Supercritical CO2 Extraction of Narcissus poeticus L. Flowers for the Isolation of Volatile Fragrance Compounds

Analysis of Volatile Compounds in Processed Cream Cheese Models for the Prediction of "Fresh Cream" Aroma Perception

Controlling flavor perception by analyzing volatile and taste compounds is a key challenge for food industries, as flavor is the result of a complex mix of components. Machine-learning methodologies are already used to predict odor perception, but they are used to a lesser extent to predict aroma perception. The objectives of this work were, for the processed cream cheese models studied, to (1) analyze the impact of the composition and process on the sensory perception and VOC release and (2) predict "fresh cream" aroma perception from the VOC characteristics. Sixteen processed cream cheese models were produced according to a three-factor experimental design: the texturing agent type (κ-carrageenan, agar-agar) and level and the heating time. A R-A-T-A test on 59 consumers was carried out to describe the sensory perception of the cheese models. VOC release from the cheese model boli during swallowing was investigated with an in vitro masticator (Oniris device patent), followed by HS-SPME-GC-(ToF)MS analysis. Regression trees and random forests were used to predict "fresh cream" aroma perception, i.e., one of the main drivers of liking of processed cheeses, from the VOC release during swallowing. Agar-agar cheese models were perceived as having a "milk" odor and favored the release of a greater number of VOCs; κ-carrageenan samples were perceived as having a "granular" and "brittle" texture and a "salty" and "sour" taste and displayed a VOC retention capacity. Heating induced firmer cheese models and promoted Maillard VOCs responsible for "cooked" and "chemical" aroma perceptions. Octa-3,5-dien-2-one and octane-2,3-dione were the two main VOCs that contributed positively to the "fresh cream" aroma perception. Thus, regression trees and random forests are powerful statistical tools to provide a first insight into predicting the aroma of cheese models based on VOC characteristics.

Modeling Binary and Multicomponent Systems Containing Supercritical CO2 with Polyethylene Glycols and Compounds Relevant to the Biodiesel Production

The CPA equation of state is applied to model binary, ternary, and multicomponent mixtures that contain CO₂ with polyethylene glycols or compounds relevant to biodiesel production, such as glycerol and various triglycerides. Effort has been made to evaluate the model performance on correlating both the liquid and the vapor phase compositions, which is a demanding task, revealing the model’s and parameters’ limitations, due to the rather low concentrations of heavy compounds in the vapor phase. Initially the model’s binary parameters, which in all cases were temperature independent, were estimated using experimental data for binary systems. Those parameters were used to predict the phase behavior of supercritical CO₂ containing ternary and multicomponent mixtures. Since no parameter was adjusted to ternary or multicomponent systems’ data, the reported CPA results for such mixtures are considered as pure predictions. This is the final part of a series of studies [Tsivintzelis et al. Fluid Phase Equilibria 430 (2016) 75–92 and 504 (2020) 112337] that complete the parameterization of the CPA equation of state for systems relevant to the biodiesel production, which allows the application of the model to multicomponent mixtures of the relevant processes.

Oxygen Scavenger and Antioxidant LDPE/EVOH/PET-Based Films Containing β-Carotene Intended for Fried Peanuts (Arachis hypogaea L.) Packaging: Pilot Scale Processing and Validation Studies

The aim of this study was to develop an oxygen scavenger and antioxidant active packaging material for fried peanuts. The packaging solution, which has been made at the laboratory previously, has been developed by cast film extrusion and is composed of low-density polyethylene-ethylene vinyl alcohol-polyethylene terephthalate (LDPE/EVOH/PET)-based films containing β-carotene (CAR). In comparison with film without additive, developed film presented an orange colouring (higher L* and b* values and lower a* values) and an increase in oxygen induction time (OIt) from 4.5 to 14.1 min. The incorporation of β-carotene to the formulation also brings about a significant effect on the thermal stability as maximum degradation temperatures increased around 1%. Regarding the oxygen absorption capacity of the films, values of 1.39 ± 0.10 mL O₂ per g of film at laboratory scale and 1.7 ± 0.3 mL O₂ per g of multilayer (ML)/LDPE_CAR were obtained, respectively, after 3 days, proving the suitability of the packaging solutions as oxygen absorbers. To validate the packaging solution, the oxidative stability of fried peanuts packed in fabricated multilayer β-carotene bags was evaluated for 3 months at 40 °C. The hexanal content remained constant during this period. Meanwhile, peanuts packed in ML without β-carotene increased their hexanal content to 294%. This fact indicated a lower extent of oxidation in fried peanuts compared to food samples packaged in control films, suggesting the potential of ML/LDPE_CAR films as sustainable and antioxidant food packaging systems to offer protection against lipid oxidation in foods. Sensory evaluation confirmed that ML/LDPE_CAR films provided the peanut samples with an extra aroma due to the volatile degradation products of β-carotene (such as β-cyclocitral or 6-methyl-5-hepten-2-ol).