The aim of the present work was to sensorially characterize different commercial categories of Iberian dry-cured loins (varying genetic and feeding background) using a novel dynamic sensory technique, and to explore consumers preferences applying a rapid method. The samples (green label—GL, Cebo de Campo Ibérico; red label—RL, Bellota 50% Ibérico; and black label—BL, Bellota 100%) were analyzed by (i) Check-all-that-apply (CATA) with the evaluation of an ‘Ideal’ dry-cured loin and the overall liking, and by (ii) multiple-intake Temporal Dominance of Sensations (TDS). The CATA results indicated that the sensory characteristics of RL samples were closer to those of the ‘Ideal’ loin. Furthermore, juiciness, marbling, cured flavor, chewiness, persistence, and brightness were selected as ‘must-have’ attributes. Juiciness cured flavor and red color were considered as drivers of liking. TDS results showed that flavor attributes presented the highest dominance rates, with saltiness being the most dominant attribute along BL sample evaluation, and with cured and paprika flavor for GL and RL samples. These sensory technique results displayed the ability to sensorily characterize dry-cured loins, providing different, complementary, and valuable information.

This work studies the ability of a MicroNIR (VIAVI, Santa Rosa, CA) device to monitor the dry fermented sausage process with the use of multivariate data analysis. Thirty sausages were made and subjected to dry fermentation, which was divided into four main stages. Physicochemical (weight lost, pH, moisture content, water activity, color, hardness, and thiobarbiruric reactive substances analysis) and sensory (quantitative descriptive analysis) characterizations of samples on different steps of the ripening process were performed. Near-infrared (NIR) spectra (950–1650 nm) were taken throughout the process at three points of the samples. Physicochemical data were explored by distance to K-Nearest Neighbor (K-NN) cluster analysis, while NIR spectra were studied by partial least square–discriminant analysis; before these models, Principal Component Analysis (PCA) was performed in both databases. The results of multivariate data analysis showed the ability to monitor and classify the different stages of ripening process (mainly the fermentation and drying steps). This study showed that a portable NIR device (MicroNIR) is a nondestructive, simple, noninvasive, fast, and cost-effective tool with the ability to monitor the dry fermented sausage processing and to classify samples as a function of the stage, constituting a feasible decision method for sausages to progress to the following processing stage.

At present, the quality of edible oil is evaluated using traditional analysis techniques that are generally destructive. Therefore, efforts are being made to find alternative methods with non-destructive techniques such as Ultrasound. This work aims to confirm the feasibility of non-destructive ultrasonic inspection to characterise and detect fraudulent practices in olive oil due to adulteration with two other edible vegetable oils (sunflower and corn). For this purpose, pulsed ultrasonic signals with a frequency of 2.25 MHz have been used. The samples of pure olive oil were adulterated with the other two in variable percentages between 20% and 80%. Moreover, the viscosity and density values were measured. Both these physicochemical and acoustic parameters were obtained at 24 °C and 30 °C and linearly correlated with each other. The results indicate the sensitivity of the method at all levels of adulteration studied. The responses obtained through the parameters related to the components of velocity, attenuation, and frequency of the ultrasonic waves are complementary to each other. This allows concluding that the classification of pure and adulterated oil samples is possible through non-destructive ultrasonic inspection.