This is an outdated version published on 23-12-2022. Read the most recent version.

Forthcoming

Assessment of genotype by year interaction for yield components and physiological traits in cotton under drought stress using multivariate analysis and genetic parameters

Authors

Waleed Mohamed Bassuny Yehia Cotton Research Institute, Agriculture Research Center, Giza 12619, Egypt. https://orcid.org/0000-0001-9552-6635
Essam Fathy El-Hashash Department of Agronomy, Faculty of Agriculture, Al-Azhar University, Cairo 11651, Egypt. https://orcid.org/0000-0002-0488-0610
Salem Mesfir Al-Qahtani Biology Department, University College of Tayma, University of Tabuk, P.O. Box 741, Tabuk, Saudi Arabia https://orcid.org/0000-0003-0940-7985
Nadi Awad Al-Harbi Biology Department, University College of Tayma, University of Tabuk, P.O. Box 741, Tabuk, Saudi Arabia https://orcid.org/0000-0002-9631-6952

DOI:

https://doi.org/10.14719/pst.1909

Keywords:

drought stress, Cotton, Physiology, Cluster analysis

Abstract

The objective of this study was to identify genotype high yielding and drought-tolerant, by understanding the interaction GY pattern for yield, yield components and physiological traits in 24 cotton genotypes over five years under drought stress conditions using AMMI analysis, genetic parameters and multivariate analysis. All assessed traits were significantly impacted by genotypes and GY interaction using the AMMI model, with the exception of chlorophyll b by GY interaction. Meanwhile, seed cotton yield/plant, number of open bolls/plant, lint percentage, lint cotton yield/plant, and number of fruiting branches/plant were significantly affected by the year's factor. High BSH coupled with high GAM% was observed for all studied traits, indicating the heritability due to additive type of gene action and, the importance of these genotypes and the possibility of effective selection for drought-tolerant genotype development. A statistically significant correlation was discovered between cotton yield and most investigated traits under drought stress conditions. Direct selection can be done through these traits based on genetic parameters and Pearson's correlations analyses, which will be effective for drought tolerance and enhancing cotton yield. The results of our study's Pearson's correlation analysis, PCA and cluster analysis could be relevant and appropriate for studying drought tolerance mechanisms and cotton yield improvement. According to PCA and cluster analysis, the genotypes G20 and G19 followed by G5, G4 and G21 genotypes showed the best performance in response to drought stress regarding the yield, yield components and physiological-related traits. The previous genotypes could be used in future cotton breeding efforts in Egypt to promote drought tolerance, improve cotton productivity, and sustainable production during drought stress conditions.

Downloads

Download data is not yet available.

References

Rehman A, Farooq M. Morphology, Physiology and Ecology of Cotton Chapter 2. Cotton Production, 1st Ed. Edited Khawar Jabran and Bhagirath Singh Chauhan. John Wiley & Sons Ltd. 2020.

Al Didi MA. History of Egyptian cotton varieties. Egypt Cotton Gazette. 1972;58: 36-56.

Abdelbary AM, Hamoud HM, Yehiya WM, Abdelmoghny AM, Rabi EM, Ali SE et al. "Giza 97" A new Egyptian long staple cotton variety. Egyptian J of Agric Res. 2021;99(3):284-95. DOI: 10.21608/EJAR.2021.89116.1125

USDA. World Agricultural Production United States Department of Agriculture Foreign Agricultural Service, Office of Global Analysis, Circular Series, WAP 2-22, February 2022: 1-39. https://apps.fas.usda.gov/psdonline/circulars/production.pdf

Lamaoui M., Jemo M, Datla R, Bekkaoui F. Heat and drought stresses in crops and approaches for their mitigation. Front in Chem. 2018;6:26. https://doi.org/10.3389/fchem.2018.00026

Rehman T, Tabassum B, Yousaf S, Sarwar G and Qaisar U. Consequences of drought stress encountered during seedling stage on physiology and yield of cultivated cotton. Front Plant Sci. 2022;13:906444. doi: 10.3389/fpls.2022.906444

