You are here

Головна » 2020 » AGROBIOLOGY №2 2020

Cluster analysis in soybean varieties classification by economic characteristics

The aim of the study was to improve the method of soybean collection material assessment with the purpose of choosing pairs for hybridization using cluster analysis, to cluster samples according to the duration of growing period, plant height, the height of lower pod attachment, stem thickness in the lower part, the number of branches and productive joints on a plant, the number of pods and seeds per plant, the number of seeds in a pod, seed weight per plant, yield (g/m2 ), and the resistance to lodging and bean cracking. Based on the conducted cluster analysis of one hundred and forty-five soybean collection samples concerning the determined signs, it has been established that the collection material was distributed within five clusters. Soybean genotypes have been singled out as carriers of a high level of quantitative characteristics, especially the signs of yield potential which can be used as a promising selection material. The samples having analogous set of signs in the cluster and reliable distinction from others have been united in a separate cluster. The samples of the first cluster in the collection are characterized by average and close to average values of all the studied characteristics. The samples of the second cluster are characterized by high values as to the number of branches and productive joints on a plant and also the number of beans per plant. The third cluster consisted of samples having high values of the number of seeds in a bean. However, as to other signs, the samples of this group have low values. The samples of the fourth cluster are later-maturing, than those in the first three groups. They are characterized by larger plant height and the height of lower bean attachment. The fifth sample cluster is distinguished by the longest growing period and high values of the majority of signs except the number of seeds in a bean and also resistance to lodging and bean splitting. The parent forms were in four clusters out of five ones. The cluster analysis helped to conduct the choosing of parent pairs for hybridization and creation of soybean new initial material. The advantage of cluster analysis consists in being able to identify collection samples in balance according to the complex of valuable economic characteristics, rather than single out genotypes according to separate quantitative signs.

Key words: soybean, selection, collection, sample, cluster, cluster analysis, initial material.

 

Bilyavska L.


Rybalchenko A.


