Line tester analysis for different yield and its attributed traits in Upland Cotton (Gossypium hirsutum L.)

Transcription

1 AGRICULTURE AND BIOLOGY JOURNAL OF NORTH AMERICA ISSN Print: , ISSN Online: , doi: /abjna , ScienceHuβ, Line tester analysis for different yield and its attributed traits in Upland Cotton (Gossypium hirsutum L.) 1 Muhammad Sajjad, 1 Muhammad Tehseen Azhar and 1,2* Saif ul Malook 1. Department of Plant Breeding and Genetics, University of Agriculture Faisalabad, Pakistan 2. Kunming Institute of Botany, Chinese Academy of Sciences, China Corresponding Author saifulmalookpbg@gmail.com ABSTRACT Combining ability analysis was made to identify the superior general and specific combining parents for some seed cotton yield and fiber quality traits in upland cotton. Five lines/females (VH-144, MNH-786, MNH-700, FH-159, KZ-181) and three testers/males (VH-232, IUB-212, FH- 118) were crossed to develop 15 F1 hybrids. General combining ability (GCA) and specific combining ability (SCA) mean squares for various quantitative traits were significant. The seed index, fiber fineness, plant height, bolls per plant, sympodial branches, boll weight, seeds per boll, seed cotton yield, ginning out turn percentage, fiber strength and fiber length exhibited nonadditive genetic effects. Parents MNH-786, MNH-700 and KZ-181 among lines and VH-232 from testers were found as good general combiners for most of the traits. Hence these Parents proved worth to be used in hybridization and selection program for extracting desirable plants from segregating population. F1 hybrids MNH-786 VH-232, MNH-700 IUB-212 and KZ-181 VH- 232, by and large, exhibited their superiority for all traits studied and were noted as the best specific combiners. The hybrids may be preferred to improve several quantitative and qualitative traits simultaneously by selection. Keywords: Gossypium hirsutum, combining ability, GCA, SCA, hybrid, heterosis, fiber yield, additive INTRODUCTION Cotton crop is known as silver fiber for Pakistan and produces world s most important fiber. Cotton explicates 7% of value addition in the agriculture, shares 1.5% of GDP and 69% share in foreign exchange earnings (Pak. Economic Survey, ). It is second most valuable oil seed crop as it feeds almost 300 oil expellers; this further enhances its importance. Cotton is mainly grown for fiber and it also has great contribution in edible oil industry, it produces 78% edible oil of Pakistan. Pakistan is the 4 th major producer and 3 rd major consumer. During the cultivated area of cotton was 2835 thousand hectares and total production was thousand bales. Cotton provides basic byproducts like lint, oil, seed hull, meal and linters. As the lint is a major product of cotton but the byproducts are also very important most importantly seed oil which is being to fulfill the needs of cooking oil. Cotton seed hulls are also very useful, which are rich source of proteins and amino acids and are used as a cattle feed they are also being used to cover the soil known as mulching. Short fibers and linter clinging to the seed after ginning, these are removed from the seeds and are used as a great source of cellulose for synthetic fibers, batting for cushions and explosives. Cotton is a delicate crop and lots of resources are wasted on its protection against pests, diseases and proper nourishment. Cotton is an often cross pollinated crop and hold indeterminate type of growth habit. Cotton is a soft, fluffy, staple fiber that grows around the seeds as a boll. The genus of cotton i.e. Gossypium is very diverse and contains 50 species which have basic chromosome number (x) 13. Among all of the 50 species of cotton, two tetraploid and two diploid species have fiber which is known as spin-able fiber usually called as lint. These domesticated species include, (diploid, 2n= 2 X = 26) Gossypium arborium L. and Gossypium herbaceum L. which contributes only about 10 % out of total production of cotton. whereas (tetraploid, 2n= 4x= 52) Gossypium barbadance L. and Gossypium hirsutum L. Gossypium hirsutum L. is the most widely cultivated kind of cotton and accounts for about 90 % of the total production of cotton in the world. It resides a distinctive position in the global trade because it is a very important agricultural and industrial crop. The demand of cotton is increasing at a rapid pace, more than the world s population growth rate, so we have to increase the yield per unit 163

