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Trait associations and economic performance of marigold (Tagetes erecta L.) cultivars

DOI
https://doi.org/10.14719/pst.13648
Submitted
12 January 2026
Published
29-06-2026
Versions

Abstract

An experiment was conducted at the Regional Research and Technology Transfer Station (RRTTS) research field to evaluate trait associations and economic performance of five African marigold cultivars under the western undulating agro-climatic zone of Odisha, India. The experiment was conducted during the rabi seasons of 2018–2019 and 2019–2020, using a randomised block design with four replications. Significant differences among cultivars, viz., Arka Alankar, Arka Bangara, Bidhan Marigold 1, Bidhan Marigold 2 and Bidhan Marigold 3, were observed in the studied parameters related to growth, flowering and yield. High heritability associated with high genetic advance expressed as a percentage of the mean for flower yield, days to 50 % flowering, flower buds per plant and flower diameter indicate that direct selection will be effective for these traits. Correlation analysis revealed significant positive associations between flower yield and the number of branches per plant, total flowering duration, flower buds per plant, flowers per plant and flower diameter, whereas early flowering exhibited negative correlations with yield. The cultivars were grouped into distinct clusters through hierarchical cluster analysis, with Arka Bangara and Bidhan Marigold 2 identified as phenotypically superior. The first principal component explained most of the total variance and was related mainly to yield and growth parameters, which were responsible for the genotypic divergence under study. Economic analysis further confirmed the commercial superiority of Bidhan Marigold 2 and Arka Bangara, which exhibited the highest flower yield (488.2 and 482.1 q ha-1 respectively) and superior benefit to cost ratios. These cultivars are therefore recognised as the most promising for commercial cultivation and future genetic improvement programmes in the agro-climatic zone.

