Estimation of Correlation and Path Analysis of Various Yield and Related Parameters in Cotton (Gossypium hirsutum L.)  

Jehanzeb Farooq1 , Muhammad Anwar1 , Muhammad Rizwan1 , Muhammad Riaz1 , Khalid Mahmood1 , Shahzadi Mahpara2
1. Assistant Research Officer, Cotton Research Institute, AARI, Faisalabad, Pakistan
2. Faculty of Agricultural Sciences, Ghazi University, Dera Ghazi Khan, Pakistan
Author    Correspondence author
Cotton Genomics and Genetics, 2015, Vol. 6, No. 1   doi: 10.5376/cgg.2015.06.0001
Received: 20 Feb., 2015    Accepted: 05 Apr., 2015    Published: 10 Apr., 2015
© 2015 BioPublisher Publishing Platform
This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Preferred citation for this article:

Farooq et al., 2015, Estimation of Correlation and Path Analysis of Various Yield and Related Parameters in Cotton Gossypium hirsutum L., Cotton Genomics and Genetics, Vol.6, No.1 1-6 (doi: 10.5376/cgg.2015.06.0001)

Abstract

The present research work was designed to estimate genotypic and phenotypic correlation coefficients and path analysis at the genotypic level between seed cotton yield and yield contributing traits in 18 cotton cultivars. The material was sown on 15th of May to observe association among yield and its related traits. Heritability was estimated to determine the selection criteria under normal growing conditions. The values of phenotypic coefficient of variation (PCV%) were higher in magnitude than the genotypic coefficient of variation (GCV%) for all the traits. Heritability (broad sense) revealed higher estimates for all traits like plant height (98%), cotton leaf curl virus (CLCuV%) (96.8%), nodes to first fruiting branch (95%), bolls per plant (91.5%), sympodia per plant (88.8%), yield (88%) monopodia per plant (84.7%) and for boll weight (82.3%).The results of phenotypic and genotypic correlation showed that sympodia per plant showed positive significant correlation with boll per plant, boll weight and yield at both genotypic and phenotypic levels. Boll weight showed strong association with the yield at both levels. Path coefficient analysis revealed that all traits influenced directly and positively on yield except for bolls per plant. The traits showing strong association along with higher heritability may be considered for selection in future breeding endeavors.

Keywords
Broad sense heritability; Seed cotton yield; Cotton leaf curl virus; Phenotypic correlations; Sympodia per plant
Cotton (Gossypium hirsutum L.) is one of the most important cash crops in Pakistan and is being grown in warmer regions of the country (Riaz et al., 2013). A huge population of the country is engaged in the fields of agriculture, ginning factories, textile mills, and busi­ness (Imran et al., 2011). Cotton also plays a pivotal role in enhancing Pakistan’s economy being the major source of earning foreign exchange, thus, it is considered as the back bone of the economy of Pakistan (Farooq et al., 2014). The development of cultivars possessing tolerance to cotton leaf curl virus (CLCuV), along with greater yield potential are the prime objectives of a cotton breeder (Farooq et al., 2014).
Yield is a complex trait which is influenced by both genetic and climatic factors. Interaction among both these factors makes the selection procedure tough. For obtaining desirable cotton genotypes information regarding interaction between yield and related components assist the breeders in the choice of desirable genotypes. The association analysis provides a good guide to envisage the corresponding change which occurs in one parameter at the expanse of the proportionate change in the other (Ahmad et al., 2008).
Genetic variation andpositive association of seed cotton yield with yield components was also observed in hirsutum cultivars (Mendez-Natera et al., 2012). DeGui et al. (2003) found that the higher yield in cotton cultivars was mainly due to more number of bolls per plant. For selection of yield and related parameters, understanding about correlation of yield and its relevant traits is a prerequisite. The present study was designed to investigate the genetic potential of different cotton cultivars for yield and relationship of seed cotton yield with yield related traits.
1 Results
The mean performance of 18 genotypes for yield and some yield related traits is given in Figure 1~ Figure 5. All traits showed higher values of phenotypic coefficient of variance than genotypic coefficient of variance (Table 1). While studying broad sense heritability it is depicted that high estimates are present for all traits like plant height (98%), CLCuV% (96.8%), nodes to first fruiting branch (95%), bolls per plant (91.5%), sympodia per plant (88.8%), yield (88%) monopodia per plant (84.7%) and for boll weight (82.3%). Analysis of variance revealed that significant differences are present among all genotypes for all traits studied (Table 1). The results of GCV and PCV, and heritability are given in Table 1.