2 area. The use of poor quality seed is one of the primary reasons for lowering the yield per acre in Pakistan. It is essential to develop new high yielding cultivars to improve production level (Jatoi et al. 2011; Puspito et al., 2015). Conventional breeding methods are being used to increase the production of the cotton crop in the current years (Schwartz and Smith 2008). Fiber quality of a peculiar cotton genotype is a combination of different characters like, fiber strength, fiber fineness, staple length and uniformity with uttermost importance (Abbas et al., 2013; Abbas et al., 2015; Ali et al. 2008, Poehlman and Sleper 1995). Studies showed that additive and non-additive genes control the variation in seed cotton yield and its related components (Ashokkumar et al. 2010; Azam et al., 2013). The general combining (GCA) governs the additive gene action and specific combining ability (SCA) governs the non-additive type of gene action (Griffing 1956, Sprague and Tatum 1942). Thus the SCA is important for hybrid crop exploitation while the GCA is practicable for hybridization and selection programs (Ali and Ahsan, 2015; Ali et al., 2014; Ali et al., 2016; Bibi et al., 2012; Jatoi et al. 2011;). The present study were used to evaluate the genetic components of agronomic traits by using line tester analysis and evaluate the lines, testers as well as their crosses for wider adoptability. Line tester analysis could be used to find information about combining ability and provide the information about parents and their F 1 crosses which is useful for breeding program (Shakeel et al. 2012; Ali et al., 2013). It is important to understand the relationship between yield and its components in cotton for selection of superior genotypes in advance breeding program. MATERIAL AND METHODS The experimental material was planted in the research area of the Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad during crop season The experimental material was developed by crossing eight varieties namely FH-118, FH-159, VH-144, VH-232, IUB-212, MNH-700, MNH-786 and KZ-181 according to line tester mating system. The seeds of 8 parents and 15 hybrids were sown in the field in next season in randomized complete block design with three replications. All agronomic practices were followed uniformly. At the time of maturity data on the following characters were taken on individual plant basis: Plant height (cm),boll weight (g), Seed cotton yield (g), Number of bolls per plant, Number of seeds per boll, Seed index (g), Lint index (g), Ginning out turn percentage, Monopodial branches per plant, Sympodial branches per plant. tatistical Analysis : The above stated parameters were statistically analyzed according to the analysis of variance techniques (Steel et al. 1997) to see whether genotypic differences for each of the character significant or not. Combining ability analysis was performed by using line tester analysis, (Kempthorne 1957). RESULTS Plant Height: Mean squares of line tester analysis showed significant differences (P<0.05) among genotypes, parents, crosses, lines, tester and line tester for plant height (Table 1). General combining ability effects for plant height are given in Table 2. Among the lines MNH-786 (3.896) showed maximum positive GCA, so marked as a good general combiner for plant height followed by VH- 144 (2.063), whereas FH-159 (-6.340) has maximum negative GCA which revealed that it is poor general combiner for this character. Among the testers VH-232 (3.543) has maximum and significant GCA for this character which showed that it is a good general combiners, whereas IUB- 212 (-3.200) having maximum negative GCA, showed that it is a poor general combiner for the character under study. The crosses MNH-700 VH-232 (3.285) and FH-159 FH-118 (2.713) showed maximum positive SCA so revealed as good specific combiners, while VH-144 VH-232 ( ) showed maximum negative SCA value for this character followed by FH-159 IUB-212 ( ) which revealed that these hybrids are poor specific combiner for the character plant height (Table 3). GCA variance is lower than SCA variance indicating that the trait is controlled by non-additive gene action (dominant or epistasis) Table 4. Number of bolls per plant: Line tester analysis showed significant differences (P<0.05) for mean squares among genotypes, parents, crosses, lines, tester and line tester for bolls per plant (Table 1). Line MNH-700 showed maximum positive and significant (1.143) GCA, so noted as a good general combiner for the trait number of bolls per plant while, FH-159 (-1.835) showed maximum negative GCA which marked it as poor general combiner. Tester VH-232 (0.598) has maximum GCA for this character 164

