Delineation of selection criterion using pearson correlation and path coefficient analysis in mutant mungbean (Vigna radiata) lines


Abstract views: 96 / PDF downloads: 149 / PDF downloads: 15

Authors

  • P M RAHEVAR Sardarkrushinagar Dantiwada Agricultural University, Sardarkrushinagar, Gujarat 388 110, India
  • R M CHAUHAN Sardarkrushinagar Dantiwada Agricultural University, Sardarkrushinagar, Gujarat 388 110, India
  • P T PATEL Sardarkrushinagar Dantiwada Agricultural University, Sardarkrushinagar, Gujarat 388 110, India
  • S D SOLANKI Sardarkrushinagar Dantiwada Agricultural University, Sardarkrushinagar, Gujarat 388 110, India
  • R A GAMI Sardarkrushinagar Dantiwada Agricultural University, Sardarkrushinagar, Gujarat 388 110, India

https://doi.org/10.56093/ijas.v93i7.135070

Keywords:

Augmented design, Correlation, Heatmap, Mungbean, Mutation, Path analysis

Abstract

An experiment was conducted at the research farm of Sardarkrushinagar Dantiwada Agricultural University, Sardarkrushinagar, Gujarat to evaluate plant characteristics associated with grain yield and its attributes in mutant mungbean (Vigna radiata L.) lines in north Gujarat condition through correlation and path analyses during 2019. Eight independent and 1 dependent variable were evaluated for the character association analysis of the 1200 mutant mungbean lines. The uniform, healthy and dry seeds of mungbean variety GM 4 were treated with 4 different doses of gamma rays at B. A. R. C, Trombay, Mumbai during summer 2019. Selection and evaluation was performed till the M2 generation and final M3 generation was grown using augmented design in 21 blocks containing 57 selections and 3 checks. Five plants selected randomly from each replicated lines and subjected to data assortment and analysis
using OPSTAT. The seed yield was significantly and positively associated with both number of clusters per plant and number of pods per plant. Same traits, as concluded through the path analysis, had a significant positive direct effect on seed yield. Moderate magnitude of indirect positive effect was detected for number of cluster per plant thorough number of pod per plant (0.162). In order to achieve proper array of relation on seed yield, more traits need to be included in the study, clearly evidenced by the high residual effect of path analysis (0.535). Heatmap interpretation reveals colour grading according to the degree of correlation among the traits. Selection method entered on these 2 traits along with others will be productive to increase seed yield in mungbean.

Downloads

Download data is not yet available.

References

Alsamadany H. 2022. Physiological, biochemical and molecular evaluation of mungbean genotypes for agronomical yield under drought and salinity stresses in the presence of humic acid. Saudi Journal of Biological Sciences 29(9): 103385. DOI: https://doi.org/10.1016/j.sjbs.2022.103385

Alom K M, Rashid M and Biswas M. 2015. Genetic variability, L). Journal of Environmental Science and Natural Resources 7(1): 131–38. DOI: https://doi.org/10.3329/jesnr.v7i1.22161

Anonymous. 2020. Directorate of Agriculture, Government of India. Retrieved from: https://agricoop.nic.in/Documents/FirstEstimate2020-21.pdf

Anonymous. 2021. Directorate of Agriculture, Government of Gujarat. Retrieved from: https://dag.gujarat.gov.in/images/directorofagriculture/pdf/Final-Advance-Estimate-GoI-2021- 22-WEB.pdf

Bhardu D and Navale PA. 2011. Correlation and path analysis studies in F3 population of cowpea (Vigna unguiculata (L.) Walp.). Legume Research 34(1): 41–44.

