scholarly journals Prediction of Cadmium Transfer From Soil to Potato in Karst Soils, China

2021 ◽  
Vol 9 ◽  
Author(s):  
Ke Liu ◽  
Hongyan Liu ◽  
Xianyong Zhou ◽  
Zhu Chen ◽  
Xulian Wang
Keyword(s):  
Probability Distribution ◽  
Prediction Models ◽  
Critical Factor ◽  
Cumulative Probability ◽  
Soil Parameters ◽  
Cd Uptake ◽  
Distribution Method ◽  
Empirical Prediction ◽  
Karst Soils ◽  
Soil Cd

Contamination of food with the heavy metal Cd is a significant global concern. In this study, a field survey was performed to investigate the characteristics of Cd transfer from soil to potato tubers (n = 105). The results showed that the bioaccumulation factor of the potato tuber ranged from about 0.1 to 1. The soil threshold of Cd derived from the cumulative probability distribution was 0.15 mg kg−1 in order to protect 95% of potatoes. Additionally, prediction models for Cd transfer were constructed based on soil properties and the concentration of CaCl2-extractable soil Cd. The results of the analysis showed that pH was the critical factor affecting Cd uptake by potatoes. Additionally, the R2 of different empirical models increased from 0.354 to 0.715 as the number of soil parameters was increased, and the predicted soil Cd concentration approached the measured values at values of about 0–15 mg kg−1. The results of this study suggest that the probability distribution method was stricter than the empirical prediction models for estimating the ecological risk of Cd contamination of potatoes in karst soils.

scholarly journals Identifying Controlling Factors of Bioaccumulation of Selected Metal(loid)s in Various Soil–Cereal Crop Systems within Cultivated Fluvisols

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1180
Author(s):  
Jan Skála ◽  
Radim Vácha ◽  
Jarmila Čechmánková
Keyword(s):  
Plant Uptake ◽  
Ph Value ◽  
Soil Parameters ◽  
Significant Variable ◽  
Cd Uptake ◽  
Crop Models ◽  
Successful Model ◽  
Model Reliability ◽  
Contamination Levels ◽  
Single Extractions

The paired Fluvisol and cereal samples in both the field screening and controlled experiments are reported to elucidate the soil–crop relationship for As, Cd, and Pb in relation to changing contamination levels. Significant varietal differences in plant uptake were observed for crop type (barley, triticale) and the harvested part of the crop (oat shoots and grain). When parametrizing the stepwise regression models, the inclusion of soil properties often improved the performance of soil–crop models but diverse critical soil parameters were retained in the model for individual metal(loid)s. The pH value was often a statistically significant variable for Cd uptake. For As and Pb, the more successful model fit was achieved using the indicators of quantity or quality of soil organic matter, but always with lower inherent model reliability compared to Cd. Further, a single correlation analysis was used to investigate the relationship between extractable metal concentrations in soil solution and their crop accumulation. For Cd, there were strong intercorrelations among single extractions, the NH4NO3 extraction stood out with perfect correlation with plant uptake in both experiments. For As and Pb, the CaCl2 and Na2EDTA solutions outperformed other single extractions and were the better choice for the assessment of depositional fluvial substrates.

The Quantification of Internal Noise Levels and Wall Pressure Spectra in Industrial Gas Pipelines

1991 ◽  
Author(s):  
M. P. Norton ◽  
A. Pruiti
Keyword(s):  
Prediction Models ◽  
Transmission Loss ◽  
Pressure Fluctuations ◽  
Internal Noise ◽  
Wall Pressure ◽  
Gas Pipelines ◽  
Noise Levels ◽  
Empirical Prediction ◽  
Wall Pressure Fluctuations ◽  
Semi Empirical

Abstract This paper addresses the issue of quantifying the internal noise levels/wall pressure fluctuations in industrial gas pipelines. This quantification of internal noise levels/wall pressure fluctuations allows for external noise radiation from pipelines to be specified in absolute levels via appropriate noise prediction models. Semi-empirical prediction models based upon (i) estimated vibration levels and radiation ratios, (ii) semi-empirical transmission loss models, and (iii) statistical energy analysis models have already been reported on by Norton and Pruiti 1,3 and are not reported on here.