Mahmood T, Khalid S, Abdullah M, Ahmed Z, Shah MKN, Ghafoor A, Du X. Insights into drought stress signaling in plants and the molecular genetic basis of cotton drought tolerance. Cells. 2019;9:105-35. doi: 10.3390/cells9010105

Jie Z, Wei H, Li Y-X, He J-Q, Zhu H-H, Zhou Z-G. Screening of drought resistance indices and evaluation of drought resistance in cotton (Gossypium hirsutum L.). J Integ Agric. 2020;19:495-508. doi: 10.1016/S2095-3119(19)62696-1

Manivannan P, Jaleel CA, Sankar B, Kishorekumar A, Somasundaram R, Lakshmanan GMA, Panneerselvam R. Growth, biochemical modifications and proline metabolism in Helianthus annuus L. as induced by drought stress. Colloids Surf B Biointerfaces. 2007;59: 141-49. doi: 10.1016/j.colsurfb.2007.05.002

Meshram JH, Singh SB, Raghavendra KP, Waghmare VN. Chapter 6 - Drought stress tolerance in cotton: progress and perspectives, Editors: Arun K. Shanker, Chitra Shanker, Anjali Anand, M. Maheswari, Climate Change and Crop Stresspp. 2022;135-69. https://doi.org/10.1016/B978-0-12-816091-6.00005-5

El-Hashash EF, Agwa MA. Genetic parameters and stress tolerance index for quantitative traits in barley under different drought stress severities. Asian J of Res in Crop Sci. 2018;1(1): 1-16. https://doi.org/10.9734/AJRCS/2018/38702

Hall AE. Is dehydration tolerance relevant to genotypic differences in leaf senescence and crop adaptation to dry environments? In: Close T.J. and Bray E.A. (Editors). Plant Responses to Cellular Dehydration during Environmental Stress. 1993; p.1-10.

Solis J, Gutierrez A, Mangu V, Sanchez E, Bedre R, Linscombe S. Baisakh N. Genetic mapping of quantitative trait loci for grain yield under drought in rice under controlled greenhouse conditions. Front in Chem. 2018;5: 1-12. https://doi.org/10.3389/fchem.2017.00129

Blum A. Plant Breeding for Stress Environments. Florida: CRC Press. p. 212.

Falconer DS, TFC Mackay. 1996. Introduction to Quantitative Genetics, 4th edition Longman, New York. 1988;132-33p.

El-Hashash EF, EL-Agoury RYA, El-Absy KM, Sakr SMI. Genetic parameters, multivariate analysis and tolerance indices of rice genotypes under normal and drought stress environments. Asian J of Res in Crop Sci. 2018;1(3): 1-18. https://doi.org/10.9734/AJRCS/2018/41549

Eberhart SA, Russel WA. Stability parameters for comparing varieties. Crop Sci. 1966;6(1): 36-40. https://doi.org/10.2135/cropsci1966.0011183X000600010011x

Kang MS. Genotype-by-environment interaction and plant breeding. Louisana State University Agricultural Center, Baton Rouge, LA, USA. 1990; pp 392.

El-Hashash EF, Tarek SM, Rehab AA, Tharwat MA. Comparison of non-parametric stability statistics for selecting stable and adapted soybean genotypes under different environments. Asian J of Res in Crop Sci. 2019;4(4): 1-16. https://doi.org/10.9734/ajrcs/2019/v4i430080

Becker HC, Leon. J. Stability analysis in plant breeding. Plant Breeding. 1988;101(1): 1-23. https://doi.org/10.1111/j.1439-0523.1988.tb00261.x

Zobel RW, Wright MG,. Gauch HG. Statistical analysis of yield trial. Agron J. 1988;80(3): 388-93. https://doi.org/10.2134/agronj1988.00021962008000030002x

Campbell BT, Jones MA. Assessment of genotype × environment interactions for yield and fiber quality in cotton performance trials. Euph. 2005;144: 69-78. https://doi.org/10.1007/s10681-005-4336-7

