Scholar
  97. Hussein M. A., Bjornstad A. and Aastveit A. H. 2000. SASG × ESTAB: A SAS program for computing genotype × environment stability statistics. Agron. J., 92: 454–459.CrossRefGoogle Scholar
  98. Jenns A. E., Leonard K. J. and Moll R. H. 1982. Stability analyses for estimating relative durability of quantitative resistance. Theor. Appl. Genet., 63: 183–192.CrossRefGoogle Scholar
  99. Jensen R. C., Van Ooijien J. M., Stam P., Lister C. and Dean C. 1995. Genotype-by-environment interaction in genetic mapping of multiple quantitative trait loci. Theor. Appl. Genet., 91: 33–37.Google Scholar
  100. Jiang C. and Zeng Z. -B. 1995. Multiple trait analysis and genetic mapping for quantitative trait loci. Genetics, 140: 1111–1127.PubMedGoogle Scholar
  101. Jinks J. L. and Connolly V. 1973. Selection for specific and general response to environmental differences. Heridity, 30: 33–40.CrossRefGoogle Scholar
  102. Jinks J. L. and Mather K. 1955. Stability in development of heterozygotes and homozygotes. Proceedings of the Royal Society Series B, 143: 561–78.CrossRefGoogle Scholar
  103. Jinks J. L. and Perkins J. M. 1970. Environmental and genotype-environmental components of variability. VII. Simultaneous prediction across environments and generations. Heredity, 25: 475–480.CrossRefGoogle Scholar
  104. Johnson J. J., Alldredge J. R., Ullrich S. E. and Dangi O. 1992. Replacement of replications with additional locations for grain sorghum cultivar evaluation. Crop Sci., 32: 43–46.CrossRefGoogle Scholar
  105. Jones H. G. 1992. Plants and microclimate: A quantitative approach to environmental plant physiology. 2nd edition. Cambridge Univ. Press, Cambridge, U. K.Google Scholar
  106. Jones R. M. and Mather K. 1958. Interaction of genotypes and environment in continuous variation. II. Analysis, Biometrics, 14: 489–98.CrossRefGoogle Scholar
  107. Kang M. S. 1988. A rank-sum method for selecting high-yielding, stable corn genotypes. Cereal Res. Commun., 16: 113–115.Google Scholar
  108. Kang M. S. 1990. Genotype-by-environment interaction and plant breeding. Louisiana State Univ. Agric. Center, Baton Rouge, LA.Google Scholar
  109. Kang M. S. 1993a. Issues in GE interaction, p. 67–73. In: Genotype-environment interaction studies in perennial tree crops. (eds. ) Rao V., Hanson I. E. and Rajanaidu N., Palm Oil Research Institute of Malaysia, Kaula Lumpur.Google Scholar
  110. Kang M. S. 1993b. Simultaneous selection for yield and stability in crop performance trials: Consequences for growers. Agron. J., 85: 754–757.CrossRefGoogle Scholar
  111. Kang M. S. 1998. Using genotype-by-environment interaction for crop cultivar development. Adv. Agronomy, 62: 199–252.CrossRefGoogle Scholar
  112. Kang M. S. and Gauch H. G. Jr. 1996. Genotype-by-environment interaction. CRC Press, Boca Raton, FL.Google Scholar
  113. Kang M. S. and Gorman D. P. 1989. Genotype × environment interaction in maize. Agron. J., 81: 662–664.CrossRefGoogle Scholar
  114. Kang M. S., Harville B. G. and Gorman D. P. 1989. Contribution of weather variables to genotype × environment interaction in soybean. Field Crops Res., 21: 297–300.CrossRefGoogle Scholar
  115. Kang M. S. and Magari R. 1995. STABLE: Basic program for calculating yield-stability statistic. Agron. J., 87: 276–277.CrossRefGoogle Scholar
  116. Kang M. S. and Magari R. 1996. New developments in selecting for phenotypic stability in crop breeding. p. 1–14. In: Genotype-by-environment interaction. (eds. ) Kang M. S. and Gauch H. G. Jr., CRC Press, Boca Raton, FL.Google Scholar
  117. Kang M. S. and Miller J. D. 1984. Genotype × environment interactions for cane and sugar yield and their implications in sugarcane breeding. Crop Sci., 24: 435–440.CrossRefGoogle Scholar
