Morpho-yield contributing traits and correlation of soybean parental and F1 hybrids
DOI:
https://doi.org/10.5281/zenodo.13823818Keywords:
legume, soybean, collection, yield, correlation, grain, F1 hybridsAbstract
This article presents the research outcome of studies based on the screening for productivity traits of soybean's genetic and botanical collection samples, the productivity indicators of the parental forms selected for cross-breeding, analysis of the correlation between them, and heredity in the F1 species. The study results show a strong positive correlation between the number of pods per plant, the number of grains per plant, and grain weight. In contrast, the weight of 1000 grains is moderately positively correlated with the weight of grains per plant, while it displayed a weak positive and negative correlation with other species. In the F1 hybrid generation, it was found that the studied fertility traits were mostly incompletely positive and highly dominant.
References
Abdurazakova, Z.L., Kurbanbayev I.D, Yunuskhanov Sh., Narimanov A.A, Azimov A. Chlorophyll content in the leaves of soybean plants in various phases of their development// Journal of Critical Reviews, 2020, 7(13), 173–176.
Atabaeva, K.N (2004). Soybean. Tashkent. pp. 25-29.
Bashkatov, A.Y., Minchenko, J.N., Solosenkov, P.A (2009). Innovative aspects of modern technology and construction in the Kursk region. Kursk, 6.
El-Mohsen, A.A.A., Mahmoud, G.O., Safina, S.A. (2013). Agronomical evaluation of six soybean cultivars using correlation and regression analysis under different irrigation regime conditions. Journal of plant breeding and crop science, 5, 91-102.
Faisal, M., Malik, A., Ashraf, M., Sharif, A. And Ghafoor, A. 2007. Assessment of genetic variability, correlation, and path analyses for yield and its components in soybean. Pakistan Journal of Botany, 39(2), 405-413.
FAO (Food and Agriculture Organization of the United Nations) (2004): The role of soybean in fighting world hunger, FAO Commodities and Trade Division, Basic Foodstuffs Service, a study based on a paper presented at the VIIth World Soybean Research Conference held in Foz do Iguassu, Brazil, 1-5
Fayziev, V., Jovlieva, D., Juraeva, U., Shavkiev, J., Eshboev, F. (2020). Effects of PVXN-UZ 915 necrotic isolate of potato virus X on amount of pigments of Datura stramonium leaves. Journal of Critical Review, 7(9), 400-403.
Fomenko, N.D., Sinegovskaya, V. T., Slobodyanik, N. S., Kletkina, O. O., Belyaeva, G. N., Melnikova, E. N. (2015). Collective scientific monograph Blagoveshchensk, 22.
Griffing, J. (1950). Analysis of quantitative gene action by constant parent regression and related techniques. Genetics, 35, 303-321.
Hamawaki, O.T., Sousa, L.B., Romanato, F.N., Nogueira, A.P.O., Santos Júnior, C.D., Polizel, A.C. (2012). Genetic parameters and variability in soybean genotypes. Communicata Scientiae, 3, 76-83.
Juraeva, R., Tashpulatov, J., Iminov, A., Bozorov, K., Zaynitdinova L., and Kukanova S. (2020). Efficiency of symbiotic nitrogen fixation of soy nodule bacteria after preservation. Plant Cell Biotechnology and Molecular Biology, 21(61&62),72-79.
Khudaikulov, J.B., Atabaeva, K.N. (2021). Cultivation of sunflowers. A collection of 100 books. Tashkent, 56.
Kurbanbaev, I., Abdushukirova, S., Toshmatov, Z., Amanov, A., Аzimov, A., Shavkiev, J. (2023). Assessment of botanical and genetic collection of soybeans for morphological and yield attributes and their impact on nodule-associated bacteria and soil fertility. SABRAO Journal of Breeding and Genetics, 55(3), 760-777. http://doi.org/10.54910/sabrao2023.55.3.14.
Kurbanbaev, I.Z., Ataev, D.I., Yunuskhanov, S. (2008). Protein markers for identification of different species and varieties of cotton. Prikladnaia Biokhimiia i Mikrobiologiia, 44(4), 476-481.
Kwon SH, Torrie JH (1964). Heritability and interrelationship among traits of two soybean populations. C Crop Science, 4, 194– 202.
Leshchenko, A.K., Sichkar, V.I., Mikhailov, V.G., Maryushkin, V.F. (1987). Biology of soybean. 17-20.
Machikowa, T., Laosuwan, P. (2011). Path coefficient analysis for yield of early maturing soybean. Sonklanakarin Journal of Science and Technology, 33, 365-368.
Malik, M.F.N., Qureshi, A.S., Ashraf, M., Ghafoor, A. (2006). Genetic variability of the main yield-related characters in Soybean. International Journal of Agriculture and Biology, 8, 815-819.
Nesterin, M.F., Skurikhin, I.M. (1979). Chemical composition of food products. Moscow Food Industry. 245.
Petibskaya, V.S. (2012). Soybean: Chemical composition and use. Russian Academy of Science, Agricultural Science Department, 432.
Qulmamatova, D.E. (2023). Chickpea (Cicer arietinum L.) genotypes evaluation for high yield through multivariate analysis. SABRAO Journal of Breeding and Genetics, 55(1), 107-114. http://doi.org/10.54910/sabrao2023.55.1.10.
Qulmamatova, D.E., Baboev, S.K., Buronov, A.K. (2022). Genetic variability and inheritance pattern of yield components through diallel analysis in spring wheat. SABRAO J. Breed. Genet. 54(1): 21-29. http://doi.org/10.54910/sabrao2022.54.1.3
Sichkar, V.I. (1987). Genetic bases of soybean breeding for increased productivity. Techniques for regulating soybean productivity. Novosibirsk, 33-52.
Silva, A.F., Sediyama, T., Silva, F.C.S., Bezerra, A.R.G., Ferreira, L.V. (2015). Correlation and path analysis of soybean yield components. International Journal of Plant, Animal and Environmental Sciences, 5, 177-179.
Sozonova, A.N. (2019). Economic-biological and selection of valuable early ripening soybean varieties in the forest-steppe zone of the Trans-Urals. Diss. na sois.uchenoy stepeni kand.s/x nauk. Tyumen, 18.
Steel, R.G.D., Torrie, J.H. (1984). Principles and Procedures of Statistics: A Biometrical Approach. McGraw Hill Co, New York, USA.
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