You are here

Головна » 2017 » AGROBIOLOGY №1 2017

Soybean complex classification for economically valuable features complex

Multivariate analysis methods are not highlighted sufficiently and are not used often at the current stage of Agricultural sciences. Therefore, before using this method in practice we focus on the key aspects contributing to the factors comprehensive evaluation.
Cluster analysis is a dividing the sample objects into subsets, called clusters, so that each cluster consists of these objects, and various clusters differ significantly from each other. The essence of cluster analysis is to determine the optimal value of the function. Most clustering methods are based on the use of heuristic methods.
The aim of the research was to study the biological characteristics of growth and development of middle-ripening soybean varieties, and their performance formation.
Experimental research on the thesis was carried out during 2014-2016 on the experimental field of "Bogdan & Co."
PF located in the Popelnyky village, of Snyatynsky district of Ivano-Frankivsk region.
14 varieties of domestic and foreign selection listed in the State Register of plant varieties suitable for dissemination in Ukraine were studied in the research: Arisa, Anzhelika, Kassidi, PODIAKA, Rapsodiia, Aratta, ES Mentor, Luna, Kuban, Atlanta, Sofiia, NS Maksymus, VIDRA, BISER.
Special and general research methods were used during the studies, technology of cultivation was common for the region.
The use of soybean varieties producing of the same originator often results in their similar response to growing conditions and as a result – instead of diversifying risk and guarantee of yields stable gross production remains consistently low in all grades. There may be several reasons for these changes: genetic and adaptive. While from the point of genetics everything is quite clear – the selectionists often use same components to create different soybean varieties. We get another sort by its external signs and reacting similarly to changing weather conditions and technology factors  as well as other varieties of this originator institutions do. However, we do not exclude the point that genetically different soybean varieties of different origin have the same reaction to the changing weather conditions.
Based on the analysis, we identified several clusters combining the studied varieties by the complex of economically valuable traits. Thus, the first cluster included Arissa, Kassidi, Mentor, Luna, NS Maksymus. The next cluster was formed by PODIAKA and Kuban varieties.
The results of research on the classification of middle-ripening varieties it was found out that Arissa, Kassidi, Mentor, Luna, NS Maksymus or PODIAKA and Kuban approximately equally respond to growing conditions and form the same level of performance. That is, if the farm plants only these varieties of soybean, the crop productivity will be formed at about the same level, and therefore it can not make the most of the potential performance due to the risk diversification provided as planting varieties with different biological factors needs to supply.
Key words: soybean, economically valuable characteristics, middle-ripening verieties, clustering.
 
V. Dimitrov


Reference: 

1. Kamins'kyj, V.F. (2005) Vyrobnytstvo soi v Ukraini zalezhno vid pohodnykh umov [Soybean production in Ukraine, depending on weather conditions]. Mizhvidomchyi tematychnyi nauk. zbirnyk «Zemlerobstvo» [Interdepartmental thematic Sciences. collection "Agriculture"]. Kyiv, vol. 77, ECMO, pp. 144-145.

2. Kamins'kyj, V.F., Vyshnivs'kyj, P.S. (2005). Znachennia zernovykh bobovykh kultur ta napriamky intensyfikatsii yikh vyrobnytstva [Value of grain legumes and directions intensification of production]. Selektsiia i nasinnytstvo [Breeding and Seed]. Kharkiv, vol. 90, pp. 14-22.

3. Dervyanskyy, V.P. Podilska tekhnolohiia vyroshchuvannia soi [Podolsky soybean technology], 2010, no. 4, pp. 48-54.

4. Dymkovych, D.A. (2005). Vplyv elementiv biolohizatsii na produktyvnist soi [Effect elements biologization the performance of soybean]. Zb. nauk. prats Instytutu zemrebostva UAAN [Coll. Science. zemrebostva UAAS Institute works]. Kyiv, ECMO, vol. 3, pp. 18-21.

5. Shumetov, V.G., Shumetova, L.V. (2000). Klasternyj analiz: podhod s primeneniem JeVM [Klaster analysis: approach with computer]. Orel STU, 118 p.

6. Verhunova, I.M. (2000). Osnovy matematychnoho modeliuvannia dlia analizu ta prohnozu ahronomichnykh protsesiv [Basis of mathematical modeling to analyze agronomic and forecasting processes]. Kyiv, Nora-print, 146 p.

7. Drobitko, A.V. (2000). Vybir sortotypiv i ahrotekhnichnykh pryiomiv vyroshchuvannia soi v zoni Pivdenno – zakhidnoho Stepu [Selection sort types and agricultural practices products of soy in the area south – western steppe]. Zbirnyk naukovykh prats Ordena Trudovoho Chervonoho Prapora Instytutu zemlerobstva UAAN (vypusk 1) [Proceedings of the Order of the Red Banner Institute of Agriculture UAAS (issue 1) ]. Nora-print, pp. 73-79.

8. Shcherbyna, O.Z. (2003). Metodychni rekomendatsii po vyroshchuvanniu soi na zerno [Guidelines for soybean grain]. Samchyky, 25 p.

 

Download this article: 
AttachmentSize
PDF icon dimitrov_1_2017.pdf337.09 KB
YEAR: 
2017
AGROBIOLOGY №1 2017