  118. Kang M. S., Miller J. D. and Darrah L. L. 1987. A note on relationship between stability variance and ecovalence. J. Hered., 78: 107.Google Scholar
  119. Kang M. S., Miller J. D. and Tai P. Y. P. 1984. Clonal and individual repeatability of agronomic traits in sugarcane. J. Am. Soc. Sugar Cane Techno., 3: 22–27.Google Scholar
  120. Kang M. S. and Pham H. N. 1991. Simultaneous selection for high yielding and stable crop genotypes. Agron. J., 83: 161–165.CrossRefGoogle Scholar
  121. Kearsey M. J. and Pooni H. S. 1996. The genetical analysis of quantitative traits. Chapman & Hall, London, UK.Google Scholar
  122. Korol A. B., Ronin Y. I. and Kirzhner V. M. 1995. Interval mapping of quantitative trait loci employing correlated trait complexes. Genetics, 140: 1137–1147.PubMedGoogle Scholar
  123. LeClerg E. L. 1966. Significance of experimental design in plant breeding. p. 243–313. In: Plant breeding, (ed. ) K. J. Frey, Iowa State University Press, Ames, IA.Google Scholar
  124. Leigh R. A. 1993. Perception and transduction of stress by plant cells. p. 223–237. In: Plant adaptation to environmental stress. (eds. ) L. Fowden, T. Mansfield and J. Stoddart, Chapman & Hall, New York.Google Scholar
  125. Leon J. 1985. Beiträge zur Erfassung der phänötypischen Stabilität unter besonderer Berückischtigug unterschidilicher Heterogenitäts-und Heterozygotiegrade sowie einer zusammenfassenden Beurteilung von Ertragshöhe and Ertragssicherheit. Dissertation, Christian-Albrechts-Universität Kiel.Google Scholar
  126. Leon J. 1986. Methods of simultaneous estimation of yield and yield stability. In: Biometrics in Plant Breeding. Proc. 6th Meeting Eucarpia-Section. Birmingham, UK, 299–308.Google Scholar
  127. Lerner I. M. 1954. Genetic Homeostasis. Oliver & Boyd, London.Google Scholar
  128. Lin C. S. 1989. (In) Letter to the Editor, Crop Sci., 29: p. 1334.CrossRefGoogle Scholar
  129. Lin C. S. and Binns M. R. 1988. A method of analyzing cultivar × location × year experiments: A new stability parameter. Theor. Appl. Genet., 76: 425–430.CrossRefGoogle Scholar
  130. Lin C. S. and Binns M. R. 1991a. Assessment of a method for cultivar selection based on regional trial data. Theor. Appl. Genet., 82: 379–388.CrossRefGoogle Scholar
  131. Lin C. S. and Binns M. R. 1994. Concepts and methods for analyzing regional trial data for cultivar and location selection. Plant Breeding Reviews, 12. John Wiley & Sons, Inc.Google Scholar
  132. Lin C. S., Binns M. . R. and Lefkovitch L. P. 1986. Stability analysis: Where do we stand? Crop Sci., 26: 894–900.CrossRefGoogle Scholar
  133. Lin C. S. and Butler G. 1990. Cluster analyses for analyzing tow-way classification data. Agron. J., 82: 344–348.CrossRefGoogle Scholar
  134. Lin C. S. and Morrison M. J. 1992. Selection of test locations for regional trials of barley. Theor. Appl. Genet., 83: 968–972.CrossRefGoogle Scholar
  135. Macchiavelli R. E. and Beaver J. S. 1999. Analysis of genotype-by-environment interaction with AMMI models using SAS PROC MIXED. Appl. Stat Agric., Meeting held at Dep. of Statistics, Kansas State Univ., Manhattan, April 25-27, 1999. (11th): p. 171–183.Google Scholar
  136. Magari R. and Kang M. S. 1997. SAS-STABLE: Stability analyses of balanced and unbalanced data. Agron. J., 89: 929–932.CrossRefGoogle Scholar
  137. Magari R., Kang M. S. and Zhang Y. 1996. Sample size for evaluating field ear moisture loss rate in maize. Maydica, 41: 19–24.Google Scholar
  138. Magari R., Kang M. S. and Zhang Y. 1997. Genotype by environment interaction for ear moisture loss rate in corn. Crop Sci., 37: 774–779.Google Scholar
  139. Mather K. and Jones R. M. 1958. Interactions of genotypes and environment in continuous variation. I. Description. Biometrics, 14: 343–59.CrossRefGoogle Scholar
  140. Mather K. 1953. Genetical control of stability in development. Heredity, 7: 297–336.CrossRefGoogle Scholar
