O objetivo deste trabalho foi avaliar o desempenho produtivo, a adaptabilidade e a estabilidade de cultivares modernas de soja (Glycine max), em ensaios multiambientes, assim como identificar os genótipos ideais para oito ambientes de cultivo no Brasil. Utilizou-se um delineamento experimental de blocos ao acaso, com três repetições, para a avaliação de 46 cultivares em oito ambientes, nas microrregiões de adaptação 102, 201 e 202, na safra 2014/2015. Ocorreu interação genótipo x ambiente complexa, com alterações do ranqueamento de cultivares entre os locais. As cultivares NA 5909 RG, M6410IPRO, NS 5959 IPRO, NS6823RR, M5917IPRO, NS 6767 RR e 6563RSF IPRO apresentaram as maiores médias produtivas. As cultivares NA 5909 RG, NS6823RR, M6410IPRO e NS 5959 IPRO apresentaram elevada adaptabilidade e estabilidade e alta produtividade de grãos, nos ambientes avaliados, e posicionaram-se próximo do que seria considerado ideal para os ambientes analisados. Há cultivares modernas de soja adaptadas, estáveis e com elevada produtividade, para o cultivo nas microrregiões 102, 201 e 202 de adaptação da cultura da soja no Brasil.

Termos para indexação:
Glycine max; adaptabilidade e estabilidade; interação genótipo x ambiente; GGE biplot; modelos mistos

Autoria

Gilvani Matei

Universidade Tecnológica Federal do Paraná, Campus Pato Branco, Via do Conhecimento, Km 01, CEP 85503-390 Pato Branco, PR, Brazil. E-mail: GMatei@nidera.com.br, benin@utfpr.edu.br, leowoyann@gmail.com, samueldallo@hotmail.com, milioli.utfpr@gmail.com, dz_andrei@hotmail.comUniversidade Tecnológica Federal do ParanáBrazilPato Branco, PR, BrazilUniversidade Tecnológica Federal do Paraná, Campus Pato Branco, Via do Conhecimento, Km 01, CEP 85503-390 Pato Branco, PR, Brazil. E-mail: GMatei@nidera.com.br, benin@utfpr.edu.br, leowoyann@gmail.com, samueldallo@hotmail.com, milioli.utfpr@gmail.com, dz_andrei@hotmail.com

Giovani Benin

Leomar Guilherme Woyann

Samuel Cristian Dalló

Anderson Simionato Milioli

Andrei Daniel Zdziarski

SCIMAGO INSTITUTIONS RANKINGS

Figuras | Tabelas

Figuras (2)
Tabelas (5)

Thumbnail

Figure 1.
Mean and stability for the set of 46 soybean cultivars (A), and for the cultivar division in early (B), medium (C) and late cycles (D), evaluated in eight locations - seven of which in the state of Paraná (Cambé, Corbélia, Mamborê, Palotina, Realeza, São Jorge do Ivaí, and São Miguel do Iguaçu), and one in the state of São Paulo (Cândido Mota) -, in the 2014/2015 crop season. Cultivars: BMX Potência RR (1), DMario 58i (2), NK 7059 RR (3), A 6411RG (4), BMX Ativa RR (5), BMX Energia RR (6), NA 5909 RG (7), NS 4823 (8), BMX Turbo RR (9), NS 5858 (10), NS 6262 (11), SYN1059 RR (12), NS 6767 RR (13), TMG 7262RR (14), NS 4901 (15), NS 5258 (16), NS 5290 (17), NS 5401 RR (18), NS 6209 (19), NS6121RR (20), NS6823RR (21), M6210IPRO (22), M6410IPRO (23), 5958RSF IPRO (24), 6458RSF IPRO (25), 6563RSF IPRO (26), AS 3570IPRO (27), AS 3610IPRO (28), M5917IPRO (29), NS 5000 IPRO (30), NS 5106 IPRO (31), NS 5151 IPRO (32), NS 5445 IPRO (33), NS 5959 IPRO (34), NS 6909 IPRO (35), NS 7000 IPRO (36), NS 7209 IPRO (37), NS 7237 IPRO (38), NS 7300 IPRO (39), NS 7338 IPRO (40), NS 5727 IPRO (41), NS 6006 IPRO (42), NS6060IPRO (43), NS6700IPRO (44), NS6906IPRO (45), and TMG2158IPRO (46). PC, principal component.

