Euphytica

, Volume 178, Issue 2, pp 177–183 | Cite as

Bayesian threshold analysis of breeding values, genetic correlation and heritability of flowering intensity in Eucalyptus cladocalyx under arid conditions

  • Camila Cané-Retamales
  • Freddy Mora
  • Felipe Vargas-Reeve
  • Sandra Perret
  • Rodrigo Contreras-Soto
Article

Abstract

In the dry regions of Chile, prolific flowering from forest plantation is particularly advantageous for honey production, in order to supplement the erratic flowering in native plants. Eucalyptus cladocalyx is a species suitable for areas with low water availability and their flowers provide a reliable source for the production of honey. The aim of this study was to examine the heritability of flowering intensity in 49 open-pollinated families of E. cladocalyx in southern Atacama Desert, Chile, with the view to the selection for prolific flowering, but with minimal impact on precocious flowering. The Bayesian variance component estimation model was assumed using the Gibbs sampling algorithm. Threshold models were fitted to flowering data (bi-character model). Flowering intensity was found to be highly heritable (posterior mean: h 2 = 0.48; and credible interval: 0.41–0.56). The posterior mean of the genetic correlation between flowering precocity and intensity was positive (r = 0.45) and according to the credible interval (0.341–0.542), it was significantly different from zero, indicating that selection on breeding values of early flowering at age three, would have significant and positive impact on flowering intensity 5 years later (or in 8-year-old trees). These results are important for the start of a small-scale breeding program for the species in southern Atacama Desert. The genetic variability found in these breeding populations may be used for breeding purposes in regions where arid environmental conditions are limiting to the establishment of eucalypts trees.

Keywords

Gibbs sampling Heritability Genetic correlation Prolific flowering 

Abbreviations

AGG%

Additive genetic gain

DIC

Deviance information criterion

EF

Early flowering

FI

Flowering intensity

GS

Gibbs sampling

h2

Narrow-sense heritability

MM

Mean in multinomial scale

Γ

Genetic correlation

Notes

Acknowledgments

The financial support for this work was provided by the Chilean National Science and Technology Research Fund (FONDECYT). We thank farmers of the rural community of Tunga Norte. CSIRO Australian Tree Seed Centre kindly provided seeds of the Australian population used in this study.