References

  1. 1. Kumar P, Sharma S, Singh R, Singh P, Kumar A. First report of Sclerotinia sclerotiorum causing white rot of marigold in Punjab, India. J. Plant Pathol.2022;104:435. https://doi.org/10.1007/s42161-021-00996-x
  2. 2. Priyadarsihini A, Palai SK, Nath MR. Effect of source of nitrogen on growth and yield of African marigold (Tagetes erecta L.). Pharm Innov J.2018;7(7):917–21.
  3. 3. Sheoran S, Beniwal BS, Dalal R. Floral and yield attributes of African marigold as influenced by pinching and gibberellic acid in different seasons. Pharm Innov Int J.2022;11(1):937–46.
  4. 4. Netam M, Sharma G, Shukla A. Growth performance of marigold (Tagetes erecta L.) under Chhattisgarh plains agro-climatic condition. J Pharmacogn Phytochem.2019;8(2S):235–7.
  5. 5. Amala E, Singh KP, Panwar S, Namita, Jain N, Kumar S, et al. Influence of cold stress on morpho-physiological traits of African marigold (Tagetes erecta L.) genotypes during the reproductive phase. Pharm Innov J.2022;11(1):518–22.
  6. 6. Dawane PT, Desmukh M, Katwate SM, Ambad SN, Chavan SR. Influence of propagation methods of marigold (Tagetes erecta L.) on growth, yield and quality of flowers. J Agric Res Technol.2015;40(1):20.
  7. 7. Gobade N, Gajabhiye RP, Girange R, Sowjanya P, Moon SS. Evaluation of marigold genotypes for growth and flowering parameters under Vidarbha condition. J. Soils and Crops.2017;27(1):132–35.
  8. 8. Meheta N. Varietal evaluation of African marigold (Tagetes erecta L.) under Prayagraj agro-climatic conditions. Pharm Innov J.2022;11(1):1220–24.
  9. 9. Barik SK. Opportunities and challenges: floriculture – the game changer. Agric Today.2021;24(8):48–51.
  10. 10. Gomez KA, Gomez AA. Statistical procedures in agricultural research. John Wiley & Sons.1984.
  11. 11. Sheoran OP, Tonk DS, Kaushik LS, Hasija RC, Pannu RS. Statistical software package for agricultural research workers. In: Hooda DS, Hasija RC, editors. Recent advances in information theory, statistics and computer applications. Hisar: CCS HAU.1998;8(12):139-43.
  12. 12. Hammer Ø, Harper DA, Ryan PD. PAST: Paleontological statistics software package for education and data analysis. Palaeontol Electronica.2001;4(1):9.
  13. 13. Gopinath PP, Parsad R, Joseph B, Adarsh VS. GRAPES: General R-Shiny based analysis platform empowered by statistics. 2020. Version 1.0.0. https://doi.org/10.5281/zenodo.4923220
  14. 14. Ray J, Bordolui SK. 2020. Effect of GA₃ on marigold seed production in Gangetic alluvial zone. J Crop and Weed.2020;16(1):120–6.
  15. https://doi.org/10.22271/09746315.2020.v16.i1.1281
  16. 15. Naik PV, Seetaramu GK, Tejaswani, Patil MG, Sadanand GK, Shivashankara KS, et al. Evaluation of marigold genotypes for flowering and quality parameters under the Upper Krishna Project command area in Karnataka. Int J Chem Studies.2019; 7(4):1567–70.
  17. 16. Savadi R, Patil S, Hegde L. Genetic variability, heritability, genetic advance and correlation analysis in marigold (Tagetes spp.). J Adv in Bio and Biotech.2024; 27(2):1–9. http://doi.org/10.9734/jabb/2024/v27i81162.
  18. 17. Kumar S, Yadav P, Singh M. Comparative study of marigold (Tagetes spp. L.) genotypes for growth, flowering and yield attributes under Banda agro-climatic conditions. Plant Sc Today.2024;11(3):4605–15.
  19. 18. Isnawati L, Setyaningrum T, Herastuti H, Hasanov S. Growth and yield of marigold flowers (Tagetes erecta L.) under gibberellin and pinching treatments. BIO Web Conf. 2023;69:01020. https://doi.org/10.1051/bioconf/20236901020
  20. 19. Chandio SR, Meghwar MR, Shara A, Wagana M, Shara IA. Effect of pinching on growth and yield of marigold. Big Data Agric.2023;5(2):53–6. https://doi.org/10.26480/bda.02.2023.53.56
  21. 20. Sahoo S, Panda PK, Patra A. Genetic variability, heritability and genetic advance in marigold (Tagetes erecta L.) genotypes under eastern coastal conditions. Pharma Innov J.2022;11(7):1329–32.
  22. 21. Singh RK, Chaudhary BD. Biometrical methods in quantitative genetic analysis. New Delhi: Kalyani Publishers.1985.
  23. 22. Ahuja L, Dhayal LS, Prakash R. Correlation and path coefficient analysis of components in Gossypium hirsutum L. hybrids by usual and fibre quality grouping. Turk J Agric For.2006;30:317–24.
  24. 23. Alishah O, Bagherieh-Najjar MB, Fahmideh L.Correlation, path coefficient and factor analysis of some quantitative and agronomic traits in cotton (Gossypium hirsutum L.). Asian J Biol Sci.2008;1(2):61–8. https://doi.org/10.3923/ajbs.2008.61.68