 

Figure 1 Graphical representation of plant height in 18 genotypes of cotton

 

Figure 2 Graphical representation of sympodia per plant in 18 genotypes of cotton

 

Figure 3 Graphical representation of bolls per plant in 18 genotypes of cotton

 

Figure 4 Graphical representation of boll weight in 18 genotypes of cotton

 

Figure 5 Graphical representation of seed cotton yield in 18 genotypes of cotton

 

Table 1 Mean squares, genotypic and phenotypic coefficients of variation and heritability for various traits of 18 genotypes/strains of cotton

The results of phenotypic and genotypic correlation showed that nodes to 1st fruiting branch and monopodia per plant has no significant positive association with any trait at both genotypic and phenotypic levels, sympodia per plant showed positive significant correlation with boll per plant, boll weight and yield at both genotypic and phenotypic levels, Plant height showed no positive significant association with any of the traits. Boll weight showed strong association with the yield at both levels. CLCuD showed negative association with yield at both levels (Table 2; Table 3).

 

Table 2 Genotypic correlation coefficients of various traits of 18 genotypes/strains of cotton

 

Table 3 Phenotypic correlation coefficients of various traits of 18 genotypes/strains of cotton

Path coefficient analysis revealed that all traits influenced directly and positively on yield except for bolls per plant (Table 4). Nodes to first fruiting branch showed positive indirect response to on yield while all other traits indirectly showed negative response to yield. Sympodia per plant positively and indirectly influenced the yield through, plant height, boll weight and CLCuD while all other traits showed negative indirect effect on yield. Bolls per plant showed negative direct effect on yield while it showed positive indirect effect on yield via Nodes to first fruiting bud per plant, Plant height, Boll weight and CLCuV but for monopodia per plant it showed negative indirect effect. For plant height the characters like sympodia per plant and CLCuV positive indirect effect on yield while all other characters showed negative indirect response to yield. For Boll weight the characters like Nodes to first fruiting, sympodia per plant, Plant height, Boll weight and CLCuV showed positive indirect effect on yield while all other characters responded negatively and indirectly. CLCuV showed negative indirect response to yield via all characters except sympodia per plant and plant height (Table 4).

 

Table 4 Direct (diagonal) and indirect (off-diagonal) effects of various plant traits in cotton

