Genotype by environment interaction analysis of growth of Picea koraiensis families at different sites using BLUP-GGE
This study investigated the growth (height, diameter at breast height and volume) of Picea koraiensis families at two sites and explored the genotype × environment interaction (GEI) of growth traits to provide a theoretical basis for the improvement of P. koraiensis families. Genetic variation analy...
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Veröffentlicht in: | New forests 2021, Vol.52 (1), p.113-127 |
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Sprache: | eng |
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Zusammenfassung: | This study investigated the growth (height, diameter at breast height and volume) of
Picea koraiensis
families at two sites and explored the genotype × environment interaction (GEI) of growth traits to provide a theoretical basis for the improvement of
P. koraiensis
families. Genetic variation analysis and genetic parameter estimation of growth traits were carried out using 52 families of three provenances, Muling (M), Jinshantun (J), Wuyiling (W), of
P. koraiensis
at Jiangshanjiao (JSJ) and Qingshan (QS) forest farms in Heilongjiang Province, China. The variance analysis of the multisite test and the type B correlation coefficient of growth traits between the two sites were less than 0.2, indicating that the growth traits of the family had extremely significant GEI, and the growth of families of provenances J and W (experienced colder conditions) at JSJ and QS was significantly better than that of provenance M (grew in relatively warm areas). The main drivers of GEI might be the annual average temperature and frost-free period. The families from provenances J and W that experienced colder conditions might have higher environmental adaptability and superior growth compared with families from provenance M. The family with the highest but unstable volume yield at JSJ and QS was M410 and W010, respectively. While, the top five families with high and stable yields were J085, J097, W037, W045 and J068 by stability analysis (BLUP-GGE) of joint-site. This study enhanced our understanding of the GEI of
P. koraiensis
families and benefits the selection of optimal families. |
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ISSN: | 0169-4286 1573-5095 |
DOI: | 10.1007/s11056-020-09785-3 |