Xu N, Fok M, Zhang G, Li J, Zhou Z. The application of GGE biplot analysis for evaluat ng test locations and mega-environment investigation of cotton regional trials. J of Integr Agric. 2014;13(9): 1921-33. https://doi.org/10.1016/S2095-3119(13)60656-5

Maleia MP, Jamal EC, Savanguane JW, João J, Teca JO. Stability and adaptability of cotton (Gossypium Hirsutum L.) genotypes under multi environmental conditions in mozambique. J of Agron and Agric Sci. 2019;2: 017. DOI:10.24966/AAS-8292/100017

Teodoro PE, Azevedo CF, Farias FJC, Alves RS, Peixoto LA, Ribeiro LP, Carvalho LP, Bhering. LL. Adaptability of cotton (Gossypium hirsutum) genotypes analysed using a Bayesian AMMI model. Crop and Past Sci. 2019;70(7): 615-21. https://doi.org/10.1071/CP18318

Lingaiah N, Sudharshanam A, Rao VT, Prashant Y, Kumar MV, Reddy PI, Prasad BR, Reddy PRR, Rao PJM. AMMI Biplot Analysis in Cotton (Gossypium hirsutum L.) Genotypes for genotype x environment interaction at four agro-ecologies in Telangana State. Curr J of Appl Sci and Tech. 2020;39(15): 98-103. https://doi.org/10.9734/cjast/2020/v39i1530722

Dutta P, Dutta PN, Borua PK. Morphological traits as selection indices in rice: A statistical view. Univ J of Agric Res. 2013;1(3): 85-96. DOI: 10.13189/ujar.2013.010308

Sabesan T, Suresh R, Saravanan K. Genetic variability and correlation for yield and grain quality characters of rice grown in coastal saline low land of Tamilnadu. Electron J Plant Breed. 2009;1:56-59.

Shukla S, Bhargava A, Chatterjee A, Singh S. Estimates of genetic parameters to determine variability for foliage yield and its different quantitative and qualitative traits in vegetable amaranth (A. tricolor). J Gene Breed. 2004;58: 169-76.

El-Hashash EF, EL-Agoury RYA. Comparison of grain yield-based drought tolerance indices under normal and stress conditions of rice in Egypt. Scholars J of Agric and Vet Sci. 2019;6(1):41-54. DOI: 10.21276/sjavs.2019.6.1.6

Burton GW, Devane EM. Estimating heritability in tall fescue (Festuca arundinacea) from replicated clonal material. Agron J. 1953;45: 478-81. https://doi.org/10.2134/agronj1953.00021962004500100005x

Rathinavel K. Principal component analysis with quantitative traits in extant cotton varieties (Gossypium hirsutum L.) and parental lines for diversity. Currr Agric Res J. 2018;6(1). http://dx.doi.org/10.12944/CARJ.6.1.07

Shah SAI, Khan SJ, Ullah K, Sayal OU. Genetic diversity in cotton germplasm using multivariate analysis. Sarhad J of Agric. 2018;34(1): 130-35. http://dx.doi.org/10.17582/journal.sja/2018/34.1.130.135

Abdel-Monaem, MA, Abido WAE, Hadházy A, Ghoneima MH, EL-Mansy YM, EL-Shazly MW. Genetic divergence among Egyptian cotton genotypes under water deficit conditions. Acta Eco Sin. 2020. https://doi.org/10.1016/j.chnaes.2020.11.007

Sarwar G, Nazir A, Rizwan M, Shahzadi E, Mahmood A. Genetic diversity among cotton genotypes for earliness, yield and fiber quality traits using correlation, principal component and cluster analyses. Sarhad J of Agric. 2021;37(1): 307-14. http://dx.doi.org/10.17582/journal.sja/2021/37.1.307.314

Raza I, Hu D, Ahmad A, Li H, He S, Nazir MF et al. Correlation analysis of stem hardness traits with fiber and yield-related traits in core collections of Gossypium hirsutum. J of Cotton Res. 2021;4:8. https://doi.org/10.1186/s42397-021-00082-8

