Assessment of genetic variation in sainfoin landraces based on agronomic characteristics using a genotype-by-trait biplot model

Document Type : Research paper

Authors

1 Department of Plant Production and Genetics, Faculty of Agriculture, University of Maragheh, Maragheh, Iran.

2 Natural Resources and Agricultural Researches Center of East Azerbaijan Province, Tabriz, Iran.

Abstract

A mini collection comprising 32 sainfoin genotypes was cultivated using a randomized complete block design with four replicates. Various parameters were recorded, including the number of plants per area (NPA), total dry yield (TDY), thousand seed weight (TSW), number of main stems (NMS), petiole length (PL), length of inflorescence (LI), number of leaflets per leaf (NLL), leaves per main stem (LMS), number of leaves per stem (NLS), stem dry weight (SDW), leaf dry weight (LDW), inflorescence dry weight (IDW), and number of florets per inflorescence (NFI). The first and second components of the biplot accounted for 88% of the variability in the dataset, with 70% attributed to the first component and 18% to the second. A pentagon was identified, featuring two distinct sections with genotypes 16 and 25, as well as genotype 14, serving as vertex entries. Notably, genotype 14 (Azna) excelled in three traits: NLL, LMS, and NLS. Additionally, vertex genotypes 16 and 25 demonstrated superior performance in other measured traits, including economically significant traits such as total dry yield. In accordance with the ideal entry, genotypes 13, 14, and 19, along with genotypes 16 and 25, exhibited greater favorability compared to other sainfoin genotypes regarding variability in the measured traits. Based on the ideal tester, total dry yield, number of leaves per stem, and number of florets per inflorescence were identified as key factors for assessing variation among genotypes. An examination of genotypes based on total dry yield indicated that genotypes 16 and 25, followed by genotypes 14 and 16, were the most desirable.

Keywords

References

Abbasi-Holasou H., Hassanzadeh-Ghorttapeh A., and Talebzadeh Z. (2019). Evaluation of Relationships between yield and yield components in sainfoin (Onobrychis Vicifolia Scop) genotypes using multivariate methods. Journal of Crop Production and Processing, 9(1): 217-232. DOI: 10.29252/jcpp.9.1.217.
Behroz P., Aharizad S., Mohamadi S. A., Normand-Moayed F., and Hazegh-Jafari P. (2010). Investigation of genetic diversity in sainfoin ecotypes based on important characteristics using multivariate statistical analysis. Journal of Crop Breeding, 2(6): 53-66. DOI: 20.1001.1.22286128.1389.2.6.4.1.
Borreani G., Peiretti P., and Tabacco E. (2003). Evolution of yield and quality of sainfoin (Onobrychis viciifolia Scop.) in the spring growth cycle. Agronomie, 23(3): 193-201. DOI: 10.1051/agro:2002082.
Dadkhah M., Majidi M. M., and Mirlohi A. (2011). Multivariate analysis of relationships among different characters in Iranian sainfoin populations (Onobrichis viciifolia Scop.). Iranian Journal of Field Crop Science, 2: 349-357. DOI: 20.1001.1.20084811.1390.42.2.14.2.
Davazdahemami S., Ma-Alizadeh M. A., Jalali S., and Zeinali H. (2019). Assessment of variation of sainfoin (Onobrychis vicifolia Scop.) genotypes through forage yield and its components. Iranian Journal of Rangelands and Forests Plant Breeding and Genetic Research, 27: 15-27. DOI: 10.22092/ijrfpbgr.1398.120249.
Delgado J., Buil S. I., and Andres C. (2008). The agronomic variability of a collection of sainfoin accessions. Spanish Journal of Agricultural Research, 6: 401-407. DOI: 10.5424/sjar/2008063-333.
Ebrahimi H., Sabaghnia N., Javanmard A., and Abbasi A. (2023). Genotype by trait biplot analysis of trait relations in safflower. Agrotechniques in Industrial Crops, 3(2): 67-73. DOI: 10.22126/ATIC.2023.8906.1086.
Elfanah A. M., Darwish M. A., Selim A. I., Shabana M. M., Elmoselhy O. M., Khedr R. A., and Abdelhamid M. T. (2023). Spectral reflectance indices’ performance to identify seawater salinity tolerance in bread wheat genotypes using genotype by yield* trait biplot approach. Agronomy, 13(2): 353. DOI: 10.3390/agronomy13020353.
Gruffat D., Durand D., Rivaroli D., Do Prado I. N., and Prache S. (2020). Comparison of muscle fatty acid composition and lipid stability in lambs stall-fed or pasture-fed alfalfa with or without sainfoin pellet supplementation. Animal, 14(5): 1093-1101. DOI: 10.1017/S1751731119002507.
Poudel H. P., Bhattarai S., Singer S. D., Biligetu B., and Acharya S. (2023). An insight into sainfoin (Onobrychis viciifolia Scop.) breeding: Challenges and achievements. Agronomy Journal, 115(6): 2843-2858. DOI: 10.1002/agj2.21439.
Sabaghnia N., Zakeri M., Karimizadeh R., and Janmohammadi M. (2024). Entry by tester biplot model for evaluation of some kabuli chickpea genotypes based on several multiple traits. Agriculture and Forestry, 70(2): 25-36. DOI: 10.17707/AgricultForest.70.2.2.
Sutcu T., Bilgen B. B., and Tuna M. (2022). Analysis of genetic diversity among Onobrychis accessions with high agronomic performance by simple sequence repeat (SSR) markers. Molecular Biology Reports, 49(6): 5659-5668. DOI: 10.1007/s11033-022-07584-x.
Tan M., and Yolcu H. (2021). Current status of forage crops cultivation and strategies for the future in Turkey: A review. Journal of Agricultural Sciences, 27(2): 114-121. DOI: 0.15832/ankutbd.903732.
Tulu D., Gadissa S., Hundessa F., and Kebede E. (2023). Contribution of climate‐smart forage and fodder production for sustainable livestock production and environment: Lessons and challenges from Ethiopia. Advances in Agriculture, 1: 8067776. DOI: 10.1155/2023/8067776.
Vaccino P., Antonetti M., Balconi C., Brandolini A., Cappellozza S., Caputo A. R., and Verde I. (2024). Plant genetic resources for food and agriculture: The role and contribution of CREA (Italy) within the national program RGV-FAO. Agronomy, 14(6): 1263. DOI: 10.3390/agronomy14061263.
Yan W. (2021). A systematic narration of some key concepts and procedures in plant breeding. Frontiers in Plant Science 12: 724517. DOI: 10.3389/fpls.2021.724517.
Yan W. (2024). Two types of biplots to integrate multi‐trial and multi‐trait information for genotype selection. Crop Science, 64(3): 1608-1618. DOI: 10.1002/csc2.21231.
Zarabiyan M., Majidi M. M., and Amini H. (2016). Genetic diversity of Iranian and exotic sainfoin accessions (Onobrychis viciifolia Scop) based on morphological traits. Journal of Crop Production and Processing, 6(21):1-14. DOI: 10.18869/acadpub.jcpp.6.21.1.

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History

  • Receive Date: 30 September 2024
  • Revise Date: 29 December 2024
  • Accept Date: 29 December 2024

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