Thumbnail

Figure 2.
Ideal genotype of the set of 46 soybean cultivars (A), and for the cultivar divisions in early (B), medium (C) and late cycles (D), evaluated in eight locations - seven of which in the state of Paraná (Cambé, Corbélia, Mamborê, Palotina, Realeza, São Jorge do Ivaí, and São Miguel do Iguaçu), and one in the state of São Paulo (Cândido Mota) -, in the 2014/2015 crop season. Cultivars: BMX Potência RR (1), DMario 58i (2), NK 7059 RR (3), A 6411RG (4), BMX Ativa RR (5), BMX Energia RR (6), NA 5909 RG (7), NS 4823 (8), BMX Turbo RR (9), NS 5858 (10), NS 6262 (11), SYN1059 RR (12), NS 6767 RR (13), TMG 7262RR (14), NS 4901 (15), NS 5258 (16), NS 5290 (17), NS 5401 RR (18), NS 6209 (19), NS6121RR (20), NS6823RR (21), M6210IPRO (22), M6410IPRO (23), 5958RSF IPRO (24), 6458RSF IPRO (25), 6563RSF IPRO (26), AS 3570IPRO (27), AS 3610IPRO (28), M5917IPRO (29), NS 5000 IPRO (30), NS 5106 IPRO (31), NS 5151 IPRO (32), NS 5445 IPRO (33), NS 5959 IPRO (34), NS 6909 IPRO (35), NS 7000 IPRO (36), NS 7209 IPRO (37), NS 7237 IPRO (38), NS 7300 IPRO (39), NS 7338 IPRO (40), NS 5727 IPRO (41), NS 6006 IPRO (42), NS6060IPRO (43), NS6700IPRO (44), NS6906IPRO (45), and TMG2158IPRO (46). PC, principal component.

Thumbnail

Table 1
Description of 46 soybean cultivars, maturity group, cycle, year of release, technology and releaser.

Thumbnail

Table 2
Identification of test locations in the states of Paraná (PR) and São Paulo (SP), Brazil, used to evaluate 46 soybean cultivars, in the 2014/2015 crop season⁽¹⁾.

Thumbnail

Tabela 3
Estimation of genetic parameters for each of the eight locations and of the set of locations for grain yield (GY) of 46 soybean cultivars.

Thumbnail

Table 4
Grain yield (kg ha^-1) of soybean cultivars, grouping means by the Scott-Knott test, and mean of cultivars in eight sites GY (XG), mean of each location (XL), and mean of 46 soybean cultivars classified according to their cycle, in each site, in the 2014/2015 crop season.

Thumbnail

Table 5
Genetic effects (g), predicted genotypic values (u+g), gain, new mean of the genotype, ranking of genotypes by the new mean (u+g+gem), mean genotypic value in the environments, and methods of adaptability and stability, using mixed models.