Dutt A, Singh P K and Singh S. 2020. Study of path analysis to access the direct and indirect effect of yield improving components in rice (Oryza sativa L.) under sodic soil. International Journal of Current Microbiology and Applied Sciences 9(03): 631–36. DOI: https://doi.org/10.20546/ijcmas.2020.903.075

Dewey D R and Lu K. 1959. A correlation and path-coefficient analysis of components of crested wheatgrass seed production 1. Agronomy Journal 51(9): 515–18. DOI: https://doi.org/10.2134/agronj1959.00021962005100090002x

Federer W F. 1956. Experimental Design, 4th edn, Vol. 81, pp. 334). LWW. DOI: https://doi.org/10.1097/00010694-195604000-00015

Gaurav G, Verma PK and Hari K. 2017. Genetic variability, correlation and path analysis in mungbean [Vigna radiata (L.) Wilczek]. International Journal of Current Microbiology and Applied Sciences 6(11): 2166–73. DOI: https://doi.org/10.20546/ijcmas.2017.611.255

GBIF.org. 2022. Vigna radiata (L.) R. Wilczek in Doring M. English Wikipedia - Species Pages. Wikimedia Foundation. Checklist dataset https://doi.org/10.15468/c3kkgh

Geetika G, Hammer G, Smith M, Singh V, Collins M, Mellor V and Rachaputi R C. 2022. Quantifying physiological determinants of potential yield in mungbean (Vigna radiata (L.) Wilczek). Field Crops Research 287: 108648. DOI: https://doi.org/10.1016/j.fcr.2022.108648

Hemavathy A, Shunmugavalli N and Anand G. 2015. Genetic variability, correlation and path co-efficient studies on yield and its components in mungbean [Vigna radiata (L.) Wilezek]. Legume Research 38(4): 442–46. DOI: https://doi.org/10.5958/0976-0571.2015.00050.8

Karpechenko G D. 1925. On the chromosomes of Phaseolinae. Bulletin of Applied Botany and Plant Breeding 14(2): 143–48.

Kumar J. 1991. Advances in pulses research in Bangladesh. (In) Proceedings of the Second National Workshop on Pulses, Joydebpur, Bangladesh. International Crops Research Institute for the Semi-Arid Tropics, June 6–8.

Kumar R, Mishra JS, Upadhyay P K and Hans H. 2019. Rice fallows in the Eastern India: problems and prospects. Indian Journal of Agricultural Sciences 89(4): 567–77. DOI: https://doi.org/10.56093/ijas.v89i4.88838

Kumar S, Kumar A, Abrol V, Singh A P and Singh A K. 2020. Genetic variability and divergence studies in mungbean (Vigna radiata) under rainfed conditions. The Indian Journal of Agricultural Sciences 90(5): 905–08. DOI: https://doi.org/10.56093/ijas.v90i5.104357

Miller P A, Williams Jr J C, Robinson H F and Comstock R E. 2020. Estimates of genotypic and environmental variances and covariances in upland cotton and their implications in selection. Agronomy journal 50(3): 126–31. DOI: https://doi.org/10.2134/agronj1958.00021962005000030004x

Naik M G, Abhirami P and Venkatachalapathy N. 2020. Mungbean. Pulses Processing and Product Development, pp. 205–12.

Nair RM, Pandey A K, War AR, Hanumantharao B, Shwe T, Alam A, Pratap A, Malik S R, Karimi R, Mbeyagala E K, Douglas CA, Rane J and Schafleitner P. 2019. Biotic and abiotic constraints in mungbean production progress in genetic improvement. Frontiers in Plant Science 10: 13–40. DOI: https://doi.org/10.3389/fpls.2019.01340

Okuyama L, Federizzi L and Neto J. 2004. Correlation and path analysis of yield and its components and plant traits in wheat. Ciencia Rural 34: 1701–08. DOI: https://doi.org/10.1590/S0103-84782004000600006

Parsaniya T, Patel S, Patel H, Abhishek D, Mistry H and Baria K. 2022. Correlation and path analysis for yield and yield components in mungbean [Vigna radiata (L.) Wilczek]. The Pharma Innovation Journal 11: 316–20.

