Diallel analysis in cotton (Gossypium hirsutum L.) for water stress tolerance




Crop Breeding and Applied Biotechnology -

18: 24-30, 2018

UAA Vasconcelos et al.

Diallel analysis in cotton (

Gossypium hirsutum

L.) for water stress tolerance

Ubieli Alves Araújo Vasconcelos


, José Jaime Vasconcelos



, Francisco José Correia Farias


, Walmir Sousa



and Roseane Cavalcanti dos Santos


Abstract: Information about combining ability is important in determining breed

-ing strategies. The objective of this study was to estimate the general (GCA) and specific (SCA) combining abilities among twenty cotton hybrid combinations submitted to water stress, based on agronomic traits. The trails were carried out in semiarid environment (Barbalha, CE), during two years, in dry season under irrigation, and submitted to 23 days of water suppression. Wide variability was verified among parents and their hybrids, with additive effects to seed yield, lint percentage, blooming and boll weight. Dominance effect was found only to plant height. The combinations BRS 286 x CNPA 5M, BRS RUBI x CNPA 5M, FM 966 x CNPA 5M and BRS 286 x BRS Seridó showed the best SCAs and aver

-ages for the majority of the traits. In addition, at least one of their parents had high CGA. These combinations must be advanced in cotton breeding program. Key words: Breeding, combining ability, drought tolerance, genetic control, hybrid.

Crop Breeding and Applied Biotechnology 18: 24-30, 2018 Brazilian Society of Plant Breeding. Printed in Brazil

http://dx.doi.org/10.1590/1984-70332018v18n1a4 ARTICLE

*Corresponding author: E-mail: ubieli_araujo@hotmail.com Received: 14 October 2016 Accepted: 01 July 2017

1 Universidade Federal de Viçosa,

Departa-mento de Fitotecnia, Campus Universitário S/N, 36.570-900, Viçosa, MG, Brazil

2 Embrapa Algodão, 58.428-095, Campina

Grande, PB, Brazil

3 Universidade Estadual da Paraíba,

Departa-mento de Ciências Agrárias e Exatas, 58.429-500, Campina Grande, PB, Brazil


Cotton (Gossypium hirsutum L.) is one of the most important textile crop

worldwide. It is cultivated on about 35 million hectares, generating a global production of 24 million tons of fiber (Abrapa 2016). China, India, United States, Pakistan and Brazil are the main fiber producers (FAO 2016). The crop management involves more than 350 million people, in Brazilian cotton belt, located at Cerrado region, with production exceeded 1.5 million tons (Abrapa

2016, Conab 2016).

Cotton plant has a phenological cycle ranging from 120 to 200 days, depending on the cultivar, with different responses to environment conditions in order to ensure the fiber yield. Reproductive phase are quite dependent on water and fertilization supplements. According to Batista et al. (2010), water suppression in cotton plants for 23 days causes reduction in plant height, fiber growth, bud

and boll numbers, although root system length is increased as a response to

dry condition.

In Brazil, the main commercial cultivars have limited adaptation to


of populations with broad genetic base is necessary in order to increase the chances to identify water-tolerant materials in further selection procedures. Diallelic design is often adopted to study genetic inheritance of traits, supporting in breeding strategy, as selection of individuals to create a breeding population. The scheme consists in crossings among the parents, resulting in hybrids with all possible combinations and providing combining ability of the parents.

The estimative of general combining ability (GCA) refers to capability of parental to generate favorable combinations in order to promote genes predominantly additive. The higher values estimated, positive or negative, the parent is considered higher or lower than others included in a diallel. By other side, the specific combining ability (SCA) refers to dominance effects and also to non-additive interactions of genes, resulting from gene complementation between

parents. Then, the hybrid combination that shows high SCA (s�ij) and at least one parent with high GCA will be the most

favorable (Cruz et al. 2012).

