Research Article

Estimation of Combining Ability for Within-Boll Yield Components in Upland Cotton (Gossypium hirsutum)

Mishal Bano1, Amir Shakeel1, Waqar-ul-Haq1, Muhammad Nouman Khalid1*, Nadia Hussain Ahmad2, Muhammad Sajid Sharif3, Sadia Kanwal2, Muhammad Asim Bhutta2, Amna Bibi2 and Ifrah Amjad1

1Department of Plant Breeding and Genetics, University of Agriculture Faisalabad, Pakistan; 2Cotton Research Institute, Multan, Pakistan; 3Department of Plant Breeding and Genetics, Islamia University of Bahawalpur, Pakistan.

Received | October 04, 2022; Accepted | November 25, 2022; Published | February 15, 2023

*Correspondence | Muhammad Nouman Khalid, Department of Plant Breeding and Genetics, University of Agriculture Faisalabad, Pakistan; Email: noumankhalidpbg@gmail.com

Citation | Bano, M., A. Shakeel, W. Haq, M.N. Khalid, N.H. Ahmad, M.S. Sharif, S. Kanwal, M.A. Bhutta, A. Bibi and I. Amjad. 2023. Estimation of combining ability for within-boll yield components in upland cotton (Gossypium hirsutum). Sarhad Journal of Agriculture, 39(1): 174-181.

DOI | https://dx.doi.org/10.17582/journal.sja/2023/39.1.174.181

Keywords | Cotton, F1, Combing ability, Gene action

Copyright: 2023 by the authors. Licensee ResearchersLinks Ltd, England, UK.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Introduction

The usage of inferior cotton cultivars is one of the key causes of Pakistan’s low cotton production per unit area (Zafar et al., 2022a; Laghari et al., 2022). Cotton production may be increased by developing high-yielding varieties and hybrids with higher yield potential, good fiber quality, and disease resistance (Chaudhry et al., 2022). All of the yield-related traits in cotton are linked to one another (Zafar et al., 2020). Any modification in one feature has a significant impact on the others. It is quite beneficial for breeders to have all qualitative and quantitative data related to the development of good yielding cultivars (Hassan et al., 2022).

Combining ability analysis helps the breeders to collect information about the potential of inbreed lines (Zafar et al., 2022b). The combining ability is utilized in plant breeding programs to assess the performance of lines in the development of hybrid combinations (Perviz et al., 2016). The performance of a line through a series of crosses is referred to as general combining ability (GCA), whereas the hybrid performance through a specific combination of genetic factors is referred to as specific combining ability (Tulu et al., 2021). GCA is induced by additive genes, whereas specific combining ability is caused by non-additive genes that influence traits (Baloch et al., 1993; Manan et al., 2022).

Introduction of new cultivars with modified genetic base is very important step in plant breeding. The lower genetic base creates problem for researchers (Qin et al., 2008). Therefore, it is very important for a breeder to have knowledge about the variations and inheritance of different traits. The Line×Tester analysis is also helpful to provide knowledge about GCA and SCA of parents and crosses (Manan et al., 2022). A thorough investigation of the genetic process for controlling cotton plant properties under various environmental situations is also required for achieving these goals. Given the foregoing, a research project was designed to examine the genetic potential of several genotypes in the Faisalabad, Pakistan, climate.

The experiment was performed to achieve the following objectives:

• To evaluate the GCA of the parents as well as determine the hybrid which gives good results for within-boll yield components.
• To study the gene action involved in the inheritance of the traits.

Materials and Methods

The research was carried out in the Department of Plant Breeding and Genetics field area at the University of Agriculture, Faisalabad, Pakistan in 2020-21. The plant material for research was collected from the department. The experimental material consisting of three testers (CRS-2, BS-80, and CIM-595) and three lines (FH-342, VH-329, and Tarzan-05) were sown in November 2020 in a glasshouse to produce the F1 generation. All the genotypes were sown at optimum conditions like the temperature, proper light, and humidity in a glasshouse for a maximum germination. The seed was sown in earthen pots. Three lines were crossed with three testers at the time of flowering. Six parents along with nine crosses were planted in May 2021 in the field in two replications by using a randomized complete block design with 75cm spacing between lines and 30cm spacing between plants. All the precautionary measures were made to avoid the contamination of genetic material. For data collection, 5 plants of each genotype from each replication were selected randomly. Proper agronomic practices like weeding, thinning, hoeing, proper irrigation, and plant protection measures were applied from sowing to picking. The list of parents and crosses is given below:

At maturity, data was collected from each replication for following traits on the individual plant bases in the field and laboratory. PH: plant height (cm), SB/P: sympodial branches/plant, MB/P: monopodial branches/plant, FFN/P: first fruiting nodes, NB/P: number of bolls per plant, BW: boll weight (g), NS/B: number of seeds per boll, SCY/P: Seed cotton yield/plant (g), LI: lint index (g), L%: lint percentage (%), SI:seed index (g), SD: seed density (g/cm³), SV: seed volume (cm³), FF: fiber fineness (µg/inch), FS: fiber strength (g/tex), and FL:fiber length (mm).

