Skip to main navigation menu Skip to main content Skip to site footer
Plant Science Today (PST)

Research Articles

Vol. 12 No. 1 (2025)

Intergenerational relationship and Multi-trait Genotype-Ideotype Distance Indexing (MGIDI) in inter-varietal cross derivatives of black gram [Vigna mungo (L.) Hepper.

DOI
https://doi.org/10.14719/pst.3991
Submitted
29 May 2024
Published
11-02-2025 — Updated on 22-02-2025
Versions

Abstract

Black gram is a highly self-pollinated short-duration crop cultivated in various cropping systems viz., rainfed, intercrop and rice fallow. In the present study, hybridization was made between 2 black gram varieties viz., CO 6 and VBN 11, aimed to develop the recombinants and select superior progenies through Multi-trait Genotype-Ideotype Distance Index (MGIDI) at Tamil Nadu Agricultural University, Coimbatore. The parent-offspring regression analysis was carried out in the F3 and F4 progenies of CO 6 × VBN 11. The significant regression and intergenerational correlation coefficients were observed for all the traits studied. The narrow sense heritability was found to be high for the number of seeds per pod. The other traits viz., plant height, number of branches per plant, number of clusters per plant, number of pods per cluster, number of pods per plant, pod length, number of seeds per pod, hundred seed weight and seed yield per plant showed moderate narrow sense heritability. The MGIDI was calculated for 62 F4 progenies of CO 6 × VBN 11 considering nine yield component traits. In F4 progenies, high broad sense heritability was observed for all the yield-contributing traits and high selection gain was recorded for seed yield per plant (49.77%), number of branches per plant (46.29%), number of pods per plant (37.74%) and number of pods per cluster (20.80%). Based on the MGIDI, six F4 progenies viz., P1, P6, P22, P49, P50 and P53 were selected. The selected progenies could be further evaluated and yield tested for commercial exploitation.