  141. Mather K. and Jinks J. L. 1971. Biometrical Genetics. 2nd edition. Chapman and Hall, London.Google Scholar
  142. Matheson A. C. and Cotterill P. P. 1990. Utility of genotype × environment interactions. For. Ecol. Management, 30: 159–174.CrossRefGoogle Scholar
  143. Matheson A. C. and Raymond C. A. 1984. The impact of genotype × environment interactions on Australian P. radiata breeding programs. Aust. For. Res., 14: 11–25.Google Scholar
  144. Myers W. M. 1960. Genetic control of physiological processes: Consideration of differential ion uptake by plants. p. 201–226. In: Radioisotopes in the biosphere. (eds. ) Caldecott R. S. and Synder L. A., Univ. of Minnesota, Minneapolis, MN.Google Scholar
  145. Nachit M. M., Nachit G., Ketata H., Gauch H. G. Jr. and Zobel R. W. 1992. Use of AMMI and linear regression models to analyze genotype-environment interaction in durum wheat. Theor. Appl. Genet., 83: 597–601.CrossRefGoogle Scholar
  146. Nassar R., Leon J. and Huhn M. 1994. Tests of significance for combined measures of plant stability and performance. Biom. Journal, 36: 109–123.CrossRefGoogle Scholar
  147. Nassar R. and Huhn M. 1987. Studies on estimation of phenotypic stability: Test of significance for non-parametric measures of phenotypic stability. Biometrics, 43: 45–53.CrossRefGoogle Scholar
  148. Nyquist W. E. 1991. Estimates of heritability and prediction of selection response in plant populations. Crit. Rev. Plant Sci., 10: 235–322.CrossRefGoogle Scholar
  149. Pandey S. and Gardner C. O. 1992. Recurrent selection for population, variety and hybrid improvement in tropical maize. Adv. Agron., 48: 1–87.CrossRefGoogle Scholar
  150. Paterson A. H., Damon S., Hewitt J. D., Zamir D., Rabinowitch H. D., Lincoln S. E., Lander E. S. and Tanksley S. D. 1991. Mendelian factors underlying quantitative traits in tomato: Comparison across species, generations, and environments. Genetics, 127: 181–197.PubMedGoogle Scholar
  151. Patterson H. D. 1978. Routine least squares estimation of variety means in incomplete tables. J. Natn. Inst. Agric. Bot., 14: 401–413.Google Scholar
  152. Patterson H. D. 1980. Yield sensitivity and straw shortness in varieties of winter wheat. J. Natn. Inst. Agric. Bot., 13: 142–151.Google Scholar
  153. Patterson H. D. and Silvey V. 1980. Statutory and recommended test trials of crop varieties in the United Kingdom. J. Roy Stat. Soc, A143: 219–252.Google Scholar
  154. Patterson H. D. and Thompson R. 1971. Recovery of inter-block information when block sizes are unequal. Biometrika, 58: 545–554.CrossRefGoogle Scholar
  155. Pedersen A. R., Everson E. H. and Grafius J. E. 1978. The gene pool concept as basis for cultivar selection and recommendation. Crop Sci., 18: 883–886.CrossRefGoogle Scholar
  156. Perkins J. M. and Jinks J. L. 1968a. Environmental and genotype environmental components of variability Multiple inbred crops. Heredity, 23: 339–356.PubMedCrossRefGoogle Scholar
  157. Perkins J. M. and Jinks J. L. 1968b. Environmental and genotype environmental components of variability. 4. Non-linear interactions for multiple inbred lines. Heredity, 23: 525–535.CrossRefGoogle Scholar
  158. Perkins J. M. 1970. Environmental and genotype-environmental components of variability. VI. Diallel sets of crosses. Heredity, 25: 29–40.PubMedCrossRefGoogle Scholar
  159. Peschke V. M. and Sachs M. M. 1993. Multiple pyruvate decarboxylase genes in maize are induced by hypoxia. Mol. Gen. Genet., 240: 206–212.PubMedCrossRefGoogle Scholar
  160. Pham H. N. and Kang M. S. 1988. Interrelationships among and repeatability of several stability statistics estimated from International Maize trials. Crop Sci., 28: 925–928.CrossRefGoogle Scholar
  161. Piepho H. P. 1994. Missing observations in analysis of stability, Heredity, 72: 141–145. (Correction 73 (1994): (58).CrossRefGoogle Scholar
