Seleção de genótipos de aveia-branca para condições contrastantes de manejo de fungicida

Berlezi, Júlio Daronco; Carvalho, Ivan Ricardo; Silva, José Antonio Gonzalez da; Loro, Murilo Vieira; Sfalcin, Inaê Carolina; Pradebon, Leonardo Cesar; Port, Eduarda Donadel; Ourique, Rafael Soares; Roza, João Pedro Dalla

Júlio Daronco Berlezi

Universidade Regional do Noroeste do Rio Grande do Sul, Departamento de Estudos Agrários, Avenida do Comércio, n^o 3.000, Bairro Universitário, CEP 98700-000 Ijuí, RS, Brazil

http://orcid.org/0000-0003-4008-9815

Ivan Ricardo Carvalho Corresponding author

Universidade Regional do Noroeste do Rio Grande do Sul, Departamento de Estudos Agrários, Avenida do Comércio, n^o 3.000, Bairro Universitário, CEP 98700-000 Ijuí, RS, Brazil

http://orcid.org/0000-0001-7947-4900

José Antonio Gonzalez da Silva

Universidade Regional do Noroeste do Rio Grande do Sul, Departamento de Estudos Agrários, Avenida do Comércio, n^o 3.000, Bairro Universitário, CEP 98700-000 Ijuí, RS, Brazil

http://orcid.org/0000-0002-9335-2421

Murilo Vieira Loro

Universidade Federal de Santa Maria, Centro de Ciência Rurais, Departamento de Fitotecnia, Avenida Roraima, Cidade Universitária, Camobi, Prédio 77, CEP 97105-900 Santa Maria, RS, Brazil

http://orcid.org/0000-0003-0241-4226

Inaê Carolina Sfalcin

Universidade Regional do Noroeste do Rio Grande do Sul, Departamento de Estudos Agrários, Avenida do Comércio, n^o 3.000, Bairro Universitário, CEP 98700-000 Ijuí, RS, Brazil

http://orcid.org/0000-0002-7800-5392

Leonardo Cesar Pradebon

Universidade Regional do Noroeste do Rio Grande do Sul, Departamento de Estudos Agrários, Avenida do Comércio, n^o 3.000, Bairro Universitário, CEP 98700-000 Ijuí, RS, Brazil

http://orcid.org/0000-0001-7827-6312

Eduarda Donadel Port

Universidade Regional do Noroeste do Rio Grande do Sul, Departamento de Estudos Agrários, Avenida do Comércio, n^o 3.000, Bairro Universitário, CEP 98700-000 Ijuí, RS, Brazil

http://orcid.org/0000-0001-8504-4624

Rafael Soares Ourique

Universidade Regional do Noroeste do Rio Grande do Sul, Departamento de Estudos Agrários, Avenida do Comércio, n^o 3.000, Bairro Universitário, CEP 98700-000 Ijuí, RS, Brazil

http://orcid.org/0000-0002-2090-9014

João Pedro Dalla Roza

Universidade Regional do Noroeste do Rio Grande do Sul, Departamento de Estudos Agrários, Avenida do Comércio, n^o 3.000, Bairro Universitário, CEP 98700-000 Ijuí, RS, Brazil

http://orcid.org/0000-0001-6902-0454

Corresponding author

Figuras (4)
Tabelas (3)

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Figure 1
GGE biplot for thousand grain weight (TGW, g), hectoliter weight (HW, g 250 cm^-3) and grain yield (GY, kg ha^-1) of white oat (Avena sativa) in crops without and with the use of tebuconazole fungicide in 10 years of cultivation (2008 to 2017), performed in the municipality of Augusto Pestana, RS, Brazil, in relation to: TGW in management without fungicide (A); HW in management without fungicide (B); GY in management without fungicide (C); TGW in management with fungicide (D); HW in management with fungicide (E); and GY in management with fungicide (F). Biplot based on singular data decomposition standardized by genotypes. Environment: 2008 (A), 2009 (B), 2010 (C), 2011 (D), 2012 (E), 2013 (F), 2014 (G), 2015 (H), 2016 (I), 2017 (J). The name of the 26 genotypes (cultivars) is described in the material and methods