3 which showed that it is good general combiners whereas FH-118 showed maximum negative GCA so, noted it poor general combiner (Table 2). Specific combining ability effects for this character are given in (Table 3). MNH-700 IUB-212 (2.834) and MNH- 786 VH-232 (1.546) respectively showed maximum positive and significant SCA so revealed as good specific combiners, while MNH-786 IUB-212 ( ) showed maximum negative and significant SCA value for this character followed by MNH-700 VH-232 (-1.558) which exposed that these hybrids are poor specific combiner for the character. Lower GCA variance indicating that the trait is controlled by non-additive gene action (dominant or epistasis) Table 4. Number of seeds per boll: Genotypes, parents, crosses, lines, tester and line tester for seeds per boll (Table 1) showed significant differences (P<0.05) for mean squares values. Among the lines MNH-786 (5.067) showed maximum positive and significant GCA, so marked as a good general combiner for seeds per boll followed by MNH-700 (0.76), whereas KZ-181 (-3.378) has maximum negative and significant GCA which revealed that it is poor general combiner for this character. Among the testers VH-232 (1.733) has maximum and significant GCA for this character which showed that it is a good general combiners, whereas FH- 118 (-1.93) having maximum negative and significant GCA, showed that it is poor general combiner for the character under study. The crosses VH-144 IUB-212 (2.80) and MNH-786 VH-232 (1.6) showed maximum positive and significant SCA so revealed as good specific combiners, while MNH-700 IUB-212 (-1.86) showed maximum negative and significant SCA value for this character followed by VH-144 VH- 232 (-1.73) which revealed that these hybrids are poor specific combiner for the character seeds per boll (Table 3). GCA variance is lower than SCA variance indicating that the trait is controlled by non-additive gene action (dominant or epistasis) Table 4. Table 1 Analysis of variance for various quantitative and qualitative traits S.O.V. PH NBPP NSPB SBPP MBPP BW SI LI GOT% FL FS FF SCY Replication Genotypes Parents Crosses P. vs Crosses Lines Testers L x T Error Total *Significant, **Highly significant, ns Non-significant Sympodial branches per plant: Mean squares of line tester analysis showed significant differences (P<0.05) among genotypes, parents, crosses, lines, tester and line tester for sympodial branches (Table 1). General combining ability effects for sympodial branches are given in (Table 2). Among the lines MNH-786 (2.39) showed maximum positive and significant GCA, so marked as a good general combiner for sympodial branches per plant followed by MNH-700 (1.26), whereas VH-144 (-1.34) has maximum negative and significant GCA which revealed that it is poor general combiner for this character. Among the testers FH-118 (1.58) has maximum positive and significant GCA for this character which showed that it is a good general combiners, whereas VH-232 (-1.28) having maximum negative and significant GCA, showed that it is poor general combiner for the character under study MNH- 786 FH-118 (7.08) and FH-159 VH-232 (4.17) showed maximum positive and significant SCA so revealed as good specific combiners, while MNH-786 IUB-212 (-5.05) showed maximum negative and significant SCA value for this character followed by KZ-181 VH-232 (-4.6) which revealed that these hybrids are poor specific combiner for the character sympodial branches (Table 3). GCA variance is lower than SCA variance indicating that the trait is controlled by non-additive gene action (dominant or epistasis) Table

4 Table 2 General combining ability estimates of 5 lines and 3 testers for various traits Genotypes PH NBPP NSPB BPP MBPP BW SI LI GOT% FL FS FF SCY Lines VH * * * * 0.132* * MNH * * * 0.600* 0.261* 0.350* * MNH * * * * * * 2.079* * FH * * * * 0.293* 0.233* * 1.055* 0.721* 0.096* 3.275* KZ * * * * * * * S.E. (GCAlines) Testers VH * * * * * * * IUB * * * FH * * * * * * S.E (GCAtester s) * Table 3 Specific combining ability estimates and means of 15 hybrids for various traits Genotypes PH NBPP NSPB SBPP MBPP BW SI LI GOT% FL FS FF SCY VH VH * 0.704* SCA * 2.459* * VH-144 IUB * * VH * * * * 1.219* * FH * MNH VH * * * * * * MNH IUB * * 0.393* 0.347* * 1.530* 2.750* MNH-786 FH * * * * * * MNH-700 VH * * * * 0.481* * * * MNH IUB * * * * 7.327* MNH FH * * * 0.580* FH-159 VH * * * 0.997* 3.275* FH IUB * * * * 0.232* FH-159 FH * 0.151* * * 6.928* KZ-181 VH * 0.625* 0.369* 0.285* * 1.674* * * 9.009* KZ-181 IUB * * * KZ-181 FH * * S.E. (SCA) Table 4 Estimation of variances components for various cotton traits Traits ϭ2gca ϭ2a ϭ2sca ϭ2d ϭ2sca/ ϭ2gca PH NBPP NSPB SBPP MBPP BW SI LI GOT% FL FS FF SCY

