Skip to main navigation menu Skip to main content Skip to site footer

Research Articles

Early Access

Assessment of genetic variability at morpho-qualitative levels and molecular characterization of selected promising lines of field pea (Pisum sativum L. var. arvense)

DOI
https://doi.org/10.14719/pst.10915
Submitted
28 July 2025
Published
15-01-2026

Abstract

A field study was conducted during the rabi season of 2023-24 at the Genetics and Plant Breeding Research Farm of Banda University of Agriculture and Technology, Banda, to characterize 30 diverse field pea (Pisum sativum L. var. arvense) genotypes at the phenotypic and molecular levels. The study utilized two replications in an alpha lattice design with four checks and investigated 16 morpho-qualitative characters. Analysis of variance revealed significant variability among genotypes, with traits such as plant height (PH), number of pods per plant (NPP), number of effective pods per plant (NEPP), biological yield per plant (BYP), seed yield per plant (SYP), total sugars (TS), non-reducing sugars (NRS), reducing sugars (RS) and trypsin inhibitor activity (TIA) showing high values of both phenotypic and genotypic coefficients of variation (PCV and GCV). These traits also exhibited high heritability and genetic advance as a percent of the mean (GAM), indicating additive gene effects and suggesting their suitability for effective selection. Eighteen field pea genotypes were molecularly characterized using 18 polymorphic SSR markers, revealing 36 alleles and indicating moderate genetic diversity. Primer AA-446 was the most informative, while AD-249 was the least informative. Cluster analysis grouped the genotypes into three distinct clusters and Principal Coordinate Analysis (PCoA) captured 43.36 % of the total genetic variation across the first two axes. These findings confirm sufficient diversity among genotypes for effective selection and future breeding programmes.

