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Research Articles

Early Access

Stability analysis of promising sugarcane genotypes for cane and sugar yields using the AMMI model and GGE biplot

DOI
https://doi.org/10.14719/pst.7405
Submitted
24 January 2025
Published
19-03-2025
Versions

Abstract

The sugarcane clone G 2008019 is a general cross progeny of CoV 92102 that outyielded the checks in initial breeding trials. To assess its stability and yield potential under saline stress, multi-environment trials comprising 20 environments were conducted from 2022 to 2024. It produced the highest mean cane yield of 123.41 t/ha with a commercial cane sugar percentage of 13.06, representing a 27.46%, 28.89% and 31.79% increase over the checks Co 86032 (96.82 t/ha), CoG 94077 (93.64 t/ha) and CoG 95076 (95.75 t/ha) respectively. Further, it exhibited a 29.35%, 35.09% and 34.16% increase in sugar yield over the checks, respectively. From the AMMI (additive main effects and multiplicative interactions) and GGE (genotype × genotype interaction with environment) biplots, the performance and stability of the test genotypes were ascertained. The ANOVA analysis showcased a significant contribution of genotypes to total variation followed by the genotype × environment interaction and the environment itself. The yield potential and the stability of G 2008019 were confirmed through minimal ASV values and higher values for cane yield and juice-based quality traits. The biplots of AMMI I, AMMI II and GGE confirmed the constancy of G 2008019. Additionally, the sugarcane clone G 2008019 possessed good jaggery qualities, including 65.36% juice recovery, 91.84% juice purity, 11.32% jaggery recovery and 15.21 t/ha jaggery yield. The mean fibre content of the clone was 13.25%. These combined results indicate the suitability of clone G 2008019 for further utilization in the breeding cycle.