  162. Piepho H. P. 1994. Best linear unbiased prediction (BLUP) for regional yield trials: a comparison to additive main effects and multiplicative interaction (AMMI) analysis. Theor. Appl. Genet., 89: 647–654.CrossRefGoogle Scholar
  163. Piepho H. P. 1998. Methods for comparing the yield stability of cropping systems — A review. J. Agron. Crop Sci, 180: 193–213.CrossRefGoogle Scholar
  164. Pinthus M. J. 1973. Estimate of genotypic value: A proposed method. Euphytica, 22: 121–123.CrossRefGoogle Scholar
  165. Plaisted R. L. 1960. A shorter method for evaluating the ability of selections to yield consistently over locations. Amer. Potato J., 37: 166–172.CrossRefGoogle Scholar
  166. Plaisted R. L. and Peterson L. C. 1959. A technique for evaluating the ability of selections to yield consistently in different locations or seasons. Amer. Potato J., 36: 381–385.CrossRefGoogle Scholar
  167. Pooni H. S. and Jinks J. L. 1980. Non-linear genotype × environment interaction. II Statistical models and genetical control. Heredity, 45: 389–400.CrossRefGoogle Scholar
  168. Prabhakaran V. T. and Jain J. P. 1994. Statistical techniques for studying genotype-environment interactions. South Asian Publishers, New Delhi, India.Google Scholar
  169. Raiger H. L. and Prabhakaran V. T. 2000. A statistical comparison between non-parametric and parametric stability measures. Indian J. Genet., 60: 417–432.Google Scholar
  170. Raiger H. L and Prabhakaran V. T. 2001. A study on the performance of a few non-parametric stability measures using pearl-millet data. Indian J. Genet., 61: 7–11.Google Scholar
  171. Rameau C. and Denis J. B. 1992. Characterization of environments in long-term multi-site trials in asparagus, through yield of standard varieties and use of environmental covariates. Plant Breeding, 109: 183–191.CrossRefGoogle Scholar
  172. Rao A. R. and Prabhakaran V. T. 2000. On some useful interrelationships among common stability parameters. Indian J. Genet., 60: 25–361.Google Scholar
  173. Rao V., Henson I. E. and Rajanaidu N. 1993. Genotype × environment interaction in perennial tree crops. International Society of Oil Palm Breeders and Palm Oil Research Institute of Malaysia, Kuala Lumpur, Malaysia.Google Scholar
  174. Robbertse P. J. 1989. The role of genotype-environment interaction in adaptability. So. African For. J., 150: 18–19.Google Scholar
  175. Robertson A. 1959. The sampling variance of the genetic correlation coefficient. Biometrics, 15: 469–485.CrossRefGoogle Scholar
  176. Romagosa I., Ullrich S. E., Han F. and Hayes P. M. 1996. Use of additive main effects and multiplicative interaction model in QTL mapping for adaption in barley. Theor. Appl. Genet., 93: 30–37.CrossRefGoogle Scholar
  177. Ronin Y. I., Kirzhner V. M. and Korol A. B. 1995. Linkage between loci of quantitative traits and marker loci. Multi-trait analysis with a single marker. Theor. Appl. Genet., 90: 776–786.CrossRefGoogle Scholar
  178. Rosielle A. A. and Hamblin J. 1981. Theoretical aspects of selection for yield in stress and non-stress environments. Crop Sci., 21: 943–946.CrossRefGoogle Scholar
  179. Saeed M. and Francis C. A. 1984. Association of weather variables in genotype × environment interaction in grain sorghum. Crop Sci., 24: 13–16.CrossRefGoogle Scholar
  180. Sari-Gorla M., Calinski T., Kaczamarek Z. and Krajewski P. 1997. Detection of QTL-environment interaction in maize by a least squares interval mapping method. Heredity, 78: 146–157.Google Scholar
  181. Scandalios J. G. 1990. Response of plant antioxidant defense genes to environmental stress, p. 1–41. In: Advances in genetics, (eds. ) G. Scandalios and T. R. F. Wright. Academic Press, New York.Google Scholar