5 Monopodial branches per plant: Mean squares of ine tester analysis showed significant differences (P<0.05) among genotypes, parents, crosses, lines, tester and line tester for monopodial branches (Table 1). General combining ability effects for monopodial branches are given in (Table 2). Among the lines MNH-786 (0.6) showed maximum positive and significant GCA, so marked as a good general combiner for monopodial branches per plant followed by KZ-181 (0.27), whereas MNH-700 (-0.7) has maximum negative and significant GCA which revealed that it is poor general combiner for this character. Among the testers IUB-212 (0.26) has maximum positive and significant GCA for this character which showed that it is a good general combiners, whereas FH-118 (-0.49) having maximum negative and significant GCA, showed that it is poor general combiner for the character under study. VH- 144 IUB-212 (1.73) and KZ-181 FH-118 (0.66) showed maximum positive and significant SCA so revealed as good specific combiners, while KZ-181 IUB-212 (-1.29) showed minimum significant SCA value which revealed its poor specific combiner for this trait (Table 3). GCA variance is lower than SCA variance indicating that the trait is controlled by nonadditive Boll weight: Mean squares of line tester analysis showed significant differences (P<0.05) among genotypes, parents, crosses, lines, tester and line tester for boll weight (Table 1). General combining ability effects for boll weight are given in (Table 2). Among the lines FH-159 (0.29) showed maximum positive and significant GCA, so marked as a good general combiner for boll weight followed by MNH- 786 (0.26), whereas MNH-700 (-0.2) has maximum negative and significant GCA which revealed that it is poor general combiner for this character. Among the testers IUB-212 (0.05) has maximum positive and significant GCA for this character which showed that it is a good general combiners, whereas VH-232 (- 0.06) having maximum negative and significant GCA, showed that it is poor general combiner for the character under study. VH-144 VH-232 (0.70) and KZ-181 VH-232 (0.369) showed maximum positive and significant SCA so revealed as good specific combiners, while VH-144 FH-118 (-0.69) showed maximum negative and significant SCA value for this character followed by KZ-181 IUB-212 (-0.62) which revealed that these hybrids are poor specific combiner for the character boll weight (Table 3). GCA variance is lower than SCA variance indicating the trait is controlled by non-additive gene action (dominant or epistasis) Table 4. Seed index: Mean squares of line tester analysis showed significant differences (P<0.05) among genotypes, parents, crosses, lines, tester and line tester for seed index (Table 1). General combining ability effects for seed index are given in (Table 2). Among the lines MNH-786 (0.35) showed maximum positive and significant GCA, so marked as a good general combiner for seed index followed by FH-159 (0.23), whereas MNH-700 (-0.14) has maximum negative and significant GCA which revealed that it is poor general combiner for this character. Among the testers VH-232 (0.053) has maximum positive and significant GCA for this character which showed that it is a good general combiners, whereas FH-118 ( ) having maximum negative and significant GCA, showed that it is poor general combiner for the character under study. The crosses MNH-786 IUB- 212 (0.33) and MNH-700 VH-232 (0.30) showed maximum positive and significant SCA so revealed as good specific combiners, while MNH-786 FH-118 (- 0.44) showed maximum negative and significant SCA value for this character followed by FH-159 VH-232 (-0.35) which revealed that these hybrids are poor specific combiner for the character seed index (Table 3). GCA variance is lower than SCA variance indicating that the trait is controlled by non-additive Lint index: Mean squares of line tester analysis showed significant differences (P<0.05) among genotypes, parents, crosses, lines, tester and line tester for lint index (Table 1). General combining ability effects for lint index are given in (Table 2). Among the lines FH-159 (0.048) showed maximum positive and significant GCA, so marked as a good general combiner for lint index followed by VH-144 (0.037), whereas MNH-786 (-0.078) has maximum negative and significant GCA which revealed that it is poor general combiner for this character. Among the testers VH-232 (0.032) has maximum positive and significant GCA for this character which showed that it is a good general combiners, whereas IUB-212 ( ) having maximum negative and significant GCA, showed that it is poor general combiner for the character under study. The crosses VH-144 VH- 232 (0.244) and MNH-700 IUB-212 (0.243) showed maximum positive and significant SCA so revealed as good specific combiners, while VH-144 FH-118 (-0.48) showed maximum negative and significant SCA value for this character followed by MNH-700 VH-232 (-0.47) which revealed that these 167

