BMC Plant Biology (Feb 2024)

Genetic parameter changes and age−age correlations in Pinus koraiensis growth over 40-year progeny testing

  • Kyungmi Lee,
  • Changyoung Oh,
  • In Sik Kim

DOI
https://doi.org/10.1186/s12870-024-04752-y
Journal volume & issue
Vol. 24, no. 1
pp. 1 – 11

Abstract

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Abstract Background Early selection in tree breeding could be achieved by addressing the longevity of tree improvement activities. Genetic parameter changes and age–age correlations are essential for determining the optimal timing of early selection. Practical tracking of genetic parameters of Pinus koraiensis, a major timber species with economic and ecological value, has become feasible as its progeny testing has entered the mid-term age in Korea. However, research on the age−age correlation of P. koraiensis as progeny trials approach rotation age is limited. This study aimed to investigate genetic parameter trends and age−age correlations in P. koraiensis progeny. P. koraiensis progeny were assessed at two sites using a linear mixed-effects model with two-dimensional spatial autoregressive structure. Height, diameter, and volume growth were measured in 11 assessments over 40 years. Results Genetic parameters, such as height and diameter, showed different patterns of change. The heritability ranged for the three growth traits in 0.083–0.710, 0.288–0.781, and 0.299–0.755 across the sites and age. Height heritability and its coefficient of variance decreased, whereas the diameter and volume estimates remained relatively constant. Correlations with Age 40 for phenotypic, genetic, and rank of breeding values ranged between 0.16 and 0.92, 0.594 and 0.988, and 0.412 and 0.965, respectively. These correlations generally increased as the age approached Age 40, with particularly high levels observed at Age 26 and Age 30. Conclusion The observed genetic trends in P. koraiensis progeny testing offer valuable insights for early and precise selection. Notably, selecting superior genotypes at Ages 26–30 is supported by discernible genetic gains and robust correlations. Future research should integrate unbalanced data for selecting mother trees or families and conduct a comprehensive economic analysis of early selection to validate its practical benefits.

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