  182. Searle S. R. 1987. Linear models for unbalanced data. John Wiley & Sons, New York.Google Scholar
  183. Searle S. R., Casella G. and McCulloch C. E. 1992. Variance components. John Wiley & Sons, New York.CrossRefGoogle Scholar
  184. Seyedsadr M. S. and Cornelius P. L. 1992. Shifted multiplicative models for non-additive two-way tables. Comm. Stat. B. Simul Comp., 21: 807–832.CrossRefGoogle Scholar
  185. Seyedsadr M. S. and Cornelius P. L. 1992. Using the shifted multiplicative model to search for “separability” in crop cultivar trials. Theor. Appl. Genet., 84: 161–172.Google Scholar
  186. Shafii B. and Price W. J. 1998. Analysis of genotype-by-environment interaction using the Additive Main Effects and Multiplicative Interaction model and stability estimates. J. Agric. Biol. Environ. Stat., 3: 335–345.CrossRefGoogle Scholar
  187. Shukla G. K. 1972. Some statistical aspects of partitioning genotype-environmental components of variability. Heredity, 29: 237–245.PubMedCrossRefGoogle Scholar
  188. Silvey V. 1981. The contribution of new wheat, barley and oat varieties to increasing yield in England and vales 1947-78. J. National Inst. Agric. Bot., 15: 399–412.Google Scholar
  189. Simmonds N. W. 1981. Genotype (G), environment (E) and GEI components of crop yields. Expl. Agric., 17: 355–362.CrossRefGoogle Scholar
  190. Smith H. 1990. Signal perception, differential expression within multigene families and the molecular basis of phenotypic plasticity. Plant Cell Environ., 13: 585–594.CrossRefGoogle Scholar
  191. Smith M. E., Coffman W. R. and Barker T. C. 1990. Environmental effects on selection under high and low input conditions. p. 261–272. In: Genotype-by-environment interaction and plant breeding. (ed. ) M. S. Kang, Louisiana State Univ. Agric. Center, Baton Rouge, LA.Google Scholar
  192. Specht J. E. and Laing D. R. 1993. Selection for tolerance to abiotic stresses — discussion, p. 381–382. In: International Crop Science I., (eds. ) Bruxton D. R., Shibles R., Forsberg R. A., Blad B. L., Asay K. H., Paulsen G. M. and Wilson R. G., Crop Sci. Soc. America, Madison, WI.Google Scholar
  193. Sprague G. F. and Federer W. T. 1951. A comparison of variance components in corn yield trials. II, Error, year-variety, location-variety and variety components. Agronomy Jounrnal, 43: 535–41.CrossRefGoogle Scholar
  194. Steiner K. C, Barbour J. R. and McCormick L. H. 1984. Response of Populus hybrids to aluminium toxicity. Forest Sci., 30: 404–410.Google Scholar
  195. Stroup W. W. and Mulitze D. K. 1991. Nearest neighbor adjusted best linear unbiased prediction. Am. Stat., 45: 194–200.Google Scholar
  196. Stuber C. W. and Le Deaux J. R. 2000. QTL × environment interaction in maize when mapping QTLs under several stress conditions, p. 101–112. In: Simposium interaccion genotipo × ambiente. (eds. ) F. Zavala Garcia and N. E. Treviqo Hernandez, SOMEFI-CSSA-UG, Irapuato, Gto, Mexico.Google Scholar
  197. Stuber C. W., Polacco M. and Senior M. L. 1999. Synergy of empirical breeding, marker-assisted selection, and genomics to increase crop yield potential. Crop Sci., 39: 1571–1583.CrossRefGoogle Scholar
  198. Tai G. C. C. 1971. Genotypic stability analysis and its application to potato regional trials. Crop Sci., 11: 84–190.CrossRefGoogle Scholar
  199. Thennarasu K. 1995. On certain non-parametric procedures for studying genotype-environment interactions and yield stability. Unpublished Ph. D. Thesis, P. G. School, IARI, New Delhi.Google Scholar
  200. Tinker N. A. and Mather D. E. 1995. Methods for QTL analysis with progeny replicated in multiple environments. JQTL, 1: http://probe. nalusda. gov:8000/otherdocs/qtl/Jqtl 1995-02/jqtll6r2. html.Google Scholar
  201. Tiret L., Abel L. and Rakotovao R. 1993. Effect of ignoring genotype-environment interaction in segregation analysis of quantitative traits. Genetic Epidemiology, 10: 581–586.PubMedCrossRefGoogle Scholar