Figure 1. Mean and stability for the set of 46 soybean cultivars (A), and for the cultivar division in early (B), medium (C) and late cycles (D), evaluated in eight locations - seven of which in the state of Paraná (Cambé, Corbélia, Mamborê, Palotina, Realeza, São Jorge do Ivaí, and São Miguel do Iguaçu), and one in the state of São Paulo (Cândido Mota) -, in the 2014/2015 crop season. Cultivars: BMX Potência RR (1), DMario 58i (2), NK 7059 RR (3), A 6411RG (4), BMX Ativa RR (5), BMX Energia RR (6), NA 5909 RG (7), NS 4823 (8), BMX Turbo RR (9), NS 5858 (10), NS 6262 (11), SYN1059 RR (12), NS 6767 RR (13), TMG 7262RR (14), NS 4901 (15), NS 5258 (16), NS 5290 (17), NS 5401 RR (18), NS 6209 (19), NS6121RR (20), NS6823RR (21), M6210IPRO (22), M6410IPRO (23), 5958RSF IPRO (24), 6458RSF IPRO (25), 6563RSF IPRO (26), AS 3570IPRO (27), AS 3610IPRO (28), M5917IPRO (29), NS 5000 IPRO (30), NS 5106 IPRO (31), NS 5151 IPRO (32), NS 5445 IPRO (33), NS 5959 IPRO (34), NS 6909 IPRO (35), NS 7000 IPRO (36), NS 7209 IPRO (37), NS 7237 IPRO (38), NS 7300 IPRO (39), NS 7338 IPRO (40), NS 5727 IPRO (41), NS 6006 IPRO (42), NS6060IPRO (43), NS6700IPRO (44), NS6906IPRO (45), and TMG2158IPRO (46). PC, principal component.

Figure 2. Ideal genotype of the set of 46 soybean cultivars (A), and for the cultivar divisions in early (B), medium (C) and late cycles (D), evaluated in eight locations - seven of which in the state of Paraná (Cambé, Corbélia, Mamborê, Palotina, Realeza, São Jorge do Ivaí, and São Miguel do Iguaçu), and one in the state of São Paulo (Cândido Mota) -, in the 2014/2015 crop season. Cultivars: BMX Potência RR (1), DMario 58i (2), NK 7059 RR (3), A 6411RG (4), BMX Ativa RR (5), BMX Energia RR (6), NA 5909 RG (7), NS 4823 (8), BMX Turbo RR (9), NS 5858 (10), NS 6262 (11), SYN1059 RR (12), NS 6767 RR (13), TMG 7262RR (14), NS 4901 (15), NS 5258 (16), NS 5290 (17), NS 5401 RR (18), NS 6209 (19), NS6121RR (20), NS6823RR (21), M6210IPRO (22), M6410IPRO (23), 5958RSF IPRO (24), 6458RSF IPRO (25), 6563RSF IPRO (26), AS 3570IPRO (27), AS 3610IPRO (28), M5917IPRO (29), NS 5000 IPRO (30), NS 5106 IPRO (31), NS 5151 IPRO (32), NS 5445 IPRO (33), NS 5959 IPRO (34), NS 6909 IPRO (35), NS 7000 IPRO (36), NS 7209 IPRO (37), NS 7237 IPRO (38), NS 7300 IPRO (39), NS 7338 IPRO (40), NS 5727 IPRO (41), NS 6006 IPRO (42), NS6060IPRO (43), NS6700IPRO (44), NS6906IPRO (45), and TMG2158IPRO (46). PC, principal component.

Table 1 Description of 46 soybean cultivars, maturity group, cycle, year of release, technology and releaser.