Mahmood T, Wang X, Ahmar S, Abdullah M, Iqbal MS, Rana RM et al. Genetic potential and inheritance pattern of phenological growth and drought tolerance in cotton (Gossypium hirsutum L.). Front Plant Sci. 2021;12:705392. https://doi.org/10.3389/fpls.2021.705392

Zahid Z, Khan MKR, Hameed A, Akhtar M, Ditta A, Hassan HM, Farid G. Dissection of drought tolerance in upland cotton through morpho-physiological and biochemical traits at seedling stage. Front Plant Sci. 2021;12:627107. doi: 10.3389/fpls.2021.627107

Zafar MM, Jia X, Shakeel A, Sarfraz Z, Manan A, Imran A et al. Unraveling heat tolerance in upland cotton (Gossypium hirsutum L.) using univariate and multivariate analysis. Front Plant Sci. 2022;12: 727835. https://doi.org/10.3389/fpls.2021.727835

Lichtenthaler HK. Chlorophylls and carotenoids: pigments of photosynthetic biomembranes. In: Packer, L.; Douce, R., Editors. Methods in enzymology. London: Academic Press. 1987;148: 350-82. https://doi.org/10.1016/0076-6879(87)48036-1

Bates LS, Waldren RP Teare ID. Rapid determination of free proline for water-stress studies. Plant Soil. 1973;39: 205-07. https://doi.org/10.1007/BF00018060

Gomes FP. Curso de estatística experimental. 15.ed. Piracicaba: Esalq. 2009; p 477.

Searle SR, Casella G, McCulloch CE. Variance components. New Jersey: A John Wiley & Sons Inc. 2006.

Fehr WR. Principle of Cultivars Development. Macmillan publishing company. A division of Macmillan Inc. New Yor. 1987; pp.1: 1-465.

Robinson HF, Comstock RE, Harvey PH. Estimates of heritability and degree of dominance in corn. Agron J. 1949;41(8): 353-59. https://doi.org/10.2134/agronj1949.00021962004100080005x

Burton GW. Quantitative Inheritance in Grasses. Proceeding of 6th International Grassland Congress, Vol. 1, Pennsylvania State College. 17-23 August: 1952; 277-83.

Johnson HW, Robinson HF, Comstock RE. Estimates of genetic and environmental variability in soya bean. Agron J. 1955;47: 318-24. https://doi.org/10.2134/agronj1955.00021962004700070009x

Gauch HG Jr. 1992. Statistical analysis of regional yield trials: AMMI analysis of factorial designs. Elsevier Science Publishers. 1992.

Enyew M, Feyissa T, Geleta M, Tesfaye K, Hammenhag C, Carlsson AS. Genotype by environment interaction, correlation, AMMI, GGE biplot and cluster analysis for grain yield and other agronomic traits in sorghum (Sorghum bicolor L. Moench). PLoS ONE. 2021;16(10): e0258211. https://doi.org/10.1371/journal.pone.0258211

Manan A, Zafar M, Ren M, Khurshid M, Sahar A, Rehman A, Firdous H, Youlu Y, Razzaq A, Shakeel A. Genetic analysis of biochemical, fiber yield and quality traits of upland cotton under high-temperature. Plant Prod Sci. 2021. https://doi.org/10.1080/1343943X.2021.1972013

Yehia WMB, El-Hashash EF. Correlation and multivariate analysis across non-segregation and segregation generations in two cotton crosses. Egyptian J of Agric Res. 2021;99(3): 354-64. DOI: 10.21608/EJAR.2021.81571.1117

El-Hashash EF, Yehia WMB. Estimation of heritability, genes number and multivariate analysis using non- segregation and segregation generations in two cotton crosses. Asian J of Bioch Genet and Mol Bio. 2021;9(3): 45-62. https://doi.org/10.9734/ajbgmb/2021/v9i330221

