Hostname: page-component-6587cd75c8-67gbf Total loading time: 0 Render date: 2025-04-23T15:14:35.980Z Has data issue: false hasContentIssue false
  • English
  • Français

Insights into the genetic divergence in Asiatic cotton (Gossypium arboreum L.) germplasm for fibre-quality traits

Published online by Cambridge University Press:  09 October 2024

Bana Venkata Ravi Prakash Reddy Open the ORCID record for Bana Venkata Ravi Prakash Reddy [Opens in a new window] ,
K. Mohan Vishnuvardhan ,
K. Amarnath ,
U. Nikhil Sagar ,
D. Lakshmi Kalyani ,
M. Siva Ramakrishna ,
Y. Rama Reddy  and
N. C. Venkateswarulu
Bana Venkata Ravi Prakash Reddy*
Affiliation:
Regional Agricultural Research Station, Acharya N G Ranga Agricultural University, Nandyal, India
K. Mohan Vishnuvardhan
Affiliation:
Regional Agricultural Research Station, Acharya N G Ranga Agricultural University, Nandyal, India
K. Amarnath
Affiliation:
Regional Agricultural Research Station, Acharya N G Ranga Agricultural University, Nandyal, India
U. Nikhil Sagar
Affiliation:
Regional Agricultural Research Station, Acharya N G Ranga Agricultural University, Nandyal, India
D. Lakshmi Kalyani
Affiliation:
Regional Agricultural Research Station, Acharya N G Ranga Agricultural University, Nandyal, India
M. Siva Ramakrishna
Affiliation:
Regional Agricultural Research Station, Acharya N G Ranga Agricultural University, Nandyal, India
Y. Rama Reddy
Affiliation:
Regional Agricultural Research Station, Acharya N G Ranga Agricultural University, Nandyal, India
N. C. Venkateswarulu
Affiliation:
Regional Agricultural Research Station, Acharya N G Ranga Agricultural University, Nandyal, India
*
Corresponding author: Bana Venkata Ravi Prakash Reddy; Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Asiatic cotton (Gossypium arboreum L.) has evolved in the Indian subcontinent and is known for its adaptability to low-input management conditions. In the present study, 300 diverse G. arboreum lines, including 100 Nandyal arboreum breeding lines (NAB), 132 Arboreum germplasm collections (AGC) and 68 long-linted arboreum genotypes (LLA), were evaluated for fibre quality to assess the diversity among them and to identify promising genotypes with desirable fibre traits. Significant variations were observed among the genotypes for the studied fibre-quality traits. Principal component analysis showed that the traits micronaire (Mic) and elongation percentage (E%) followed by upper half mean length (UHML) and bundle tenacity (tenacity) were the most significant contributors to variation. Cluster analysis based on the Euclidian distance method showed 16 clusters among 300 G. arboreum genotypes. The genotypes in cluster 4 have desirable UHML, tenacity and UI (uniformity index) traits, and cluster 12 has Mic and E% traits. Furthermore, the number of genotypes with desirable fibre-quality traits was found to be higher in the AGC group than in the LLA and NAB groups. The trait tenacity followed by the UHML showed relatively higher Shannon–Weiner diversity index values across different genotypic groups. Based on the superior performance, the genotypes PA 847, PA 809, PA 837, PA 863, NDLA 3147-2, NDLA 2974 and NDLA 3081 were found to be having desirable fibre traits. The identified promising genotypes are valuable genetic resources for improving fibre quality in G. arboreum cotton.

