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Hydrophobic Deep Eutectic Solvents (HDESs) represent a novel kind of solvent. While several studies investigated their properties, just a few dealt with their use for extracting and recovering bioactive compounds from raw materials, wastes and by-products, even if HDESs might represent an interesting alternative when producing pharmaceuticals, foodstuffs and cosmetics. Furthermore, their use may contribute to realizing more sustainable green processes. This review focuses on HDESs, with particular emphasis on Natural HDESs, discussing their properties and uses, highlighting their role as extractants in food applications, both from an analytical and processing point of view, and underlining the positive and negative aspects. While of prospective interest, currently the use of HDESs at industrial level remains a challenge, with several aspects needing further investigation. In order to scale-up the process, more research should focus on key issues, such as solute recovery, solvent recycling and extraction yields, as well as potential health hazards., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

In this study, 40% of unmalted gluten free (GF) grains (sorghum, millet, buckwheat, quinoa and amaranth) was used in brewing process, in gelatinized and ungelatinized form, in order to produce GF beer and to extend current knowledge about their suitability as brewing adjuncts. Partial replacement of barley malt with GF grains led to a significant decrease of extract (°P) and alcohol (%v/v) content compared to control beer (p < 0.05), except for quinoa beer (QB). Results from Principal Component Analysis (PCA) highlighted a satisfactory classification of experimental beers according to the two different forms of GF grains (gelatinized and ungelatinized). However, beers brewed with ungelatinized grains (mainly sorghum and quinoa) showed acceptable technological and sensory properties, thus suggesting that the pre-gelatinization step could be bypassed with a view to more environmentally and economically sustainable time-saving process. In addition, all beer samples showed a gluten content higher than 20 ppm., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

A chemical characterisation was conducted on 75 commercial extra virgin olive oils (EVOO) produced in the years 2011-2012 in Southern Italy from five different olive monovarieties (Coratina, Leccino, Maiatica, Ogliarola del Vulture and Ogliarola del Bradano). The possibility of estimating the antioxidant activity of EVOO by using a chemical index as predictor of this property was considered. In order to build up and validate an antioxidant activity predictive model, the relationship between the antioxidant activity and the chosen chemical parameters was systematically investigated. The results indicated that oil antioxidant activity, measured as IC50, could be satisfactorily predicted, for olive oils from the considered region, by using a simple index, such as the K225 value of oil samples, which represents a spectrophotometric index of the compounds responsible for oil bitterness measured at 225 nm., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

An experimental investigation was performed on blend extra virgin olive oils (EVOOs) from different cultivars and EVOO from different olive monovarieties (Coratina, Leccino, Maiatica, Ogliarola) with the aim to evaluate the possibility of estimating the perceived bitterness intensity by using chemical indices, such as the total phenol content and the compounds responsible for oil bitterness measured spectrophotometrically at 225 nm (K225 value), as bitterness predictors in different EVOO. Therefore, a bitterness predictive model, based on the relationship between the perceived bitterness intensity of the selected stimuli and the chosen chemicals parameters has been built and validated. The results indicated that the oil bitterness intensity could be satisfactorily predicted by using the K225 values of oil samples., (Copyright © 2013 Elsevier Ltd. All rights reserved.)