  25. 24. Burton GW, DeVane EH. Estimating heritability in tall fescue (Festuca arundinacea) from replicated clonal material. Agron J.1953;45(10):478–81. https://doi.org/10.2134/agronj1953.00021962004500100005x
  26. 25. Tripathy P, Sahoo S. Estimation of genetic parameters for growth and yield traits in African marigold (Tagetes erecta L.) genotypes. Int J Agric Sci.2023;15(2):118–123.
  27. 26. Panse VG, Sukhatme PV. Statistical methods for agricultural workers. 2nd ed. New Delhi: ICAR.1967.
  28. 27. Al-Jibouri HA, Miller PA, Robinson HF. Genotypic and environmental variances and covariances in upland cotton crosses of interspecific origin. Agron J.1958;50(10):633–36. https://doi.org/10.2134/agronj1958.00021962005000100020x
  29. 28. Johnson HW, Robinson HF, Comstock RE. Estimates of genetic and environmental variability in soybeans. Agron J.1955;47(7):314–18. https://doi.org/10.2134/agronj1955.00021962004700070009x
  30. 29. Sharma JR. Statistical and biometrical techniques in plant breeding. New Delhi: New Age International Publishers; 2006.
  31. 30. Falconer DS, Mackay TFC. Introduction to quantitative genetics. 4th ed. Harlow: Longman; 1996.
  32. 31. Mahanta S, Dharmatti PR. Genetic divergence studies in marigold (Tagetes erecta L.). Int J Curr Microbiol Appl Sci.2019;8(5):8–12. https://doi.org/10.20546/ijcmas.2019.805.002
  33. 32. Mortensen KO, Zardbani F, Haque MA, Agustsson SY, Mottin D, Hofmann P, et al. Marigold: Efficient k-means clustering in high dimensions. Proc VLDB Endow. 2023;16(7):1740–48. https://doi.org/10.14778/3587136.3587147.
  34. 33. Mohammadi SA, Prasanna BM. Analysis of genetic diversity in crop plants-salient statistical tools and considerations. Crop Sc.2003;43:1235–48. https://doi.org/10.2135/cropsci2003.1235
  35. 34. Rao CR. The use and interpretation of principal component analysis in applied research. Sankhya B.1964;26:329–58.
  36. 35. Kumar R, Raghava SPS, Verma VK. Assessment of genetic diversity in marigold (Tagetes spp.) using multivariate analysis. J Orn Hort.2019;22(1):12–18.
  37. 36. Jolliffe IT. Principal component analysis. 2nd ed. New York: Springer; 2002.
  38. 37. Yan W, Kang MS. GGE biplot analysis. A graphical tool for breeders, geneticists and agronomists. Boca Raton (FL): CRC Press;2002. https://doi.org/10.1201/9781420040371
  39. 38. Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate data analysis. 8th ed. Boston: Cengage Learning; 2019.
  40. 39. Bhat DJ, Sheikh MA, Wani KP. Genetic variability and correlation studies in African marigold (Tagetes erecta L.). Int J Chem Stud.2018;6(5):1940–44.
  41. 40. Singh D, Kumar S, Kumar R. Multivariate analysis for genetic divergence in African marigold (Tagetes erecta L.). Plant Sci Today.2020; 7(3):401–6.
  42. 41. Jolliffe IT, Cadima J. Principal component analysis. A review and recent developments. Philos Trans A Math Phys Eng Sci.2016;374:20150202. https://doi.org/10.1098/rsta.2015.0202
  43. 42. Singh J, Singh KP. Economic analysis of marigold (Tagetes spp.) cultivation under different agro-climatic conditions. Indian J Hortic. 2012;69(2):284–87.
  44. 43. Ali M, Kumar S. Economics of production and marketing of flowers in India. Indian J Agric Econ. 2008;63(3):379–91.
  45. 44. Narayan P, Singh R. Profitability and resource use efficiency in floriculture: A case study of marigold cultivation. Int J Agric Sci. 2017;9(6):3792–95.
  46. 45. Kaur S, Kaur P, Kumar S. Economic analysis of flower crops cultivation in Punjab. Agric Econ Res Rev. 2015;28(1):165–72.
  47. 46. Dillon JL, Hardaker JB. Farm management research for small farmer development. Rome: FAO.1993.
  48. 47. Pandey RK, Maranville JW, Admou A. Deficit irrigation and nitrogen effects on maize in a Sahelian environment: II. Shoot growth, nitrogen uptake and water extraction. Agric Water Manag.2000;46(1):15–27. https://doi.org/10.1016/S0378-3774(00)00074-3
  49. 48. Reddy AV, Rao PV, Devi LB. Economic viability of floriculture crops for income generation among smallholder farmers. Int J Agri Sci.2021;13(6):1298–305.
  50. 49. Ghosh R, Panda S, Nayak S. Economic assessment of flower crop cultivation under varying market conditions in Eastern India. Indian J Hortic Econ.2023;78(2):215–22.

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