DOI: https://doi.org/10.21498/2518-1017.13.4.2017.117757

Comparative analysis of statistical software products for the qualifying examination of plant varieties suitable for dissemination

Н. В. Лещук, К. М. Мажуга, Н. С. Орленко, Є. М. Стариченко, Є. А. Шкапенко

Abstract


Purpose. To define statistical methods and tools (application packages) for creating the decision support system (DSS) for qualifying examination of plant varieties suitable for dissemination (VSD) in the context of data processing tasks. To substantiate the selection of software for proces­sing statistical data relative to field and laboratory investigations that are included into the qualifying examination for VSD.

Methods. Analytical one based on the comparison of methods of descriptive and multivariate statistics and tools of intellectual analysis of data obtained during qualifying examination for VSD. Comparative analysis of software tools for processing statistical data in order to prepare proposals for the final decision on plant variety application. Decomposition of tasks was carried out which were included into the decision support system for qualifying examination of varieties-candidates for VSD.

Results. Statistical package SPSS, analysis package included in MS Excel and programe language R was compared for the following criteria: interface usability, functionality, quality of calculation result presentation, visibility of graphical information, software cost. The both packages were widely used in the world for statistical data processing, they have similar functions for statistics calculation.

Conclusion. Tasks of VSD were separated and recommended to tackle using investigated tools. Programe language R was a product recommended to use as a tool. The main advantage of R as compared to the package IBM SPSS Statistics is the fact that R is an open source software.


Keywords


decision support system; qualifying examination; varieties suitability for dissemination; conditional standard; statistical methods in breeding; dispersion analysis; cluster analysis; R; IBM SPSS Statistics

References


Metodyka provedennia kvalifikatsiinoi ekspertyzy sortiv roslyn na prydatnist do poshyrennia v Ukraini. Zahalna chastyna [Regulations on the procedure and the conduct of qualification tests for suitability of crop varieties for dissemination in Ukraine. General part]. (2016). Vinnytsia: FOP Korzun D. Yu. [in Ukrainian]

Goryainova, E. R., Pankov, A. R., & Platonov, E. N. (2012). Prikladnye metody analiza statisticheskikh dannykh [Applied methods of statistical data analysis]. Moscow: Vysshaya shkola ekonomiki. [in Russian]

Compton, M. E. (1994). Statistical methods suitable for the analysis of plant tissue culture data. Plant Cell. Tiss. Organ. Cult. Vol. 37, Iss. 3. P. 217–242. doi: 10.1007/BF00042336

Bryman, A., & Cramer, D. (2011). Quantitative Data Analysis with IBM SPSS 17, 18 and 19: A Guide for Social Scientists. New York: Routledge.

Levesque, R. (2007). SPSS Programming and Data Mana­gement: A Guide for SPSS and SAS Users. (4th ed.). Chicago, IL: SPSS Inc.

Byuyul, A., & Tsefel, P. (2002). SPSS: iskusstvo obrabotki. Analiz statisticheskikh dannykh i vosstanovlenie skrytykh zakono­mernostey [SPSS: Art of Handling. Analysis of statistical data and restoration of hidden patterns]. St. Petersburg: DiaSoftYuP. [in Russian]

Baumer, B. S., Kaplan, D. T., & Horton, N. J. (2017). Modern Data Science with R. Boca Raton: Chapman & Hall/CRC.

Cheshkova, A. F., Aleynikov, A. F., & Stepochkin, P. I. (2016). Application of graphical capabilities of the R programming environment for analysis of experimental data on triticale breeding. Vychislitel’nye tekhnologii [Computational Technologies], 21(1), 104–115. [in Russian]

Kirilenko, Yu., Kuznetsova, Yu., Sokolova, Ye., & Frolova, H. (2013). Methods to estimate the usability of a user’s interface. Visnyk Natsionalnoho universytetutu «Lvivska рolitekhnika». Seriia: Kompiuterni nauky ta informatsiini tekhnolohii [Bulletin of National University “Lvivska Politechnika”. Ser.: Computer Engineering and Information Technologies], 751, 244–256. [in Ukrainian]


GOST Style Citations


Методика проведення кваліфікаційної експертизи сортів рослин на придатність до поширення в Україні. Загальна частина. Вінниця : ФОП Корзун Д. Ю., 2016. 120 с.

Горяинова Е. Р., Панков А. Р., Платонов Е. Н. Прикладные методы анализа статистических данных. Москва : Высшая школа экономики, 2012. 312 c.

Compton M. E. Statistical methods suitable for the analysis of plant tissue culture data. Plant Cell. Tiss. Organ. Cult. 1994. Vol. 37, Iss. 3. P. 217–242. doi: 10.1007/BF00042336

Bryman A., Cramer D. Quantitative Data Analysis with IBM SPSS 17, 18 and 19: A Guide for Social Scientists. New York : Routledge, 2011. 408 p.

Levesque R. SPSS Programming and Data Management: A Guide for SPSS and SAS Users. 4th ed. Chicago, IL : SPSS Inc, 2007. 540 p.

Бююль А., Цефель П. SPSS: искусство обработки. Анализ статистических данных и восстановление скрытых закономерностей. Санкт-Петербург : ДиаСофтЮП, 2002. 608 c.

Baumer B. S., Kaplan D. T., Horton N. J. Modern Data Science with R. Boca Raton : Chapman & Hall/CRC, 2017. 556 р.

Чешкова А. Ф., Алейников А. Ф., Степочкин П. И. Применение графических возможностей программной среды R для анализа экспериментальных данных по селекции тритикале. Вычислительные технологии. 2016. Т. 21, спец. вып. 1. С. 104–115.

Кіріленко Ю., Кузнецова Ю., Соколова Є., Фролова Г. Методи оцінювання usability інтерфейсу користувача. Вісн. Нац. ун-ту «Львів. політехніка». Серія: Комп’ютерні науки та інформаційні технології. 2013. № 751. С. 244–256.







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DOI: 10.21498/2518-1017

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