Unraveling trait relationships for the selection of drought-tolerant wheat genotypes

Ribeiro, João Paulo Oliveira; Silva, Caique Machado e; Sousa, João Marcos Amario de; Freitas, Davi Soares de; Mezzomo, Henrique Caletti; Vasconcelos, Aline de Almeida; Nardino, Maicon

doi:10.1590/0103-8478cr20230624

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BIOLOGY • Cienc. Rural 55 (2) • 2025 • https://doi.org/10.1590/0103-8478cr20230624 copy

Unraveling trait relationships for the selection of drought-tolerant wheat genotypes

Desvendando as relações de caracteres para a seleção de genótipos de trigo tolerantes a seca

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT:

The study of genotypic relationships between drought tolerance indices and agronomic traits of interest in wheat breeding is useful for designing selection strategies. The objective of this research was to investigate the cause-and-effect relationships between agronomic traits and drought tolerance indices through the analysis of canonical correlations. Two trials (control and stress) were conducted in winter 2020 in Viçosa, MG, Brazil. The traits evaluated were: (days for heading, plant height, mass and number of grains per spike, mass of one hundred grains, and grain yield). Grain yield data from the control and stress conditions were used to construct five drought tolerance indices. The data were subjected to mixed model analysis for estimation of genetic parameters and prediction of genotypic values (REML/BLUP), and then the genotypic values were used to calculate the correlation coefficients between the traits. Two groups of traits were established for the study of canonical correlations, the first group consisting of agronomic traits and the second by drought tolerance indices. There was a significant genotype effect for all evaluated traits. The canonical pairs were significant, which indicated the existence of dependence between the groups. Days to heading trait can be used in the indirect selection of wheat genotypes for drought tolerance.

Key words:
Triticum aestivum L.; mixed model; drought stress tolerance; tropical wheat breeding; genetics parameters.

Universidade Federal de Santa Maria Universidade Federal de Santa Maria, Centro de Ciências Rurais , 97105-900 Santa Maria RS Brazil , Tel.: +55 55 3220-8698 , Fax: +55 55 3220-8695 - Santa Maria - RS - Brazil
E-mail: cienciarural@mail.ufsm.br

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[1] E-mail: nardino@ufv.br. ^*Corresponding author

Drought tolerance index	Code	Equation	Reference
Stress tolerance index	STI	$\frac{Y_{S} * Y_{C}}{{(Y_{C})}^{2}}$	FERNANDEZ (1992FERNANDEZ, G. J. Effective selection criteria for assessing plant stress tolerance. In: Proceedings of the International Symposium on Adaptation of Vegetables and other Food Crops in Temperature and Water Stress. Shanhua, Taiwan, p 257-270, 1992.)
Yield index	YI	$\frac{Y_{S}}{{\overset{̅}{Y}}_{S}}$	GAVUZZI et al. (1997GAVUZZI, P. et al. Evaluation of field and laboratory predictors of drought and heat tolerance in winter cereals. Canadian Journal Plant Science, v.77, p.523-531, 1997. Available from: <Available from: https://cdnsciencepub.com/doi/10.4141/P96-130 >. Accessed: Nov. 20, 2023. doi: 10.4141/P96-130. https://cdnsciencepub.com/doi/10.4141/P9... )
Geometric mean productivity	GMP	$\sqrt{Y_{S} * Y_{C}}$	KRISTIN et al. (1997)
Mean productivity	MP	$\frac{Y_{S} * Y_{C}}{2}$	ROSIELLE & HAMBLING (1981ROSIELLE, A. A.; HAMBLIN, J. Theoretical Aspects of Selection for Yield in Stress and Non-Stress Environment. Crop Science, v.21, p.943-946, 1981. Available from: <Available from: https://acsess.onlinelibrary.wiley.com/doi/10.2135/cropsci1981.0011183X002100060033x >. Accessed: Nov. 20, 2023. doi: 10.2135/cropsci1981.0011183X002100060033x. https://acsess.onlinelibrary.wiley.com/d... )
Harmonic mean	MH	$\frac{2 (Y_{C} - Y_{S})}{Y_{C} + Y_{S}}$	JAFARI et al. (2009JAFARI, A. et al. Evaluation of selection indices for Drought Tolerance of corn (Zea mays L.) hybrids. International Journal Plant Production, v.3, p.33-38, 2009. Available from: <Available from: https://ijpp.gau.ac.ir/article_661.html >. Accessed: Nov. 20, 2023. doi: 10.22069/IJPP.2012.661. https://ijpp.gau.ac.ir/article_661.html... )