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Figure 2
Multitrait selection of white oat (Avena sativa) genotypes by MGIDI (A) and visualization of strengths and weaknesses of genotypes (B) in management without tebuconazole fungicide in 10 years of cultivation (2008 to 2017) and multitrait selection of white oat genotypes by MGIDI (C) and visualization of the strengths and weaknesses of the genotypes (D) in the management with tebuconazole in 10 years of cultivation (2008 to 2017) - performed in the municipality of Augusto Pestana, RS, Brazil.Genotypes: Barbarasul (1), Brisasul (2), Carlasul (3), Chiarasul (4), Dilmasul (5), Fapa 4 (6), Guapa (7), IAC 7 (8), Afrodite (9), Louise (10), UPF 18 (11), Temprama (12), Gaudéria (13), Ouro (14), URS 21 (15), Charrua (16), Corona (17), Estampa (18), Fapa Slava (G19), Guará (20), Guria (21), Penca (22), Tarimba (23), Taura (24), Torena (25), URS 22 (26).

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Figure 3
Pearson’s linear correlation estimates between disease incidence variables, meteorological, phenological, morphological and productive variables of 26 white oat (Avena sativa) genotypes cultivated without and with the use of tebuconazole fungicide in 10 years of cultivation (2008 to 2017) - performed in the municipality of Augusto Pestana, in the state of Rio Grande do Sul, Brazil. Pearson’s linear correlation coefficient (n = 1,560) significant at 5% probability by the T test; SR (%), stem rust; LR (%), leaf rust; LS (%), leaf spot; Tmax (°C), maximum temperature; Rad (MJ m^-2 per day), solar radiation; Tmed (°C), medium temperature; Tmin (°C), minimum temperature; TGW (g), thousand grain weight; DFM, days from flowering to maturation; DEF, days from emergence to flowering; DEM, days from emergence to maturation; GY (kg ha^-1), grain yield; HW (g 250 cm^-3), hectoliter weight; Prec (mm), precipitation; RH (%), relative humidity air; PA (cm), plant architecture; LOG (%), lodging.

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Figure 4
Regression tree for the dependent variable grain yield of white oat (Avena sativa) in environments with and without the use of tebuconazole fungicide in 10 years of cultivation (2008 to 2017). Branches indicate the independent variables leaf rust (LR, %), stem rust (SR, %), plant architecture (PA, cm), days from emergence to maturation (DEM), relative air humidity (RH, %), thousand grain weight (TGW, g), radiation (Rad, MJ m^-2 per day), leaf spot (LS, %) and lodging (LOD, %) - performed in the municipality of Augusto Pestana, RS, Brazil.

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Table 1
Analysis of variance (ANOVA) for thousand grain weight (TGW, g), hectoliter weight (HW, g 250 cm^-3), and grain yield (GY, kg ha^-1) of white oat (Avena sativa) in systems without and with the use of tebuconazole fungicide in 10 years of cultivation (2008 to 2017), performed in the municipality of Augusto Pestana, RS, Brazil⁽¹⁾.

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Table 2
Estimates of variance components and genetic parameters by restricted maximum likelihood (REML) for the variables analyzed in white oats (Avena sativa) in cultivation without and with the use of tebuconazole fungicide in 10 years of cultivation (2008 to 2017), in the municipality of Augusto Pestana, RS, Brazil⁽¹⁾.

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Table 3
Genetic gain predicted by multitrait genotype-ideotype distance index (MGIDI) analysis in white oat (Avena sativa) traits in crops with and without the use of tebuconazole fungicide in 10 years of cultivation (2008 to 2017), in the municipality of Augusto Pestana, RS, Brazil⁽¹⁾.

Source of variation	DF	Mean square
Source of variation	DF	TGW	HW	GY
		With tebuconazole
Env	9	406.09^*	1,423.70^*	24,883,039.90^*
Rep (Env)	20	8.59^*	8.31^*	403,184.78^*
Gen	25	110.01^*	100.86^*	3,244,286.03^*
Gen x Env	225	23.45^*	29.79^*	547,455.44^*
Residue	500	4.89	3.91	79,041.48
Total	779
		Without tebuconazole
Env	9	618.39^*	1,091.58^*	30,000,000.00^*
Rep (Env)	20	5.97	7.62^*	318,296.00^*
Gen	25	112.05^*	50.16^*	3,919,224.00^*
Gen x Env	225	15.21^*	13.70^*	348,222.00^*
Residue	500	4.05	3.60	101,105.00^*
Total	779

