Age trends in genetic parameters and genetic gains of growth traits in multiple progeny test sites of hinoki cypress (Chamaecyparis obtusa)

References

• Dong L, Xie Y, Sun X. 2020. Full-diallel-based analysis of genetic parameters for growth traits in Japanese larch (Larix kaempferi). New For. 51(2):261–271. doi: 10.1007/s11056-019-09729-6.
   Google Scholar
• Falconer DS, Mackay TFC. 1996. Introduction to quantitative genetics. 4th ed. UK: Longman Group Ltd.
   Google Scholar
• Farjon A. 2005. Monograph of Cupressaceae and Sciadopitys. Kew: Royal Botanic Gardens.
   Google Scholar
• Forest Tree Breeding Association. 2004. Forest tree breeding project in Japan. Tokyo: Japan Forest Tree Breeding Association. in Japanese.
   Google Scholar
• Forest Tree Breeding Center. 2020. Execution condition and statistics of forest tree breeding, in 2019. Ibaraki: Forest Tree Breeding Center. in Japanese.
   Google Scholar
• Franklin EC. 1979. Model relating levels of genetic variance to stand development of four north American conifers. Silva Genet. 28:207–212.
   Web of Science ®Google Scholar
• Fukatsu E, Matsunaga K, Kurahara K, Chigira Y, Takahashi M. 2013. The efficiency of the evaluation of wood density using Pilodyn and the genetic relationship with growth traits in hinoki cypress (Chamaecyparis obtusa) in Japan. Kyushu J For Res. 66:13–16. in Japanese.
   Google Scholar
• Gwaze DP, Woolliams JA, Kanowski PJ. 1997. Optimum selection age for height in Pinus taeda L. in Zimbabwe. Silva Genet. 46:358–365.
   Web of Science ®Google Scholar
• Hannrup B, Wilhelmsson L, Danell O. 1998. Time trends for genetic parameters of wood density and growth traits in Pinus sylvestris L. Silva Genet. 41:252–262.
   Google Scholar
• Hiraoka Y, Miura M, Fukatsu E, Iki T, Yamanobe T, Kurita M, Isoda K, Kubota M, Takahashi M. 2019. Time trends of genetic parameters and genetic gains and optimum selection age for growth traits in sugi (Cryptomeria japonica) based on progeny tests conducted throughout Japan. J For Res. 24(5):303–312. doi: 10.1080/13416979.2019.1661068.
   Google Scholar
• Hodge GR, White TL. 1992. Genetic parameter estimates for growth traits at different ages in slash pine and some implications for breeding. Silva Genet. 41:252–262.
   Web of Science ®Google Scholar
• Hosoda K, Mitsuda Y, Iehara T. 2010. Differences between the present stem volume tables and the volume equations, and their correction. Jpn J For Plann. 44:23–39. doi: 10.20659/jjfp.44.2_23. in Japanese with English summary.
   Google Scholar
• Jansson G, Li B, Hannrup B. 2003. Time trends in genetic parameters for height and optimal age for parental selection in scots pine. For Sci. 49:696–705.
   Google Scholar
• Kremer A. 1992. Predictions of age-age correlations of total height based on serial correlations between height increments in maritime pine (Pinus pinaster Ait.). Theor Appl Genet. 85(2–3):152–158. doi: 10.1007/BF00222853.
   PubMed Web of Science ®Google Scholar
• Kroon J, Andersson B, Mullin TJ. 2008. Genetic variation in the diameter–height relationship in scots pine (Pinus sylvestris). Can J For Res. 38(6):1493–1503. doi: 10.1139/X07-233.
   Google Scholar
• Kroon J, Ericsson T, Jansson G, Andersson B. 2011. Patterns of genetic parameters for height in field genetic tests of Picea abies and Pinus sylvestris in Sweden. Tree Gene Genom. 7(6):1099–1111. doi: 10.1007/s11295-011-0398-y.
   Web of Science ®Google Scholar
• Kusnandar D, Galwey NW, Hertzler GL, Butcher TB. 1998. Age trends in variances and heritabilities for diameter and height in maritime pine (Pinus pinaster AIT.) in western Australia. Silva Genet. 47:136–141.
   Web of Science ®Google Scholar
• Lambeth CC. 1980. Juvenile-mature correlations in Pinaceae and implications for early selection. For Sci. 26:571–580.
   Google Scholar
• Lambeth C, Dill LA. 2001. Prediction models for juvenile-mature correlations for loblolly pine growth traits within, between and across test sites. For Genet. 8:101–108.