Several studies have been available in literature reporting on diallel analysis in cotton. Raza et al. (2013) evaluated five cultivars and detected additive effects to plant height, lint yield, lint percentage and boll weight. Khan and Hassan (2011) estimated the GCA and SCA in a diallel scheme involving 12 cotton cultivars and found differences in all hybrid combinations to lint yield, boll weight and boll numbers, with more genetic variances to SCA than to GCA indicating predominance of non-additive gene.

The genetic study of cotton under water restriction can support the cotton breeding program in semiarid environments. Thus, the objective of this research was to evaluate the hybrid combination, with the diallel design under water stress condition in order to identify the best combinations to water stress tolerance, based on GCA and SCA estimates.


Twenty F1 hybrid combinations generated from partial diallel crossing were used for this study using two parents

groups: GI - formed by five cultivars with high fiber yield (Cia et al. 2014, Carvalho et al. 2015, Coutinho et al. 2015, Zonta et al. 2016) and GII - composed of by four drought tolerance cultivars (Freire et al. 1999, Vidal Neto and Freire 2013). These cultivars are inbred lines developed by Brazilian Company of Agricultural Research (Embrapa), Bayer and Mato Grosso Foundation (FMT) (Table 1).

The trials were carried out in Embrapa Cotton Experimental Station, in Barbalha (lat 7° 18′ 18″ S, long 39° 18′ 7″ W, alt 414 m asl), CE, in two years, during the dry season (July to December, 2014 and 2015). The mean of temperature recorded during the trial was 24.1 °C. The soil is classified as Fluvic Neosoil, clay loam texture (Embrapa 1999). Based

on fertilization soil analysis, a previous fertilization was performed by using 250 kg ha-1 of monoammonium phosphate

(MAP) at sowing, and further 125 kg ha-1 of urea-N fertilization divided into two applications (35 and 50 DAE).

Plants were submitted to two water treatments: Control (C): normal watering, by sprinkler irrigation system during all cycle, and Stress (S): water suppression for 23 days, starting at 42 days after emergence (DAE), corresponding to

blooming. The sprinkler irrigation was maintained with a flow rate of 1.49 m³ h-1, according assays previously carried out

Table 1. Groups of cotton parents used in the partial diallelic crossing scheme

Parent Type Company Cycle Fiber color Main trait

Group I:

FMT 705 Upland FMT Mid-earliness White High fiber yield

FM 966 Upland Bayer Earliness White High fiber yield

BRS RUBI Upland Embrapa Mid Brown High fiber yield

BRS 286 Upland Embrapa Mid-earliness White High fiber yield

FMT 701 Upland FMT Late White High fiber yield

Group II:

CNPA ITA 90 Upland Embrapa Late White Water stress tolerant

CNPA 5M Moco Embrapa Late White Water stress tolerant

CNPA 7MH Hybid Embrapa Late White Water stress tolerant



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UAA Vasconcelos et al.

by Bezerra et al. (2010). The plot consisted of two 5 m-rows, spaced in 0.90 m. Plants were spaced in 0.14 m, maintaining

a population of 70 plants plot-1. A randomized block design was adopted with 20 treatments and 3 repetitions. Plants

were maintained free of pests and weeds by using pesticides. At harvest (128 DAE), the following traits were registered:

plant height (PH, cm), cotton seed yield (CSY, kg ha-1), lint percentage (LP, %) and boll weight (BW, g).

The statistical-genetic analyzes were performed using the GENES program version 6.1 2014 (Cruz 2016). F and Scott and Knott (1974) tests were adopted to variance analysis (ANOVA) and mean comparisons, respectively. The joint analyses were performed considering genotypes as fixed effect and years and water treatments were random effects (Cruz et al. 2012). A partial diallel analysis model was adopted to genetic analysis, according to Griffing (1956)’s method 4 and adapted by Geraldi and Miranda Filho (1988) in order to estimate the effects of GCA of each parent and the effects of SCA among their combinations.


