Using Statistical Modeling for Assessing Lettuce Crops Contaminated with Zn, Correlating Plants Growth Characteristics with the Soil Contamination Levels
| Autor: | Nicoleta Ungureanu, Oana Diana Cristea, Valentin Vlăduț, Florin Nenciu, Petru Cardei, I. Găgeanu, Mirabela Augustina Pruteanu, D. Cujbescu |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Plant growth
Technology QH301-705.5 QC1-999 Lactuca Soil science Hazardous waste General Materials Science Biology (General) heavy metals zinc accumulation Instrumentation QD1-999 Fluid Flow and Transfer Processes Pollutant biology Mathematical model Process Chemistry and Technology Physics fungi General Engineering food and beverages Statistical model Contamination biology.organism_classification Engineering (General). Civil engineering (General) Soil contamination Computer Science Applications Chemistry Environmental science TA1-2040 soil contamination |
| Zdroj: | Applied Sciences, Vol 11, Iss 8261, p 8261 (2021) Applied Sciences Volume 11 Issue 17 |
| ISSN: | 2076-3417 |
| Popis: | The aim of the study was to identify new mathematical models and strategies that can characterize the behavior of pollutants accumulating in the soil over time, considering the special characteristics of these chemicals that cannot be degraded or destroyed easily. The paper proposes a statistical model for assessing the accumulation of Zn in the lettuce (Lactuca sativa L.), based on three indicators that characterize the development of lettuce plants over time. The experimental data can be used to obtain interpolated variations of the mass increase functions and to determine several functions that express the time dependence of heavy metal accumulation in the plant. The resulting interpolation functions have multiple applications, being useful in generating predictions for plant growth parameters when they are grown in contaminated environments, determining whether pollutant concentrations may be hazardous for human health, and may be used to verify and validate dynamic mathematical contamination models. |
| Databáze: | OpenAIRE |
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