Phenotypic and genotypic correlation and path analysis in the advance breeding lines of desi cotton

Bangaremma S. Wadeyar; S. T. Kajjidoni

Phenotypic and genotypic correlation and path analysis in the advance breeding lines of desi cotton

Bangaremma S. Wadeyar

, S. T. Kajjidoni

Department of Genetics and Plant Breeding, University of Agricultural Sciences, Dharwad-580005, India

Author

Correspondence author
Molecular Plant Breeding, 2014, Vol. 5, No. 12 doi: 10.5376/mpb.2014.05.0012
Received: 19 Jul., 2014 Accepted: 28 Aug., 2014 Published: 22 Oct., 2014

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:

Wadeyar and Kajjidoni, Phenotypic and genotypic correlation and path analysis in the advance breeding lines of desi cotton, Molecular Plant Breeding, 2014, Vol.5, No. 12 1-4 (doi: 10.5376/mpb.2014.05.0012)

Abstract

Diploid cotton Gossypium herbaceum has wide adaptability under rainfed situation and also high degree of resistance to biotic and abiotic stresses. Correlation and path coefficient analysis have been worked out using five phenotypically diverse genotypes of diploid cotton (G. herbaceum (3) andG. arboreum (2)), with the objective to study the association between seed cotton yield and its components for seven quantitative characters in 202 progenies of desi cotton. High significant positive phenotypic and genotypic correlation coefficients were noticed for some of the important traits like number of bolls per plant, boll weight and plant height traits towards seed cotton yield. And also among the traits (inter) significant association was noticed which indirectly contributed to seed cotton yield. The correlation and path coefficient analysis together indicated that these traits should be considered as selection indices for seed cotton yield plant improvement programme.

Keywords

G. herbaceum; G. arboreum, diploid cotton; phenotypic correlation; genotypic correlation; path coefficient

Diploid cottons belonging to G. herbaceum and G. arboreum were being cultivated in an area of 90 per cent of the total cotton cultivation before 1947. But today their cultivation is restricted to 8 per cent (Anon., 2013). This area has remained with these two species because tetraploid cottons cannot replace diploids completely due to their unsuitability. Increasing the ability of these cottons with respect to seed cotton yield and their fibre traits may possibly increase or gain their area back, as they are tolerant to moisture stress and sucking pests.

Breeding methods like domestication, germplasm collection, plant introduction, somatic hybridization, genetic engineering, mutation breeding, intraspecific hybridization, interspecific hybridization and using wild species for introgression are seen in cotton genetic improvement. Among these interspecific hybridization between cultivated and wild species is used to create considerable amount of variability.

Jayadhar belonging to G. herbaceum species was released during 1950 and has been under commercial cultivation as a popular variety till date. Even today, no single new cultivar is stable and sound. Due to change in the need of textile industries there is a need for enhanced fibre properties of Jayadhar.

In any crop, improvement of yield will be the first and foremost objective of plant breeding. Yield is a complex biometrical trait and its genetic analysis is rather difficult. Seed cotton yield is a resultant product of all its component traits and it could be improved by exploiting the positive influence of yield components. Therefore, the information on nature of association of different yield contributing characters generated out of the studies will serve as an effective selection procedure for improving the yield indirectly. Generally, selections will be effective when selection is made F₂ generation onwards and hence estimation of association among the yield components and association of yield contributing traits on seed cotton yield will provide useful information about the positive influence of different traits on seed cotton yield and yield attributing traits. With the above idea, the present investigation was carried out using 202 advance breeding lines of desi cotton.

Material and methods

The materials for present investigation consisted of 202 progeny lines. Experiment was evaluated in randomized block design (RBD) replicated thrice during winter 2011-12 at Department of Genetics and Plant Breeding, University of Agricultural Sciences, Dharwad. The experimental materials were raised in single rows of 5 m length with the spacing of 60 × 30 cm. Recommended agronomic practices and need based plant protection measures were followed to obtain good crop stand. Observations were recorded on plant height (cm), number of bolls per plant, boll weight (g), ginning out turn (%) (GOT), lint index (g) (LI) and seed index (g) (SI). Datas were recorded on five randomly selected plants of each genotype in each replication. On the mean basis, the character association was carried out by method suggested by Fisher and Yates (1963) and path analysis according to method suggested by Deway and Lu (1959).