Combinations resulting from a partial diallel crosses with upland and Moco cultivars were grown in Barbalha (CE), under irrigation and water suppression (for 23 days) treatments. The physiological symptoms caused by water stress in

the plants were observed soon, after the 2nd week of water suppression. In this occasion, plants showed slow growth

and reduction in leaf turgidity. At the end of water suppression, irrigation was restored and the symptoms resulting

from water stress were disappearing over plant growth.

The results of ANOVA (Table 2) showed that significant statistic differences (p<0.05) were verified in Genotype (G), Year (Y) and Water Treatment (WT) to all traits, excepting to boll weight (BW) in year (Y) and water treatment (WT). For these source of variation, the F test uses the interaction Y x WT. As it was very high and significant for this trait, it caused no-significance effect for them (Y and WT). The same results were seen for G x WT, that uses G x Y x WT interaction to test it, indicating different behavior of cultivars submitted to water treatments. On the other hand, the interaction G x Y did not demonstrate significant effect indicating that the genotypes had similar behaviors in both years (2014 and 2015). The CV values ranged from 2.14 for LP to 10.48% for CSY, and they are in accordance with the results found by Carvalho et al. (2015), Carvalho et al. (2016) and Zonta et al. (2016) for this crop. The means of traits (Table 3), obtained from different hybrid combinations submitted to two water treatments, demonstrate that the water suppression influenced the growth and production of plants at different levels. For all traits, some hybrid averages showed good potential to develop new genotypes with better performance in water stress condition. The number of groups formed by Scott-Knott test ranged from two groups (PH) to seven groups (LP). These results are expected due to the differences among the genetic variability and the influence of the environment in each trait. The reduction in height ranged from 12.88 to 24.71%. This difference promoted a direct impact in yield, with losses ranging from 3.08 to 44.78%. These results explain the effect seen in G x WT, in which some combinations were more negatively impacted by water stress, such as FMT 705 x BRS Seridó (1 x 9) with yield reduced of 44.78%, revealing a highly sensitive genotype. In contrast, BRS 286 x CNPA

Table 2. Synthesis of joint analysis to cotton traits obtained by irrigation and water stress treatments among cotton F

1 hybrids

Means square


(Block/WT)/Y 8 5.48 235850.08 1.08 0.01 2.01

G 19 82.06** 7735192.43* 61.11** 6.92** 4.73**

Y 1 2.84** 7364006.66** 2.97** 1.61 1.20**

WT 1 26878.06** 19883526.66** 31.56** 0.24 121.00**

G x Y 19 2.59 230650.59 0.41 0.19 0.51

G x WT 19 73.80** 3352632.22** 3.35** 0.19 3.34**

Y x WT 1 1.22 81033.75 0.13 1.76** 0.03

G x Y x WT 19 4.12 128211.94 0.26 0.18** 0.37

Error 152 5.07 248601.79 0.78 0.02 0.93

Mean 102.62 4756.72 41.34 5.94 42.21

CV (%) 2.19 10.48 2.14 2.56 2.29


sis i n c ott on ( Goss ypium hirsutum L.) f or w a te r s tr e ss t oler ance


op Br

eeding and Applied Biot


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5M (4 x 7) sho w ed an exc elle nt pe rfor m anc e, de m ons tr a te d b y hig h c apac ity t o pr oduc fiber s, e ven in a situa tion of w ater s tr ess, as

imposed in this w

ork. Other s fi v e c ombi na ti ons ar e al so pr oduc tiv e in w ate r st ress conditions, clus ter ed in “a” gr oup, classifie d by Sc ott and Knott tes t: FM 966 x CNP A 5M (2 x 7), BR S RUBI x CNP A 5M (3 x 7) and BR S 286 x BR S Seridó (4 x 9),