Number	Cultivar	Maturity Group	Cycle	Year of release	Technology	Releaser
1	BMX Potência RR	6.7	Later	2007	RR	GDM Genética
2	DMario 58i	5.5	Early	2007	RR	GDM Genética
3	NK 7059 RR	6.2	Medium	2007	RR	Syngenta
4	A 6411RG	6.4	Later	2008	RR	Nidera
5	BMX Ativa RR	5.6	Early	2008	RR	GDM Genética
6	BMX Energia RR	5.3	Early	2008	RR	GDM Genética
7	NA 5909 RG	5.9	Medium	2008	RR	Nidera
8	NS 4823	4.8	Early	2008	RR	Nidera
9	BMX Turbo RR	5.8	Medium	2009	RR	GDM Genética
10	NS 5858	5.8	Medium	2010	RR	Nidera
11	NS 6262	6.2	Medium	2010	RR	Nidera
12	SYN1059 RR	5.9	Medium	2010	RR	Syngenta
13	NS 6767 RR	6.7	Later	2011	RR	Nidera
14	TMG 7262RR	6.2	Medium	2011	RR	TMG
15	NS 4901	4.9	Early	2012	RR	Nidera
16	NS 5258	5.2	Early	2012	RR	Nidera
17	NS 5290	5.2	Early	2012	RR	Nidera
18	NS 5401 RR	5.4	Early	2012	RR	Nidera
19	NS 6209	6.2	Medium	2012	RR	Nidera
20	NS6121RR	6.1	Medium	2013	RR	Nidera
21	NS6823RR	6.8	Later	2013	RR	Nidera
22	M6210IPRO	6.2	Medium	2011	IPRO	Monsoy
23	M6410IPRO	6.4	Later	2011	IPRO	Monsoy
24	5958RSF IPRO	5.8	Medium	2012	IPRO	GDM Genética
25	6458RSF IPRO	6	Medium	2012	IPRO	GDM Genética
26	6563RSF IPRO	6.3	Later	2012	IPRO	GDM Genética
27	AS 3570IPRO	5.7	Early	2012	IPRO	Monsoy
28	AS 3610IPRO	6.1	Medium	2012	IPRO	Monsoy
29	M5917IPRO	5.9	Medium	2012	IPRO	Monsoy
30	NS 5000 IPRO	5	Early	2012	IPRO	Nidera
31	NS 5106 IPRO	5.1	Early	2012	IPRO	Nidera
32	NS 5151 IPRO	5.1	Early	2012	IPRO	Nidera
33	NS 5445 IPRO	5.4	Early	2012	IPRO	Nidera
34	NS 5959 IPRO	5.9	Medium	2012	IPRO	Nidera
35	NS 6909 IPRO	6.9	Later	2012	IPRO	Nidera
36	NS 7000 IPRO	7	Later	2012	IPRO	Nidera
37	NS 7209 IPRO	7.2	Later	2012	IPRO	Nidera
38	NS 7237 IPRO	7.2	Later	2012	IPRO	Nidera
39	NS 7300 IPRO	7.3	Later	2012	IPRO	Nidera
40	NS 7338 IPRO	7.3	Later	2012	IPRO	Nidera
41	NS 5727 IPRO	5.7	Early	2013	IPRO	Nidera
42	NS 6006 IPRO	6	Medium	2013	IPRO	Nidera
43	NS6060IPRO	6	Medium	2013	IPRO	Nidera
44	NS6700IPRO	6.7	Later	2013	IPRO	Nidera
45	NS6906IPRO	6.9	Later	2013	IPRO	Nidera
46	TMG2158IPRO	5.8	Medium	2013	IPRO	TMG

Table 2 Identification of test locations in the states of Paraná (PR) and São Paulo (SP), Brazil, used to evaluate 46 soybean cultivars, in the 2014/2015 crop season⁽¹⁾.

Municipality, state⁽¹⁾	Macro-region⁽²⁾	Micro-region⁽²⁾	Latitude	Longitude	Altitude (m)	Climate⁽³⁾
Cambé, PR	2	201	23°16'S	51°16'W	520	Cfa
CM, SP	2	201	22°44'S	50°23'W	440	Cwa
Corbélia, PR	2	201	24°47'S	53°18'W	650	Cfa
Mamborê, PR	2	201	24°19'S	52°31'W	715	Cfa
Palotina, PR	2	201	24°17'S	53°50'W	330	Cfa
Realeza, PR	1	102	25°46'S	53°31'W	520	Cfa
SJI, PR	2	202	23°25'S	52°17'W	560	Cfa
SMI, PR	2	201	25°20'S	54°14'W	290	Cfa

⁽¹⁾CM, Cândido Mota municipality; SJI, São Jorge do Ivaí municipality; SMI, São Miguel do Iguaçu municipality. ⁽²⁾Macroregion is determined by latitude (photoperiod/temperature) and rainfall; and microregions, within a same macroregion, differ by temperature (altitude) and soil type (Kaster & Farias, 2012KASTER, M.; FARIAS, J.R.B. Regionalização dos testes de Valor de Cultivo e Uso e da indicação de cultivares de soja - terceira aproximação. Londrina: Embrapa Soja, 2012. 69p. (Embrapa Soja. Documentos, 330).). ⁽³⁾The climate refers to Köppen climate classification.

