Optimization of an analytical method based on the use of zwitterionic- phosphorylcholine -HILIC column for the determination of multiple polar emerging contaminants in reclaimed water.

The aim of this study was to optimize a Liquid Chromatography Mass Spectrometry (LC-MS) method using a zwitterionic phosphorylcholine HILIC column for the determination of several Persistent and Mobile Organic Contaminants (PMOC) in wastewater samples. An experimental design approach was implemented to both better understand the retention mechanisms of several polar compounds and to find the optimal operating conditions for their detection and quantification. Eleven PMOCs, with logD ranging from -5.

Chemical Characterization and Temporal Variability of Pasta Condiment By-Products for Sustainable Waste Management.

Sustainable waste management is an extremely important issue due to its environmental, economic, and social impacts. Knowledge of the chemical composition of the waste produced is a starting point for its valorization. This research focuses, for the first time, on the by-products of pasta condiment production, starting with their characterization.

Does hyperspectral always matter? A critical assessment of near infrared versus hyperspectral near infrared in the study of heterogeneous samples.

Near Infrared spectroscopy (NIR), in combination with Chemometrics, has been used for many years in diverse scenarios, mostly focused on the classification and quantitation of properties in food, pharmaceutical preparations, artwork material, etc. This success has been possible due to their desirable properties: fast, reliable (under certain conditions), non-destructive, easy to implement from a hardware perspective, and able to create robust and transferable multivariate models. For some years now, another modality has been gaining the attention of NIR users, especially in the Food sector.

Implementing multiblock techniques in a full-scale plant scenario: On-line prediction of quality parameters in a continuous process for different acrylonitrile butadiene styrene (ABS) products.

Background: The study explores the challenges of handling multiblock data of different natures (process and NIR sensors) for on-line quality prediction in a full-scale plant scenario, namely a plant operating in continuous on an industrial scale and producing different grade Acrylonitrile Butadiene Styrene (ABS) products. This environment is an ideal scenario to evaluate the use of multiblock data analysis methods, which can enhance data interpretation, visualization, and predictive performances. In particular, a novel multiblock extension of Locally Weighted PLS has been proposed by the authors, namely Locally Weighted Multiblock Partial Least Squares (LW-MB-PLS).