6 hybrids are poor specific combiner for the character lint index (Table 3). GCA variance was lower than SCA variance and SCA/ GCA ratio greater than unity which indicated the predominance of non-additive Ginning out turn percentage: Mean squares of line tester analysis showed significant differences (P<0.05) among genotypes, parents, crosses, lines, tester and line tester for GOT % (Table 1). General combining ability effects for ginning out turn percentage are given in (Table 2). Among the lines KZ-181 (0.606) showed maximum positive GCA, so marked as a good general combiner for ginning out turn percentage. Whereas MNH-700 (-0.267) has maximum negative and significant GCA which revealed that it is poor general combiner for this character. Among the testers FH-118 (0.398) has maximum positive and significant GCA for this character which showed that it is a good general combiners, whereas VH-232 (-0.348) having maximum negative and significant GCA, showed that it is poor general combiner for the character under study. The crosses FH-159 IUB-212 (1.44) and MNH-786 FH-118 (1.152) showed maximum positive and significant SCA so revealed as good specific combiners, while MNH-786 IUB-212 ( ) showed maximum negative and significant SCA value for this character followed by FH-159 VH-232 (-1.349) which revealed that these hybrids are poor specific combiner for the character GOT % (Table 3). GCA is lower than SCA variance indicating that the trait is controlled by non-additive genes (dominant or epistasis) Table 4. Fiber length: Mean squares of line tester analysis showed significant differences (P<0.05) among genotypes, parents, crosses, lines, tester and line tester for fiber length (Table 1). FH-159 (1.055) showed maximum positive GCA, so marked as a good general combiner for fiber length. Whereas MNH-700 (-0.496) has maximum negative and significant GCA which revealed that it is poor general combiner for this character. Among the testers IUB- 212 (0.503) has maximum positive and significant GCA for this character which showed that it is a good general combiners, whereas VH-232 (-0.407) having maximum negative and significant GCA, showed that it is poor general combiner for the character under study. The crosses KZ-181 VH-232 (1.67) and MNH-786 IUB-212 (1.53) showed maximum positive and significant SCA so revealed as good specific combiners, while FH-159 IUB-212 (-1.58) showed maximum negative and significant SCA value for this character followed by VH-144 VH-232 (-1.309) which revealed that these hybrids are poor specific combiner for the character fiber length (Table 3). GCA variance is lower than SCA variance indicating that the trait is controlled by non-additive Fiber strength: Mean squares of line tester analysis showed significant differences (P<0.05) among genotypes, parents, crosses, lines, tester and line tester for fiber strength (Table 1). General combining ability effects for fiber strength are given in (Table 2). Among the lines MNH-700 (2.07) showed maximum positive GCA, so marked as a good general combiner for fiber strength. Whereas KZ-181 (-2.323) has maximum negative and significant GCA which revealed that it is poor general combiner for this character. Among the testers FH-118 (0.496) has maximum positive and significant GCA for this character which showed that it is a good general combiners, whereas VH-232 (-0.327) having maximum negative and significant GCA, showed that it is poor general combiner for the character under study. The crosses FH-159 VH-232 (3.275) and MNH-786 IUB-212 (2.75) showed maximum positive and significant SCA so revealed as good specific combiners, while MNH-786 VH-232 (-2.70) showed maximum negative and significant SCA value for this character followed by MNH-700 VH- 232 (-1.95) which revealed that these hybrids are poor specific combiner for the character fiber strength (Table 3). GCA variance is lower than SCA variance indicating that the trait is controlled by non-additive Fiber fineness: Mean squares of line tester analysis showed significant differences (P<0.05) among genotypes, parents, crosses, lines, tester and line tester for fiber fineness (Table 1). General combining ability effects for fiber fineness are given in (Table 2). Among the lines VH-144 (0.132) showed maximum positive GCA, so marked as a good general combiner for fiber fineness. Whereas FH-159 (0.096) has maximum negative and significant GCA which revealed that it is poor general combiner for this character. Among the testers IUB-212 (0.302) has maximum positive and significant GCA for this character which showed that it is a good general combiners, whereas VH-232 (-0.290) having maximum negative and significant GCA, showed that it is poor general combiner for the character under study. The crosses MNH-700 FH-118 (0.58) and 168