  202. Unsworth M. H. and Fuhrer J. 1993. Crop tolerance to atmospheric pollutants, pp. 363–370. In: International Crop Science I., (eds. ) Bruxton D. R., Shibles R., Forsberg R. A., Blad B. L., Asay K. H., Paulsen G. M. and Wilson R. F., Crop Science Soc, America, Madison, WI.Google Scholar
  203. Utz H. F. 1972. Die Zerlengung der Genotyp × Umwelt Interaktion. EDV in Medizin und Biologie, 3: 52–59.Google Scholar
  204. Van Eeuwijk F. A., Denis J. B. and Kang M. S. 1996. Incorporating additional information on genotypes and environments in models for two-way genotype by environment tables, p. 15–49. In: Genotype-by-environment interaction. (eds. ) M. S. Kang and H. G. Gauch Jr., C. R. C. Press, Boca Raton, Florida, USA.CrossRefGoogle Scholar
  205. Van Eeuwijk F. A., Crossa J., Vargas M. and Ribaut J. M. 2000. Modeling QTLs and QTL × E using factorial regression models and partial least squares techniques, p. 43–60. In: Simposium interaccion genotipo × ambiente. (eds. ) F. Zavala Garcia and N. E. Treviqo Hernandez, SOMEFI-CSSA-UG, Irapuato, Gto, Mexico.Google Scholar
  206. Vasil J. D. and Milas S. 1984. Relationship between yield stability parameters estimated with different methods for maize and wheat genotypes. Vortr. Pflanzenzuchtg. 7: 266–279.Google Scholar
  207. Verma M. M., Chahal G. S. and Murty B. R. 1978. Limitations of conventional agression analysis-A proposed modification. Theor. Appl. Genet., 53: 89–91.Google Scholar
  208. Via S. and Lande R. 1987. Evolution of genetic variation in a spatially heterogeneous environment. Genet. Res., 49: 147–156.PubMedCrossRefGoogle Scholar
  209. Virk D. S. and Mangat B. K. 1991. Detection of cross over genotype × environment interactions in pearl millet. Euphytica, 52: 193–199.CrossRefGoogle Scholar
  210. Weber W. E., Wricke G. and Westermann T. 1996. Selection of genotypes and prediction of performance by analyzing GE interactions, p. 353–371. In: Genotype-by-environment interaction, (eds. ) M. S. Kang and H. G. Gauch Jr., CRC Press, Boca Raton, FL.CrossRefGoogle Scholar
  211. Williams W. T. 1976. Patter Analysis in Agricultural Science. Elsevier Scientific Publishing Co., Oxford.Google Scholar
  212. Wricke G. 1962. Uber eine Methode zur Erfassung der Vkologischen Streubreite. Zeitschrift für Pflanzenzlchtung, 47: 92–96.Google Scholar
  213. Wricke G. and Weber W. E. 1980. Erweiterte analyse von Wechselwirkungen in versuchsserien. In: Biometrie-heute and morgen, (eds. ) Kopeke, W. and K. Uberla, 87–95. Berlin Heidelberg-New York: Springer-Verlag.CrossRefGoogle Scholar
  214. Yamada Y. 1962. Genotype by environment interaction and genetic correlation of the same trait under different environments. Jap. J. Genet., 37: 498–509.CrossRefGoogle Scholar
  215. Yan W., Hunt A. L., Sheng Q. and Szlavnics Z. 2000. Cultivar evaluation and mega-environment investigation based on the GGEI biplot. Crop Sci., 40: 597–605.CrossRefGoogle Scholar
  216. Yates F. and Cochran W. G. 1938. The analysis of groups of experiments. J. Agric. Sci., 28: 556–580.CrossRefGoogle Scholar
  217. Zhang Q. and Geng S. 1986. A method of estimating varietal stability for long-term trials. Theor. Appl. Genet., 71: 810–814.CrossRefGoogle Scholar
  218. Zobel R. W., Wright M. J. and Gauch H. G. Jr. 1988. Statistical analysis of a yield trial. Agron. J., 80: 388–393.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2004

Authors and Affiliations

  • Manjit S. Kang
    • 1
  • V. T. Prabhakaran
    • 2
  • R. B. Mehra
    • 3
  1. 1.Louisiana State University Agricultural CenterBaton RougeUSA
  2. 2.Indian Agricultural Statistics Research InstituteNew DelhiIndia
  3. 3.Indian Agricultural Research InstituteNew DelhiIndia

Personalised recommendations