Reference: 
1. Abugalieva, A.I., Didorenko S.V. (2016). Geneticheskoe raznoobrazie sortov soi razlichnyh grupp spelosti po priznakam produktivnosti i kachestva [Genetic diversity of soybean cultivars belonging to different ripeness groups with regard to performance and quality]. Vavilovskij zhurnal genetiki i selekcii [Vavilov journal of Genetics and Breeding]. Vol. 20, no. 3, рр. 303–310. Available at: https:// doi.org/10.18699/VJ16.168.
2. Belyavskaya, L.G., Rybalchenko, A.M. (2019). Skrining kollekcii soi po skorospelosti i produktivnosti v usloviyah Levoberezhnoj Lesostepi Ukrainy [Screening soya collection as to early maturing and productivity in the conditions of the left bank Forrest-steppe of Ukraine]. Zernobobovye i krupyanye kultury [Legumes and groat crops], no. 1 (29), рр. 63–69. Available at: https://doi. org/10.24411/2309-348X-2019-11074.
3. Vilchinska, L.A., Gorodinska, O.P., Diyanchuk, M.V., Kaminna O.O. (2017). Klasternij analiz v selekciyi grechki [Cluster analysis in the selection of buckwheat]. Visnуk Ukrayinskogo tovarуstva genetуkiv i selekcioneriv [The Bulletin of Ukrainian Society of Geneticists and Breeders]. Vol. 15, no. 2, рр. 145–149.
4. Guba, I.I., Starichenko, V.M. (2018). Klasterizaciya kolekcijnih zrazkiv zhita ozimogo za kilkistyu kvitok ta inshimi gospodarskocinnimi oznakami [Clustering of winter rye collections on the number of flowers and other economically valuable traits]. Naukovi praci Institutu bioenergetichnih kultur i cukrovih buryakiv [Scientific Papers of the Institute of Bioenergy Crops and Sugar Beet], no. 26, pp. 113–119.
5. Dospekhov, B.A. (1985). Metodika polevogo opyta (s osnovami statisticheskoy obrabotki rezultatov issledovaniy) [Methods of field experiment (with fundamentals of statistical processing of research results]. Moscow, Agropromizdat, 351 р.
6. Kazydub, N.G., Marakaeva, T.V., Korobejnikova, M.M., Epanchincev M.V. (2014). Otbor perspektivnyh obrazcov dlya selekcii fasoli s ispolzovaniem klasternogo analiza v usloviyah yuzhnoj lesostepi Zapadnoj Sibiri [Selection of perspective standards for selection of kidney bean with the use of cluster analysis in the conditions of south forest-steppe of Western Siberia]. Vestnik Omskogo gosudarstvennogo agrarnogo universiteta [Bulletin of Omsk State Agrarian University], no. 4 (16), pp. 8–14.
7. Kobizeva, L.N., Ryabchun, V.K., Bezugla, O.M. (2004). Shirokiy unіfіkovaniy klasifіkator rodu Glycine max. (L). Merr [Great unified classifier kind of Glycine max. (L). Merr]. Kharkiv, Institute of Plant Breeding names of V.Y. Yur'yev, 37 р.
8. Korsakov, N.I., Adamova, O.A., Budakova, V.I. (1975). Metodicheskiye ukazaniya po izucheniyu kollektsii zernovykh bobovykh kultur [Methodical instructions to studies of leguminous and cereal crops collections]. Leningrad, VIR, 59 p.
9. Kohanyuk, N.V., Temchenko, I.V., Shtuc, T.M., Lehman, A.A., Barvinchenko, S.V. (2019). Klasternij analiz u selekciyi zernobobovih kultur [Cluster analysis in the breeding of leguminous crops]. Kormу i kormovуrobnуctvo [Feeds and Feed Production], no. 87, pp. 9–19. Available at: https://doi.org/10.31073/kormovyrobnytstvo201987-02.
10. Litun, P.P. (1980). Identifikaciya genotipov v selekcionnyh populyaciyah [Identification of genotypes in breeding populations]. Selekciya i semenovodstvo [Breeding and Seed Production], no. 46, pp. 27–34.
11. Litun, P.P., Kirichenko, V.V., Petrenkova, V.P., Kolomacka, V.P. (2009). Sistemnij analiz v selekciyi polovih kultur: navch. posib. [System analysis in field crop selection]. Kharkiv, 354 p.
12. Majdanyuk, V.O., Holodnyak, O.G. (2014). Metod pidboru batkivskih par pri stvorenni novih adaptivnih sortiv kabachka dlya vidkritogo gruntu pivdnya Ukrayini [Method of selection of parental pairs when creating new adaptive varieties zucchini for open ground of the Southern Ukraine]. Zroshuvane zemlerobstvo [Irrigated agriculture], no. 61, pp. 137–139.
13. Mandel, I.D. (1988). Klasternyj analiz [Сluster analysis]. Moscow, Finance and statistics, 176 p.
14. Marakaeva, T.V. (2018). Klasternyj analiz v selekcii chechevicy [Сluster analysis in lentil breeding]. Uspehi sovremennogo estestvoznaniya [Advances in current in natural sciences], no. 12, Part 1, pp. 75–80.
15. Martynov, S.P. (1989). Klasternyj analiz saratovski h sortov yarovoj pshenicy po koefficientam rodstva [Cluster analysis of Saratov spring wheat varieties by kinship coefficients]. Citologiya i genetika [Cytology and genetics]. Vol. 23, no. 4, pp. 37–43.
16. Melnik, A.V. (2013). Vikoristannya klasternogo analizu za pidboru sortiv i gibridiv ripaku yarogo dlya viroshuvannya v livoberezhnomu stepu Ukrayini [Use of cluster analysis in the selection of varieties and hybrids of spring rape for cultivation in the Left-Bank Forest-Steppe Ukraine]. Visnуk Poltavskoi derzhavnoi agrarnoi akademii [News of Poltava State Agrarian Academy], no. 4, pp. 6–11.
17. Prisyazhnyuk, O.I., Kalyuzhna, E.A., Ukrayinec, V.V., Shevchenko, O.P. (2013). Ocinka sortiv gorohu za kompleksom gospodarsko-cinnih oznak [Evaluation of pea varieties on a set of economically valuable features]. Cukrovi buryaki [Sugar Beet], no. 5, pp. 16–17.
18. Starichenko, V.M. (2012). Vikoristannya klasternogo analizu dlya ocinki F2 populyaciyi soyi [Using the cluster analysis for an estimation F2 population of soybean]. Zbirnуk naukovуh prac NNC «Instуtut zemlerobstva NAAN [Collection of scientific papers of NSC “Institute of agriculture of NAAS”], no. 3–4, pp. 124–134.
19. Tishenko, V.M., Gusenkova, O.V., Dubenec, M.V., Kolisnik, A.V. (2018). Sistematizaciya sortiv ta selekcijnih linij pshenici ozimoyi za kilkisnimi oznakami v umovah kontrolovanogo seredovisha z vikoristannyam klasternogo analizu [Systemization of sort and selection lines of wheat lines by numbership in conditions of controlled environment with using cluster analysis]. Visnуk Poltavskoi derzhavnoi agrarnoi akademii [Bulletin of Poltava State Agrarian Academy], no. 3, pp. 56–65. Available at: https://doi. org/10.31210/visnyk2018.03.09.
20. Tishenko, V.N., Chekalin, N.M., Zyukov, M.E. (2004). Ispolzovanie klasternogo analiza dlya identifikacii i otbora vysokoproduktivnyh genotipov ozimoj pshenicy na rannih etapah selekcii [The use of cluster analysis for the identification and selection of highly productive winter wheat genotypes at the early stages of breeding]. Faktorу eksperimentalnoi evolyucii organizmiv [Factors in experimental evolution of organisms]. Vol. 2, pp. 270–278.
21. Chekalin, N.M., Tishenko, V.N., Panchenko, P.M., Sidorenko, V.S. (2009). Ispolzovanie klasternogo analiza kak metoda individualnogo otbora u prosa (Panicum miliaceum L.) [Use cluster analysis as method of millet individual selection Panicum miliaceum L.]. Visnуk Poltavskoi derzhavnoi agrarnoi akademii [News of Poltava State Agrarian Academy], no. 2, pp. 10–17.
 
Download this article: 
AttachmentSize
PDF icon biluavska_2_2020.pdf742.01 KB
YEAR: 
2020
AGROBIOLOGY №2 2020