Advertisement

Clonal variations in cone, seed and nut traits in a Pinus koraiensis seed orchard in Northeast China

  • David Kombi Kaviriri
  • Yuxi Li
  • Dawei Zhang
  • Hongtao Li
  • Zuoyi Fan
  • Jingyuan Wang
  • Lianfu Wang
  • Qi Wang
  • Deqiu Wang
  • Vincent L. Chiang
  • Xiyang ZhaoEmail author
Original Paper

Abstract

Korean pine (Pinus koraiensis Siebold & Zucc.) in Northeastern China has been genetically improved to increase seed yields in addition to timber. To assess seed yield variability and select highly productive clones, 14 cone, seed and nut traits were measured and analyzed. Variance analysis showed that all clones were significantly different in various traits (P < 0.01). Phenotypic coefficients of variation and repeatability of traits ranged from 9.1 to 34.4% and from 27.5 to 97.7%, respectively. Except for the cone layer and cone seed numbers, the other traits were positively or negatively correlated. Three principal components were identified. Seed and nut traits were the most important traits in the first principal component, and cone traits more important in the second. Using correlation and principal component analyses, cone number and other traits were selected to evaluate materials. Twenty-two clones were selected using a selection rate of 10% based on cone number independently or other combined traits. The genetic gain for different traits ranged from 6.2 to 24.3%. The selected elite clones can supply seedlings for reforestation and the selection method can provide a theoretical basis for selection in other conifer species.

Keywords

Pinus koraiensis Clones Cone Seed Nut traits Principal component analysis 

Notes

Author contributions

DKK, YL and DZ have contributed equally to this work.

