Identification of buckwheat varieties Fagopyrum esculentum Moench by morphological characters by applying the nearest neighbors algorithm

Authors

DOI:

https://doi.org/10.21498/2518-1017.16.2.2020.209221

Keywords:

variety, feature distinctness, model, buckwheat, statistical methods

Abstract

Purpose. Evaluate buckwheat Fagopyrum esculentum Moench varieties by morphological characteristics by using the nearest neighbors algorithm and identify groups of similar varieties by plant varieties clustering procedure.

Methods. Analytical, mathematical, statistical. As input information for statistical processing, the results of the exa­mination for distinctness, uniformity and stability (DUS) from the database of the automated information system of the Ukrainian Institute for the Examination of Plant Varieties were used. The simulation was performed using Nearest Neighbors algorithm, which belong to Machine Learning method. Data processing was carried out by using trial version of the statistical package IBM SPSS Statistics “Statistical Package for the Social Sciences”. The follo­wing types of variables were used as model parameters: target (optional) variable is “Plant: growth type”, focal case identifier is “Plant: ploidy”, case name is Varieties Name, feature variables are “Cotyledon: anthocyanin coloration”, “Stem: anthocyanin coloration”, “Inflorescence: anthocyanin coloration of bud”, “Time of beginning flowering”, “Plant: height”, “Leaf blade: shape of base”, “Leaf blade: intensity of green color”, “Flower: size”, “Flower: color of petals”, “Flower: length of pedicel”, “Plant: total number of flower clusters”, “Stem: length”, “Stem: number of nodes”, “Stem: diameter”, “Time of maturity”, “Seed: length”, “Seed: shape”, “Seed: skin color”, “Seed: 1000 seed weight”. This model contains 25 buckwheat varieties, included in the State Register of plant varieties suitable for distribution in Ukraine in 2020. These varieties are of foreign and domestic origin.

Results. The model of similar buckwheat varieties was a result of computer modeling. This model was based on seventeen morphological features, selected using frequency analysis of buckwheat morphological features. The generated model contained 17 training objects (varieties) and nine control objects (varieties). 22 groups of similar varieties of common buckwheat were identified.

Conclusion. The most similar groups of varieties are the following: first – ‘Krupnozelena’, ‘Dykul’, ‘Deviatka’ that ‘Yuvileina 100’; second – ‘Ruta’, ‘Malwa ’,‘Nadiina’ and ‘Volodar’; third – ‘Kseniia’, ‘Simka’, ‘Selianochka’ and ‘Malva’.

Author Biographies

Н. С. Орленко, Ukrainian Institute for Plant Variety Examination

Orlenko, N. S.

С. М. Гринів, Ukrainian Institute for Plant Variety Examination

Hryniv, S. М.

С. П. Лікар, Ukrainian Institute for Plant Variety Examination

Likar, S. P.

М. С. Юшкевич, Ukrainian Institute for Plant Variety Examination

Yushkevich, M. S.

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How to Cite

Орленко, Н. С., Гринів, С. М., Лікар, С. П., & Юшкевич, М. С. (2020). Identification of buckwheat varieties Fagopyrum esculentum Moench by morphological characters by applying the nearest neighbors algorithm. Plant Varieties Studying and Protection, 16(2), 137–143. https://doi.org/10.21498/2518-1017.16.2.2020.209221

Issue

Section

VARIETY STUDYING AND VARIETY SCIENCE

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