Statistical analysis

The collected data were analyzed through analysis of variance (Steel et al., 1997) by using statisticx 8.1 to determine the significant differences among genotypes under study. For the estimation of combining ability effects, the analysis was carried out by following Kempthorne (1957) by DOS Box.

 

 

 

General combining ability effects

Line gi = {(xj../tr) – (x../ltr)}

Testers gt = {(xj../lr) – (x../ltr)}

Where, l= number of lines; t= number of testers; r= number of replications; xii= total number of F1 resulting from ith lines with all testers; x… = total of all crosses.

Estimation of SCA effects

Si = {(xij.)/r - (xi../tr) – (x.j./lr) + x…/ltr}

Where; Xij = total number of F1 resulting from ith lines with all testers with jth tester; Xi = total of all crosses of ith line with all testers; Xj = total of all crosses of jth tester with all lines.

Contribution of lines, testers and their interaction to total variance

Contribution of lines = {SS (l)/ SS (crosses)} × 100

Contribution of testers = {SS (t)/ SS (crosses)} × 100

Contribution of interaction = {SS (l)/ SS (l × t)} × 100

Results and Discussion

Genetic change in plant character through natural selection plays a crucial role to create genetic variation in traits (Bashir et al., 2022). Results of ANOVA depicted that all the genotypes were significantly different for the most of the attributes under study (Table 1). Different components of genetic variation in characters hold valuable information that helps in the selection of the breeding population (Zafar et al., 2021; Yali, 2022). Results of line × tester ANOVA manifested that FS, FL, BW, FF, L%, NB/P, FFN/P, MB/P, and SB/P exhibit significant differences among parents and their crosses that showed existence of genetic variability (Table 2). Kempthorne (1957) further categories the genetic variability into general combining ability (GCA) and specific combining ability (SCA) that helps us to understand the genetic control of character.

For hybrid development combining ability studies is a useful tool for parental lines selection (Solongi et al., 2019). Further, Neelima et al. (2004) revealed six parents for their general combining abilities for different characters in cotton. The results of this research work indicated that parent line Tarzon-05 proved to be a very good general combiner for PH and SD. VH-329 showed good general combining ability for number of SB/P and MB/P, NB/P, FFN/P, SCY/P and L%. The line, FH-342 found to be a good combiner for BW. These results indicated that these three lines Tarzon-05, VH-329 and FH-342 have desired traits for a breeder to exploit variability in the traits which are investigated here. Among the testers, CIM-595 proved to be a good general combiner for NB/P, MB/P, and FFN/P, SCY/P and L%. CRS-2 found to be good combiner for PH, BW, and SD (Table 3). Similarly, Munir et al. (2016) reported the same results as the parents proved to be good general combiners. The parents which have good GCA for a specific trait are expected to give good yield in cross combinations (Khan et al., 2017). This trend is found in present studies for example Tarzon-05 from lines and CRS-2 from testers indicated good general combining ability for PH and produced desired hybrids. So, these parents are supposed to be used in future breeding programs. Results of SCA of all the crosses are presented in Table 4. Among crosses, Tarzon-05 × BS-80 proved to be very good hybrids for PH. Both type of gene actions i.e., additive and non-additive found to be important for PH (Khan, 2017; Mishra et al., 2015). For MB/P non-additive type of gene action is more important than additive type of gene action. The same findings were reported by (Khan et al., 2017; Khokhar et al., 2018). These branches give bushy look to the plants which result in slow boll formation.

 

 

 

Table 5: Combined table for estimation of GCA variance (σ2GCA), SCA variance (σ2SCA) and ratio of σ2GCA/σ2SCA.