all of the

m with r



d losse

s in y

ie ld. B the w ay, BR S RUBI x CNP A 5M (3 x 7) sho w ed a diff er en tial beha vior , incr easing the yie ld in 21 .8 8% in w ate r st ress tre atm en t. It m ea ns an in ter esting ability to ph ysiologic al res tor ation, which is oft en associa ted with tole rance to dr ough t. Taki ng in acc ou nt th e oth er s tr ai ts, w e veri fied tha t F M 966 x CNP A 5M (2 x 7) and BR S 28 6 x BR S Se ridó (4 x 9) also m ain taine d slig ht gai ns for LP and BW , in str ess trea tmen t. As to blooming , w e f ound tha t w a ter suppr ession did not in flue nc e ha rdly in this tra it due to it occu rr ed in th e peri od cl ose to flo w eri ng (42 DAE). Ho w ev er , w e found tha t the mos t com bina tions had a slig ht ear line ss to star ting the fir st flo w er (T able 3). These results agr ee w ith Ba tis ta et al. (2 01 0) tha t subm itt ed cott on pla n ts t o dif fe re n t m e

thods of ir

rig a tion and found tha t in w ater str ess condition an earlier blooming

took place in g

enotypes. As to Go w da and Hedg e (1986), this earliness is oft en associa ted t o r eduction of plan t cy cle,

and it is a de

sir able f e a tur e , e spe cially in e n v ir onm e n ts pr one t

o “indian sum

m e r” (v era nic os) or w ate r r ain fall irre gula ritie s. Conse que ntly , the am oun t of re pr oduc tiv e structur

es is r

educed (Baldo e

t al. 2009).

The join t diallel analy sis of the F

1 h

ybrids for cott on traits (T able 4) w as perf ormed onl y u n d er s tr ess tr ea tmen ts i n o rd er t o sel ect th e par en ts an d th ei r h yb rid co mb ina tio ns for this condition. A signific an t e ffect of GCA w as see n in both gr oup

s I and

II t o all tr aits (p<0. 05), excep tin g to B, in GCA–II, indi ca ting additiv e eff ects in the con tr ol of PH, CS Y, LP and BW traits. For SCA , no signi fic an t e ffect w as found only to BW , indic ating non-aditiv e (do mi nan ce or ep istasi s) t o o th er s tr ai ts. Th ese results agr ee with those found b

y Aguiar e

Hybrid* PH CSY LP BW B


1 x 6 113.08 d 91.28 b -19.28 5690.50 b 3593.00 b -36.86 45.02 a 43.77 a -2.86 6.22 a 6.12 b -1.63 41.00 b 40.83 b -0.42

1 x 7 124.67 a 94.00 a -24.60 6258.33 b 4244.33 b -32.18 40.83 d 39.02 e -4.64 5.30 b 4.95 d -7.07 41.83 b 41.17 b -1.60

1 x 8 113.11 d 93.45 a -17.38 5498.50 c 3929.17 b -28.54 43.22 b 41.43 c -4.32 6.63 a 6.49 b -2.16 41.83 b 41.66 b -0.41

1 x 9 116.36 c 92.36 b -20.63 7229.83 a 3992.50 b -44.78 45.46 a 43.95 a -3.44 5.80 b 6.27 b 7.50 41.50 b 41.83 a 0.79

2 x 6 110.47 d 91.50 b -17.17 5477.17 c 4361.17 b -20.38 43.05 b 42.27 b -1.85 6.77 a 6.68 a -1.35 41.67 b 41.33 b -0.82

2 x 7 111.89 d 93.33 a -16.59 5735.00 b 5499.33 a -4.11 38.76 f 38.01 f -1.97 5.43 b 5.45 c 0.37 41.50 b 41.33 b -0.41

2 x 8 103.39 e 90.00 b -12.95 3904.17 d 4292.67 b 9.95 41.48 c 41.97 b 1.17 6.86 a 7.02 a 2.28 42.67 b 40.83 b -4.51

2 x 9 109.42 d 91.08 b -16.76 4255.50 d 4160.17 b -2.24 43.24 b 43.06 a -0.42 7.28 a 7.18 a -1.39 42.33 b 41.66 b -1.61

