Abstract
Sorption and desorption determine the amount of an herbicide in soil solution. Therefore, knowledge of the sorption and desorption coefficients in different soils is an essential factor to estimate the potential for environmental contamination by herbicides. We evaluated the feasibility of multivariate and linear discriminant analyses to predict the sorption and desorption capacity of a soil for diuron, one of the most used herbicides on sugarcane plantations. The adsorptive capacity in twenty-seven Brazilian soil samples was estimated using the sorption constant (Kfs) and desorption constant (Kfd) obtained by the Freundlich isotherms. The regression model was created from the sorbed and nonsorbed concentrations of diuron in soils. Ultra-performance liquid chromatography was applied to quantify the diuron concentrations. The multivariate analysis separated the soils into four groups considering the similarity of the following attributes: pH, organic matter, clay, and base saturation. The groups showed a similar pattern of sorption and desorption for diuron: Lom-Lclay: low sorption (5.9 ± 1.2) and high desorption (10.9 ± 0.6); Lclay: low sorption (7.5 ± 1.1) and high desorption (11.4 ± 1.3); Hom-Hclay: high sorption (11.2 ± 1.2) and low desorption (13.8 ± 1.2); HpH-Hclay: high sorption (10.1 ± 1.1) and medium desorption (11.5 ± 1.4). Linear discriminant analysis of these soil attributes was used to classify other soils described in the literature with adsorption capacity. This analysis was able to identify soils with high and low sorption using the pH, organic matter, clay, and base saturation, demonstrating the enormous potential of the technique to group soils with different contamination risks for subterranean waters. Sugarcane crops in northeastern Brazil showed a higher pollution risk through the leaching of diuron. Multivariate analysis revealed significant diuron-related changes in the soil composition of different Brazilian regions; therefore, this statistical analysis can be used to improve understanding of herbicide behavior in soils.
Highlights
The application of pesticides in modern agriculture has allowed production systems to minimize losses caused by pests, diseases, and weeds[1]
We constructed three hypotheses: (1) What soil attributes should be used for the cluster and discriminant analysis? (2) Do soils collected from sugarcane-producing states show a similar pattern of sorption and desorption when grouped due to the similarity of their physical-chemical attributes? (3) Are there Brazilian regions with higher contamination risks due to the application of diuron? (4) Will the linear discriminant analysis classify other soils with higher and lower sorption and desorption capacities? The results demonstrated that a linear model from discriminant analysis could be construed to identify agricultural areas with a high risk of contamination by diuron
The samples were collected from the 0–20 cm layer in areas that were free of herbicide application
Summary
The application of pesticides in modern agriculture has allowed production systems to minimize losses caused by pests, diseases, and weeds[1]. Among the agrochemicals applied during the productive cycle of sugarcane, herbicides are often used as a management tool. This crop has a long critical weed period of prevention, requiring frequent applications or use of herbicides with a longer residual period[3]. An herbicide that is commonly used in areas cultivated with sugarcane is diuron [N-(3,4-dichlorophenyl)-N, N-dimethylurea]. This herbicide belongs to the chemical group of substituted ureas, with a water solubility of www.nature.com/scientificreports/. Among soil-herbicide interactions, sorption and desorption define the amount available in the soil solution and, the mobility of this pesticide in the environment[13]. Thereby, studies involving large numbers of soil samples from different regions are necessary to evaluate the behavior of this herbicide
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