References

  1. 1. Smykal P, Aubert G, Burstin J, Coyne CJ, Ellis NT, Flavell AJ, et al. Pea (Pisum sativum L.) in the genomic era. Agronomy. 2012;2(2):74-115. https://doi.org/10.3390/agronomy2020074
  2. 2. Cousin R. Peas (Pisum sativum L.). Field Crops Res. 1997;53(1-3):111-30. https://doi.org/10.1016/S0378-4290(97)00026-9
  3. 3. Urbano G, Aranda P, Gomez-Villalva E, Frejnagel S, Porres JM, Frías J, et al. Nutritional evaluation of pea (Pisum sativum L.) protein diets after mild hydrothermal treatment and with and without added phytase. J Agric Food Chem. 2003;51(8):2415-20. https://doi.org/10.1021/jf0209239
  4. 4. Anonymous. Project coordinator’s report of AIRCRP on MULLaRP. IIPR Report. Kanpur (India): Indian Institute of Pulses Research; 2022.
  5. 5. Pratap V, Sharma V, Kumar H, Shukla G, Kumar M. Multivariate analysis of quantitative traits in field pea (Pisum sativum L. var. arvense). Legume Res. 2024;47(6):917-21. https://doi.org/10.18805/LR-4604
  6. 6. Kesawat MS, Das Kumar B. Molecular markers: its application in crop improvement. J Crop Sci Biotechnol. 2009;12(4):169-81. https://doi.org/10.1007/s12892-009-0124-6
  7. 7. Jasim Aljumaili S, Rafii MY, Latif MA, Sakimin SZ, Arolu IW, Miah G. Genetic diversity of aromatic rice germplasm revealed by SSR markers. Biomed Res Int. 2018;2018:7658032. https://doi.org/10.1155/2018/7658032
  8. 8. Seepal YS, Sharma V, Mishra A, Singh SK, Gangwar V. Trait association and genetic diversity analysis in field pea (Pisum sativum var. arvense L.) under timely and late sown conditions. Electron J Plant Breed. 2025;16(2):249-57. https://doi.org/10.37992/2025.1602.024
  9. 9. Lowry OH, Rosebrough NJ, Farr AL, Randall RJ. Protein estimation by Lowry’s method. J Biol Chem. 1951;193:52451-6. https://doi.org/10.1016/S0021-9258(19)52451-6
  10. 10. DuBois M, Gilles KA, Hamilton JK, Rebers PA, Smith F. Colorimetric method for determination of sugars and related substances. Anal Chem. 1956;28(3):350-6. https://doi.org/10.1021/ac60111a017
  11. 11. Nelson N. A photometric adaptation of the Somogyi method for the determination of glucose. J Biol Chem. 1944;153(2):375-80. https://doi.org/10.1016/S0021-9258(18)71980-7
  12. 12. Somogyi M. Notes on sugar determination. J Biol Chem. 1952;195(1):19-23. https://doi.org/10.1016/S0021-9258(19)50870-5
  13. 13. Kakade ML, Arnold RL, Liener IE, Waibel PE. Unavailability of cystine from trypsin inhibitors as a factor contributing to the poor nutritive value of navy beans. J Nutr. 1969;99(1):34-42. https://doi.org/10.1093/jn/99.1.34
  14. 14. Doyle JJ. Isolation of plant DNA from fresh tissue. Focus. 1990;12:13-5. https://doi.org/10.2307/2419362
  15. 15. Panse VG. Genetics of quantitative characters in relation to plant breeding. Indian J Genet Plant Breed. 1957;17:318-28.
  16. 16. Yadav I, Sharma V, Kumar M, Yadav LP, Mishra A, Singh V, et al. Assessment of gene action and identification of heterotic hybrids for enhancing yield in field pea. Horticulturae. 2023;9(9):997. https://doi.org/10.3390/horticulturae9090997
  17. 17. Uhlarik A, Ceran M, Zivanov D, Grumeza R, Skøt L, Sizer-Coverdale E, et al. Phenotypic and genotypic characterization and correlation analysis of pea (Pisum sativum L.) diversity panel. Plants. 2022;11(10):1321. https://doi.org/10.3390/plants11101321
  18. 18. Wang N, Hatcher DW, Gawalko EJ. Effect of variety and processing on nutrients and certain anti-nutrients in field peas (Pisum sativum L.). Food Chem. 2008;111(1):132-8. https://doi.org/10.1016/j.foodchem.2008.03.047
  19. 19. Jagadeesh K, Mahto CS, Kumar N. Genetic variability studies in field pea (Pisum sativum L.) for yield and associated characters. Environ Conserv J. 2023;24(2):244-9. https://doi.org/10.36953/ECJ.13172379
  20. 20. Kumar M, Jeberson MS, Singh NB, Sharma R, Dahiphale AV, Singh V. Genetic diversity and trait association analysis in field pea (Pisum sativum L.) genotypes. J Pharmacogn Phytochem. 2019;8(2):2186-93.
  21. 21. Kumar M, Jeberson MS, Singh NB, Sharma R, Patel RS. Analysis of trait association and principal component of variability in field pea (Pisum sativum L.) genotypes. Pharma Innov J. 2018;7(8):437-41.
  22. 22. Pujari PK, Salam JL, Sao A, Mandavi NC, Singh DP. Study of genetic variability in field pea (Pisum sativum L.). J Pharmacogn Phytochem. 2021;10(1):1053-5.
  23. 23. Bishnoi R, Marker S, Kumar KY, Taranum SA. Genetic variability parameters for quantitative traits in farmers’ pea (Pisum sativum var. arvense L.) varieties. Biol Forum Int J. 2021;13:320-5.
  24. 24. Al-Aysh FM, Habib NJ, Nejla S, Murshed R, Abo Trabi B. Genetic variability and association of quality characters and pod yield in garden peas (Pisum sativum L.). Walailak J Sci Technol. 2015;12(3):259-65. https://doi.org/10.14456/wjst.2015.21
  25. 25. Hedau NK, Pal RS, Sood S, Vasudeo CG, Kant L, Pattanayak A. Biochemical characterization and variability in garden pea (Pisum sativum var. hortense) under cool hilly weather conditions. Indian J Agric Sci. 2018;88(9):1442-8. https://doi.org/10.56093/ijas.v88i9.83511
  26. 26. Jeberson MS, Shashidhar KS, Iyanar K. Estimation of genetic variability, expected genetic advance, correlation and path analysis in field pea (Pisum sativum L.). Electron J Plant Breed. 2016;7(4):1074-8. https://doi.org/10.5958/0975-928X.2016.00147.2
  27. 27. Gupta AJ, Singh YV, Verma TS. Genetic variability and heritability in garden pea (Pisum sativum L.). Indian J Hortic. 2006;63(3):332-4.
  28. 28. Pujari PK, Salam JL, Sao A, Mandavi NC, Singh DP. Study of genetic variability in field pea (Pisum sativum L.). J Pharmacogn Phytochem. 2021;10(1):1053-5.
  29. 29. Ravindran G, Nalle CL, Molan A, Ravindran V. Nutritional and biochemical assessment of field peas (Pisum sativum L.) as a protein source in poultry diets. J Poult Sci. 2010;47(1):48-52. https://doi.org/10.2141/jpsa.009071
  30. 30. Singh KH, Singh L, Parmar N, Kumar S, Nanjundan J, Singh G, et al. Molecular characterization and genetic diversity analysis in Indian mustard (Brassica juncea L.) varieties using SSR markers. PLoS One. 2022;17(8):e0272914. https://doi.org/10.1371/journal.pone.0272914
  31. 31. Nayak SN, Zhu H, Varghese N, Datta S, Choi HK, Horres R, et al. Integration of novel SSR and gene-based SNP marker loci in the chickpea genetic map and establishment of new anchor points with Medicago truncatula genome. Theor Appl Genet. 2010;120(7):1415-41. https://doi.org/10.1007/s00122-010-1265-1
  32. 32. Rana JC, Rana M, Sharma V, Nag A, Chahota RK, Sharma TR. Genetic diversity and structure of pea (Pisum sativum L.) germplasm based on morphological and SSR markers. Plant Mol Biol Rep. 2017;35(1):118-29. https://doi.org/10.1007/s11105-016-1006-y
  33. 33. Kumar S, Singh RK, Sharma RK. Genetic diversity analysis of rice germplasm using SSR markers. Indian J Genet Plant Breed. 2011;71(1):67-70.
  34. 34. Janani R, Sharma BB, Dhar S, Arora A, Kumar P, Choudhary H, et al. Population structure and diversity analysis using SSR markers in garden pea (Pisum sativum L.): implications in breeding. Plant Mol Biol Rep. 2025. https://doi.org/10.1007/s11105-025-01610-5
  35. 35. Singh N, Choudhury DR, Tiwari G, Singh AK, Kumar S, Srinivasan K, et al. Genetic diversity trend in Indian rice varieties: an analysis using SSR markers. BMC Genet. 2016;17:1-12. https://doi.org/10.1186/s12863-016-0437-7
  36. 36. Sharma V, Vaishali, Kumar P, Yadav MK, Chand P. Assessment of genetic diversity among twenty Indian wheat (Triticum aestivum L.) cultivars using simple sequence repeat markers. Int J Curr Microbiol Appl Sci. 2018;7(3):1708-17. https://doi.org/10.20546/ijcmas.2018.703.202
  37. 37. Sharma R, Kumar S, Singh SK, Sharma P, Singh GP. Genetic diversity among bread wheat (Triticum aestivum L.) genotypes as assessed by SSRs. J Cereal Res. 2021;13(2):205-10. https://doi.org/10.25174/2582-2675/2021/112954

Downloads

Download data is not yet available.