Cluster analysis in the selection of buckwheat

Abstract

Abstract. The purpose: using cluster analysis to shorten the selection process duration in buckwheat by grouping hybrid combinations into cluster classes by the similarity of morphological estimates, yield and technological parameters Methods. We evaluated samples of buckwheat (124), created by hybridization methods using samples of the Buckwheat genus Fagopyrum Mill. using tree-like clustering with the Euclidean distances measure. Results. Based on the cluster analysis results, we made a distribution of the 124 studied samples, created by the hybridization method, into four main clusters according to the main morphological, yield and technological indicators of grain quality. It was found that 66 samples, 53.6 %, refer to the second cluster with the average parameters of the main biometric, yield and technological indicators of grain quality. Only 25 % of samples or 31 samples were characterized by high economic-value indicators. Very high indicators of the studied samples are characterized by 13 samples — 10.5 %, very low — 14 samples — 11.3 %. It has been practically established that the morphological improvement, yield and grain quality technological indicators in buckwheat varieties from Belarus — Alenushka, Zhniaiarka, Smuglianka; Tatarstan — Kazan large-fruited; France — collection sample No. 4013; Russia — Mig, Solianska, Skorostyhla 86. Bringing them to hybridization with varieties of Ukrainian selection buckwheat makes it possible to obtain valuable raw material. Conclusions. The cluster analysis usage in the buckwheat selection makes it possible in the early stages of the selection process to perform a quick assessment, distribution and the source material selection.Keywords: buckwheat, cluster analysis, morphological, yield and grain quality technological indicators