3 x 6 112.39 d 91.67 b -18.44 3856.17 d 4367.33 b 13.26 40.20 d 39.37 e -2.11 4.95 c 5.31 c 6.78 44.00 a 42.00 a -4.76

3 x 7 120.42 b 90.67 b -24.71 4438.67 d 5409.83 a 21.88 36.95 g 35.30 g -4.67 4.73 c 4.61 d -2.60 43.33 a 42.00 a -3.17

3 x 8 112.03 d 95.53 a -14.73 3940.67 d 3497.17 b -11.25 38.32 f 38.18 f -0.37 6.36 a 5.98 c -6.35 42.50 b 41.83 a -1.60

3 x 9 109.83 d 88.67 b -19.27 3720.17 d 3795.50 b 2.02 39.41 e 40.33 d 2.28 5.69 b 5.73 c 0.70 42.67 b 41.17 b -3.64

4 x 6 119.75 b 91.33 b -23.73 4147.00 d 3904.83 b -5.84 43.42 b 43.27 a -0.35 5.73 b 5.78 c 0.87 43.00 a 41.83 a -2.80

4 x 7 112.45 d 90.47 b -19.55 7107.67 a 6758.33 a -4.91 39.79 e 39.72 c -0.18 5.46 b 5.04 c -8.33 42.17 b 40.67 c -3.69

4 x 8 110.83 d 95.06 a -14.23 4060.33 d 4183.17 b 3.03 42.05 c 42.00 b -0.12 5.68 b 5.38 c -5.58 43.50 a 40.83 b -6.54

4 x 9 110.14 d 95.95 a -12.88 5251.17 c 5089.50 a -3.08 43.06 b 43.50 a 1.01 6.76 a 6.93 a 2.45 42.83 a 41.17 b -4.03

5 x 6 111.70 d 90.67 b -18.83 4594.83 d 4088.17 b -11.03 43.70 b 43.09 a -1.42 5.78 b 5.65 c -2.30 42.67 b 42.17 a -1.19

5 x 7 114.92 d 87.83 b -23.57 6067.67 b 4958.83 b -18.27 41.83 c 38.06 f -9.91 4.67 c 4.93 d 5.27 41.50 b 41.83 a 0.79

5 x 8 114.47 d 90.33 b -21.09 3785.50 d 4532.83 b 19.74 42.09 c 41.13 c -2.33 6.35 a 6.12 b -3.76 42.00 b 41.50 b -1.20

5 x 9 112.75 d 95.58 a -15.23 5872.33 b 4720.00 b -19.62 42.33 c 42.25 b -0.19 7.18 a 6.73 a -6.69 42.83 a 41.17 b -4.03



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al. (2007), Bertini et al. (2005) and Menezes et al. (2013) and mean that, at least, one hybrid combination differs from

others, suggesting complementation of favorable alleles between parents, in loci with dominance (Cruz et al. 2012). These results demonstrate the importance of the GCA and SCA effects in the genetic variance of genotypes, especially GCA in all traits, accounting to whole variance of 24.27% (PH), 72.13% (CSY), 93.74% (LP), 87.64% (BW) and 64.12% (B), whose can be exploited in selection procedures of hybrid combinations in order to identify top lines and achieve expressive genetic gains. The effects of interaction G x Y, GCA-I x Y, GCA-II x Y and SCA x Y were all not significant (p>0.05), indicating similar behavior of genotypes during two years in this study. The only exception was found to BW, which revealed significant effect to all interactions, suggesting variations in behavior of parents (GCA-I and II) and hybrids (SCA).

The estimates of GCA (g�) for genotypes of the groups I and II (Table 5) detected a significant and distinct contributions

from the parents in order to improve the traits of hybrids demonstrating the contribution of diallel crossing to crop improvement, focusing on yield and adaptation to semiarid environment. Highlights were found to BRS 286 (GI) and

CNPA 5M (GII) that contributed to increase the yield of hybrids in 515.06 kg ha-1 and 905.24 kg ha-1, respectively. BRS 286

(GI) also contributed to increase the height of plants in 1.16 cm. Of course that this trait must be carefully maintained in selection procedures, in order to avoid further problems to mechanical harvesters. According to Chanselme and Ribas (2010), cotton plants should get 90 cm, at most, in the harvest period.

