Liquid and Solid Functional Bio-Based Coatings.

The development of new bio-based coating materials to be applied on cellulosic and plastic based substrates, with improved performances compared to currently available products and at the same time with improved sustainable end of life options, is a challenge of our times. Enabling cellulose or bioplastics with proper functional coatings, based on biopolymer and functional materials deriving from agro-food waste streams, will improve their performance, allowing them to effectively replace fossil products in the personal care, tableware and food packaging sectors. To achieve these challenging objectives some molecules can be used in wet or solid coating formulations, e.g., cutin as a hydrophobic water- and grease-repellent coating, polysaccharides such as chitosan-chitin as an antimicrobial coating, and proteins as a gas barrier. This review collects the available knowledge on functional coatings with a focus on the raw materials used and methods of dispersion/application. It considers, in addition, the correlation with the desired final properties of the applied coatings, thus discussing their potential.

HPLC-UV and HPLC-CAD chromatographic data fusion for the authentication of the geographical origin of palm oil.

Data fusion combined with a multivariate classification approach (partial least squares-discriminant analysis, PLS-DA) was applied to authenticate the geographical origin of palm oil. Data fusion takes advantage of the synergistic effect of information collected from more than one data source. In this study, data from liquid chromatography coupled to two detectors -ultraviolet (UV) and charged aerosol (CAD)- was fused by high- and mid-level data fusion strategies. Mid-level data fusion combines a few variables from each technique and then applies the classification technique. Principal component analysis and interval partial least squares were applied to obtain the variables selected. High-level data fusion combines the PLS-DA classification results obtained individually from the chromatographic technique with each detector. Fuzzy aggregation connective operators were used to make the combinations. Prediction rates varied between 73% and 98% for the individual techniques and between 87% and 100% and 93% and 100% for the mid- and high-level data fusion strategies, respectively.