Li B, Tian Q, Wang X, Han B, Liu L, Kong X et al. Phenotypic plasticity and genetic variation of cotton yield and its related traits under water-limited conditions. The Crop J. 2020;8(6): 966-76. https://doi.org/10.1016/j.cj.2020.02.003

Fang Y, Xiong L. General mechanisms of drought response and their application in drought resistance improvement in plants. Cell and Mol Life Sci. 2015;72: 673-89. https://doi.org/10.1007/s00018-014-1767-0

Anwar M, Saleem MA, Dan M, Malik W, Ul-Allah S, Ahmad MQ et al. Morphological, physiological and molecular assessment of cotton for drought tolerance under field conditions. Saudi J of Biolog Sci. 2022;29(1): 444-52. https://doi.org/10.1016/j.sjbs.2021.09.009

Grzesiak S, Hordy?ska N, Szczyrek P, Grzesiak MA, Noga A, Szechy?ska-Hebda M. Variation among wheat (Triticum easativum L.) genotypes in response to the drought stress: I – selection approaches. J of Plant Interac. 2019;14(1): 30-44. https://doi.org/10.1080/17429145.2018.1550817

Parida AK, Dagaonkar VS, Phalak MS, Umalkar GV, Aurangabadkar LP. Alterations in photosynthetic pigments, protein and osmotic components in cotton genotypes subjected to short-term drought stress followed by recovery. Plant Biotech. Repor. 2007;1: 37-48. https://doi.org/10.1007/s11816-006-0004-1

Parida AK, Dagaonkar VS, Phalak MS, Aurangabadkar LP. Differential responses of the enzymes involved in proline biosynthesis and degradation in drought tolerant and sensitive cotton genotypes during drought stress and recovery. Acta Physiolo. Planta. 2008;30(5): 619-27. doi: 10.1007/s11738-008-0157-3

Ergashova GS. Determination of chlorophyll content in leaves of G. hirsutum L. species in conditions of water shortage. Intern J of Sci and Res. 2020;9(8): 1427-30. DOI: 10.21275/SR20813122004

Ahmadizadeh M. Physiological and agro-morphological response to drought stress. Middle East J of Scient Res. 2013;13(8): 998-1009. DOI: 10.5829/idosi.mejsr.2013.13.8.3531

Ahmad A, Aslam Z, Javed T, Hussain S, Raza A, Shabbir R et al. Screening of wheat (Triticum aestivum L.) genotypes for drought tolerance through agronomic and physiological response. Agron. 2022;12: 287. https://doi.org/10.3390/agronomy12020287

Monteoliva MI, Guzzo MC,. Posada GA. Breeding for drought tolerance by monitoring chlorophyll content. Gene Technolo. 2021;10:165.

Reddy AR, Chaitanya KV, Vivekanandan M. Drought-induced responses of photosynthesis and antioxidant metabolism in higher plants. J of Plant Physiolo. 2004;161(11): 1189-202. https://doi.org/10.1016/j.jplph.2004.01.013

Iqbal S. Physiology of wheat (Triticum aestivum L.) accessions and the role of phytohormones under water stress Quaid-I-Azam University. 2009; Available online at: http://173.208.131.244:9060/xmlui/handle/123456789/7315

Dhanda SS, Sethi GS, Behl RK. Indices of drought tolerance in wheat genotypes at early stages of plant growth. J Agron Crop Sci. 2004;190(1): 6-12. https://doi.org/10.1111/j.1439-037X.2004.00592.x

Sarif HM, Rafii, MY, Ramli A, Oladosu Y, Musa HM, Rahim HM et al. Genetic diversity and variability among pigmented rice germplasm using molecular marker and morphological traits. Biotechnology and Biotechnological Equip. 2020; 34(1): 747-62. https://doi.org/10.1080/13102818.2020.1804451

Garg HS, Kumar, P, Bhattacharya C, Panja S, Kumar R. Genetic parameters estimation for yield and yield related traits in rice (Oryza sativa L.) with drought tolerance trait under stress condition. J of Crop and Weed. 2017;13(1):83-88.