7 KZ-181 IUB-212 (0.465) respectively showed maximum positive and significant SCA so revealed as good specific combiners, while MNH-700 IUB- 212 (-0.53) showed maximum negative and significant SCA value for this character followed by KZ-181 IUB-212 (-0.46) which revealed that these hybrids are poor specific combiner for the character fiber fineness (Table 3). GCA variance is lower than SCA variance indicating that the trait is controlled by non-additive gene action (dominant or epistasis) Table 4. Seed cotton yield: Mean squares of line tester analysis showed significant differences (P<0.05) among genotypes, parents, crosses, lines, tester and line tester for seed cotton yield (Table 1). General combining ability effects for seed cotton yield are given in (Table 2). Among the lines FH-159 (3.275) showed maximum positive GCA, so marked as a good general combiner for seed cotton yield. Whereas VH-144 (-4.334) has maximum negative and significant GCA which revealed that it is poor general combiner for this character. Among the testers VH-232 (0.269) has maximum positive and significant GCA for this character which showed that it is a good general combiners, whereas IUB-212 ( ) having maximum negative and GCA, showed that it is poor general combiner for the character under study. The crosses MNH-786 FH-118 (9.966) and KZ-181 VH-232 (9.009) showed maximum positive and significant SCA so revealed as good specific combiners, while VH-144 FH-118 ( ) showed maximum negative and significant SCA value for this character followed by MNH-786 VH- 232 (-8.268) which revealed that these hybrids are poor specific combiner for the character seed cotton yield (Table 3). GCA variance is lower than SCA variance indicating that the trait is controlled by nonadditive DISCUSSION For any genetic change to occur in a plant character, either through natural selection, genetic variation in the character must be present. Thus availability of information on the relative contribution of different genetic components of variation in a character is essential before subjecting the breeding population to selection. Biometric analysis of the data revealed that variation in plant height, number of sympodial branches, number of bolls, boll weight, number of seeds per boll, seed index, seed cotton yield, lint percentage, fiber length, fiber strength and fiber fineness were genetically manifested. The genetic variability in each character was further partitioned into various casual components i.e. due to general and specific combining ability as out lined by Kempthorne (1957). The relative contribution of general and specific combining ability provided some understanding on the genetic control of the character. It was revealed that non additive genetic effects were important to control plant height, number of bolls, sympodial branches, boll weight, seed index, seed cotton yield fiber strength, fiber length and lint percentage as had been discussed by Pavasia et al. (1999), Subhan et al. (2000), Amir et al., (2012) and Neelima et al. (2004), unlike the results obtained by the studies of Carvalho et al. (1995) and Khan et al. (1999). For the number of bolls per plant non-additive genetic effects were important, similar results were found by Murtaza et al. (1995) and Neelima et al. (2004) while non-additive effects were showed for the characters by the findings of Khan et al. (1992) and Ahmed et al. (1997). For boll weight non-additive genetic effects appeared to be predominant, this confirms the finding of Khan et al. (1992) and Murtaza et al. (1995) while this result differ from those showed by Ahmad and Azhar (1999) and Khan et al. (1999). For seed cotton yield non-additive genetic component appeared to be predominant, this confirms the finding of Khan et al. (1992) and Murtaza et al. ( 1995) while Keerio et al. (1995) and Ahmed et al. (1997) showed that non additive effects controlled the seed cotton yield. For lint percentage non-additive genetic effects were important similar results were found by Sayal and Sulemani (1996) while opposite results were showed by Khan et al. (1991). For fiber fineness non-additive genetic effects were important which confirms the finding of Khan et al. (1991), while finding of Rajan et al. (1999) and Banumathy and Patil (2000) reflected it as controlled by additive gene effects. For fiber strength, non-additive genetic components appeared to be predominant this confirms the finding of Rajan et al. (1999), Banumathy and Patil (2000), while Murtaza et al. (2004) found that additive effects controlled the character. For fiber length non-additive genetic components appeared to be predominant this confirms the finding of Banumathy and Patil (2000) whereas Rajan et al. (1999) showed that fiber length is controlled by additive gene action. The present results may provide a guideline to a breeder while handling the breeding material. It had been reported that the characters controlled by non-additive properties of genes may have low heritability (Falconer and Mackay (1996), suggesting that the 169

