The probabilitys of forecasting of content of 129I in cow's milk
Journal Title: Наукові горизонти. Scientific Horizons - Year 2018, Vol 71, Issue 9
Abstract
This work completes the cycle of five-year studies on the main nutrient streams of 127I and 129I in typical agroecosystems of Ukraine, which was held at the National University of Life Sciences and Natural Resources of Ukraine "UkrNDISh". One of the main sources of isotope iodine in humans is cow's milk. To predict the iodine content of milk, it is necessary to determine their content in the components of the daily diet (water, herbs, hay, grain and its derivatives). In the work on the basis of the probabilistic approach to the description of the spe-cific content of 129I isotopes in the soil of plants and possible values of the coeffi-cients of its accumulation (transition) on the example of the Naroditsky district of Zhytomyr region, a methodology for predicting the specific activity of 129I in milk of cows without direct measurement in soil and vegetable components of the diet was developed. For the practical implementation of the proposed methodology, the statistical characteristics of the accumulation coefficients 127I for meadow grasses, potatoes, straw (oats, wheat) and iodine transfer coefficients from the daily ration to cow's milk for various settlements of continental Ukraine were es-timated. The scope of research covers the areas that have undergone significant radioactive contamination as a result of the Chornobyl accident and relatively "clean" territory. The proposed methodology allows to obtain point, as well as interval esti-mates of the contents of 127I and 129I in of cows milk, with the level of trust that the user specifies, as well the evaluate possible exceedances of the established norms of this content. An approximate exspres method of probabilistic prediction of spe-cific content of 129I in cow's milk in the settlements is proposed and tested. This can greatly simplify the probabilistic forecasting process by confining itself to the means of the EXCEL spreadsheets, bypassing methods and algorithms for statis-tical simulation.
Authors and Affiliations
Yu. Khomutinin, V. Kashparov, N. Lazarev, L. Otreshko
Keywords
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- EP ID EP631673
- DOI 10.33249/2663-2144-2018-71-9-10-104-114
- Views 49
- Downloads 0
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