Keywords

desi cottondiversity indexfibre lengthfibre strengthG. arboreum
Type
Research Article
Information
Plant Genetic Resources , Volume 23 , Issue 1 , February 2025 , pp. 18 - 26
Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press on behalf of National Institute of Agricultural Botany

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Aguado, A, De Los Santos, B, Gamane, D, Del Moral, LG and Romero, F (2010) Gene effects for cotton-fibre traits in cotton plant (Gossypium hirsutum L.) under Verticillium conditions. Field Crops Research 116, 209–217. doi: 10.1016/j.fcr.2009.12.011CrossRefGoogle Scholar
Axmedov, ОА, Xalikova, МB and Matyakubova, EU (2022) G. arboreum L. and G. herbaceum L. types: history of research, now and in the future. Journal of Pharmaceutical Negative Results 13, 445–450. doi: 10.47750/pnr.2022.13.S10.047Google Scholar
Azzouz, B, Ben Hassen, M and Sakli, F (2008) Adjustment of cotton fibre length by the statistical normal distribution: application to binary blends. Journal of Engineered Fibres and Fabrics 3, 155892500800300304. doi: 10.1177/155892500800300304CrossRefGoogle Scholar
Bajracharya, J, Steele, KA, Jarvis, DI, Sthapit, BR and Witcombe, JR (2006) Rice landrace diversity in Nepal: variability of agro-morphological traits and SSR markers in landraces from a high-altitude site. Field Crops Research 95, 327–335. doi: 10.1016/j.fcr.2005.04.014CrossRefGoogle Scholar
Baxevanos, D, Tsialtas, IT and Goulas, C (2013) Repeatability and stability analysis for fibre traits in upland cotton (Gossypium hirsutum L.). Australian Journal of Crop Science 7, 1423–1429.Google Scholar
Bhatti, MH, Yousaf, MI, Munir, M, Khan, MN, Hussain, D, Akbar, W, Hafeez, MA, Kohli, SA, Khalid, MU and Abdullah, M (2020) Genetic variation and association among upland cotton genotypes under semi-arid conditions. International Journal of Biology and Biotechnology 17, 693–699.Google Scholar
Bradow, JM and Davidonis, GH (2000) Quantitation of fibre quality and the cotton production-processing interface: a physiologist's perspective. Journal of Cotton Science 4, 34–64.Google Scholar
Campbell, BT and Jones, MA (2005) Assessment of genotype × environment interactions for yield and fibre quality in cotton performance trials. Euphytica 144, 69–78. doi: 10.1007/s10681-005-4336-7CrossRefGoogle Scholar
Campbell, BT, Chee, PW, Lubbers, E, Bowman, DT, Meredith, WR Jr, Johnson, J, Fraser, D, Bridges, W and Jones, DC (2012) Dissecting genotype × environment interactions and trait correlations present in the Pee Dee cotton germplasm collection following seventy years of plant breeding. Crop Science 52, 690–699. doi: 10.2135/cropsci2011.07.0380CrossRefGoogle Scholar
Carvalho, LPD, Farias, FJC, Santos, RGD, Teodoro, LPR and Teodoro, PE (2022) Genotype selection for fibre quality traits in cotton in the Brazilian Northeast. Agronomy Journal 114, 3068–3073. doi: 10.1002/agj2.21176CrossRefGoogle Scholar
Chandra, M and Sreenivasan, S (2011) Studies on improved Gossypium arboreum cotton: part I – fibre quality parameters. Indian Journal of Fibre and Textile Research 36, 24–34. http://nopr.niscpr.res.in/handle/123456789/11216Google Scholar
Chinchane, VN and Baig, KS (2018) Performance of long linted desi cotton (Gossypium arboreum) genotypes for yield and fibre quality parameters under rainfed condition. Journal of Pharmacognosy and Phytochemistry 7, 3409–3411.Google Scholar
Clement, JD, Constable, GA, Stiller, WN and Liu, SM (2012) Negative associations still exist between yield and fibre quality in cotton breeding programs in Australia and USA. Field Crops Research 128, 1–7. doi: 10.1016/j.fcr.2011.12.002CrossRefGoogle Scholar
Darawsheh, MK, Beslemes, D, Kouneli, V, Tigka, E, Bilalis, D, Roussis, I, Karydogianni, S, Mavroeidis, A, Triantafyllidis, V, Kosma, C and Zotos, A (2022) Environmental and regional effects on fibre quality of cotton cultivated in Greece. Agronomy 12, 943. doi: 10.3390/agronomy12040943CrossRefGoogle Scholar