Tabela 3 Estimation of genetic parameters for each of the eight locations and of the set of locations for grain yield (GY) of 46 soybean cultivars.

Parameter	Location								Parameter	Mean of locations
Parameter	Cambé, PR	Corbélia, PR	Mamborê, PR	Palotina, PR	Realeza, PR	São Jorge do Ivaí, PR	São Miguel do Iguaçu, PR	Cândido Mota, SP	V_G	222102
V_G	198089	771929	903687	370107	327417	276953	683526	586966	V_GxA	292728
Ve	130764	105619	74431	69894	51372	117540	59123	87360	Ve	87014
V_F	328853	877548	978118	440001	378790	394494	742649	674326	V_F	601844
h² _g	0.60(±0.19)	0.88(±0.22)	0.92(±0.23)	0.84(±0.22)	0.86(±0.22)	0.70(±0.20)	0.92(±0.23)	0.87(±0.22)	h² _g	0.37 (±0.05)
h² _mg	0.82	0.96	0.97	0.94	0.95	0.88	0.97	0.95	h² _mg	0.85
Acgen	0.91	0.98	0.99	0.97	0.97	0.94	0.99	0.98	Acgen	0.92
CVgi%	10.49	18.42	22.85	21.15	12.49	12.69	20.23	23.41	c² _int	0.49
CVe%	8.53	6.81	6.56	9.19	4.95	8.26	5.95	9.03	rgloc	0.43
PEV	35727	33671	24147	21918	16273	34324	19156	27744	CVgi%	11.73
SEP	189.01	183.50	155.39	148.05	127.57	185.27	138.40	166.56	CVe%	7.34
GY mean (kg ha^-1)	4,242	4,770	4,160	2,876	4,582	4,148	4,087	3,273	General mean	4,017

V_G, genotypic variance; V_GxA, genotype x environment interaction variance; Ve, residual variance; V_F, individual phenotypic variance. h² _g, heritability of individual plots of the total genotypic effects (in the broad sense); c² _int, coefficient of determination of the G x E interaction effects; h² _mg, heritability of the genotype mean; Acgen, accuracy of genotype selection; rgloc, genotypic correlation between perfomances in various environments; CVgi%, coefficient of genotypic variation; CVe%, coefficient of residual variation; PEV, variance of the prediction error of genotypic values; SEP, standard deviation of the predicted genotypic value.

Table 4 Grain yield (kg ha^-1) of soybean cultivars, grouping means by the Scott-Knott test, and mean of cultivars in eight sites GY (XG), mean of each location (XL), and mean of 46 soybean cultivars classified according to their cycle, in each site, in the 2014/2015 crop season.