Modeling and Analysis of Surface Roughness with Statistical and Soft Computing Approach

2021 ◽  
Vol 106 ◽  
pp. 109-115
Author(s):  
L.B. Abhang ◽  
M. Hameedullah
Keyword(s):  
Surface Roughness ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Prediction Models ◽  
Tool Geometry ◽  
Modeling And Analysis ◽  
Empirical Prediction ◽  
Lathe Machine ◽  
Carbide Inserts ◽  
Computing Approach

The objective of this study focuses on developing empirical prediction models using response regression analysis and fuzzy-logic. These models latter can be used to predict surface roughness according to technological variables. The values of surface roughness produced by these models are compared with experimental results. Experimental investigation has been carried out by using scientific composite factorial design on precision lathe machine with tungsten carbide inserts. Surface roughness measured at end of each experimental trial (three times), to get the effect of machining conditions and tool geometry on the surface finish values. Research showed that soft computing fuzzy logic model developed produces smaller error and has satisfactory results as compared to response regression model during machining.

scholarly journals Modelling Current and Future Potential Habitats for Plantations of Eucalyptus grandis Hill ex Maiden and E. dunnii Maiden in Uruguay

Forests ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 948 ◽  
Author(s):  
Fernando Resquin ◽  
Joaquín Duque-Lazo ◽  
Cristina Acosta-Muñoz ◽  
Cecilia Rachid-Casnati ◽  
Leonidas Carrasco-Letelier ◽  
...  
Keyword(s):  
Climate Change ◽  
Prediction Models ◽  
Eucalyptus Grandis ◽  
Soil Parameters ◽  
Climate Change Scenarios ◽  
High Susceptibility ◽  
Productive Potential ◽  
Potential Habitats ◽  
Future Potential ◽  
South Of Brazil

Eucalyptus grandis and E. dunnii have high productive potential in the South of Brazil, Uruguay, and central Argentina. This is based on the similarity of the climate and soil of these areas, which form an eco-region called Campos. However, previous results show that these species have differences in their distribution caused by the prioritization of Uruguayan soils for forestry, explained by the particular conditions of each site. In this study, the site variables (climate, soil, and topography) that better explain the distribution of both species were identified, and prediction models of current and future distribution were adjusted for different climate change scenarios (years 2050 and 2070). The distribution of E. grandis was associated with soil parameters, whereas for E. dunnii a greater effect of the climatic variables was observed. The ensemble biomod2 model was the most precise with regard to predicting the habitat for both species with respect to the simple models evaluated. For E. dunnii, the average values of the AUC, Kappa, and TSS index were 0.98, 0.88, and 0.77, respectively. For E. grandis, their values were 0.97, 0.86, and 0.80, respectively. In the projections of climatic change, the distribution of E. grandis occurrence remains practically unchanged, even in the scenarios of temperature increase. However, current distribution of E. dunnii shows high susceptibility in a scenario of increased temperature, to the point that most of the area currently planted may be at risk. Our results might be useful to political government and foresters for decision making in terms of future planted areas.

scholarly journals Empirical Prediction Models of 1-min Rain Rate Distribution for Various Integration Time

2008 ◽  
Vol 8 (2) ◽  
pp. 84-89 ◽  
Author(s):  
Myoung-Won Jung ◽  
Il-Tak Han ◽  
Moon-Young Choi ◽  
Joo-Hwan Lee ◽  
Jeong-Ki Pack
Keyword(s):  
Rain Rate ◽  
Prediction Models ◽  
Integration Time ◽  
Rate Distribution ◽  
Empirical Prediction

scholarly journals Measurement and Prediction of Short-Range Path Loss between 27 and 40 GHz in University Campus Scenarios

2020 ◽  
Author(s):  
Glaucio Ramos ◽  
Carlos Vargas ◽  
Luiz Mello ◽  
Paulo Pereira ◽  
Sandro Gonçalves ◽  
...  
Keyword(s):  
Short Range ◽  
Prediction Models ◽  
Path Loss ◽  
Prediction Method ◽  
University Campus ◽  
Millimetre Wave ◽  
Empirical Prediction ◽  
Loss Prediction ◽  
Path Loss Prediction ◽  
Path Loss Measurements

Abstract In this paper, we present the results of short-range path loss measurements in the microwave and millimetre wave bands, at frequencies between 27 and 40 GHz, obtained in a campaign inside a university campus in Rio de Janeiro, Brazil. Existing empirical path loss prediction models, including the alpha-beta-gamma (ABG) model and the close-in free space reference distance with frequency dependent path loss exponent (CIF) model are tested against the measured data, and an improved prediction method that includes the path loss dependence on the height di erence between transmitter and receiver is proposed. A fuzzy technique is also applied to predict the path loss and the results are compared with those obtained with the empirical prediction models.

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