References

  1. Bink MCAM, Boer MP, Ter Braak CJF, Cansen J, Voorrips RE, Van de Weg WE (2007) Bayesian analysis of complex traits in pedigreed plant populations. Euphytica. doi: 10.1007/s10681-007-9516-1
  2. Butcher PA, McDonald MW, Bell JC (2009) Congruence between environmental parameters, morphology and genetic structure in Australia’s most widely distributed eucalypt, Eucalyptus camaldulensis. Tree Genet Genomes 5:189–210CrossRefGoogle Scholar
  3. Chambers PGS, Potts BM, Tilyard PA (1997) The genetic control of flowering precocity in Eucalyptus globulus ssp. globulus. Silvae Genet 46:207–214Google Scholar
  4. Fohouo FNT, Djonwangwe D, Bruckner D (2008) Foraging behaviour of the African honey bee (Apis mellifera adansonii) on Annona senegalensis, Croton macrostachyus, Psorospermum febrifugum and Syzygium guineense var. guineense flowers at Ngaoundere (Cameroon). Pak J Biol Sci 11:719–725CrossRefPubMedGoogle Scholar
  5. Gonçalves-Vidigal MC, Mora F, Bignotto TS, Munhoz REF, Souza LD (2008) Heritability of quantitative traits in segregating common bean families using a Bayesian approach. Euphytica 164:551–560CrossRefGoogle Scholar
  6. Guarnaschelli AB, Lemcoff JH, Prystupa P, Basci S (2003) Responses to drought preconditioning in Eucalyptus globulus Labill provenances. Trees- Struct Funct 17(6):501–509CrossRefGoogle Scholar
  7. Hanks LM, Paine TD, Millar JG, Hom JL (1994) Variation among Eucalyptus species in resistance to eucalyptus long-horned borer in southern. Calif Entomol Exp Appl 74:185–194Google Scholar
  8. Heidelberger P, Welch PD (1983) Simulation run length control in the presence of an initial transient. Oper Res 31:1109–1114CrossRefGoogle Scholar
  9. Hudson IL, Kim SW, Keatley MR (2009) Climatic influences on the flowering phenology of four Eucalypts: a GAMLSS approach. In: 18th world IMACS/MODSIM Congress, Cairns, Australia, 13–17 July 2009Google Scholar
  10. Jordan GJ, Potts BM, Wiltshire RJE (1999) Strong, independent, quantitative genetic control of the timing of vegetative phase change and first flowering in Eucalyptus globulus ssp. globulus (Tasmanian Blue Gum). Heredity 83:179–187CrossRefPubMedGoogle Scholar
  11. Marcar NE, Crawford DF, Leppert PM, Jovanovic T, Floyd R, Farrow R (1995) Trees for saltland: a guide to selecting native species for Australia. CSIRO, Melbourne, p 72Google Scholar
  12. McDonald MW, Rawlings M, Butcher PA, Bell JC (2003) Regional divergence and inbreeding in Eucalyptus cladocalyx (Myrtaceae). Aust J Bot 51:393–403CrossRefGoogle Scholar
  13. Montenegro G, Pizarro R, Avila G, Castro R, Ríos C, Muñoz O, Bas F, Gómez M (2003) Origen botánico y propiedades químicas de las mieles de la región mediterránea árida de Chile. Ciencia e Investigación Agraria 30:161–174Google Scholar
  14. Mora F, Perret S, Scapim CA, Martins EN, Molina MP (2007) Source-dependent blooming variability of Eucalyptus cladocalyx in the region of Coquimbo, Chile. Ciencia e Investigación Agraria 34(2):99–106CrossRefGoogle Scholar
  15. Mora F, Tapia F, Scapim CA, Martins EN, Pinto RJB, Ibacache A (2008) Early performance of Olea europaea cv. Arbequina, Picual and Frantoio in southern Atacama Desert. Crop Breed Appl Biotechnol 8:30–38Google Scholar
  16. Mora F, Gleadow R, Perret S, Scapim CA (2009) Genetic variation for early flowering, survival and growth in sugar gum (Eucalyptus cladocalyx F. Muell) in southern Atacama Desert. Euphytica 169:335–344CrossRefGoogle Scholar
  17. Ormazábal CS (1991) Silvopastoral systems in arid and semiarid zones of northern Chile. Agrofor Syst 14:207–217CrossRefGoogle Scholar
  18. Porter JW (1978) Relationships between flowering and honey production of red ironbark, Eucalyptus sideroxylon (A. Cunn.) Benth., and climate in the Bendigo district of Victoria. Aust J Agric Res 29:815–829CrossRefGoogle Scholar
  19. Ruthrof KX, Loneragan WA, Yates CJ (2003) Comparative population dynamics of Eucalyptus cladocalyx in its native habitat and as an invasive species in an urban bushland in south-western Australia. Divers Distrib 9:469–483CrossRefGoogle Scholar
  20. SAS-Institute (1996) Statistical analysis system: user’s guide. SAS Institute, CaryGoogle Scholar
  21. Spiegelhalter DJ, Best NG, Carlin BP, Van der Linde A (2002) Bayesian measures of model complexity and fit (with discussion). J R Statist Soc B 64(2):583–639CrossRefGoogle Scholar
  22. Squeo FA, Tracol Y, López D, Gutiérrez JR, Cordova AM, Ehleringer JR (2006) ENSO effects on primary productivity in southern Atacama Desert. Adv Geosci 6:273–277CrossRefGoogle Scholar
  23. Tuberosa R, Salvi S (2006) Genomic based approaches to improve drought tolerance of crops. Trends Plant Sci 11:405–412CrossRefPubMedGoogle Scholar
  24. Van-Tassell CP, Van-Vleck LD (1996) Multiple-trait Gibbs sampler for animal models: flexible programs for Bayesian and likelihood-based (co)variance component inference. J Anim Sci 74:2586–2597PubMedGoogle Scholar
  25. Van-Tassell CP, Van-Vleck LD, Gregory KE (1998) Bayesian analysis of twinning and ovulation rates using a multiple trait threshold model and Gibbs sampling. J Anim Sci 76:2048–2061PubMedGoogle Scholar
  26. Varghese M, Kamalakannan R, Harwood CE, Lindgren D, McDonald MW (2009) Changes in growth performance and fecundity of Eucalyptus camaldulensis and E. tereticornis during domestication in southern India. Tree Genet Genomes 5:629–640CrossRefGoogle Scholar
  27. Wei RP, Lindgren D (1996) Effective family number following selection with restrictions. Biometrics 52:198–208CrossRefGoogle Scholar
  28. Williams DR, Potts BM, Smethurst PJ (2003) Promotion of flowering in Eucalyptus nitens by paclobutrazol was enhanced by nitrogen fertilizer. Can J For Res 33:74–78CrossRefGoogle Scholar
  29. Wiltshire RJE, Reid JB, Potts BM (1998) Genetic control of reproductive and vegetative phase change in the Eucalyptus risdoniiE. tenuiramis complex. Aust J Bot 46:45–63CrossRefGoogle Scholar
  30. Woodrow IE, Slocum D, Gleadow RM (2002) Influence of water stress on cyanogenic capacity in Eucalyptus cladocalyx. Aus J Plant Physiol 29:103–110Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Camila Cané-Retamales
    • 1
  • Freddy Mora
    • 1
  • Felipe Vargas-Reeve
    • 1
  • Sandra Perret
    • 2
  • Rodrigo Contreras-Soto
    • 1
  1. 1.Facultad de Ciencias ForestalesUniversidad de Concepción, Victoria 631, Barrio UniversitarioConcepciónChile
  2. 2.Instituto de Investigación ForestalMinistro de Agricultura de ChileSantiagoChile

Personalised recommendations