2 Discussion
Presence of sufficient genetic variation is a pre requisite for an effective breeding programme to study the nature and strength of association among yield related traits (Irum et al., 2011). In this study the sufficient amount of genetic variation is quite evident from analysis of variance for all traits. PCV% was higher in magnitude than GCV% for all the traits which are in accordance with the results of Mendez-Natera et al., (2012). Ali et al., (2009) reported higher values of GCV and PCV% for seed cotton yield. Heritability is the measure of phenotypic variance computed from genetic variance (Songsri et al., 2008). High estimates of heritability were present in all the traits in present study. Farooq et al. (2014) reported higher estimates for boll weight, moderate estimates for nodes to 1st fruiting branch, monopodia per plant and sympodia per plant. Basbeg and Gencer (2004) reported lower estimates for bolls per plant and seed cotton yield which are in contradiction to the present research. Similarly, Mendez-Natera et al. (2012) found moderate estimates for plant height, and low values for bolls per plant, boll weight and seed cotton yield which also contradict the present results.
Early generation selection will be more useful in all the traits showing higher values of broad sense heritability (Farooq et al., 2014). The higher values of narrow heritability show an additive genetic effect that’s why the adoption of selection procedure for the traits showing higher estimates is much easier (Soomro et al., 2010). Environmental factors play a vital role in the development of phenotypic correlations (Ali et al., 2009).
Phenotypic correlation can be computed from the net result of genotypic and environmental correlations. In the present study, the seed cotton yield has significant positive association with sympodia per plant, bolls per plant and boll weight, while it has negative association with monopodia per plant and CLCuV. These results of positive association of yield components are in agreement with the findings of Iqbal et al. (2006), Ashokkumar and Ravikesavan (2010) and Farooq et al. (2014). Early generation selection may be adopted for traits having significant genotypic correlation (Farooq et al., 2014). Significant role of strong genotypic association was observed in the present studies. These results are in accordance with the findings of Desalegn et al. (2009) and Qayyum et al. (2010) who reported the chief role of genetic effects. Positive correlation of sympodia per plant with plant height and seed cotton yield was reported by Ashokkumar and Ravikesavan (2010) and Ahuja et al. (2006) which are in accordance with the present findings Negative direct effects for sympodial branches on seed cotton yield have been earlier reported by Ahuja et al (2006) and Rauf et al. (2004). The traits like nodes to 1st fruiting branch, sympodia per plant and bolls per plant indirectly influenced seed cotton yield through most of the yield contributing traits. Similar indirect effects were found in the studies of Ashokkumar and Ravikesavan (2010).
3 Material and methods
3.1 Plant material and site characteristics
A total of 18 diverse genotypes were evaluated in the experimental area of Cotton Research Institute, Faisalabad during the year 2013-2014. The material was sown on 15th of May to observe their tolerance ability regarding CLCuV and some yield and related parameters
3.2 Experimental design, plot size and cultural practices
Layout of the experiment was randomized complete block design (RCBD) with three replications. For each entry, plot size measured 4.572 m × 6.096 m, comprising six rows set 75 cm apart. Distance between plants within rows was 30 cm. Normal agronomic and cultural practices (irrigation, weeding, hoeing, and fertilizer applications) were adopted as and when required.
3.3 Measurement of various traits studied
For measuring the traits ten representative, undamaged plants were selected in each line and marked for identification. Nodes to 1st fruiting branch counted from zero node (cotyledonary node) to the node at which first flower was appeared. Data on plant height in centimeters were recorded from the base to the tip of the plant. Data on monopodia and sympodia were taken by counting the number of vegetative and fruiting branches, respectively. Number of bolls counted from the guarded plants upto final picking. The bolls were picked and seed cotton yield was calculated in grams (g). Average boll weight in grams (g) was calculated by dividing the total seed cotton yield per plant with the total number of bolls of that plant. Mean boll weight of each plant was taken in grams (g) and then overall averaged. Seed cotton was picked when the crop was mature and recorded as Kg/plot and extrapolated to Kg/hectare.
3.4 Cotton leaf curl virus (CLCuV) disease incidence (%) methodology
CLCuV disease incidence (%) and the reaction of the cultivars was determined using the disease scale (Table 5) described by Akhtar et al. 2010 and Farooq et al. 2011. Then, % of CLCuV disease incidence was calculated by using the following formula;

 