Others cultivars were also more contributive to others traits. FMT 705 (GI), FMT 701 (GI), CNPA ITA 90 (GII) and BRS Seridó (GII) contributed to raising the percentage of lint in 1.92%, 0.78%, 1.36% and 0.98%, respectively. FMT 705 also contributed to reduce the blooming in 1.09 days. As to BW, both FM 966 and BRS Seridó contributed to increase this trait in about 0.65g. Based on these results, we conclude that the genetic base of parents used to diallel crossing are important

Table 4. Diallelic analysis of cotton hybrid combinations under water stress condition

Mean square


Genotype (G) 19 32.04** 3570844.32** 30.26** 3.47** 4.81**

GCA - I 4 19.41** 3654532.77* 80.38** 4.36** 12.35**

GCA - II 3 23.39* 11439070.30** 72.47** 13.48** 3.05

SCA 12 38.43** 1575891.34** 3.00** 0.68 2.73**

Y 1 0.16 449500.20 2.18 3.38** 0.41

G x Y 19 0.61 134811.07 0.34 0.37** 0.58

GCA - I x Y 4 0.46 300177.61 0.08 0.09* 0.44

GCA - II x Y 3 1.63 33866.95 0.25 0.35** 0.61

SCA x Y 12 0.40 104924.92 0.44 0.47** 0.61

Error 76 1.56 138236.66 1.19 0.02 1.06

Mean 92.03 4468.89 41.71 5.91 42.92

* and **: significant at 5 and 1% probability, respectively; Y: year; PH: plant height (cm); CSY: cotton seed yield (kg ha-1); LP: lint percentage (%); BW: boll weight (g) and B: blooming (DAE).

Table 5. Estimates of GCA (g�) of cotton parents from groups I and II under water stress condition. Barbalha, CE, 2014-2015



1. FMT 705 0.73* -529.14* 1.92* 0.04 -1.09*

2. FM 966 -0.55 109.44 -0.07 0.66* 0.74*

3. BRS RUBI -0.40 -201.43 -2.99* -0.51* 0.49

4. BRS 286 1.16* 515.06* 0.36 -0.13* -0.25

5. FMT 701 -0.93* 106.06 0.78* -0.06 0.11


6. CNPA ITA 90 -0.74 -405.99* 1.36* -0.01 -0.35

7. CNPA 5M -0.77 905.24* -2.07* -0.92* 0.41

8. CNPA 7MH 0.83 -381.89* -0.27 0.28 0.40

9. BRS SERIDO 0.69 -117.35 0.98* 0.64* -0.09


to increase the frequency of favorable alleles, based on the traits studied, allowing to obtain top lines and genetic gain. The estimates of SCA (sij) to hybrid combinations (Table 6) presented positive and negative values of s�ij were obtained

in different traits, suggesting deviation of dominance, with alleles that contribute to increase or reduce the expression of traits in loci with dominance. Based on these results, we recommended that the selection procedures of hybrids should be focused in PH and CSY, since the gains of others traits were zero or negligible, indicating low contribution to

plant improvement.

The selection based on height should focus on requirements established to mechanized harvesting. Hybrids that contributed to increase the plant height were: FMT 705 x CNPA 5M, FM 966 x CNPA 5M, BRS RUBI x CNPA 7MH and FMT 701 x BRS Seridó, demonstrating better adjustment to water stress conditions. On other hand, FM 966 x CNPA 7MH, BRS RUBI x BRS Seridó, BRS 286 x CNPA 5M, FMT 701 x CNPA 5M and FMT 701 x CNPA 7MH can be interesting genotypes selected to reduced height. As to yield, four combinations were highly promising, revealing gains up to 300

kg ha-1: BRS 286 x CNPA 5M (869.13 kg ha-1), BRS RUBI x CNPA ITA 90 (505.86 kg ha-1), FMT 705 x CNPA 7MH (371.30 kg

ha-1) and FMT 701 x CNPA 7MH (339.76 kg ha-1). All of them showed high genetic complementation, with potential to

generating distinct and top lines.

