Effects of physical-chemical properties of soils on 60Co and 65Zn bioavailability

Anisimov, V. S.; Kochetkov, I. V.; Dikarev, D. V.; Anisimova, L. N.; Korneev, Yuri N.

doi:10.1007/s11368-015-1153-z

Cited by 5 publications

(3 citation statements)

References 2 publications

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“…Fv relates the radionuclide activity in the edible part of the plant (Bq kg -1 , dry matter), to the soil activity (Bq kg -1 , dry matter) [2]. Several factors can affect Fv, among them: soil properties, the physical-chemical form of the radionuclide, plant phenology and physiology, and levels of technologies involved in agricultural production [3,4]. A radionuclide can have different Fv values with up to five orders of magnitude in a plant (or group of plants), depending on the soil properties and the time elapsed after contamination, as already observed for 137 Cs in cereals [5,6].…”

Section: Introductionmentioning

confidence: 99%

Application of deep neural networks to forecast 60Co soil to plant transfer factor values based in pedological parameters

et al. 2022

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The soil-plant transfer factor (Fv) is used methods in the computational models for radiological risk assessment by ingestion of radiocobalt-contaminated food. Different soil types, plants types and agricultural practices contribute to a wide dispersion of Fv values, indicating the need to study the criteria that influence root uptake in a regional view. In this scenario, Artificial Neural Networks (ANN) have become a possibility to predict Fv values based on critical pedological parameters. This work aims to apply ANN to evaluate the possibility of predicting Fv for 60Co in reference plants as a function of soil properties considered relevant for transfer processes in the soil-plant system. Through the systematic literature review, mineralogy, organic matter, texture, pH, CEC and nutrients were identified as soil properties that affect Fv values for 60Co. However, although these attributes were not always reported, still it was possible to create databases of Fv for 60Co in radish root and leaf, with pH, organic matter, and CTC as potential edaphic indicators. Learning sets were structured and due to the complexity of the search space and the small amount of available data, deep ANN with regularization (dropout) layers were required to achieve good prediction and avoid overfitting. The best model obtained showed good correlation in the validation and training set, considering the chosen parameters.

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Section: Introductionmentioning

confidence: 99%

Application of deep neural networks to forecast 60Co soil to plant transfer factor values based in pedological parameters

et al. 2022

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“…Романовой (2003), В.С. Анисимова (2013, 2015aM.A.Wasserman et al (2008) и др. Однако, как признают и сами авторы, предлагаемый перечень основных показателей состояния почв и оценка их вклада в регулирование миграционной способности ТМ в системе почва -растение требуют серьезной доработки.…”

Section: Introductionunclassified

The Study of the Combined Effect of Soil Properties on the Rate of Diffusion of 60Co

2017

Biogeosystem Technique

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During the laboratory experiment, devoted to studying of the process of vertical migration 60 Co radionuclide/in water-saturated soil samples of disturbed structure and the same initial bulk density, there were obtained the values of effective diffusion coefficients (Deff 60 Co) for 8 different types, species and varieties of soils.There was noted a significant variability of Deff 60 Co for investigated soils due to different soil characteristics. To assess this influence a statistical approach has been used, where edaphic factors representing the most important characteristics of the soils acted as independent variables (predictors), and the dependent (resulting) variable was Deff 60 Co.Based on the study of the dependence between the main physico-chemical soil properties and the magnitude of effective diffusion coefficients (Deff 60 Co) the selected physico-chemical characteristics of soils were ranked by degree of influence on the value of the dependent variable: pHKCl > (fr.<0.01) > Corg.There was also identified the contribution of each of the selected indicators of soils state (independed variables) in varying of Deff 60 Co. The contribution for pHKCl, (fr.<0.01), and Corg was, respectively, 36,32; 27,90 and 17,08 %. During the experiments revealed a particularly strong increase in the Deff 60 Co for soils with high content of humus in conditions of excessive moisture.

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“…ТМ во многом определяют риски для окружающей среды конфликт биосферы и агроэкосистем , здоровье почвы (Глинушкин и др., 2016). Их миграция и перераспределение в компонентах экосистемы зависят как от целого комплекса природных факторов, так и от интенсивности и характера техногенеза (Прохорова, Матвеев, 1996;Sparks, 2005;Anisimov et. al., 2015;Анисимов и др., 2016).…”

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Mechanism of Migration Processes of Heavy Metals (Zn, Cu, Pb, Cd) in Agroecosystems by the Example of Cabbage and Fodder Beet (Root Crops)

2017

Biogeosystem Technique

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The studies of heavy metals behaviour into the components of "soil -plant" system is an important task of contemporary ecology, focused on scientific substantiation of permissible limits of man impact to natural complexes and agroecosystems, and control and regulation of chemical elements content in plant products. The paper presents an analysis of heavy metals migration in the system "soil -agricultural plants" based on accumulation coefficients of Cu, Zn, Pb, Cd on example of cabbage and fodder beet (root crops). The analysis was performed by statistical methods.It was detected that distributions of accumulation coefficients of Cu, Zn, Pb, Cd for cabbage and fodder beet (root crops) in most cases do not follow the normal distribution law. It was shown that in the range of considered chemical elements the distributions of accumulation coefficients for cabbage could be presented as descending order: Zn > Cu > Cd > Pb.It was established that soil type determines 52 % of variations of Cu accumulation in fodder beet (Fisher's ratio test is 9.22 at confidence level of p=0.0019). To the greater degree a variation of Zn accumulation in fodder beet could be caused by unsuspected factors (82 %). In this case the influence of soil type has also a higher probability (Fisher's ratio test is 2.0423 at confidence level of p=0.12), that highlights the significant effect of soil type on the processes of microelements accumulation by plant organism.

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Effects of physical-chemical properties of soils on 60Co and 65Zn bioavailability

Cited by 5 publications

References 2 publications

Application of deep neural networks to forecast 60Co soil to plant transfer factor values based in pedological parameters

Application of deep neural networks to forecast 60Co soil to plant transfer factor values based in pedological parameters

The Study of the Combined Effect of Soil Properties on the Rate of Diffusion of 60Co

Mechanism of Migration Processes of Heavy Metals (Zn, Cu, Pb, Cd) in Agroecosystems by the Example of Cabbage and Fodder Beet (Root Crops)

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