Table 5 Rating scale for cotton leaf curl virus (CLCuV) symptoms

CLCuV disease incidence (%) = Sum of all disease ratings/total number of plants ×16.16
3.5 Statistical Analysis:
The data were subjected to analysis of variance (ANOVA) using the MSTAT-C package (Russell, D. Freed, Michigan State University, USA, 1984). Heritability in broad sense was estimated according to the technique of Burton and De Vane (1953). All correlations (phenotypic and genotypic) were computed following the statistical technique prescribed by Kwon and Torrie (1964). Genotypic correlations were tested following the method of Lotherop et al. (1985). Statistical significance of phenotypic correlations was determined by T-test as described by Steel and Torrie (1984). Path coefficient analysis was done following to the method suggested by Dewey and Lu (1959).
4 Conclusion
Positive correlation, high heritability and positive direct effects of sympodia per plant, bolls per plant and plant height with seed cotton yield is indicative that selection for these traits may be practiced to enhance seed cotton yield.
References
Ahmad W., Khan N.U., Khalil M.R., Parveen A., Aimen U., Saeed M., Samiullah and Shah S.A., 2008, Genetic variability and correlation analysis in upland cotton. Sarhad Journal of Agriculture, 24: 573-580
Ahuja L., Dhayal L.S., and Prakash R., 2006, A correlation and path coefficient analysis of components in G. hirsutum L. hybrids by usual and fibre quality grouping. Turkish Journal of Agriculture and Forestry, 30: 317-324
Akhtar K.P., Haider S., Khan M.K.R., Ahmad M., Sarwar N., Murtaza M.A., and Aslam M., 2010, Evaluation of Gossypium species for resistance to leaf curl Burewala virus. Annals of Applied Biology, 157: 135-147
http://dx.doi.org/10.1111/j.1744-7348.2010.00416.x
Ali M.A., Khan I.A., and Nawab N.N., 2009, Estimation of genetic divergence and linkage for fibre quality traits in upland cotton. Journal of Agricultural Research, 47(3): 229-236
Ashokkumar, and Ravikesavan R., 2010, Genetic Studies of Correlation and Path Coefficient analysis for seed oil, yield and Fibre quality traits in Cotton (G. hirsutum L.) Australian Journal of Basic and Applied Sciences, 4(11): 5496-5499
Basbag S., and Gencer O., 2004, Investigations on the heritability of seed cotton yield, yield components and technological characters in cotton (G. hirsutum L.). Pakistan Journal of Biological Sciences, 7(8): 1390-1393
http://dx.doi.org/10.3923/pjbs.2004.1390.1393
Burton G.W., and De vane E.H., 1953, Estimating heritability in tall fescue (Fescuea arundienancea) from replicated clonal material. Agronomy Journal, 45(10):478-481
http://dx.doi.org/10.2134/agronj1953.00021962004500100005x
DeGui, Z., FanLing K., QunYuan Z., WenXin L., FuXin Y., NaiYin X., Qin L., and Kui Z., 2003, Genetic improvement of cotton varieties in the Yangtse valley in China since 1950s. I. Improvement on yield and yield components. Acta Agronomica Sinica, 29(2): 208-215
Desalegn Z., Ratanadilok N., and Kaveeta R., 2009, Correlation and heritability for yield and fiber quality parameters of Ethiopian cotton (G. hirsutum L.) estimated from 15 (diallel) crosses. Kasetsart Journal: Natural Science,43: 1-11
Dewey D.R., and Lu K.H., 1959, A correlation and path coefficient analysis of components of crested wheat grass seed production. Agronomy Journal, 51: 515-518
http://dx.doi.org/10.2134/agronj1959.00021962005100090002x
Farooq A., Farooq J., Mahmood A., Shakeel A., Rehman A., Batool A., Riaz M., Shahid M.T.H., and Mahboob S., 2011, An overview of cotton leaf curl virus disease (CLCuD) a serious threat to cotton productivity. Australian Journal of Crop Science, 5(13):1823-1831