Delhom, CD, Wanjura, JD and Hequet, EF (2022) Cotton fibre elongation: a review. The Journal of the Textile Institute 12, 1–2. doi: 10.1080/00405000.2022.2157940Google Scholar
Ghanmi, H, Ghith, A and Benameur, T (2017) Open-end yarn properties prediction using HVI fibre properties and process parameters. AUTEX Research Journal 17, 6–11. doi: 10.1515/aut-2015-0026CrossRefGoogle Scholar
Han, YJ, Cho, YJ, Lambert, WE and Bragg, CK (1998) Identification and measurement of convolutions in cotton fibre using image analysis. Artificial Intelligence Review 12, 201–211. doi: 10.1023/A:1006521329471CrossRefGoogle Scholar
Hequet, EF, Wyatt, B, Abidi, N and Thibodeaux, DP (2006) Creation of a set of reference material for cotton fibre maturity measurements. Textile Research Journal 76, 576–586. doi: 10.1177/0040517506064710CrossRefGoogle Scholar
Hinchliffe, DJ, Thyssen, GN, Condon, BD, ZengL, Hron RJ, Madison, CA, Jenkins, JN, McCarty, JC, Delhom, CD and Sui, R (2023) Interrelationships between cotton fibre quality traits and tensile properties of hydroentangled nonwoven fabrics. Journal of Industrial Textiles 53, 1–23. doi: 10.1177/15280837231171CrossRefGoogle Scholar
Hu, Y, Chen, J, Fang, L, Zhang, Z, Ma, W, Niu, Y, Ju, L, Deng, J, Zhao, T, Lian, J, Baruch, K, Fang, D, Liu, X, Ruan, Y, Rahman, M, Han, J, Wang, K, Wang, Q, Wu, H, Mei, G, Zang, Y, Han, Z, Xu, C, Shen, W, Yang, D, Si, Z, Dai, F, Zou, L, Huang, F, Bai, Y, Zhang, Y, Brodt, A, Hamo, H, Zhu, X, Zhou, B, Guan, X, Zhu, S, Chen, X and Zhang, T (2019) Gossypium barbadense and Gossypium hirsutum genomes provide insights into the origin and evolution of allotetraploid cotton. Nature Genetics 51, 739–748. doi: 10.1038/s41588-019-0371-5CrossRefGoogle ScholarPubMed
Hussain, GF, Iyer, JK, Singhvi, B and Iyer, KR (2002) Estimation of fibre maturity from micronaire value. Indian Journal of Fibre and Textile Research 27, 335–341. http://nopr.niscpr.res.in/handle/123456789/23292Google Scholar
Ibrahim, W, Zhu, YM, Chen, Y, Qiu, CW, Zhu, S and Wu, F (2019) Genotypic differences in leaf secondary metabolism, plant hormones and yield under alone and combined stress of drought and salinity in cotton genotypes. Physiologia Plantarum 165, 343–355. doi: 10.1111/ppl.12862CrossRefGoogle ScholarPubMed
Ijaz, B, Zhao, N, Kong, J and Hua, J (2019) Fibre quality improvement in upland cotton (Gossypium hirsutum L.): quantitative trait loci mapping and marker assisted selection application. Frontiers in Plant Science 10, 1585. doi: 10.3389/fpls.2019.01585CrossRefGoogle ScholarPubMed
International Cotton Advisory Committee (ICAC) data portal. (2021–22) Cotton Statistics. Available at https://www.icac.org. Accessed 12 December 2023.Google Scholar
Iqbal, Z, Hu, D, Nazeer, W, Ge, H, Nazir, T, Fiaz, S, Gul, A, Iqbal, MS, El-Sabrout, AM, Maryum, Z and Pan, Z (2022) Phenotypic correlation analysis in F2 segregating populations of Gossypium hirsutum and Gossypium arboreum for boll-related traits. Agronomy 12, 330. doi: 10.3390/agronomy12020330CrossRefGoogle Scholar
Jarwar, AH, Wang, X, Iqbal, MS, Sarfraz, Z, Wang, L, Ma, Q and Shuli, FJ (2019) Genetic divergence on the basis of principal component, correlation and cluster analysis of yield and quality traits in cotton cultivars. Pakistan Journal of Botany 51, 1143–1148. doi: 10.30848/PJB2019-3(38)CrossRefGoogle Scholar
Khan, A, Najeeb, U, Wang, L, Tan, DK, Yang, G, Munsif, F, Ali, S and Hafeez, A (2017) Planting density and sowing date strongly influence growth and lint yield of cotton crops. Field Crops Research 209, 129–135. doi: 10.1016/j.fcr.2017.04.019CrossRefGoogle Scholar
Kranti, KR (2015) Desi cotton – returns. Cotton Statistics & News 15, 1–4.Google Scholar