Yehia WMB, Hamoud, HME, EL-Akhader AAA, Abd EL-Gelil MA. Yield and fiber quality potential for triallel hybrids in cotton .2- Superiority J Agric Sci. Mansoura Univ. 2009;34(6): 6145-62. DOI: 10.21608/JACB.2009.90279

Khokhar ES, Shakeel A, Maqbool MA, Anwar MW, Tanveer Z, Irfan MF. Genetic study of cotton (Gossypium hirsutum L.) genotypes for different agronomic, yield and quality traits. Pakistan J of Agric Res. 2017;30(4):363-72. http://dx.doi.org/10.17582/journal.pjar/2017/30.4.363.372

Sahar A, Zafar MM, Razzaq A, Manan A, Haroon M, Sajid S et al. Genetic variability for yield and fiber related traits in genetically modified cotton. J of Cotton Res. 2021;4:19. https://doi.org/10.1186/s42397-021-00094-4

Abro S, Rizwan M, Deho ZA, Abro SA, Sial MA. Identification of heat tolerant cotton lines showing genetic variation in cell membrane thermostability, stomata and trichome size and its effect on yield and fiber quality traits. Front Plant Sci. 2022;12: 804315. https://doi.org/10.3389/fpls.2021.804315

Khodadadi M, Fotokian MH, Miransari M. Genetic diversity of wheat (Triticum aestivum L.) genotypes based on cluster and principal component analyses for breeding strategies. Australian J of Crop Sci. 2011;5: 17-24.

Magwanga RO, Lu, P, Kirungu JN, Cai X, Zhou Z, Agong SG et al. Identification of QTLs and candidate genes for physiological traits associated with drought tolerance in cotton. J of Cotton Res. 2020;3: 3. https://doi.org/10.1186/s42397-020-0043-0

Soomro AW. Estimation of genetic variability parameters in segregating F2 generation of cotton. Fuuast J of Bio. 2020;10(2):83-87.

Chaudhari M, Faldu G, Ramani HJAIB. Genetic variability, correlation and path coefficient analysis in cotton (Gossypium hirsutum L.). Adva in Bioresea. 2017;8(6): 226-33..DOI: 10.15515/abr.0976-4585.8.6.226233

Sabri RS, Rafii MY, Ismail MR, Yusuff O, Chukwu SC, Hasan N. Assessment of agro-morphologic performance, genetic parameters and clustering pattern of newly developed blast resistant rice lines tested in four environments. Agron. 2020;10(8): 1098. https://doi.org/10.3390/agronomy10081098

Majeed S, Malik TA, Rana IA, Azhar MT. Antioxidant and physiological responses of upland cotton accessions grown under high-temperature regimes. Iranian J of Sci and Tech Transactions A: Sci. 2019; 43: 2759-68. https://doi.org/10.1007/s40995-019-00781-7

Yehia WMB, El-Hashash EF. Combining ability effects and heterosis estimates through line x tester analysis for yield, yield components and fiber traits in Egyptian cotton. Elixir Agric. 2019; 131: 53238-46.

Downloads

Published

23-12-2022

Versions

How to Cite

Yehia WMB, El-Hashash EF, Al-Qahtani SM, Al-Harbi NA. Assessment of genotype by year interaction for yield components and physiological traits in cotton under drought stress using multivariate analysis and genetic parameters . Plant Sci. Today [Internet]. 2022 Dec. 23 [cited 2024 Dec. 22];. Available from: https://horizonepublishing.com/journals/index.php/PST/article/view/1909

Download Citation

Issue

Early Access

Section

Research Articles

License

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

Copyright and Licence details of published articles

Authors who publish with this journal agree to the following terms:

Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.

Open Access Policy

Plant Science Today is an open access journal. There is no registration required to read any article. All published articles are distributed under the terms of the Creative Commons Attribution License (CC Attribution 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited (https://creativecommons.org/licenses/by/4.0/). Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).