Parameter	LOD	LR	SR	LS	GY	TGW	HW
	Without tebuconazole
Gen_var	52.418	80.095	14.349	19.690	90,719.876	3.159	2.405
Gen (%)	7.521	12.645	12.416	10.528	14.794	17.146	7.733
Res_var	644.558	553.329	101.224	167.345	522,519.983	15.263	28.699
Res (%)	92.479	87.355	87.584	89.472	85.206	82.854	92.267
Phen_var	696.976	633.423	115.573	187.036	613,239.859	18.422	31.104
H²	0.075	0.126	0.124	0.105	0.148	0.171	0.077
h²mg	0.196	0.303	0.298	0.261	0.342	0.383	0.201
Accuracy	0.443	0.550	0.546	0.511	0.585	0.619	0.448
CVg (%)	9.534	19.977	23.326	14.642	16.141	6.572	3.602
CVr (%)	33.432	52.507	61.953	42.686	38.737	14.447	12.444
CV ratio	0.285	0.380	0.377	0.343	0.417	0.455	0.289
	With tebuconazole
Gen_var	118.632	14.021	2.858	5.577	112,282.900	3.244	1.017
Gen (%)	13.798	4.721	10.714	7.216	17.150	18.007	4.906
Res_var	741.119	282.986	23.818	71.715	542,431.449	14.771	19.703
Res (%)	86.202	95.279	89.286	92.784	82.850	81.993	95.094
Phen_var	859.751	297.007	26.676	77.292	654,714.349	18.015	20.719
H²	0.138	0.047	0.107	0.072	0.171	0.180	0.049
h²mg	0.324	0.129	0.265	0.189	0.383	0.397	0.134
Accuracy	0.570	0.360	0.514	0.435	0.619	0.630	0.366
CVg (%)	20.120	19.337	25.218	15.822	11.536	5.772	2.087
CVr (%)	50.290	86.874	72.799	56.735	25.356	12.316	9.186
CV ratio	0.400	0.223	0.346	0.279	0.455	0.469	0.227

Traits	Factor	Xo	Xs	SD	Sdperc	H²	SG	Sgperc	Sense	Goal
		Without tebuconazole
LR (%)	FA 1	44.8	38.1	-6.68	-14.9	0.303	-2.02	-4.52	Reduce	100
SR (%)	FA 1	16.2	12.2	-4.05	-25	0.298	-1.21	-7.45	Reduce	100
LS (%)	FA 1	30.3	24.8	-5.52	-18.2	0.261	-1.44	-4.75	Reduce	100
GY (kg ha^-1)	FA 1	1,866	2,081	215	11.5	0.342	73.7	3.95	Increase	100
TGW (g)	FA 1	27	28.6	1.54	5.68	0.383	0.588	2.17	Increase	100
HW (g 250 cm^-3)	FA 1	43	43.6	0.583	1.35	0.201	0.117	0.272	Icrease	100
LOD (%)	FA 2	75.9	65	-10.9	-14.4	0.196	-2.14	-2.82	Reduce	100
		With tebuconazole
LR (%)	FA 1	19.4	16.3	-3.09	-16	0.129	-0.4	-2.07	Reduce	100
SR (%)	FA 1	6.7	5.89	-0.812	-12.1	0.265	-0.215	-3.21	Reduce	100
LS (%)	FA 1	14.9	12.2	-2.71	-18.1	0.189	0.512	-3.43	Reduce	100
GY (kg ha^-1)	FA 1	2,905	3,330	426	14.7	0.383	163	5.62	Increase	100
TGW (g)	FA 1	31.2	32.5	1.29	4.14	0.397	0.513	1.65	Increase	100
HW (g 250 cm^-3)	FA 1	48.3	49.3	0.991	2.05	0.134	0.133	0.275	Increase	100
LOD (%)	FA 2	54.1	46.3	-7.86	-14.5	0.324	-2.55	-4.71	Reduce	100

[1] Corresponding author

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Seleção de genótipos de aveia-branca para condições contrastantes de manejo de fungicida

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