   Google Scholar
• Leksono B, Kurinobu S, Ide Y. 2006. Optimum age for selection based on a time trend of genetic parameters related to diameter growth in seedling seed orchards of Eucalyptus pellita in Indonesia. J For Res. 11(5):359–364. doi: 10.1007/s10310-006-0223-x.
   Google Scholar
• Magnussen S, Keith CT. 1990. Genetic improvement of volume and wood properties of Jack pine: selection strategies. For Chron. 66(3):281–286. doi: 10.5558/tfc66281-3.
   Google Scholar
• McKeand SE. 1988. Optimum age for family selection for growth in genetic tests of loblolly pine. For Sci. 34:400–411.
   Google Scholar
• McKeand SE, Grisson JE, Isik F, Jayawickrama JS. 2008. Genetic parameter estimates for growth traits from diallel tests of loblolly pine throughout the southeastern United States. Silva Genet. 57(1–6):101–110. doi: 10.1515/sg-2008-0016.
   Google Scholar
• The Ministry of Land, Infrastructure, Transport and Tourism of Japan. 2012. Digital national land information (mesh normal value 2010) Accessed 7 Feb 2022.
   Google Scholar
• Miura M, Kubota M, Nomura T, Kurinobu S. 2005. Investigation of regionalization in the Kanto breeding region based on data gained from the clonal tests on 20 years-old sugi (Cryptomeria japonica). J Jpn For Soc. 87(3):233–240. in Japanese. doi: 10.4005/jjfs.87.233.
   Google Scholar
• Mojena R. 1977. Hierarchical grouping methods and stopping rules: an evaluation. Comput J. 20(4):359–363. doi: 10.1093/comjnl/20.4.359.
   Web of Science ®Google Scholar
• Munoz F, Sanchez L 2020. breedR: statistical methods for forest genetic resources analysts. R package version 0.12-5. <https://github.com/famuvie/breedR>.
   Google Scholar
• Nasu J, Tamaki S, Itahana N. 2006. Time trend of genetic parameters for growth traits from clonal lines and open-pollinated progenies of sugi (Cryptomeria japonica) test sites and open-pollinated progenies of hinoki (Chamaecyparis obtusa) test sites in Kionki and Setonaikai part of Kansai forest tree breeding region -The analysis of individual progeny test site-. Bull For Tree Breed Center. 22:1–11. in Japanese.
   Google Scholar
• Paul AD, Foster GS, Caldwell T, McRae J. 1997. Trends in genetic and environmental parameters for height, diameter, and volume in a multilocation clonal study with loblolly pine. For Sci. 43:87–98.
   Google Scholar
• R Core Team. 2021. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. <https://www.R-project.org/>.
   Google Scholar
• Rweyongeza DM. 2016. A new approach to prediction of the age-age correlation for use in tree breeding. Ann For Sci. 73(4):1099–1111. doi: 10.1007/s13595-016-0570-5.
   Web of Science ®Google Scholar
• St. Clair JB. 1994. Genetic variation in tree structure and its relation to size in Douglas-fir. I. Biomass partitioning efficiency, stem form, and wood density. Can J For Res. 24(6):1226–1235. doi: 10.1139/x94-161.
   Google Scholar
• Weng YH, Tosh KJ, Park YS, Fullarton MS. 2007. Age-related trends in genetic parameters for jack pine and their implications for early selection. Silva Genet. 56(1–6):242–252. doi: 10.1515/sg-2007-0035.
   Google Scholar
• White TL, Adams WT, Neale DB. 2007. Forest genetics. UK: CAB International. p. 682. doi: 10.1079/9781845932855.0000.
   Google Scholar
• Yamaya K, Kato R, Mori M, Goto K. 1984. Growth condition of the plantations of Chamaecyparis obtusa and its silvicultural problems in Tohoku district Japan. Bull For For Prod Res Inst. 325:1–96.
   Google Scholar
• Ye TZ, Jayawickrama KJS. 2012. Early selection for improving volume growth in coastal Douglas-fir breeding programs. Silva Genet. 61(1–6):186–198. doi: 10.1515/sg-2012-0024.
   Google Scholar
• Ye CY, Ying CC. 1996. Heritabilities, age-age correlations, and early selection in lodgepole pine (Pinus contorta ssp. Latifolia) Silva Genet. 45:101–105.
   Web of Science ®Google Scholar
• Yomogida H. 1999. Analysis of growth traits measured for 1 to 20 year-old sugi (Cryptomeria japonica D.Don) plus tree clone tests in Iwate prefecture. Bull Iwate Pref For Tech Center. 8:15–25. in Japanese.
   Google Scholar
• Zobel B, Talbert J. 1984. Applied Forest tree improvement. New Jersey: Blackburn Press. 505p.
   Google Scholar