8 segregating populations are not amenable to selection pressure in early generations like F 2 and thus selection must be delayed till the genes are established in the breeding population. By contrast, the characters might have high heritability which were controlled by the genes acting additively, and therefore can easily be identified from the F 2 generation (Falconer and Macky 1996). The study of general combining ability is useful in classifying parental lines in term of their hybrid performance. The comparison of the performance of eight parents for their general combining ability shows that among the lines MNH-786 proved to be good general combiner for monopodial branches, fiber length and lint percentage, KZ-181 proved to be good general combiner for number of bolls, fiber fineness. MNH-700 and MNH-786 proved to be good general combiners for sympodial branches. MNH-786 proved to be good general combiner for boll weight and seed cotton yield. MNH-786 proved to be good general combiner for plant height, number of seeds per boll and seed index. Among testers VH-232 proved to be good general combiner for plant height, fiber strength and fiber length, VH-232 and IUB-212 proved to be good general combiners for plant height, number of bolls, monopodial branches, sympodial branches, number of seeds, seed index, seed cotton yield and lint percentage. Thus on the basis of these results that it is concluded that three parental lines i.e. MNH-786, MNH-700, KZ-181 may hold good promise to a breeder for exploiting variability in the characters investigated here. It had been reported that parents having good GCA for a particular character are expected to yield good hybrids (Ayub et al. 1991, Khan et al, 1991, Irfanullah et al. 1994) and this behavior of the parents studied here was found to be valid in the present studies e.g. MNH-786, MNH-700, KZ-181 which were good combiners for plant height and produced good hybrids i.e. MNH-786 VH-232, MNH-700 IUB-212, KZ-181 VH-232. Parents MNH-786, MNH-700, KZ-181 which displayed best general combining ability for number of bolls, seemed to have nicked well to yield best cross combinations, MNH-786 VH-232, MNH-700 IUB-212, MNH-786 IUB-212. For seed index, parents MNH-786 and FH-159 showed their best general combining ability and they yielded best varietal combination FH-159 FH-118, MNH-786 IUB-212 and MNH-700 VH-232. For ginning out turn percentage KZ-181 exhibited good general combining ability and the crosses MNH-786 FH- 118 and FH-159 IUB-212 gave the best performance. For fiber length KZ-181 was the best general combiner and when it was crossed with FH- 118 the combination yielded the best performance. Variety MNH-700 being best general combiner for fiber strength nicked well with VH-232. For fiber fineness KZ-181 best produced varietal combination with IUB-212. By contrast, varieties FH-159 and IUB-212 showed poor general combining ability for fiber length, but they produced best cross combination, KZ-181 IUB-212.For number of bolls varietal crosses FH-159 FH-118 appeared to be promising combination but these crosses originated from parents having poor general combining ability. For fiber strength and fiber length the cross combination VH-144 FH-118 and KZ-181 FH-118 were the best respectively, and had parents with poor combining ability. For seed index varieties VH-144, IUB-212 and KZ-181 showed poor GCA but they yielded best cross combination for the character. For seed cotton yield varietal combination FH-159 FH-118 displayed best but these crosses had originated from parents those were poor general combiner. For the fiber fineness KZ-181 and IUB-212 were revealed to have poor general combining ability but they yielded best cross combination KZ-181 IUB-212. Thus from all the results it seems that it is not always necessary that good hybrids are produced by parents having high GCA, sometimes the parents with poor GCA nick well to produce potential hybrids as had been examines in the present study. Similar opinion had been made by Khan et al. (1991) in their studies. Greater contribution of lines towards variation in plant height, number of seeds per boll and seed index indicates the predominant maternal influence for these traits. By contrast, lower contribution of testers and higher contribution of L T interaction appear to be more important for variation in number of bolls per plant, number of sympodial branches per plant, number of monopodial branches per plant, boll weight, lint index, ginning out turn percentage, fiber length, fiber strength, fiber fineness and seed cotton yield revealed the preponderance of interaction effects for these traits, so the contribution of maternal, paternal and interaction effects studied in this study were similar to the results obtained by Subhan et al. (2000). CONCLUSIONS It was concluded that MNH-786, MNH-700 and KZ- 181 among lines and VH-232 from testers were found as good general combiners for most of the traits. 170

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