Cultivar	Locations
Cultivar	Cambé, PR	Corbélia, PR	Mamborê, PR	Palotina, PR	Realeza, PR	São Jorge do Ivaí, PR	São Miguel do Iguaçu, PR	Cândido Mota, SP	XG
BMX Potência RR	4151cB	6186 aA	4453bB	3072cD	4348cB	4706bB	3656dC	3859bC	4304c
DMario 58i	4241cB	4373dB	4804bA	2325eC	4623bA	3982cB	4580bA	2602dC	3941d
NK 7059 RR	4020cC	5813bA	3957cC	3579bD	4461bC	3955cC	5277aB	3364cD	4303c
A 6411RG	3495dB	4105eA	1174eD	2307eC	3997cA	2840eC	2286fC	2601dC	2851h
BMX Ativa RR	2770eB	3030fA	972eD	1743eC	3308dA	2525eB	2269fB	1653fC	2284i
BMX Energia RR	3624dB	4445dA	4850bA	2817dC	4953bA	4088cB	3580dB	3857bB	4027d
NA 5909 RG	4614bB	5557bA	5373aA	3240cC	5343aA	4808bB	5283aA	4588aB	4851a
NS 4823	3816cB	3129fC	3771cB	2251eD	5086aA	3635dB	2836eC	2463dD	3373g
BMX Turbo RR	4495bB	5108cB	5577aA	2445eE	5000bB	3928cC	4824bB	3202cD	4322c
NS 5858	3947cB	3548fB	3897cB	2242eC	4619bA	4301cA	4278cA	3437cB	3784e
NS 6262	4156cB	3938eB	4664bA	2230eD	4980bA	4195cB	3963cB	2726dC	3856e
SYN1059 RR	5099aA	4810cA	4475bB	2586dD	4749bA	4320cB	4278cB	3605cC	4240c
NS 6767 RR	4999aB	5886bA	4686bB	3673bD	4104cD	4447cC	4909bB	4011aD	4589a
TMG 7262RR	4441bB	5123cA	4800bB	2158eC	5315aA	4634bB	4288cB	2502dC	4158c
NS 4901	3911cB	4182eB	3915cB	2255eD	5090aA	4067cB	3943cB	2832dC	3774e
NS 5258	4299bB	4052eB	4035cB	2175eC	4678bA	4670bA	4181cB	3677bB	3971d
NS 5290	4446bA	4228eA	4478bA	2424eB	4586bA	4441cA	4109cA	2317eB	3879e
NS 5401 RR	4093cA	3161fB	4008cA	2474dC	4083cA	4081cA	4033cA	2638dC	3571f
NS 6209	4199cB	5167cA	5253aA	3122cC	3984cB	3969cB	3607dB	3767bB	4134c
NS6121RR	3906cB	5345cA	3958cB	2886dC	4247cB	4189cB	3186eC	2976dC	3836e
NS6823RR	4586bB	6097aA	4277cC	3923bC	4699bB	4675bB	4458cB	4437aB	4644a
M6210IPRO	4328bC	5605bA	4257cC	3777bC	4117cC	4794bB	4705bB	3889bC	4434b