Parameters	DH	PH	GMS	NGS	HGM	GY
-----------------------------------------------------------------------------Control-------------------------------------------------------------------------------
${\hat{σ}}_{g}^{2}$	4.20	13.54	0.05	8.36	0.12	193721.05
${\hat{σ}}_{e}^{2}$	2.39	18.11	0.07	23.54	0.19	342299.86
${\hat{σ}}_{f}^{2}$	6.59	31.65	0.12	31.89	0.31	536020.91
${\hat{h}}^{2}$	0.84	0.69	0.70	0.52	0.66	0.63
$\hat{h}$	0.92	0.83	0.84	0.72	0.81	0.79
CV _g	3.53	4.13	9.16	4.81	8.99	10.55
CV _e	2.66	4.78	10.34	8.08	11.19	14.02
CV _g /CV _e	1.32	0.86	0.89	0.60	0.80	0.75
-------------------------------------------------------------------------------Stress-------------------------------------------------------------------------------
${\hat{σ}}_{g}^{2}$	3.75	12.10	0.07	16.80	0.23	131836.48
${\hat{σ}}_{e}^{2}$	1.20	16.04	0.03	16.47	0.13	203932.51
${\hat{σ}}_{f}^{2}$	4.95	28.14	0.10	33.27	0.35	335768.99
${\hat{h}}^{2}$	0.90	0.69	0.87	0.75	0.84	0.66
$\hat{h}$	0.95	0.83	0.93	0.87	0.92	0.81
CV _g	3.41	4.14	12.03	7.75	12.60	9.90
CV _e	1.93	4.76	8.07	7.67	9.52	12.31
CV _g /CV _e	1.76	0.87	1.49	1.01	1.32	0.80
-------------------------------------------------------------------------------Indexes-----------------------------------------------------------------------------
	GMP	MP	MH	STI		YI
${\hat{σ}}_{g}^{2}$	169243.75	168353.96	170138.80	0.03		0.01
${\hat{σ}}_{e}^{2}$	134501.52	137723.11	132421.26	0.03		0.02
${\hat{σ}}_{f}^{2}$	303745.27	306077.07	302560.06	0.06		0.02
${\hat{h}}^{2}$	0.79	0.79	0.79	0.78		0.65
$\hat{h}$	0.89	0.89	0.89	0.88		0.80
CV _g	10.56	10.47	10.65	20.57		9.68
CV _e	9.41	9.47	9.40	19.14		12.39
CV _g /CV _e	1.12	1.11	1.13	1.07		0.78

Traits	---------------------------------------------------------Canonical pairs-----------------------------------------------------------
	1st	2nd	3rd	4th	5th
-----------------------------------------------------------------------------Group I-------------------------------------------------------------------------------
GMP	0.93	0.00	-0.05	0.00	-0.03
MP	0.94	0.01	-0.05	0.00	-0.03
HM	0.92	-0.01	-0.05	0.01	-0.03
STI	0.92	0.01	-0.02	0.00	-0.03
YI	0.73	0.02	-0.12	0.03	-0.06
-----------------------------------------------------------------------------Group II------------------------------------------------------------------------------
DHc	-0.50	0.62	-0.05	-0.45	0.12
PHc	0.12	0.56	0.09	0.47	0.16
GMSc	0.30	-0.22	-0.58	0.65	-0.31
NGSc	-0.16	-0.28	-0.33	0.73	0.32
HGMc	0.40	-0.19	-0.74	-0.02	-0.29
GYc	0.99	0.01	0.02	0.03	0.03
r¹	0.98	0.58	0.35	0.28	0.11
-----------------------------------------------------------------------------Group III-----------------------------------------------------------------------------
GMP	0.90	0.16	-0.05	0.09	0.00
MP	0.89	0.17	-0.04	0.10	0.00
HM	0.91	0.15	-0.05	0.09	0.00
STI	0.90	0.15	-0.02	0.10	0.00
YI	1.00	0.00	0.00	0.00	0.00
-----------------------------------------------------------------------------Group IV-----------------------------------------------------------------------------
DHs	-0.34	-0.67	0.24	-0.32	0.47
PHs	0.27	-0.71	-0.33	0.49	-0.27
GMSs	0.24	0.35	-0.81	0.20	0.08
NGSs	-0.18	-0.05	-0.69	-0.27	-0.31
HGMs	0.31	0.55	0.06	0.50	0.44
GYs	1.00	-0.01	-0.01	0.02	0.02
r¹	0.99	0.60	0.46	0.30	0.20