Farooq J., Anwar M., Riaz M., Farooq A., Mahmood A., Shahid M.T.H., Shahid M.R., and Ilahi, F., 2014, Correlation and path coefficient analysis of earliness, fiber quality and yield contributing traits in cotton (Gossypium hirsutum L.), The Journal of Animal & Plant Sciences, 24(3): 781-790
Imran M., Shakeel A., Farooq J., Saeed A., Farooq A., and Riaz M., 2011, Genetic studies of fiber quality parameter and earliness related traits in upland cotton (Gossypium hirsutum L.), Advances in Agriculture and Botanics, 3(3):151-159
Iqbal M., Hayat K., Khan R.S.A., Sadiq A., and Islam N.U., 2006, Correlation and path coefficient analysis for earliness and yield traits in cotton (G. hirsutum L.). Asian Journal of Plant Sciences, 5: 341-344
http://dx.doi.org/10.3923/ajps.2006.341.344
Irum A., Tabasum A., and Iqbal M.Z., 2011, Variability, correlation and path coefficient analysis of seedling traits and yield in cotton (Gossypium hirsutum L.). African Journal of Biotechnology, 10(79):18104-18110
Kwon S.H., and Torrie J.H., 1964, Heritability and interrelationship among traits of two soybean population. Crop Science, 4: 196-8
http://dx.doi.org/10.2135/cropsci1964.0011183X000400020023x
Lotherop J.E., Akins R.E., Smith O.S., 1985, Variability of yield and yield components in IAPIR grain sorghum random mating population means variance components and heritabilities. Crop Science, 25:235-240
http://dx.doi.org/10.2135/cropsci1985.0011183X002500020009x
Méndez-Natera J.R., Rondón A., Hernández J., and Merazo-Pinto J.F., 2012, Genetic studies in upland cotton. III. Genetic parameters, correlation and path analysis. Sabrao Journal of Breeding & Genetics, 44(1) 112-128
Qayyum A. Murtaza N., Azhar F.M., Iqbal M.Z., and Malik W., 2010, Genetic variability and association among oil, protein and other economic traits of G. hirsutum L. in F2 generation. Journal of Agricultural Research,48(2): 137-142
Rauf S., Khan T.M., Sadaqat H.A., and Khan A.I., 2004, Correlation and path coefficient analysis of yield components in cotton (G. hirsutum L.). International Journal of Agriculture and Biology,6(4): 686-688
Riaz M., Farooq J., Sakhawat G., Mahmood A., Sadiq M.A., and Yaseen M., 2013, Genotypic variability for root/shoot parameters under water stress in some advanced lines of cotton (Gossypium hirsutum L.). Genetics and Molecular Research, 12 (1): 552-561
http://dx.doi.org/10.4238/2013.February.27.4
Songsri P., Jogllo S., Kesmala T., Vorasoot N., Akkasaeng C.P.A., and Holbrook C., 2008, Heritability of drought resistance traits and correlation of drought resistance and agronomic traits in peanut. Crop Science, 48: 2245-2253
http://dx.doi.org/10.2135/cropsci2008.04.0228
Soomro Z.A., Kumbhar M.A., Larik A.S., Imran M., and Brohi S.A., 2010, Heritability and selection response in segregating generations of upland cotton. Pakistan Journal of Agricultural Research, 23(1-2): 25-30

Steel R.D.G., and Torrie J.H., 1984, Principles and Procedures of Statistics. McGraw Hill Book Co. Inc. New York, USA

Cotton Genomics and Genetics
• Volume 6
View Options
. PDF(913KB)
. FPDF
. HTML
. Online fPDF
Associated material
. Readers' comments
Other articles by authors
. Jehanzeb Farooq
. Muhammad Anwar
. Muhammad Rizwan
. Muhammad Riaz
. Khalid Mahmood
. Shahzadi Mahpara
Related articles
. Broad sense heritability
. Seed cotton yield
. Cotton leaf curl virus
. Phenotypic correlations
. Sympodia per plant
Tools
. Email to a friend
. Post a comment

Terms and Conditions | Returns and Refund Policy | Privacy Statement | Information for Advertisers | Contact CropSci Publisher

Copyright © 2019 Sophia Publishing Group Inc.