M6410IPRO	4613bB	5711bA	4184cC	2920dD	4815bB	5453aA	5296aA	4645aB	4705a
5958RSF IPRO	4686bB	5402cA	4657bB	3107cD	4188cC	3947cC	4951bB	3499cD	4305c
6458RSF IPRO	4056cC	4753dB	4668bB	3103cD	5130aA	4373cB	4158cC	3905bC	4268c
6563RSF IPRO	5342aA	5539bA	4970bB	3253cD	4763bB	4029cC	4373cC	4358aC	4578a
AS 3570IPRO	4200cA	3874eA	4063cA	2243eC	3834cA	4140cA	3084eB	3526cA	3621f
AS 3610IPRO	4329bB	5175cA	4625bA	3303cC	4776bA	4068cB	4870bA	4149aB	4412b
M5917IPRO	4215cC	5430cA	4793bB	3368cD	4797bB	4864bB	4870bB	4379aC	4590a
NS 5000 IPRO	4216cB	3360fC	3853cC	2785dD	4861bA	3762dC	3637dC	2217eE	3586f
NS 5106 IPRO	4131cC	4051eC	3961cC	2567dD	5416aA	4807bB	4370cC	2436dD	3967d
NS 5151 IPRO	4043cB	4238eB	3879cB	2656dD	5443aA	4093cB	3805cB	3259cC	3927d
NS 5445 IPRO	3328dC	4004eB	4355cB	2125eD	5056aA	3776dB	3172eC	2602dD	3552f
NS 5959 IPRO	4765bC	5120cB	5532aA	2725dE	5668aA	4490bC	5124aB	3936bD	4670a
NS 6909 IPRO	4579bA	4654dA	4600bA	2521dC	4665bA	4617bA	3796cB	2122eC	3944d
NS 7000 IPRO	4360bC	5730bA	3411dD	3866bD	4527bC	4923bB	4151cC	4152aC	4390b
NS 7209 IPRO	4178cB	6080aA	3026dD	4494aB	3489dC	4320cB	4613bB	3792bC	4249c
NS 7237 IPRO	4077cB	4895cA	3663cC	3437cC	3399dC	4326cB	2281fD	3019dC	3637f
NS 7300 IPRO	4114cC	6087aA	3975cC	3340cD	3091dD	3592dD	4852bB	3366cD	4052d
NS 7338 IPRO	4098cB	4628dA	3729cC	3647bC	3936cC	3629dC	4177cB	2712dD	3819e
NS 5727 IPRO	4722bA	3885eB	4274cB	2678dD	5182aA	3062eC	3178eC	2539dD	3690f
NS 6006 IPRO	4643bA	4420dB	5103aA	2754dC	4870bA	3961cB	4691bA	2505dC	4118c
NS6060IPRO	3224dB	3575fB	1343eD	1948eC	4898bA	2997eB	2150fC	2098eC	2779h
NS6700IPRO	4395bA	4691dA	4091cA	3369cB	4396cA	4376cA	4258cA	4251aA	4228c
NS6906IPRO	3940cC	6265aA	4474bB	3983bC	4279cC	3968cC	4945bB	3827bC	4460b
TMG2158PRO	5231aA	4975cA	4513bB	2388eD	4946bA	4005cC	4664bB	2275eD	4124c