References

  1. Aït-Sahalia Y, Xiu DC (2019) Principal component analysis of high-frequency data. J Am Stat Assoc 114:287–303.  https://doi.org/10.1080/01621459.2017 CrossRefGoogle Scholar
  2. Bai FY, Kang N, Zhang PD, Kang XY (2019) Selection of female parents with high fertility and high combining abilities for cross-breeding Populus tomentosa. J For Res 30(2):445–450CrossRefGoogle Scholar
  3. Brancher M, Piringer M, Franco D, Belli Filho P, Lisboa H, Schauberger G (2019) Assessing the inter-annual variability of separation distances around odor sources to protect the residents from odor annoyance. J Environ Sci 79:11–24CrossRefGoogle Scholar
  4. Davis L (1967) Investments in loblolly pine clonal seed orchards: production costs and economic potential. J For 65:882–887Google Scholar
  5. Destaillats F, Cruz-Hernandez C, Giuffrida F, Dionisi F (2010) Identification of the botanical origin of pine nuts found in food products by gas-liquid chromatography analysis of fatty acid profile. J Agric Food Chem 58:2082–2087CrossRefGoogle Scholar
  6. Dyjakon A (2019) The influence of apple orchard management on energy performance and pruned biomass harvesting for energetic applications. Energies 12:632CrossRefGoogle Scholar
  7. Feng FJ, Sui X, Chen MM, Zhao D, Han HJ, Li MH (2010) Mode of pollen spread in clonal seed orchard of Pinus koraiensis. J Biophys Chem 1:33CrossRefGoogle Scholar
  8. Field A (2013) Discovering statistics using IBM SPSS statistics. Sage Publication Ltd 1, Oliver’s YardGoogle Scholar
  9. Gonçalves E, Graça A, Martins A (2019) Grapevine clonal selection in Portugal: a different approach. BIO Web Conf.  https://doi.org/10.1051/bioconf/20191201003 CrossRefGoogle Scholar
  10. Guerra F, Richards J, Fiehn O, Famula R, Stanton B, Shuren R, Sykes R, Davis M, Neale D (2016) Analysis of the genetic variation in growth, ecophysiology, and chemical and metabolic composition of wood of Populus trichocarpa provenances. Tree Genet Genomes 12(1):6–24CrossRefGoogle Scholar
  11. Hammer Y, Harper D (2001) PAST: paleontological statistics software package for education and data analysis. Palaeontologia Electron 4(1):1–9Google Scholar
  12. Hietz P, Rosner S, Hietz S, Wright S (2017) Wood traits related to size and life history of trees in a Panamanian rainforest. New Phytol 213:170–180CrossRefGoogle Scholar
  13. Ivković M, Wu H, Kumar S (2010) Bio-economic modelling as a method for determining economic weights for optimal multiple-trait tree selection. Silvae Genet 59:77–90CrossRefGoogle Scholar
  14. Jiang GY, Jiang LP, Song SL, Wang JY, Wang Q, Wang LF, Zhang P, Zhao XY (2018) Genetic variance analysis and excellent fruit-timber families selection of half-sib Pinus koraiensis. Bull Bot Res 38(5):775–784 in Chinese with English abstract Google Scholar
  15. Jiang LP, Wang JY, Zhang P, Liang DY, Zhang QH, Wang BY, Pei XN, Zhao XY (2019) Variation and selection of growth and fruit traits among 170 Pinus koraiensis Clones. For Res 32(1):58–64Google Scholar
  16. Li CZ, Löfgren KG (2000) A theory of red pine (Pinus koraiensis) management for both timber and commercial seeds. For Sci 46:284–290Google Scholar
  17. Li Y, Suontama M, Burdon RD, Dungey HS (2017) Genotype by environment interactions in forest tree breeding: review of methodology and perspectives on research and application. Tree Genet Genomes 13:60.  https://doi.org/10.1007/s11295-017-1144-x CrossRefGoogle Scholar
  18. Liang DY, Wang BY, Song SL, Wang JY, Wang LF, Wang Q, Ren XB, Zhao XY (2019) Analysis of genetic effects on a complete diallel cross test of Pinus koraiensis. Euphytica.  https://doi.org/10.1007/s10681-019-2414-5 CrossRefGoogle Scholar
  19. Man BX, Zhang L, Sun JZ, Yuan HS, Sun JJ, Wang XY, Sun YB, Qiu L, Wang YL (2012) Wang, YZ (2012) On plant growth regulator accelerate seed setting earlier of Pinus koraiensis. J Beihua Univ (Nat Sci) 13(3):329–334Google Scholar
  20. Matziris D (1998) Genetic variation in cone and seed characteristics in a clonal seed orchard of Aleppo pine grown in Greece. Silvae Genet 47:37–41Google Scholar
  21. Miyaki M (1987) Seed dispersal of the Korean pine, Pinus koraiensis, by the red squirrel, Sciurus vulgaris. Ecol Res 2:147–157CrossRefGoogle Scholar
  22. Mutke S, Gordo J, Gil L (2005) Cone yield characterization of a stone pine (Pinus pinea L.) clone bank. Silvae Genet 54:189–197CrossRefGoogle Scholar
  23. Nardo M, Saisana M, Saltelli A, Tarantola S (2005) Tools for composite indicators building. Eur Comission, Ispra 15:19–20Google Scholar
  24. Pan YY, Pei XN, Wang FW, Wang CL, Shao LL, Dong LH, Zhao XY, Qu GZ (2019) Forward, backward selection and variation analysis of growth traits in half-sib Larix kaempferi families. Silvae Genet 68:1–8CrossRefGoogle Scholar
  25. Pollak E, Van der Werf J, Quaas R (1984) Selection bias and multiple trait evaluation. J Dairy Sci 67:1590–1595CrossRefGoogle Scholar
  26. Rawat K, Bakshi M (2011) Provenance variation in cone, seed and seedling characteristics in natural populations of Pinus wallichiana A. B. Jacks (blue pine) in India. Ann For Res 54:39–55Google Scholar
