Scientific Journal of KubSAU

Polythematic online scientific journal
of Kuban State Agrarian University
ISSN 1990-4665
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â„– 144(10), December, 2018

Date issued: 28.12.2018

Life Sciences
426 kb

CHANGE OF INDICATORS OF FERTILITY OF BLACK SOIL UNDER DIFFERENT TECHNOLOGIES OF CULTIVATION OF MAIZE IN TERMS OF SEED FARMING

abstract 1441810011 issue 144 pp. 1 – 18 28.12.2018 ru 503
The article presents the results of a study to determine the changes in fertility in the typical black soil of the Belgorod region with different technologies of maize cultivation in seed farming
157 kb

BIOLOGICAL CONTROL OF THE APPLE MOTH NUMBER BASED ON ENTOMOPATHOGENIC VIRUSES (REVIEW)

abstract 1441810012 issue 144 pp. 19 – 31 28.12.2018 ru 358
The article considers the data on the applicability of bioinsecticides based on the granulovirus as an active ingredient against the apple moth. The methods for producing strains of the Cydia pomonella granulovirus to develop bioinsecticides are explained. The methods for the reproduction of laboratory populations of insects, the method of their infection and isolation of viral onset are described. The stages of obtaining bioinsecticides in vitro, as well as methods for their storage are provided
222 kb

DEVELOPMENT OF MULTIPLEX SETS OF SSR MARKERS FOR GENOTYPING APRICOT VARIETIES (PRUNUS ARMENIACA L.)

abstract 1441810013 issue 144 pp. 32 – 43 28.12.2018 ru 315
Genetic studies of apricot are the actual direction in the genetics of fruit crops. In this regard, the improvement of the collection of SSR markers for the genotyping of this culture is an objectively significant task. In a study for the 16 SSR-markers previously developed on almonds (PdUnchar2, PdSLD1, PdGMGT1, PdTrTFGT1, PdUnchar2, PdSLD1, PdGMGT1, PdTrTFGT1) and Siberian apricot (A3-72, A1-63, H2-22, A3- 7-1, H2-5, A1-7, A3-9, H2-45), approbation and evaluation of the prospects of using for genotyping Prunus armeniaca L. were performed. Approbation, performed on 3 varieties of different origin, revealed markers and their combinations optimal for their use. During the study, all tested DNA markers were grouped into multiplex sets, including 4 markers. This allows carrying out genotyping simultaneously on 4 loci in the formulation of one reaction. One marker (PdUnchar2) from the studied sample included in the multiplex set did not show amplification. Five markers gave a monomorphic product. The remaining 11 SSR markers allowed us to obtain polymorphic, cultivar-specific SSR fingerprints for all the studied cultivar. These multiplex sets are proposed for use in studying the genetic polymorphism of the species Prunus armeniaca L.
Life Sciences
14224 kb

FORMATION OF A SEMANTIC KERNEL IN VETERINARY MEDICINE WITH THE AUTOMATED SYSTEM-COGNITIVE ANALYSIS OF PASSPORTS OF SCIENTIFIC SPECIALTIES OF THE HIGHER ATTESTATION COMMISSION OF THE RUSSIAN FEDERATION AND THE AUTOMATIC CLASSIFICATION OF TEXTS ACCORDING TO THE AREAS OF SCIENCE

abstract 1441810033 issue 144 pp. 44 – 102 28.12.2018 ru 273
This work is a continuation of the author's series of works on cognitive veterinary medicine. The present period is characterized by the appearance of huge volumes of texts in different languages in the open access, generated by people. Currently, these texts are accumulated in various electronic libraries and bibliographic databases (WoS, Scopus, RSCI, etc.), as well as on the Internet on various sites. All these texts have specific authors, dates and can belong simultaneously to many non-alternative categories and genres, in particular: educational; scientific; artistic; political; news; chats; forums and many others. The solution of the generalized problem of attribution of texts is of great scientific and practical interest, i.e. studying these texts, which would reveal their probable authors, date of creation, the ownership of these texts to the above generalized categories or genres, and might evaluate the similarities - differences of authors and texts according to their content, highlight key words etc. To solve all these problems it seems necessary to form the generalized linguistic images of texts into groups (classes), i.e. to form semantic kernels of classes. A special case of this problem is the creation of the semantic kernel in various scientific specialties of the HAC of the Russian Federation and the automatic classification of scientific texts in the areas of science. Traditionally, this task is solved by dissertation councils, i.e. experts, on the basis of expert assessments, i.e. in an informal way, on the basis of experience, intuition and professional competence. However, the traditional approach has a number of serious drawbacks that impose significant limitations on the quality and volume of analysis. Currently, there are all grounds to consider these restrictions as unacceptable, because they can be overcome. Thus, there is a problem, the solutions of which are the subject of consideration in this article. Therefore, the efforts of researchers and developers to overcome them are relevant. Therefore, the aim of the work is to develop an automated technology (method and tools), as well as methods of their application for the formation of the semantic core of veterinary medicine by automated system-cognitive analysis of passports of scientific specialties of the HAC of the Russian Federation and automatic classification of texts in the areas of science. A detailed numerical example of solving the problem on real data has been given as well
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