Rao M, Rao Y K and Reddy M. 2006. Genetic variability and path analysis in mungbean. Legume Research 29(3): 216–18.

Raturi A, Singh S K, Sharma V and Rakesh P. 2015. Genetic variability, heritability, genetic advance and path analysis in mungbean [Vigna radiata (L.) Wilczek]. Legume Research 38(2): 157–63. DOI: https://doi.org/10.5958/0976-0571.2015.00024.7

Reddy A A. 2009. Pulses production technology: Status and way forward, pp. 73–80. Economic and Political weekly. DOI: https://doi.org/10.2139/ssrn.1537540

Sarfraz A and Vikas B. 2019. Study of correlation and path analysis for yield and yield attributing traits in mungbean [Vigna radiata (L.) Wilczek]. International Journal of Chemical Studies 8: 2140–43. DOI: https://doi.org/10.22271/chemi.2020.v8.i1af.8586

Satyanarayana H, Babu S, Lakshmi M S, Madhavi G B and Ramana M V. 2022. Character association and path coefficient analysis in mungbean. The Journal of Research ANGRAU 50(3): 10–16.

Searle S.R. 1965. The value of indirect selection: I. Mass Selection, pp. 682–707. Biometrics. DOI: https://doi.org/10.2307/2528550

Sheoran O P, Tonk D S, Kaushik L S, Hasija R C and Pannu R S. 1998. Statistical Software Package for Agricultural Research Workers. Recent Advances in information theory, Statistics and Computer Applications by D S Hooda and R C Hasija, Haryana. pp. 139–43. Department of Mathematics Statistics, CCS HAU, Hisar.

Shood R, Mittal R K, Shood V K and Sharma S. 2021. Correlation and path analysis studies for various yield and component traits in the segregating generations of Blackgram [Vigna mungo (L). Hepper]. Legume Research 1–7. DOI: https://doi.org/10.18805/LR-4732

Sineka T, Murugan E, Sheeba A, Hemalatha G and Vanniarajan C. 2021. Genetic relatedness and variability studies in greengram (Vigna radiata (L.) Wilczek). Electronic Journal of Plant Breeding 12(4): 1157–62. DOI: https://doi.org/10.37992/2021.1204.159

Singh G, Srivastav R L, Prasad B K and Kumar R. 2021. Genetic variability and character association in mungbean (Vigna radiata (L.) Wilczek). South Asian Journal of Agricultural Sciences 2(1): 04–07. DOI: https://doi.org/10.33545/26631067.2022.v4.i1a.80

Singh S K, Singh I P, Singh B B and Singh O. 2009. Correlation and path coefficient studies for yield and its components in mungbean (Vigna radiata (L.) Wilczek). Legume Research 32(3): 180–85.

Stebbins G L. 1957. Self-fertilization and population variability in the higher plants. The American Naturalist 91(861): 337–54. DOI: https://doi.org/10.1086/281999

Wu M, Li Y, Yuan Y, Li S, Song X and Yin J. 2023. Comparison of NIR and Raman spectra combined with chemometrics for the classification and quantification of mungbeans (Vigna radiata L.) of different origins. Food Control 145: 109498. DOI: https://doi.org/10.1016/j.foodcont.2022.109498

Yadav R. 2022. Assessment of genetic variability and trait association in mungbean (Vigna radiata L.) genotypes during summer season. Journal of Food Legumes 35(3): 170–74.

Submitted

2023-04-05

Published

2023-08-08

Issue

Section

Articles

How to Cite

RAHEVAR, P. M., CHAUHAN, R. M., PATEL, P. T., SOLANKI, S. D., & GAMI, R. A. (2023). Delineation of selection criterion using pearson correlation and path coefficient analysis in mutant mungbean (Vigna radiata) lines. The Indian Journal of Agricultural Sciences, 93(7), 738–742. https://doi.org/10.56093/ijas.v93i7.135070
Citation