Characterization of Plant Accumulation of Pharmaceuticals from Soils with Their Concentration in Soil Pore Water.

Predicting plant uptake of pharmaceuticals from soils is very challenging because many pharmaceuticals are ionizable compounds, which experience highly variable sorption/desorption and transformation processes in soils. This study aimed to elucidate how the equilibrium between sorbed and dissolved phases influences radish uptake of 15 pharmaceuticals from three soils with different properties. After 30 days of uptake, the accumulation of acetaminophen, carbamazepine, lamotrigine, carbadox, trimethoprim, and triclosan in radish ranked as Riddles > Capac > Spinks soil.

Direct Prediction of Bioaccumulation of Organic Contaminants in Plant Roots from Soils with Machine Learning Models Based on Molecular Structures.

Root concentration factor (RCF) is an important characterization parameter to describe accumulation of organic contaminants in plants from soils in life cycle impact assessment (LCIA) and phytoremediation potential assessment. However, building robust predictive models remains challenging due to the complex interactions among chemical-soil-plant root systems. Here we developed end-to-end machine learning models to devolve the complex molecular structure relationship with RCF by training on a unified RCF data set with 341 data points covering 72 chemicals.

Metabolomic Approaches to Studying the Response to Drought Stress in Corn () Cobs.

Metabolomics is a technique that allows for the evaluation of the entire extractable chemical profile of a plant, for example, using high-resolution mass spectrometry (HRMS) and can be used to evaluate plant stress responses, such as those due to drought. Metabolomic analysis is dependent upon the efficiency of the extraction protocol. Currently, there are two common extraction procedures widely used in metabolomic experiments, those that extract from plant tissue processed in liquid nitrogen or extraction from lyophilised plant tissues.

An Automated Methodology for Non-targeted Compositional Analysis of Small Molecules in High Complexity Environmental Matrices Using Coupled Ultra Performance Liquid Chromatography Orbitrap Mass Spectrometry.

The life-critical matrices of air and water are among the most complex chemical mixtures that are ever encountered. Ultrahigh-resolution mass spectrometers, such as the Orbitrap, provide unprecedented analytical capabilities to probe the molecular composition of such matrices, but the extraction of non-targeted chemical information is impractical to perform via manual data processing. Automated non-targeted tools rapidly extract the chemical information of all detected compounds within a sample dataset.

Detection, occurrence, and fate of emerging contaminants in agricultural environments (2019).

A review of 82 papers published in 2018 is presented. The topics ranged from detailed descriptions of analytical methods, to fate and occurrence studies, to ecological effects and sampling techniques for a wide variety of emerging contaminants likely to occur in agricultural environments. New methods and studies on veterinary pharmaceuticals, microplastics, and engineered nanomaterials in agricultural environments continue to expand our knowledge base on the occurrence and potential impacts of these compounds.