References

  1. O’Connell A, Deo J, Deomano E, Wei X, Jackson P, Aitken KS, et al. Combining genomic selection with genome-wide association analysis identified a large-effect QTL and improved selection for red rot resistance in sugarcane. Front Plant Sci. 2022;13:1021182. https://doi.org/10.3389/fpls.2022.1021182
  2. Thangavelu S. Role of sugarcane varieties on jaggery research- A review. Cooperative Sugar. 2005;36(10):823-26. https://api.semanticscholar.org/CorpusID:221214038
  3. Santaella J. The sugarcane agribusiness – An energy focused vision. Bulletin Published by Technische Universität Berlin – TU International. 2007;60(8):3.
  4. Sudhagar R, Rajkumar S, Ramachandiran K, Saravanan NA. Identification of location-specific male and female sugarcane parents and formulation of breeding strategies. Sugar Tech. 2023;25(3):670–80. https://doi.org/10.1007/s12355-022-01225-0
  5. Shahbaz M, Ashraf M. Improving salinity tolerance in cereals. Crit Rev Plant Sci. 2013;32(4):237–49. https://doi.org/10.1080/07352689.2013.758544
  6. Glick BR, Cheng Z, Czarny J, Duan J. Promotion of plant growth by ACC deaminase-producing soil bacteria. Eur J Plant Pathol. 2007;119:329–39. https://doi.org/10.1007/s10658-007-9162-4
  7. Williams ARE, Ahmed MPP. Impact of leather industries on groundwater in Tamil Nadu with special reference to Vellore district. Int Rev Bus Econ. 2020;4:351–57. https://doi.org/10.56902/irbe.2020.4.2.65
  8. Sinduja M, Sathya V, Maheswari M, Dinesh GK, Prasad S, Kalpana P. Groundwater quality assessment for agricultural purposes at Vellore district of Southern India: A geospatial based study. Urban Clim. 2023;47:101368. https://doi.org/10.1016/j.uclim.2022.101368
  9. Hu Y, Schmidhalter U. In: Limitation of salt stress to plant growth. New York: Marcel Dekker Inc; 2004. https://doi.org/10.1201/9780203023884.ch5
  10. Javid MG, Sorooshzadeh A, Moradi F, Sanavy SAMM, Allahdadi I. The role of phytohormones in alleviating salt stress in crop plants. Aust J Crop Sci. 2011;5(6):726–34. https://doi.org/10.3316/informit.282135746215551
  11. Mani AK, Santhi R, Sellamuthu KM. A Handbook of laboratory analysis. AE Publications; 2007. p. 156–67
  12. Chen JCP, Chi CC. Cane sugar handbook: A manual for cane sugar manufacturers and their chemists. John Wiley and Sons; 1993
  13. Whalley HCS. ICUMSA methods of sugar analysis official and tentative methods recommended by the International commission for uniform methods of sugar analysis (ICUMSA). New York: Elsevier; 1964
  14. Meade GP, Chen JCP. Cane sugar handbook. 10th ed. New York: John Wiley and Sons; 1977
  15. Gauch HG, Zobel RW. Imputing missing yield trial data. Theor Appl Genet. 1990;79:753–61. https://doi.org/10.1007/bf00224240
  16. Yan W, Kang MS. GGE biplot analysis: A graphical tool for breeders, geneticists and agronomist. CRC Press; 2002. https://doi.org/10.1201/9781420040371-4
  17. Purchase JL, Hatting H, van Deventer CS. Genotype × environment interaction of winter wheat (Triticum aestivum L.) in South Africa: II. Stability analysis of yield performance. South African J Plant Soil. 2013;17(3):101–07. https://doi.org/10.1080/02571862.2000.10634878
  18. Dashiell KE, Ariyo OJ, Ojo K. Genotype X environment interaction and simultaneous selection for high yield and stability in soybeans (Glycine max (L.) Merr.). Ann Appl Biol. 1994;124(1):133–39. https://doi.org/10.1111/j.1744-7348.1994.tb04121.x
  19. Nelson PN, Ham GJ. Exploring the response of sugar cane to sodic and saline conditions through natural variation in the field. Field Crops Res. 2000;66(3):245–55. https://doi.org/10.1016/s0378-4290(00)00077-0
  20. Rietz DN, Haynes RJ. Effect of irrigation-induced salinity and sodicity on sugarcane yield. Proc S Afr Surg Technol Assoc. 2002;76:173–85. https://doi.org/10.1016/S0038-0717(03)00125-1
  21. Rao VP, Sengar RS, Singh S, Sharma V. Molecular and metabolic perspectives of sugarcane under salinity stress pressure. Prog Agric. 2015;15(1):77–84.
  22. Alarmelu S, Balakrishnan R, Hemaprabha G. G × E interaction studies in multi-location trials of sugarcane using GGE biplot and ANOM analysis. J Sugarcane Res. 2015;5(1):12–23.
  23. Farshadfar E, Mahmodi N, Yaghotipoor A, Sability A. Value and simultaneous estimation of yield and yield stability in bread wheat (Triticum aestivum L.). Aust J Crop Sci. 2011;5(13):1837–44.
  24. Oladosu Y, Rafii MY, Abdullah N, Magaji U, Miah G, Hussin. Genotype × Environment interaction and stability analyses of yield and yield components of established and mutant rice genotypes tested in multiple locations in Malaysia. Acta Agric Scand Sect B Soil Plant Sci. 2017;67(7):590–606. https://doi.org/10.1080/09064710.2017.1321138
  25. Sudhagar R, Saravanan NA, Kanchanarani R, Shanmuganathan M, Ganapathy S, Babu C, et al. Evolution, identification, evaluation and characterization of a stable salinity tolerant sugarcane variety CoG 7. Sci Rep. 2024;14(1):20448. https://doi.org/10.1038/s41598-024-70756-1
  26. Bose KL, Jambhulkar NR, Pande K, Singh NO. Use of AMMI and other stability statistics in the simultaneous selection of rice genotypes for yield and stability under direct-seeded conditions. Chil J Agric Res. 2014;74(1):3–9. https://doi.org/10.4067/s0718-58392014000100001
  27. Bhatt R, Kumar R, Kashyap L, Alataway A, Dewidar AZ, Mattar MA. Growth, yield, quality and insect-pests in sugarcane (Saccharum officinarum) as affected by differential regimes of irrigation and potash under stressed conditions. Agronomy. 2022;12(8):1942. https://doi.org/10.3390/agronomy12081942

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