Results and Discussion

The correlation co-efficients provide a reliable measure of association among the characters and help to differentiate vital associates useful in breeding from those of the non vital ones (Falconer, 1981). The phenotypic and genotypic correlation co-efficient between seed cotton yield with six biometric characters such as seed cotton yield and its component traits were worked out and are presented in Table 1 and 2.

Table 1 Phenotypic correlation coefficient analysis of component traits towards seed yield/plant in desi cotton

Table 2 Genotypic correlation coefficient analysis of component traits towards seed yield/plant in desi cotton

In the present study, seed cotton yield was significant positive correlation with three traits namely number of bolls per plant (0.959) followed by boll weight (0.246) and plant height (0.165). Following these characters, lint index and seed index recorded positive correlation with yield. Hence, selection for these characters will help in selecting genotypes with high seed cotton yield per plant. Similar results for positive correlation between yield and its components traits were already reported by Basbag and Gencer (2007), Aguado et al. (2008), Do-Thi-Haan et al. (2008), Kalpande et al. (2008) and Reddy and Reddy (2008).

Hence for undertaking a selection programme in interspecific cross combinations, selection based on important yield contributing traits viz., number of bolls per plant, boll weight and plant height will bring about breakthrough in desi cotton yields.

Path co-efficients are the subdivision of phenotypic and genotypic correlation co-efficients of individual characters with seed cotton yield. Path co-efficient analysis is done in order to study the direct and indirect effects of individual component characters on the dependent variable, seed cotton yield per plant. Study of path co-efficients enable breeders to concentrate on the variable which shows high direct effect on seed cotton yield. Ultimately we can reduce the time in looking for more number of component traits by restricting selection to one or few important traits (Dewey and Lu, 1959). The phenotypic and genotypic correlation coefficients of seed cotton yield with other yield traits was further partitioned into direct and indirect effects and the results are presented in Table 3 and 4, Figure 1 and 2.

Table 3 Phenotypic direct and indirect effects of yield components on seed cotton yield in desi cotton

Table 4 Genotypic direct and indirect effects of yield components on seed cotton yield in desi cotton

Figure 1 Phenotypic path diagram for seed cotton yield and yield attributing traits

Figure 2 Genotypic path diagram for seed cotton yield and yield attributing traits

The component of residual effect of path analysis in yield traits was 0.162 at phenotypic and 0.066 at genotypic level. The lower residual effect indicated that the characters chosen for path analysis were adequate and appropriate. From this study, very high positive direct effect was observed for number of bolls per plant (0.953), which was followed by positive direct effect for lint index (0.356) and boll weight (0.226). This is in accordance with the findings of Sakthi et al. (2007) and Do-Thi-Haan et al. (2008) for number of bolls per plant and boll weight, while the remaining characters namely seed index (-0.692) and GOT (-0.546) recorded direct negative effect on seed cotton yield per plant. These results confirm the findings of Altaher and Singh (2003), Sakthi et al. (2007) and Reddy and Reddy (2008) for seed index, while Sakthi et al. (2007), Ahuja et al. (2008) and Kalpande et al. (2008) for GOT. The high indirect positive effect on seed cotton yield per plant was noticed by ginning out turn through seed index followed by seed index via lint index and plant height through number of bolls per plant.

Hence, the direct and indirect effect of number of bolls per plant, boll weight, plant height, seed index, lint index and ginning out turn are the major yield contributing traits and should be considered for improvement in seed cotton yield levels.

Conclusion

The conclusion of correlation and path co-efficient analysis revealed that simultaneous selection based on number of bolls per plant, boll weight and plant height may be promising to breakthrough in seed cotton yield per plant.

References

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