Assessing Stability and Correlations Among Cotton Seed Quality Traits Across Multiple Environments Using the Stability Index
Source abstract
Abstract
The stability of seed quality traits is a key factor for developing reliable cotton cultivars with consistent performance across diverse environments. This study evaluated six seed traits (1000-seed weight, crude protein, oil, ash, crude fiber, and moisture) across five commercial upland cotton cultivars grown in four distinct environments in Greece. Field trials were conducted in ten independent commercial fields per cultivar within each environment, with four samples collected from each field. Seed quality traits were analyzed using recommended official methods, and the Stability Index (SI) was calculated for each trait to quantify consistency across environments and cultivars. Traits such as 1000-seed weight, oil, and crude protein exhibited more consistent expression across environments and cultivars, whereas crude fiber and moisture showed substantial variation in stability across environments and cultivar × environment combinations, reflecting strong genotype × environment effects. Evaluation of relationships between traits revealed significant positive associations between 1000-seed weight and oil, and between crude protein and ash, as well as negative associations between 1000-seed weight and moisture and between crude protein and oil, indicating potential trade-offs among seed traits. Principal component analysis further highlighted trait associations and variability patterns across genotypes and environments. Overall, the combined use of Stability Index assessments and multivariate analyses provides a robust descriptive framework for evaluating cultivar performance and supporting cultivar selection under diverse agro-ecological conditions.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Research in Cotton Cultivation · Genetics and Plant Breeding · Seed Germination and Physiology
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Industrial and Forage Crops, Hellenic Agricultural Organization Demeter (ELGO-Dimitra), 41335 Larissa, Greece
National Center for Quality Control, Classification & Standardization of Cotton, Hellenic Agricultural Organization Demeter (ELGO-Dimitra), 1st km Karditsa-Mitropolis, 43100 Karditsa, Greece
Department of Viticulture and Oenology, Democritus University of Thrace, 66100 Drama, Greece
Department of Animal Science, University of Thessaly, Campus Gaiopolis, 41500 Larissa, Greece
Regional Administration of West Macedonia, 50131 Kozani, Greece
References (37)
Show source-provided references
1. Stability Parameters for Comparing Varieties10.2135/cropsci1966.0011183X000600010011x ↗
2. Fasoulas, A.C. (1988). The Honeycomb Methodology of Plant Breeding, Department of Genetics and Plant Breeding, Aristotle University of Thessaloniki.
3. Genotypic stability10.1007/BF00285245 ↗
4. Repeatability of stability estimators for grain yield in wheat10.2135/cropsci1993.0011183X003300040017x ↗
5. Fasoulas, A.C. (1993). Principles of Crop Breeding, Department Genetic and Plant Breeding, Aristotelian University of Thessaloniki.
6. Prognostic Breeding: A new paradigm for crop improvement10.1002/9781118497869.ch6 ↗
7. Stability analysis: Where do we stand?10.2135/cropsci1986.0011183X002600050012x ↗
8. Statistical analysis of yield trial10.2134/agronj1988.00021962008000030002x ↗
9. Yan, W., and Kang, M.S. (2003). GGE Biplot Analysis: A Graphical Tool for Breeders, Geneticists, and Agronomists, CRC Press.10.1201/9781420040371 ↗
10. Statistical analysis of yield trials by AMMI and GGE10.2135/cropsci2005.07-0193 ↗
11. Greveniotis, V., Bouloumpasi, E., Zotis, S., Korkovelos, A., Kantas, D., and Ipsilandis, C.G. (2023). Genotype-by-Environment Interaction Analysis for Quantity and Quality Traits in Faba Beans Using AMMI, GGE Models, and Stability Indices. Plants, 12.10.3390/plants12213769 ↗
12. Greveniotis, V., Bouloumpasi, E., Zotis, S., Korkovelos, A., Kantas, D., and Ipsilandis, C.G. (2023). A Comparative Study on Stability of Seed Characteristics in Vetch and Pea Cultivations. Agriculture, 13.10.3390/agriculture13051092 ↗