  27. Ren X, He H, Zhang L, Li F, Liu M, Yu G, Zhang J (2018) Modeling and uncertainty analysis of carbon and water fluxes in a broad-leaved Korean pine mixed forest based on model-data fusion. Ecol Model 379:39–53CrossRefGoogle Scholar
  28. Rosengarten J (2004) The book of edible nuts. Courier Corporation, Dover Publications Inc., p 375Google Scholar
  29. Roy SM, Thapliyal R, Phartyal S (2004) Seed source variation in cone, seed and seedling characteristic across the natural distribution of Himalayan low level pine Pinus roxburghii Sarg. Silvae Genet 53:116–123CrossRefGoogle Scholar
  30. Salvatore R, Moya D, Pulido L, Lovreglio R, LópezSerrano F, De Las HJ, Leone V (2010) Morphological and anatomical differences in Aleppo pine seeds from serotinous and non-serotinous cones. New For 39:329–341CrossRefGoogle Scholar
  31. Sevik H, Topacoglu O (2015) Variation and inheritance pattern in cone and seed characteristics of Scots pine (Pinus sylvestris L.) for evaluation of genetic diversity. J Environ Biol 36:1125–1130PubMedGoogle Scholar
  32. Singh N (1992) Propagation, selection and establishment of clonal seed orchard of chilgoza pine (Pinus gerardiana Wall.). Indian For 118:901–908Google Scholar
  33. Sivacioglu A (2010) Genetic variation in seed cone characteristics in a clonal seed orchard of Scots pine (Pinus sylvestris L.) grown in Kastamonu-Turkey. Rom Biotechnol Lett 15:5695–5701Google Scholar
  34. Sivacioglu A, Ayan S (2008) Evaluation of seed production of Scots pine (Pinus sylvestris L.) clonal seed orchard with cone analysis method. Afr J Biotechnol 7(24):4393–4399Google Scholar
  35. Turna I (2004) Variation of morphological characters of oriental spruce (Picea orientalis) in Turkey. Biologia-Bratislava 59:519–526Google Scholar
  36. Wang H, Hong J (2004) Genetic resources, tree improvement and gene conservation of five-needle pines in East Asia. USDA Forest Service Proceedings RMRS-P 32: 73–78Google Scholar
  37. Wang F, Zhang QH, Tian YG, Yang SC, Wang HW, Wang LK, Li YL, Zhang P, Zhao XY (2018) Comprehensive assessment of growth traits and wood properties in half-sib Pinus koraiensis families. Euphytica.  https://doi.org/10.1007/s10681-018-2290-4 CrossRefGoogle Scholar
  38. Xia H, Zhao GH, Zhang LS, Sun XY, Yin SP, Liang DY, Li Y, Zheng M, Zhao XY (2016) Genetic and variation analyses of growth traits of half-sib Larix olgensis families in northeastern China. Euphytica 212:387–397CrossRefGoogle Scholar
  39. Xiao Y, Ma WJ, Lu N, Wang Z, Wang N, Zhai WJ, Kong LS, Qu GZ, Wang QX, Wang JH (2019) Genetic variation of growth traits and genotype-by-environment interactions in clones of Catalpa bungei and Catalpa fargesii f. duclouxii. Forests 10:57.  https://doi.org/10.3390/f10010057 CrossRefGoogle Scholar
  40. Xu ZW, Yu GR, He NP, Wang QF, Wang SZ, Xu XF, Wang RL, Zhao N (2018) Biogeographical patterns of soil microbial community as influenced by soil characteristics and climate across Chinese forest biomes. Appl Soil Ecol 124:298–305CrossRefGoogle Scholar
  41. Yin SP, Xiao ZH, Zhao GH, Zhao X, Sun XY, Zhang Y, Wang FW, Li SC, Zhao XY, Qu GZ (2017) Variation analyses of growth and wood properties of Larix olgensis clones in China. J For Res 28(4):687–697CrossRefGoogle Scholar
  42. Yuan HW, Niu SH, Zhou XQ, Du QP, Li Y, Li W (2016) Evaluation of seed production in a first-generation seed orchard of Chinese pine (Pinus tabuliformis). J For Res 27:1003–1008CrossRefGoogle Scholar
  43. Zhang Z, Zhang HG, Zhou Y, Liu L, Yu HY, Wang X, Feng WJ (2015) Variation of seed characters in Korean pine (Pinus koraiensis) multi-clonal populations. J Beijing For Univ 37:67–78Google Scholar
  44. Zhao XY, Xia H, Wang XW, Wang C, Liang DY, Li KL, Liu GF (2016) Variance and stability analyses of growth characters in half-sib Betula platyphylla families at three different sites in China. Euphytica 208:173–186CrossRefGoogle Scholar
  45. Zheng HQ, Hu DH, Wang RH, Wei RP, Yan S (2015) Assessing 62 Chinese Fir (Cunninghamia lanceolata) breeding parents in a 12-year grafted clone test. Forests 6:3799–3808CrossRefGoogle Scholar
  46. Zhu BA, Wang XP, Fang JY, Piao SL, Shen HH, Zhao SQ, Peng CH (2010) Altitudinal changes in carbon storage of temperate forests on Mt Changbai, Northeast China. J Plant Res 123:439–452CrossRefGoogle Scholar

Copyright information

© Northeast Forestry University 2020

Authors and Affiliations

  • David Kombi Kaviriri
    • 1
    • 3
    • 4
  • Yuxi Li
    • 1
  • Dawei Zhang
    • 1
  • Hongtao Li
    • 2
  • Zuoyi Fan
    • 2
  • Jingyuan Wang
    • 2
  • Lianfu Wang
    • 2
  • Qi Wang
    • 2
  • Deqiu Wang
    • 2
  • Vincent L. Chiang
    • 1
  • Xiyang Zhao
    • 1
    Email author
  1. 1.State Key Laboratory of Tree Genetics and BreedingNortheast Forestry UniversityHarbinPeople’s Republic of China
  2. 2.Forest Cultivation CenterLinjiang Forestry Bureau of JilinLinjiangPeople’s Republic of China
  3. 3.Department of Natural Resources Management, Faculty of Agricultural SciencesUniversity of KinshasaKinshasaDemocratic Republic of Congo
  4. 4.Department of Forestry, Faculty of Agricultural SciencesSemuliki Official UniversityBeniDemocratic Republic of Congo

Personalised recommendations