The use of automated system-cognitive analysis (ASC-analysis) and the intelligent system “Aidos” for identifying genotypes Actinidia deliciosa (kiwi) on the outer contour of the leaf

Federal Research Centre the Subtropical Scientific Centre of the Russian Academy of Sciences (FRC SSC RAS), st.Yana Fabritsius, 2/28, 364002, Sochi, Russia

^* Corresponding author: nskiselyeva_05@mail.ru

Abstract

The content of this publication reveals the results of the selection and selection of options for solving tasks regarding selection and varietalization of kiwi (Actinidia deliciosa). The “tool” is identified by individual varieties according to the leaves available in the leaf contours, because in their form the information data characterizing the variety (on the phenotype and genotype) are stored in their form. In the context of this research work, an analysis of the signs of the morphological order was carried out, which are inherent in kiwi leaves on the sheet circuit. For this, a system called “Aidos” was used, and the targets were the establishment of (indirect) gender of kiwi plants and the identification of varieties based on the contour of the leaves. The information obtained using the ASC-complex (automated system-cognitive analysis) and the “Aidos” smart system, into which the scanned leaves of leaves, was loaded with it, are disclosed. A evaluative procedure was performed using the quantitative method of the relative sheet circuit of 10 varieties of kiwi. According to the information received, class samples of analyzed genotypes based on the sheet configuration were compiled systematizing. The effect of the characteristic values of the genotypic nature in the most accurate INF4-model of the second iteration in the conditions of the integral order (“sum of knowledge”). Clastorization of the cognitive nature of classes made it possible to differentiate four key cluster structures consisting of subcategories, allocated according to the quantitative features of determinants of the sheet circuit.