№ 138(4), April, 2018
Public date: 30.04.2018
Archive of journal: Articles count 13, 48 kb
-
05.20.00 Processes and machines of agroengineering systems
DescriptionThe article presents the results of the research of the influence of preliminary treatment of garden beet roots with electromagnetic fields of extremely low frequency on the loss of dry and biologically active substances, such as vitamin C and P-active substances, in the process of long term storage. Garden beet roots of Bordo 237 variety were the objects of research. The objects of research were stored for 7 months at a temperature of 0…+1° С and relative humidity of 90 %. Sampling was carried out every month during the entire storage period. The treatment with electromagnetic fields of extremely low frequency was carried out using an experimental setup of our own assembly. As a result of the conducted research it is established, that the treatment of garden beet roots of Bordo 237 variety with electromagnetic fields of extremely low frequency before dispatching into storage allows to decrease the losses of dry substances by 4,1 % by the end of the 7 months storage period, and also to decrease the losses of vitamin C by 14,8 % and P-active substances by 15,1 %. The data obtained can be used to develop new or improve existing technologies of garden beet roots storing
-
Description
Watermelon has great economic importance. The fruits have high nutritional and medicinal value, excellent taste, very healthy and are in great demand among the population. Soil and climatic conditions of the Temryuk district are favourable for growing watermelon. High yield and excellent fruit quality in the commercial led to the popularity of the Temryuk watermelon not only on the black sea coast, but also throughout Russia. The urgency of improving the assortment of the watermelon is increased competition among manufacturers, increasing consumer culture of the population, the increase in sales volumes, including due to the appearance on the market of varieties and hybrids of non-traditional colors of bark and pulp. The aim of our study was to establish the most adapted hybrids of watermelon of different segments, with high yield and marketability of fruits, which are promising for growing in the Temryuk district. Scientific novelty of our work lead to the research objects – new, recently created hybrids of watermelon, promising for cultivation in the Krasnodar region. The work has great practical significance, since on the basis of these studies identified promising hybrids of watermelon foreign seeds of various segments of the precocity, which with appropriate cultivation agrobiological and economic points of view
-
AGGLOMERATIVE COGNITIVE CLUSTERING OF NOSOLOGICAL IMAGES IN VETERINARY MEDICINE
06.02.00 Veterinary and Husbandry
DescriptionThe article deals with the similarity and difference of nosological images in veterinary medicine using a new method of agglomerative clustering implemented in Automated system-cognitive analysis (ASC-analysis) on a small numerical example. This method is called Agglomerative cognitive clustering. This method differs from the known traditional facts: a) parameters of a generalized image of the cluster are computed not as averages from the original objects (classes) or their center of gravity, and are defined using the same underlying cognitive operations of ASC-analysis, which is used for the formation of generalized images of the classes on the basis of examples of objects and which is really correct and provides a synthesis; b) as a criterion of similarity we do not use Euclidean distance or its variants, and the integral criterion of non-metric nature: "the total amount of information", the use of which is theoretically correct and gives good results in non-orthonormal spaces, which are usually found in practice; c) cluster analysis is not based on the original variables, matrices of frequency or a matrix of similarities (differences) dependent on the measurement units of the axes, and in the cognitive space in which all the axes (descriptive scales) use the same unit of measurement: the quantity of information, and therefore, the clustering results do not depend on the original units of measurement features. All this makes it possible to obtain clustering results that are understandable to specialists and can be interpreted in a meaningful way that is in line with experts' assessments, their experience and intuitive expectations, which is often a problem for classical clustering methods