	σ2GCA	σ2SCA	σ2GCA/σ2SCA	σ2A	σ2D
PH	7.5388	84.4974	0.089	30.1554	337.9895
SB/P	1.5323	17.1585	0.0893	6.1293	68.6339
MB/P	-0.0052	0.2056	-0.0253	-0.0206	0.8224
FFN/P	0.0554	2.1288	0.0260	0.2218	8.5153
NB/P	-0.0052	0.2056	-0.0253	-0.0206	0.8224
BW	0.0097	0.0536	0.1809	0.0388	0.2146
SCY/P	-30.7565	644.448	-0.04772	-123.0262	2577.791
NS/B	-0.0932	1.6553	-0.0563	-0.3729	6.6210
L%	0.7805	-0.2153	-3.6252	3.1222	-0.8610
LI	0.0017	0.0640	0.0266	0.0067	0.2559
FF	0.0799	0.2361	0.3384	0.3194	0.9444
FS	-0.0097	0.3028	-0.03203	-0.0386	1.2111
FL	-0.6146	7.7885	-0.0789	-2.4585	31.1547
SI	0.0356	-0.0280	-1.2714	0.1425	-0.1121
SV	-0.0779	-0.4685	0.1663	-0.3115	-1.8741
SD	0.0020	0.0121	0.1653	0.0078	0.0485

For more details and abbreviation see Table 1.

 

Results of GCA, SCA variances and their ratio is presented in Table 5. For SB/P non-additive type of gene action is important than additive type of gene action. Subhan et al. (2003) reported that non-additive type of gene action is more important for SB/P branches. More the SB/P more will be the fruiting, because plant enters into the fruiting stage earlier. The tester CIM-595 and parental line VH-329 indicated positive GCA values which revealed that the both parents are best general combiner for number of bolls per plant. For this trait non-additive genes are more important than additive genes. The findings of present study related to the findings of (Lakho et al., 2016; Khan et al., 2017; Khokhar et al., 2018). For FF non-additive genetic effects were more important which relate to the findings of (Khan et al., 2017). FL was also controlled by non-additive genes which confirm the results of (Isong et al., 2019). FS is mostly reported to be controlled by non-additive type of gene action which is also confirmed in the previous studies by the (Gungor and Efe, 2016; Vekariya et al., 2017). Fiber properties are very important in outcome of spinning process. In some traits like PH and FL, the male (testers) contribution was found to be dominant and in case of SCY/P, SB/P and NB/P, the female (lines) contributions were found to be dominant which identical to the findings of (Khokhar et al., 2018). The parental lines which showed good general combining ability for a specific trait expected to produce good hybrids (Khan et al., 2017). In the present, study critical comparison of cross combinations gives some interesting information. Some crosses with one parent have good GCA value and other parent have low GCA value for a particular trait showed best combinations for that trait. For example, FH-342 and CIM-595 showed poor combining ability for PH but they produced best combination with highly significant SCA value for PH. FH-342 and CIM-595 cross combination was very good combination SD but this cross produced from parents with poor combining ability. So, it is cleared from these results that parents with poor combining abilities can produce desired hybrids for a specific trait which confirms the findings of (Solongi et al., 2019).

Testers i.e., CIM-595 plays an important role towards variation in MB/P, FFN/P, NB/P, SCY/P, and FS. The SI is influenced by additive genetic variance (Sahin et al., 2018). This showed similar results to this research about SI. The contribution of both parents was found to be greater for variation in PH, MB/P and SB/P, NB/P, BW, SCY/P, and SD which relate to the results of (Isong et al., 2019).

Conclusions and Recommendations

Cotton genotype VH-329 recorded maximum GCA effects followed by Tarzon-05, whereas the hybrid combination for the number of nodes for first fruiting branch, boll weight, fibre length, and seed cotton yield/plant. VH-329 × CRS-2 was determined to be a good specific combiner. Except seed index, all the characters of these genotypes of cotton indicated variance of SCA greater than variance of GCA, when variance of SCA is higher than variance of GCA it means non-additive gene action is dominant over additive gene action. So heterosis breeding will be more fruitful than varietal development. Selection must be delayed in breeding populations because non - additive genes have low heritability. Parents which have good general combining ability for specific traits and the cross combinations with good specific combining ability are supposed to be used in future breeding programs for the improvement of these traits in cotton.

Novelty Statement

VH-329×CRS-2 was observed as a good specific combiner for the number of nodes for first fruiting branch, boll weight, fibre length, and seed cotton yield/plant.

Author’s Contribution

Mishal Bano: Conducted the research and wrote-up the manuscript

Amir Shakeel: Supervisor and provided guidelines for research study.

Waqar-ul-Haq: Helped in data collection

Muhammad Nouman Khalid: Helped in manuscript write-up

Nadia Hussain Ahmad: Proofread the manuscript

Muhammad Sajid Sharif: Helped in manuscript write-up

Sadia Kanwal: Helped in data analysis

Muhammad Asim Bhutta: Provided technical guidelines during research work

Amna Bibi: Helped in relevant literature

Ifrah Amjad: Helped in format setting

Conflict of interest

The authors have declared no conflict of interest.

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