№ 159(5), May, 2020
Public date: 29.05.2020
Archive of journal: Articles count 23, 89 kb
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EVALUATION OF THE BIOLOGICAL EFFICIENCY OF L-EXPRESS FOOD AGROCHEMICAL
06.01.01 General agriculture, crop production (agricultural sciences)
DescriptionIn the study, there is an estimation of the biological effectiveness of the agrochemical called “L-express food L-Express-Mangamino”, based on buckwheat. As a result of the research, it was found that non-root feeding of buckwheat plants: the first - in the branching phase, the second-in the budding phase with organomineral fertilizer L-Express-Nutrition brand: l-Express-Mangamino contributed to immune modulation and increased plant adaptability to stress factors of abiotic and biotic nature. Powdery mildew, ascochitosis, false powdery mildew, gray rot spread on the experimental versions did not receive. The use of organic fertilizer L-Express-Nutrition brand: L-Express-Mangamino had a significant impact on the safety of plants. The safety of plants when using fertilizer at a dose of 1 l / ha was 72%, 1.5 l / ha-74.3%, 2 l / ha-75.2%, which is higher in comparison with the control by 0.9%, 3.2% and 4.1%, respectively. Balanced nutrition of buckwheat plants during the growing season contributed to an increase in the number of stems, inflorescences, the number of seeds per plant of buckwheat, the weight of 1000 seeds, increase productivity by 1.1-1.2 times. The positive effect of agrochemicals on the quality of buckwheat grain was established. The size increased when using increasing doses of agrochemicals by 1.0%, 3.1% and 5.2%, respectively, relative to the control
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06.01.01 General agriculture, crop production (agricultural sciences)
DescriptionIn the article, we have studied the influence of biological nitrogen deposition on the physical and chemical parameters of natural semi-sweet wine, on the example of two grape varieties – classic European Chardonnay and interspecific hybrid Ekaterinodar, including amino acids and aroma-forming components. It is established, that the use of the proposed technology contributes to the active consumption of amino acids by yeast in the fermentation stage. At the same time, yeast cells consumed most actively alanine, valine, phenylalanine, histidine, aspartic, aminobutyric, glutamic acids, leucine, lysine, Sirin, tyrosine, threonine. A slight increase in the concentration of amino acids was observed at the end of fermentation, when the yeast cells entered the stationary phase of development. However, the content of all amino acids, with the exception of Proline, in the wine material was less than in grapes and fermenting wort. As a result of biological nitrogen deposition in experimental versions, the concentration of nitrogen compounds (total and amine nitrogen) was three times less than in the control ones. There is a difference in the concentration of flavor-forming components in wines prepared from both grape varieties using different technologies. In experimental versions, we observed a greater accumulation of almost all components of the aroma-binding complex (especially esters, terpenes, phenylethanol, and ionone), with the exception of higher alcohols. Experimental samples of natural semi-sweet wines from the Chardonnay and Ekaterinodar grape varieties were characterized by a bright floral and fruit aroma and had a higher tasting rating in comparison with the classic technology
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BASIC REQUIREMENTS FOR DATA ANALYSIS METHODS (ON THE EXAMPLE OF CLASSIFICATION TASKS)
08.00.13 Mathematical and instrumental methods of Economics
DescriptionThere is a need to clean up the classification methods. This will increase their role in solving applied problems, in particular, in the diagnosis of materials. For this, first of all, it is necessary to develop requirements that classification methods must satisfy. The initial formulation of such requirements is the main content of this work. Mathematical classification methods are considered as part of the applied statistics methods. The natural requirements to the considered methods of data analysis and the presentation of calculation results arising from the achievements and ideas accumulated by the national probabilistic and statistical scientific school are discussed. Concrete recommendations are given on a number of issues, as well as criticism of individual errors. In particular, data analysis methods must be invariant with respect to the permissible transformations of the scales in which the data are measured, i.e. methods should be adequate in the sense of measurement theory. The basis of a specific statistical method of data analysis is always one or another probabilistic model. It should be clearly described, its premises justified - either from theoretical considerations, or experimentally. Data processing methods intended for use in real-world problems should be investigated for stability with respect to the tolerances of the initial data and model premises. The accuracy of the solutions given by the method used should be indicated. When publishing the results of statistical analysis of real data, it is necessary to indicate their accuracy (confidence intervals). As an estimate of the predictive power of the classification algorithm, it is recommended to use predictive power instead of the proportion of correct forecasts. Mathematical research methods are divided into "exploratory analysis" and "evidence-based statistics." Specific requirements for data processing methods arise in connection with their "docking" during sequential execution. The article discusses limits of applicability of probabilistic-statistical methods. Concrete statements of classification problems and typical errors when applying various methods for solving them are also considered