References

  1. Arumuganathan K, Earle E. Nuclear DNA content of some important plant species. Plant Mol Bio Reporter. 1991;9:208-18. https://doi.org/10.1007/BF02672069
  2. Vavilov N. Centers of origin of cultivated plants. Inst Appl Bot Plant breed. 1926;16(2):139-248.
  3. Chandel K, Lester R, Starling R. The wild ancestors of urid and mung beans (Vigna mungo (L.) Hepper and V. radiata (L.) Wilczek). Botanical Journal of the Linnean Society. 1984;89(1):85-96. https:// doi.org/10.1111/j.1095-8339.1984.tb01002.x
  4. Castillo C. The archaeobotany of Khao Sam Kaeo and Phu Khao Thong: theagriculture of late prehistoric southern Thailand. London: United Kingdom: University College London; 2013.
  5. Kaewwongwal A, Kongjaimun A, Somta P, Chankaew S, Yimram T, Srinives P. Genetic diversity of the black gram [Vigna mungo (L.) Hepper] gene pool as revealed by SSR markers. Breed Sci. 2015;65 (2):127-37. https://doi.org/10.1270/jsbbs.65.127
  6. Gupta DS, Kumar J, Parihar AK, Chandra A, Sujayanand G, Gupta S. Urdbean breeding. Fundamentals of Field Crop Breed: Springer; 2022. p. 1151-79. https://doi.org/10.1007/978-981-16-9257-4_23
  7. Indiastat. Season-wise Area, Production and Productivity of Urad in India 2023 [Available from: https://www.indiastat.com/
  8. USDA. National Nutrient Database. https://www.usda.gov/. 2018.
  9. Khan F, Nayab M, Ansari AN, Zubair M. Medicinal properties of m?sh (Vigna mungo (Linn.) Hepper): A comprehensive review. J of Drug Delivery and Therapeutics. 2021;11(3-S):121-24. https:// doi.org/10.22270/jddt.v11i3-S.4888
  10. Pandey S. Review on medicinal importance of Vigna genus. Plant Sci Today. 2019;6(4):450-56. https://doi.org/10.14719/ pst.2019.6.4.614
  11. Falconer D. Quantitative genetics Edinburgh. Scotland: Oliver and Boyd. 1960.
  12. Falconer D, Mackay T. Introduction to quantitative genetics. 4 ed. London: Longman Group Ltd.; 1996. 464 p.
  13. Chen Y, Lübberstedt T. Molecular basis of trait correlations. Trends in Plant Sci. 2010;15(8):454-61. https://doi.org/10.1016/ j.tplants.2010.05.004
  14. Olivoto T, Nardino M. MGIDI: Toward an effective multivariate selection in biological experiments. Bioinformatics. 2021;37 (10):1383-89. https://doi.org/10.1093/bioinformatics/btaa981
  15. Smith J, Kinman ML. The use of parent?offspring regression as an estimator of heritability. Crop Sci. 1965;5(6):595-96. https:// doi.org/10.2135/cropsci1965.0011183X000500060035x
  16. Olivoto T, Lúcio ADC. metan: An R package for multi?environment trial analysis. Methods in Ecol and Evol. 2020;11(6):783-89. https:// doi.org/10.1111/2041-210X.13384
  17. Muralidhara Y, Lokeshkumar B, Uday D, Savithramma D. Intergeneration correlation and narrow-sense heritability between F2 and F3 generations for yield components in green gram [Vigna radiata L. Wilczek]. Int J of Agri Sci and Res. 2015;5(4):357-62.
  18. Selvi VM, Nirmalakumari A, Anandakumar C, Amudha R. Evaluation of genetic potential between F2 and F3 generations of cowpea (Vigna unguiculata L.) Walp.) using parent progeny regression analysis. Biol Forum - An Int J. 2022;14(1):1146-53. https://doi.org/10.30726/esij/ v9.i1.2022.91003
  19. Chikalipa E, Tembo L. Analysis of parent offspring regression of selected cowpea (Vigna unguiculata [L]. Walp.) agronomic traits in phosphorus limiting soil. Int J of Plant and Soil Sci. 2023;35(19):1488 -94. https://doi.org/10.9734/ijpss/2023/v35i193692
  20. Nadarajan N, Manivannan N, Gunasekaran M. Quantitative genetics and biometrical techniques in plant breeding. 1 ed: Kalyani Publishers; 2016.
  21. Koseoglu K, Adak A, Sari D, Sari H, Oncu Ceylan F, Toker C. Transgressive segregations for yield criteria in reciprocal interspecific crosses between Cicer arietinum L. and C. reticulatum Ladiz. Euphytica. 2017;213:1-11. https://doi.org/10.1007/s10681-017-1903-7
  22. Costa AEdS, Santos CAF. Heritability estimated by different methods in four generations of progenies from a pigeon pea cross. Pesquisa Agropecuária Brasileira. 2022;57(02889):1-9. https:// doi.org/10.1590/s1678-3921.pab2022.v57.02889
  23. Punithavathy P, Kumaresan D, Manivannan N, Boopathi NM, Senthilraja G. Variability and association analyses of powdery mildew disease scores, seed yield and component traits in blackgram [Vigna mungo (L.) Hepper]. Electr J of Plant Breed. 2023;14(3):811-17. https:// doi.org/10.37992/2023.1403.093
  24. Ragul S, Manivannan N, Iyanar K, Ganapathy N, Karthikeyan G. Estimation of genetic parameters and gene action among crosses of blackgram (Vigna mungo (L.) Hepper) for seed yield and its component traits. Electr J of Plant Breed. 2021;12(4):1244-48. https://doi.org/10.37992/2021.1204.170
  25. Maranna S, Nataraj V, Kumawat G, Chandra S, Rajesh V, Ramteke R, et al. Breeding for higher yield, early maturity, wider adaptability and waterlogging tolerance in soybean (Glycine max L.): A case study. Scientific Reports. 2021;11(1):22853. https://doi.org/10.1038/ s41598-021-02064-x
  26. Sellami MH, Pulvento C, Lavini A. Selection of suitable genotypes of lentil (Lens culinaris Medik.) under rainfed conditions in south Italy using multi-trait stability index (MTSI). Agronomy. 2021;11(9):1807. https://doi.org/10.3390/agronomy11091807
  27. Philanim W, Kumar A, Shittegar N, Sankar SM, Bharadwaj C, Ngangkham U, et al. Stability analysis of yield and yield related traits in ricebean [Vigna umbellata (Thunb.) Ohwi and Ohashi]. Indian Journal of Genetics and Plant Breeding. 2022;82(02):208-16. https://doi.org/10.31742/IJGPB.82.2.10
  28. Azam MG, Hossain MA, Sarker U, Alam AM, Nair RM, Roychowdhury R, et al. Genetic analyses of mungbean [Vigna radiata (L.) Wilczek] breeding traits for selecting superior genotype (s) using multivariate and multi-traits indexing approaches. Plants. 2023;12(10):1984. https://doi.org/10.3390/plants12101984
  29. Abderemane BA, Fakiri M, Idrissi O, Baidani A, Zeroual A, Mazzucotelli E, et al. Evaluation of the productive potential of a world collection of chickpeas (Cicer arietinum L.) for the initiation of breeding programs for adaptation to conservation agriculture. Sustain. 2023;15 (15):11927. https://doi.org/10.3390/su151511927
  30. Amrate PK, Shrivastava M, Bhale M, Agrawal N, Kumawat G, Shivakumar M, et al. Identification and genetic diversity analysis of high-yielding charcoal rot resistant soybean genotypes. Scientific Reports. 2023;13(1):8905. https://doi.org/10.1038/s41598-023-35688-2

Downloads

Download data is not yet available.