Genetic diversity analysis of mango genotypes using morphological and quality traits via D² statistics

Diversity Analysis of Mango Genotypes

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Published

2026-03-31

DOI:

https://doi.org/10.58993/ijh/2026.83.1.2

Keywords:

Mango genotypes, genetic diversity, mahalanobis D2, morphological traits, breeding
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Vol. 83 No. 01 (2026): Indian Journal of Horticulture

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Research Articles

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Copyright (c) 2026 Amit Kumar, Arvind Kumar, Satya Prakash, Vibhu Pandey

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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Authors

  • Amit Kumar Department of Fruit Science, Sardar Vallabhbhai Patel University of Agriculture and Technology, Meerut, U.P. 250 110, India
  • Arvind Kumar 1Department of Fruit Science, Sardar Vallabhbhai Patel University of Agriculture and Technology, Meerut, U.P. 250 110, India
  • Satya Prakash 1Department of Fruit Science, Sardar Vallabhbhai Patel University of Agriculture and Technology, Meerut, U.P. 250 110, India
  • Vibhu Pandey 1Department of Fruit Science, Sardar Vallabhbhai Patel University of Agriculture and Technology, Meerut, U.P. 250 110, India

Abstract

The present investigation was carried out during two consecutive years (2021-22 and 2022-23) on twelve mango (Mangifera indica L.) genotypes from an 8–10-year-old orchard to evaluate morphological and quality traits and assess genetic diversity. Fruits were harvested based on maturity indices such as skin color, flesh color and aroma, with undamaged fruits selected for evaluation. A total of 192 fruits representing 48 treatments were analyzed under a Randomized Block Design (RBD). The genotypes studied included Ambika, Pusa Arunima, Dashehari-51, Kesar, Pusa Surya, Mallika, Amrapali, Burma Surakha, Neelum Chausa, Mithua Malda, Rataul and Saurav. Multivariate analysis through Mahalanobis D² statistics and Tocher’s method was employed to classify genotypes into distinct clusters. Pooled data over two years revealed four clusters, with Cluster IV recording the highest mean fruit yield per tree (338.31 fruits), followed by Cluster II (268.15) and Cluster III (234.85). The maximum inter-cluster distance was observed between Cluster IV and Cluster II (D=9.789), indicating substantial genetic divergence, while intra-cluster distance ranged from 0.01 (Cluster IV) to 3.114 (Cluster I). Cluster I, comprising six genotypes, exhibited the highest intra-cluster diversity. Based on inter-cluster distances, hybridization between Cluster IV (Amrapali) and Cluster II (Kesar, Burma Surakha and Rataul) is suggested to exploit heterosis and develop superior recombinants. The findings highlight significant genetic diversity among mango genotypes, providing useful information for selecting promising parents in breeding programs aimed at enhancing yield and quality attributes.

How to Cite

Kumar, A., Kumar, A., Prakash, S., & Pandey, V. (2026). Genetic diversity analysis of mango genotypes using morphological and quality traits via D² statistics: Diversity Analysis of Mango Genotypes. Indian Journal of Horticulture, 83(01), 10–15. https://doi.org/10.58993/ijh/2026.83.1.2

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References

1. Anonymous, (2023-24). Indian Horticulture Database. Ministry of Agriculture & Farmers Welfare, Government of India. www.agricoop.nic.in

2. Bally, I. S., & Dillon, N. L. (2018). Mango (Mangifera indica L.) breeding. Advances in Plant Breeding Strategies: Fruits: Volume 3, 811-896.

3. Crossa, J., & Franco, J. (2004). Statistical methods for classifying genotypes. Euphytica, 137, 19-37.

4. Das, S. S., Kishore, K., Lenka, D., Dash, D. K., Samal, K. C., Samant, D., ... & Dash, S. N. (2021). Assessment of Genetic Diversity in Morphological Traits of Mango Genotypes Using D2 Statistics. International Journal of Plant & Soil Science, 33(17), 31-42.