Krishnamoorthi, A, Ramakrishnan, SH, Premalatha, N, Boopathi, NM and Thiruvengadam, V (2020) Evaluation of desi cotton (Gossypium arboreum L.) germplasm using qualitative descriptors and principal component analysis. Electronic Journal of Plant Breeding 11, 789–795. doi: 10.37992/2020.1103.130Google Scholar
Ksenia, S, Elena, K and Larisa, P (2020) Cotton genome evolution and features of its structural and functional organization. Biological Communications 65, 15–27. doi: 10.21638/spbu03.2020.102Google Scholar
Li, R and Erpelding, JE (2016) Genetic diversity analysis of Gossypium arboreum germplasm accessions using genotyping-by-sequencing. Genetica 144, 535–545. doi: 10.1007/s10709-016-9921-2CrossRefGoogle ScholarPubMed
Lingaiah, N, Sudharshanam, A, Rao, VT, Prashant, Y, Kumar, MV, Reddy, P and Rao, P (2020) AMMI biplot analysis in cotton (Gossypium hirsutum L.) genotypes for genotype × environment interaction at four agro-ecologies in Telangana State. Current Journal of Applied Science and Technology 39, 98–103. doi: 10.9734/cjast/2020/v39i1530722CrossRefGoogle Scholar
Manivannan, A (2023) Assessing genetic variation in Gossypium barbadense L. germplasm based on fibre characters. Journal of Cotton Research 6, 15. doi: 10.1186/s42397-023-00153-yGoogle Scholar
Mathangadeera, RW, Hequet, EF, Kelly, B, Dever, JK and Kelly, CM (2020) Importance of cotton fibre elongation in fibre processing. Industrial Crops and Products 147, 112217. doi: 10.1016/j.indcrop.2020.112217CrossRefGoogle Scholar
Mayank, S and Singh, MP (2013) Assessment of plant diversity indices of Gomati riparian corridors in district Jaunpur, India. Ecoprint 20, 71–76.Google Scholar
Meena, RA, Monga, D, Venugopalan, MV, Ahuja, SL and Sahay, R (2016) Screening of desi cotton (G. arboreum) suitable for surgical properties. Journal of Scientific & Industrial Research 75, 570–573. http://nopr.niscpr.res.in/handle/123456789/35285Google Scholar
Mehetre, SS, Aher, AR, Gawande, VL, Patil, VR and Mokate, AS (2003) Induced polyploidy in Gossypium: a tool to overcome interspecific incompatibility of cultivated tetraploid and diploid cottons. Current Science 84, 1510–1512. https://www.jstor.org/stable/24108253Google Scholar
Mendez-Natera, JR, Rondón, A, Hernandez, J and Merazo-Pinto, JF (2012) Genetic studies in upland cotton. III. Genetic parameters, correlation and path analysis. Sabrao Journal of Breeding and Genetics 44, 112–128.Google Scholar
Meredith, WJ, Boykin, DL, Bourland, FM, Caldwell, WD, Campbell, BT, Gannaway, JR, Glass, K, Jones, AP, May, LM, Smith, CW and Zhang, JF (2012) Genotype × environment interactions over seven years for yield, yield components, fibre quality, and gossypol traits in the regional high quality tests. Journal of Cotton Science 16, 160–169.Google Scholar
Morris, EK, Caruso, T, Buscot, F, Fischer, M, Hancock, C, Maier, TS, Meiners, T, Müller, C, Obermaier, E, Prati, D and Socher, SA (2014) Choosing and using diversity indices: insights for ecological applications from the German biodiversity exploratories. Ecology and Evolution 4, 3514–3524. doi: 10.1002/ece3.1155CrossRefGoogle ScholarPubMed
Naoumkina, M, Thyssen, GN, Fang, DD, Jenkins, JN, McCarty, JC and Florane, CB (2019) Genetic and transcriptomic dissection of the fibre length trait from a cotton (Gossypium hirsutum L.) MAGIC population. BMC Genomics 20, 112. doi: 10.1186/s12864-019-5427-5CrossRefGoogle ScholarPubMed
Narayanan, SS, Vidyasagar, P and Babu, KS (2014) Cotton germplasm in India – new trends. World Cotton Germplasm Resources, 87–118. https://dx.doi.org/10.5772/58622Google Scholar
Parsi, RD, Kakde, MV, Pawar, K and Patil, RP (2016) Influence of fibre length on ring spun yarn quality. International Journal of Research and Scientific Innovation 3, 154–156.Google Scholar