13. Greveniotis, V., Bouloumpasi, E., Zotis, S., Korkovelos, A., Kantas, D., and Ipsilandis, C.G. (2023). Stability Dynamics of Main Qualitative Traits in Maize Cultivations across Diverse Environments regarding Soil Characteristics and Climate. Agriculture, 13.10.3390/agriculture13051033 ↗
14. Zhang, J., Wang, M., Peng, C., Chen, H., and Cao, X. (2025). Adaptability and Stability of Proso Millet Grain Yield: A Multi-Environment Evaluation Using AMMI, GGE, and GYT Biplots. Plants, 14.10.3390/plants14172719 ↗
15. AMMI and GGE biplot analysis for yield performance and stability assessment of selected Bambara groundnut (Vigna subterranea L. Verdc.) genotypes under the multi-environmental trials (METs)10.1038/s41598-021-01411-2 ↗
16. Omrani, A., Omrani, S., Khodarahmi, M., Shojaei, S.H., Illés, Á., Bojtor, C., Mousavi, S.M.N., and Nagy, J. (2022). Evaluation of Grain Yield Stability in Some Selected Wheat Genotypes Using AMMI and GGE Biplot Methods. Agronomy, 12.10.3390/agronomy12051130 ↗
17. Yield Adaptability and Stability of Grain Sorghum Genotypes across Different Environments in Egypt Using AMMI and GGE-Biplot Models
18. Screening of cotton genotypes for protein content, oil and fatty acid composition
19. Genotype × Environment Interactions for Oil Content in Cotton (Gossypium hirsutum L.) Cultivars Grown in Northern Cameroon
20. Compositional profile of barley landlines grown in different regions of Gilgit-Baltistan10.1002/fsn3.2215 ↗
21. European Soil Data Centre (ESDAC) (2026, January 15). Soil Map of Greece (1:1,000,000 Scale), Available online: https://esdac.jrc.ec.europa.eu/public_path/shared_folder/maps/eudasm_newmaps/GR/PDF/GRSoilMap_ENG.pdf.
22. FAO, and IUSS Working Group WRB World Reference Base for Soil Resources 2022, Update 2022, Food and Agriculture Organization of the United Nations. Available online: https://www.fao.org/soils-portal/data-hub/soil-classification/en/.
23. AOAC (2005). Official Methods of Analysis of AOAC International, AOAC International. [18th ed.].
24. Steel, R.G.D., Torrie, H., and Dickey, D.A. (1997). Principles and Procedures of Statistics. A Biometrical Approach, McGraw-Hill. [3rd ed.].
25. Estimations of fibre trait stability and type of inheritance in cotton10.17221/12/2017-CJGPB ↗
26. Multi-environment Evaluations Across Ecological Regions Reveal That the Kernel Oil Content of Cottonseed Is Equally Determined by Genotype and Environment10.1021/acs.jafc.1c07082 ↗
27. Cottonseed oil: A review of extraction techniques, physicochemical, functional, and nutritional properties10.1080/10408398.2021.1963206 ↗
28. Genotypic and environmental variability and stability of seed yield, oil content and fatty acids in high-oleic and high-linoleic safflower (Carthamus tinctorius L.) lines and cultivars
29. Quantifying Genotypic and Environmental Contributions to Yield and Fiber Quality in Georgia: Data from Seven Commercial Cultivars and 33 Yield Environments
30. Genetic variation for agronomic and fiber properties in an introgressed recombinant inbred population of cotton10.2135/cropsci2005.08-0284 ↗
31. Heatmap clustering and performance analysis of cotton genotypes in response to environmental conditions10.1038/s41598-025-02682-9 ↗
32. Sehgal, A., Sita, K., Siddique, K.H.M., Kumar, R., Bhogireddy, S., Varshney, R.K., HanumanthaRao, B., Nair, R.M., Prasad, P.V.V., and Nayyar, H. (2018). Drought or/and Heat-Stress Effects on Seed Filling in Food Crops: Impacts on Functional Biochemistry, Seed Yields, and Nutritional Quality. Front. Plant Sci., 9.10.3389/fpls.2018.01705 ↗
33. Heterosis and gene action in cotton (Gossypium hirsutum L)10.2135/cropsci1972.0011183X001200030015x ↗
34. Seed Oil Content, Yield and Fiber Quality Traits in Some Egyptian Cotton Genotypes
35. Li, Y., Guo, W., He, L., and Cao, X. (2025). Genetic Analysis of Main Gene + Polygenic Gene of Nutritional Traits of Land Cotton Cottonseed. Agronomy, 15.10.3390/agronomy15071713 ↗
36. Wu, M., Pei, W., Wedegaertner, T., Zhang, J., and Yu, J. (2022). Genetics, Breeding and Genetic Engineering to Improve Cottonseed Oil and Protein: A Review. Front. Plant Sci., 13.10.3389/fpls.2022.864850 ↗
37. Quantitative genomics-enabled selection for simultaneous improvement of lint yield and seed traits in cotton (Gossypium hirsutum L.)10.1007/s00122-024-04645-6 ↗