Table 5 Genetic effects (g), predicted genotypic values (u+g), gain, new mean of the genotype, ranking of genotypes by the new mean (u+g+gem), mean genotypic value in the environments, and methods of adaptability and stability, using mixed models.

Cultivar	g	u+g	Gain	New mean	Rank	u+g+gem	HMGV	RPGV *OM	HMRPGV *OM
BMX Potência RR	242	4260	424	4441	14	4300	4155	4300	4254
DMario 58i	-64	3953	247	4265	29	3942	3702	3904	3852
NK 7059 RR	242	4259	412	4429	15	4299	4178	4317	4260
A 6411RG	-988	3029	57	4075	44	2867	2559	2866	2605
BMX Ativa RR	-1468	2550	0	4017	46	2308	2056	2291	2111
BMX Energia RR	8	4025	295	4313	25	4027	3913	4042	3998
NA 5909 RG	706	4723	706	4723	1	4839	4718	4855	4829
NS 4823	-545	3472	81	4099	43	3382	3195	3363	3293
BMX Turbo RR	258	4276	454	4472	12	4318	4059	4278	4219
NS 5858	-198	3819	181	4198	35	3787	3631	3785	3736
NS 6262	-136	3881	214	4231	32	3859	3630	3823	3773
SYN1059 RR	189	4206	376	4394	18	4237	4073	4223	4203
NS 6767 RR	484	4502	557	4574	6	4582	4497	4615	4572
TMG 7262RR	119	4136	354	4371	20	4156	3795	4081	3992
NS 4901	-206	3812	170	4187	36	3778	3582	3745	3716
NS 5258	-39	3978	282	4300	26	3972	3780	3960	3908
NS 5290	-118	3900	225	4243	31	3880	3634	3841	3782
NS 5401 RR	-378	3640	108	4126	41	3577	3445	3580	3533
NS 6209	98	4116	341	4359	21	4132	4028	4155	4104
NS6121RR	-153	3864	203	4220	33	3839	3701	3830	3800
NS6823RR	531	4548	593	4610	4	4635	4572	4683	4634
M6210IPRO	353	4370	505	4522	9	4428	4366	4473	4427
M6410IPRO	582	4599	644	4661	2	4695	4529	4704	4646
5958RSF IPRO	243	4261	438	4455	13	4301	4179	4306	4279
6458RSF IPRO	212	4230	399	4417	15	4265	4178	4283	4266
6563RSF IPRO	475	4492	545	4562	7	4570	4460	4590	4555
AS 3570IPRO-(M 3570 IPRO)	-336	3681	133	4150	39	3626	3493	3632	3586
AS 3610IPRO	334	4352	488	4505	10	4407	4332	4436	4412
M5917IPRO	484	4502	571	4588	5	4582	4501	4612	4585
NS 5000 IPRO	-365	3652	121	4138	40	3592	3422	3585	3520
NS 5106 IPRO	-42	3975	270	4288	27	3968	3721	3932	3862
NS 5151 IPRO	-76	3941	237	4254	30	3928	3789	3918	3896
NS 5445 IPRO	-394	3624	96	4114	42	3559	3337	3522	3466
NS 5959 IPRO	552	4570	613	4631	3	4661	4451	4639	4601
NS 6909 IPRO	-62	3955	259	4276	28	3945	3648	3895	3809
NS 7000 IPRO	315	4333	472	4489	11	4385	4301	4436	4353
NS 7209 IPRO	196	4213	387	4405	17	4246	4113	4328	4130
NS 7237 IPRO	-322	3695	145	4163	38	3642	3495	3681	3540
NS 7300 IPRO	30	4047	307	4325	24	4052	3895	4074	3956
NS 7338 IPRO	-168	3850	192	4209	34	3822	3744	3858	3807
NS 5727 IPRO	-277	3740	158	4175	37	3694	3492	3676	3597
NS 6006 IPRO	85	4103	319	4337	23	4117	3883	4087	4024
NS6060IPRO	-1048	2969	33	4050	45	2796	2473	2764	2546
NS6700IPRO	179	4196	366	4383	19	4225	4187	4276	4243
NS6906IPRO	375	4392	524	4541	8	4454	4356	4496	4416
TMG2158IPRO	91	4108	330	4347	22	4123	3778	4059	3960

HMGV, harmonic mean of the genotypic values; RPGV*OM, relative performance of the predicted genotypic values multiplied by the overall mean of all environments; HMRPGV*OM, harmonic mean of the relative performance of the genotypic values multiplied by the overall mean of all environments.

Como citar

copiar

Embrapa Secretaria de Pesquisa e Desenvolvimento; Pesquisa Agropecuária Brasileira Caixa Postal 040315, 70770-901 Brasília DF Brazil, Tel. +55 61 3448-1813, Fax +55 61 3340-5483 - Brasília - DF - Brazil
E-mail: pab@embrapa.br

Acompanhe os números deste periódico no seu leitor de RSS

Versão para download de PDF

PDF

Inglês

Versões e tradução automática

Versão original do texto

English

Tradução automática

Google Translator
Microsoft Translator

Como citar

RIS

BIBTEX

Outros formatos de citação e exportação:

SciELO - Scientific Electronic Library Online
Rua Dr. Diogo de Faria, 1087 – 9º andar – Vila Clementino 04037-003 São Paulo/SP - Brasil
E-mail: scielo@scielo.org

Leia a Declaração de Acesso Aberto

Métricas

Mensagem

[TFN1] ⁽¹⁾CM, Cândido Mota municipality; SJI, São Jorge do Ivaí municipality; SMI, São Miguel do Iguaçu municipality. ⁽²⁾Macroregion is determined by latitude (photoperiod/temperature) and rainfall; and microregions, within a same macroregion, differ by temperature (altitude) and soil type (Kaster & Farias, 2012KASTER, M.; FARIAS, J.R.B. Regionalização dos testes de Valor de Cultivo e Uso e da indicação de cultivares de soja - terceira aproximação. Londrina: Embrapa Soja, 2012. 69p. (Embrapa Soja. Documentos, 330).). ⁽³⁾The climate refers to Köppen climate classification.