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Annals of Forest Science

, 75:96 | Cite as

Effectiveness of spatial analysis in Cryptomeria japonica D. Don (sugi) forward selection revealed by validation using progeny and clonal tests

  • Eitaro FukatsuEmail author
  • Yuichiro Hiraoka
  • Noritsugu Kuramoto
  • Hiroo Yamada
  • Makoto Takahashi
Research Paper

Abstract

Key message

Accurate evaluation of genetic performances of trees is crucial in order to improve the efficiency of forest tree breeding. We revealed that spatial analysis is effective for predicting individual tree breeding values at the forward selection stage of Cryptomeria japonica D. Don (sugi) breeding program by using a novel validation approach.

Context

In the process of selecting genetically superior trees for breeding, appropriate handling of environmental effects is important in order to precisely evaluate candidate trees. Spatial analysis has been an effective statistical approach for genetic evaluation at sites with heterogeneous microenvironments. However, the efficiency of spatial analysis on forward selection has not been validated on a practical scale to date.

Aims

This study aimed to reveal the effectiveness of spatial analysis, which incorporates spatially autocorrelated residuals into mixed models, for the prediction of breeding values at the forward selection stage by validation using progeny or clonal tests of forward-selected individuals.

Methods

Tree height was analyzed by ordinary randomized complete block design models and spatial models incorporating spatially autocorrelated residuals in a linear mixed model framework, and model selection was conducted at thirty Cryptomeria japonica D. Don breeding population sites having various topographical ruggedness. For validation, three clonal tests and one progeny test of individuals selected from three and four breeding populations, respectively, were used. The effectiveness of forward selection using the two models was evaluated based on the correlation between individual breeding values at the stage of forward selection and genotypic and breeding values that were estimated by clonal and progeny tests.

Results

Spatial models were more predictive than ordinary models in all cases. Spatial correlation parameters tend to increase with the topographical ruggedness index of each site. The correlation coefficients between breeding values at the time of forward selection and genotypic or breeding values evaluated in succeeding clonal and progeny tests were significantly higher in spatial models than in ordinary models in six out of nine cases.

Conclusion

Validation using progeny and clonal tests of forward-selected individual trees revealed that spatial analysis is more effective for the evaluation of genetic performance of individuals at the stage of forward selection in Cryptomeria japonica.

Keywords

Individual selection AR model Spatially correlated residuals Clonal test Progeny test 

Notes

Acknowledgements

The sites used in this study were established and maintained by the National Forest of Japan in collaboration with the Forest Tree Breeding Center, Forestry and Forest Products Research Institute. We thank the members of these organizations for their efforts.

Funding

This work was supported by grants from the project “Development of mitigation and adaptation techniques to global warming in the sectors of agriculture, forestry, and fisheries” financed by the Ministry of Agriculture, Forestry and Fisheries of Japan.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

Supplementary material

13595_2018_771_MOESM1_ESM.docx (273 kb)
Supplementary Table 1 (DOCX 272 kb)

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Copyright information

© INRA and Springer-Verlag France SAS, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Kyushu Regional Breeding Office, Forest Tree Breeding CenterForestry and Forest Products Research InstituteKumamotoJapan
  2. 2.Forest Tree Breeding CenterForestry and Forest Products Research InstituteHitachiJapan
  3. 3.Kansai Regional Breeding Office, Forest Tree Breeding CenterForestry and Forest Products Research InstituteOkayamaJapan

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