Life cycle assessment and yield to optimize extraction time and solvent: Comparing deep eutectic solvents vs conventional ones.

Deep eutectic solvents (DES) are gaining interest as eco-friendly alternatives for extracting bioactive compounds, but their environmental benefits remain unclear and need further evaluation. In this work, a case study of total polyphenols (TPC) extraction from spent coffee grounds (SCG) was environmentally evaluated using life cycle assessment (LCA). First, the most convenient extraction time (1, 10, 20, or 40 min) for water and acetone 20 % from an environmental perspective was identified.

Extraction of Bioactive Compounds from Spent Coffee Grounds Using Ethanol and Acetone Aqueous Solutions.

Given global coffee consumption, substantial quantities of spent coffee grounds (SCGs) are generated annually as a by-product of brewing coffee. SCG, although rich in bioactive compounds, is nowadays disposed of. The objective of this study is to compare, for the first time and from the same SCG, the efficiency of ethanol-water mixtures and acetone-water mixtures for the recovery of total polyphenols, chlorogenic acid, and caffeine.

Environmental and Yield Comparison of Quick Extraction Methods for Caffeine and Chlorogenic Acid from Spent Coffee Grounds.

This study aims to provide an overview of different extraction methods to obtain chlorogenic acid (CA) and caffeine (Caf) from spent coffee grounds (SCG). This overview shows that the quantity extracted is highly dependent on the type of SCG, so experiments using the same SCG are needed to compare different methods. Three easy and simple extraction methods will be tested at a laboratory scale and environmentally compared.

Classification of Textile Samples Using Data Fusion Combining Near- and Mid-Infrared Spectral Information.

There is an urgent need to reuse and recycle textile fibers, since today, low recycling rates are achieved. Accurate classification methods for post-consumer textile waste are needed in the short term for a higher circularity in the textile and fashion industries. This paper compares different spectroscopic data from textile samples in order to correctly classify the textile samples.