5. Kar, R. K., Mishra, T. K., Pradhan, B., Behera, D., Das, S., Swain, D. K., ... & Hossain, A. (2024). Assessment of the recurrent mutagenesis efficacy of sesame crosses followed by isolation and evaluation of promising genetic resources for use in future breeding programs. Open Agriculture, 9(1), 20220311.

6. Kumar, A., Kumar, A., Prakash, S., Singh, S., Pandey, V., Raghav, D. K., & Pal, D. (2023). Assessment of different elite mango varieties suitable for North western plain zones of Uttar Pradesh. Environment Conservation Journal, 24(4), 214-220.

7. Kumar, A., Kumar, A., Prakash, S., Kumar, V., Singh, A., Singh, M. K., ... & Singh, S. (2024a). Evaluation on Morphological and Quality Attributes of Mango Cultivars in Western Uttar Pradesh. Journal of Advances in Biology & Biotechnology, 27(9), 485-497

8. Kumar, A., Gupta, A. K., Kanth, N., Marboh, E. S., & Yadav, S. K. (2024b). Assessment of variability and genetic divergence of longan genotypes (Dimocarpus longan Lour.) based on qualitative and quantitative traits. Euphytica, 220(5), 72.

9. Lal, N., Pandey, S. K., Pandey, S. D., & Nath, V. (2023). Genetic diversity and grouping of litchi genotypes based on 83 qualitative and quantitative traits. Erwerbs-Obstbau, 65(4), 1003-1012.

10. Ma, X., Wu, H., Liu, B., Wang, S., Zhang, Y., Su, M., ... & Luo, X. (2024). Genomic diversity, population structure, and genome-wide association reveal genetic differentiation and trait improvements in mango. Horticulture Research, 11(7).

11. Mahalanobis PC (1936). On the generalized distance in statistics. Proc. Nat. Inst. Sci. (India) 49–5

12. Mukherjee, S. K. (1948). The varieties of mango (Mangifera indica L.) and their classification. Bull. hot. Soc. 2 (2): 33-19

13. Plathia, M., Bakshi, P., Sharma, N., Jamwal, M., & Jasrotia (2022) Character association and divergence studies in seedling population of Jamun (Syzygium cumini L.). International Journal of Advanced Biochemistry Research,8(2): 595-600

14. Rajpoot, M., Sharma, T. R., & Sharma, R. M. (2024). Genetic Variability in Mango Clones of Langra cv. for Physical-bio Chemical Parameters at Kymore Plateau and Satpura Hills of Madhya Pradesh, India. International Journal of Plant & Soil Science, 36(8), 364-373.

15. Rao, C.R. 1952. Advanced Statistical Methods in Biometrical Research, Wiley, New York

16. Sankaran, M., Dinesh, M. R., Gowda, D. C. S., & Venugopalan, R. (2020). Genetic Analysis in mango (Mangifera indica L.) based on fruit characteristics of 400 genotypes. Journal of Horticultural Sciences, 15(2), 161-172.

17. Sheidai, M., Noormohammadi, Z., & Vazifeshenas, M. R. (2024). A new look at genetic variability in pomegranate: Landscape genetics and structural equation modeling (SEM). Scientia Horticulturae, 334, 113323.

18. Singh, R.K. and Chaudhary, B.D. 1977. Biometrical methods in quantitative genetic analysis. New Delhi. Kalyani Publication: 318 p

19. Umesh Kanna, S., Parthiban, K. T., Senthilraja, K., Venkatesan, S., Udhaya Nandhini, D., Mohan Kumar, S., & Geethalakshmi, V. (2024). Genetic Diversity and Structure of Terminalia bellerica (Gaertn. Roxb.) Population in India as Revealed by Genetic Analysis. Plants, 13(4), 470.

20. Vincent, L., & Anushma, P. L. (2024). Mango 14. Fruit and Nut Crops, 393.

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