Cruz et al. (2012) state that in a diallel analysis, the best hybrid combination to be selected must hold a high SCA, with at least one parent with high GCA and associated with high mean. Thus, considering all the features together, we can choose the hybrid BRS 286 x CNPA 5M, BRS RUBI x CNPA 5M, FM 966 x CNPA 5M and BRS 286 x BRS Seridó as the most promising materials for cotton breeding improvement in semi-arid environment. This can lead to build on cotton seed yield and lint percentage gains, reflecting their greater genetic plasticity to tolerate water stress during the reproductive phase, with great opportunities to provide significant genetic gains in the selection process.

The parents used here in diallel crossings are commercial cultivars. They contributed to generate variability and genetic gains to cotton breeding focused on semiarid environment. Also, we found that the additive effects are the most important for yield, lint percentage, blooming and boll weight, while dominance effect are more important to

improvement of plant height.

Table 6. Estimates of SCA (s

ij) to 20 cotton F1 hybrid combinations grown in stress treatments under water stress condition. Barbalha,



Hybrid* PH CSY LP BW B

1 x 6 -0.74 59.24 0.02 0.16* 0.35

1 x 7 2.00* -600.65* -0.72 -0.08 0.29

1 x 8 -0.16 371.30* -0.13 0.25* 0.09

1 x 9 -1.10 170.10 0.84 -0.33* -0.74

2 x 6 0.77 188.82 0.05 0.11 -0.47

2 x 7 2.63* 15.75 -0.79 -0.21* -0.20

2 x 8 -2.31* 96.22 0.12 0.15* -0.07

2 x 9 -1.08 -300.80* 0.62 -0.05 0.75

3 x 6 0.78 505.86* 0.11 -0.09 0.10

3 x 7 -0.19 237.13 0.31 0.12 -0.12

3 x 8 3.06* -388.39* -0.12 0.29* -0.49

3 x 9 -3.65* -354.60* -0.30 -0.32* 0.50

4 x 6 -1.12 -673.13* -0.02 0.01 -0.13

4 x 7 -1.95* 869.13* -0.21 0.17* -0.20

4 x 8 1.02 -418.90* 0.25 -0.68* 1.25*

4 x 9 2.05* 222.89 -0.01 0.49* -0.91

5 x 6 0.31 -80.80 -0.15 -0.19* 0.15

5 x 7 -2.42* -521.36* 1.42* -0.01 0.25

5 x 8 -1.60* 339.76* -0.11 -0.01 -0.78

5 x 9 3.79* 262.39 -1.15* 0.22* 0.38



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The hybrid combinations: BRS 286 x CNPA 5M, BRS RUBI x CNPA 5M, FM 966 x CNPA 5M and BRS 286 x BRS Seridó were quite promising to advancement of cotton breeding in semiarid environment due to high potential to yield and lint percentage. Those materials showed enough genetic plasticity to adjustment to water stress during the starting of reproductive phase, recovering the productive ability, after drought alleviating. The use of these hybrids in cotton improvement could promote broad opportunities to provide expressive gains in further selection procedures.


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Table 5.  Estimates of GCA (g�) of cotton parents from groups I and II under water stress condition

Table 5.

Estimates of GCA (g�) of cotton parents from groups I and II under water stress condition p.5
Table 6.  Estimates of SCA ( s ij � ) to 20 cotton F 1  hybrid combinations grown in stress treatments under water stress condition

Table 6.

Estimates of SCA ( s ij � ) to 20 cotton F 1 hybrid combinations grown in stress treatments under water stress condition p.6