GGE biplot-based genetic selection to guide interspecific crossing in <i>Corymbia</i> spp.

Ferreira, Filipe Manoel; Rocha, João Romero do Amaral Santos de Carvalho; Alves, Rodrigo Silva; Malikouski, Renan Garcia; Peixoto, Marco Antônio; Oliveira, Suellen Sales de; Aguiar, Aurélio Mendes; Bhering, Leonardo Lopes

doi:10.1590/1678-4499.20210195

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Article • Bragantia 80 • 2021 • https://doi.org/10.1590/1678-4499.20210195 copy

GGE biplot-based genetic selection to guide interspecific crossing in Corymbia spp.

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

Tree breeders are prioritizing the increase of the interspecific diversity in the breeding programs due to the pronounced environmental changes, and expansion of the forest frontier to less productive areas. In this scenario, there is a growing interest for species of the genus Corymbia due to their good growth, resistance to biotic and abiotic factors, and industrial properties. Also, Corymbia spp. can cross with each other, generating interspecific hybrids. However, there are great difficulties on defining the best crosses. Thus, the objectives of this study were to evaluate the genetic variability of 64 progenies of Corymbia maculata and 64 progenies of Corymbia torelliana and to use the GGE biplot method to point the most appropriated crosses to broad and specific environments in order to generate stable and productive interspecific hybrids of C. maculata and C. torelliana. The GGE biplot was an efficient method for evaluating the genetic variability between progenies, for visualizing the genotype by environment interaction pattern and for identifying the best crosses in order to generate interspecific hybrids of the species. By adopting a selection intensity of 10%, the recommended progenies to generate interspecific hybrids for the Aracruz municipality (ARA) were 10, 40, 49, 64, 20, 9 and 47 of C. maculata and 24, 56, 41, 64, 43, 31 and 12 of C. torelliana. For Três Lagoas municipality (TLA), the recommended progenies were 11, 17, 1, 48, 7, 63 and 21 of C. maculata and 42, 46, 61, 44, 10, 63 and 28 of C. torelliana.

Key words
Corymbia hybrids; genotypes; environment interaction; heterosis; genetic selection

	Individual analyses				Joint analysis
	C. maculata		C. torelliana		C. maculata	C. torelliana
	ARA	TLA	ARA	TLA	C. maculata	C. torelliana
CM	6411.36	7187.23	4166.04	6303.27	13598.22	10760.55
RM _g	6848.50	7374.71	4639.25	6426.92	13610.99	10766.99
RM _b	6411.36	7187.35	4166.38	6303.83	13598.39	10761.58
RM _gxe					13744.68	10834.19
LRT _g	437.14 ^* * Significant at 5% probability level according to the Chi-square distribution. ARA is the Aracruz municipality and TLA is the Três Lagoas municipality. CM is the complete model, RMg is the reduced model without the additive genetic effect, RMb is the reduced model without the block effect, RMgxe is the reduced model without GEI effect, and LRTg, LRTb and LRTgxe are their respective likelihood ratio test.	187.48 ^* * Significant at 5% probability level according to the Chi-square distribution. ARA is the Aracruz municipality and TLA is the Três Lagoas municipality. CM is the complete model, RMg is the reduced model without the additive genetic effect, RMb is the reduced model without the block effect, RMgxe is the reduced model without GEI effect, and LRTg, LRTb and LRTgxe are their respective likelihood ratio test.	473.21 ^* * Significant at 5% probability level according to the Chi-square distribution. ARA is the Aracruz municipality and TLA is the Três Lagoas municipality. CM is the complete model, RMg is the reduced model without the additive genetic effect, RMb is the reduced model without the block effect, RMgxe is the reduced model without GEI effect, and LRTg, LRTb and LRTgxe are their respective likelihood ratio test.	123.65 ^* * Significant at 5% probability level according to the Chi-square distribution. ARA is the Aracruz municipality and TLA is the Três Lagoas municipality. CM is the complete model, RMg is the reduced model without the additive genetic effect, RMb is the reduced model without the block effect, RMgxe is the reduced model without GEI effect, and LRTg, LRTb and LRTgxe are their respective likelihood ratio test.	12.77 ^* * Significant at 5% probability level according to the Chi-square distribution. ARA is the Aracruz municipality and TLA is the Três Lagoas municipality. CM is the complete model, RMg is the reduced model without the additive genetic effect, RMb is the reduced model without the block effect, RMgxe is the reduced model without GEI effect, and LRTg, LRTb and LRTgxe are their respective likelihood ratio test.	6.44 ^* * Significant at 5% probability level according to the Chi-square distribution. ARA is the Aracruz municipality and TLA is the Três Lagoas municipality. CM is the complete model, RMg is the reduced model without the additive genetic effect, RMb is the reduced model without the block effect, RMgxe is the reduced model without GEI effect, and LRTg, LRTb and LRTgxe are their respective likelihood ratio test.
LRT _b	0	0.12	0.34	0.56	0.17	1.03
LRT _gxe					146.46 ^* * Significant at 5% probability level according to the Chi-square distribution. ARA is the Aracruz municipality and TLA is the Três Lagoas municipality. CM is the complete model, RMg is the reduced model without the additive genetic effect, RMb is the reduced model without the block effect, RMgxe is the reduced model without GEI effect, and LRTg, LRTb and LRTgxe are their respective likelihood ratio test.	73.64 ^* * Significant at 5% probability level according to the Chi-square distribution. ARA is the Aracruz municipality and TLA is the Três Lagoas municipality. CM is the complete model, RMg is the reduced model without the additive genetic effect, RMb is the reduced model without the block effect, RMgxe is the reduced model without GEI effect, and LRTg, LRTb and LRTgxe are their respective likelihood ratio test.

Components/Parameters	C. maculata	C. torelliana
$σ_{a}^{2}$	4.22	1.11
$σ_{b}^{2}$	0.04	0.02
$σ_{gxe}^{2}$	1.11	0.23
$σ_{e}^{2}$	6.07	1.86
$σ_{phen}^{2}$	11.44	3.21
$h_{a b}^{2}$	0.37	0.34
$c_{b}^{2}$	0.00	0.01
$c_{gxe}^{2}$	0.10	0.07
$r_{ge}$	0.47	0.55
CV_g (%)	15.55	9.82
CV_e (%)	18.67	12.73
$r_{\hat{g} g}$	0.76	0.79
μ	13.20	10.71

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[1] Section Editor: Carlos Alberto Scapim