Razzaq, A, Zafar, MM, Ali, A, Hafeez, A, Batool, W, Shi, Y, Gong, W and Yuan, Y (2021) Cotton germplasm improvement and progress in Pakistan. Journal of Cotton Research 4, 1–4. doi: 10.1186/s42397-020-00077-xCrossRefGoogle Scholar
Reddy, VRP, Das, S, Dikshit, HK, Mishra, GP, Aski, M, Meena, SK, Singh, A, Pandey, R, Singh, MP, Tripathi, K and Gore, PG (2020a) Genome-wide association analysis for phosphorus use efficiency traits in mungbean (Vigna radiata L. Wilczek) using genotyping by sequencing approach. Frontiers in Plant Science 11, 537766. doi: 10.3389/fpls.2020.537766CrossRefGoogle ScholarPubMed
Reddy, VRP, Aski, MS, Mishra, GP, Dikshit, HK, Singh, A, Pandey, R, Singh, MP, Gayacharan, , Ramtekey, V, Priti, and Rai, N (2020b) Genetic variation for root architectural traits in response to phosphorus deficiency in mungbean at the seedling stage. PLoS ONE 15, e0221008. doi: 10.1371/journal.pone.0221008CrossRefGoogle ScholarPubMed
Reddy, VRP, Dikshit, HK, Mishra, GP, Aski, M, Singh, A, Bansal, R, Pandey, R and Nair, RM (2021) Comparison of different selection traits for identification of phosphorus use efficient lines in mungbean. PeerJ 9, e12156. doi: 10.7717/peerj.12156CrossRefGoogle ScholarPubMed
Romeu-Dalmau, C, Bonsall, MB, Willis, KJ and Dolan, L (2015) Asiatic cotton can generate similar economic benefits to Bt cotton under rainfed conditions. Nature Plants 1, 1–5. doi: 10.1038/nplants.2015.72CrossRefGoogle Scholar
Sahar, A, Zafar, MM, Razzaq, A, Manan, A, Haroon, M, Sajid, S, Rehman, A, Mo, H, Ashraf, M, Ren, M and Shakeel, A (2021) Genetic variability for yield and fibre related traits in genetically modified cotton. Journal of Cotton Research 4, 19. doi: 10.1186/s42397-021-00094-4CrossRefGoogle Scholar
Singh, SA, Singh, VV and Choudhary, AD (2014) Genotype × environment interaction and yield stability analysis in multi environment. Tropical and Subtropical Agroecosystems 17, 477–482.CrossRefGoogle Scholar
Snider, JL, Collins, GD, Whitaker, J and Davis, JW (2013) Quantifying genotypic and environmental contributions to yield and fibre quality in Georgia: data from seven commercial cultivars and 33 yield environments. The Journal of Cotton Science 17, 285–292.Google Scholar
Sun, Z, Wang, X, Liu, Z, Gu, Q, Zhang, Y, Li, Z, Ke, H, Yang, J, Wu, J, Wu, L, Zhang, G and Ma, Z (2019) Evaluation of the genetic diversity of fibre quality traits in upland cotton (Gossypium hirsutum L.) inferred from phenotypic variations. Journal of Cotton Research 2, 1–8. doi: 10.1186/s42397-019-0041-2CrossRefGoogle Scholar
Ullah, A, Shakeel, A, Ahmed, HGMD, Ali, M, Shah, AN, Jaremko, M, Abdelsalam, NR, Ghareeb, RY and Hasan, ME (2022) Genetic basis and principal component analysis in cotton (Gossypium hirsutum L.) grown under water deficit condition. Frontiers in Plant Science 13, 981369. doi: 10.3389/fpls.2022.981369CrossRefGoogle ScholarPubMed
Wang, M, Wang, Q and Wang, B (2012) Identification and characterization of microRNAs in Asiatic cotton (Gossypium arboreum L.). PLoS ONE 7, e33696. doi: 10.1371/journal.pone.0033696CrossRefGoogle ScholarPubMed
Yadav, RK, Gautam, S, Palikhey, E, Joshi, BK, Ghimire, KH, Gurung, R, Adhikari, AR, Pudasaini, N and Dhakal, R (2018) Agro-morphological diversity of Nepalese naked barley landraces. Agriculture & Food Security 7, 1–2. doi: 10.1186/s40066-018-0238-5CrossRefGoogle Scholar
Yu, J, Zhang, K, Li, S, Yu, S, Zhai, H, Wu, M, Li, X, Fan, S, Song, M, Yang, D and Li, Y (2013) Mapping quantitative trait loci for lint yield and fibre quality across environments in a Gossypium hirsutum × Gossypium barbadense backcross inbred line population. Theoretical and Applied Genetics 126, 275–287. doi: 10.1007/s00122-012-1980-xCrossRefGoogle Scholar
Supplementary material: File

Prakash Reddy et al. supplementary material

Prakash Reddy et al. supplementary material
Download Prakash Reddy et al. supplementary material(File)
File 510.7 KB