Characterizing the Dynamic Taste and Retro-Nasal Aroma Properties of Oral Nutritional Supplements Using Temporal Dominance of Sensation and Temporal Check-All-That-Apply Methods

Multi-attribute temporal descriptive methods in sensory analysis applied in food science: A systematic scoping review

Among descriptive sensory evaluation methods, temporal methods have a wide audience in food science because they make it possible to follow perception as close as possible to the moment when sensations are perceived. The aim of this work was to describe 30 years of research involving temporal methods by mapping the scientific literature using a systematic scoping review. Thus, 363 research articles found from a search in Scopus and Web of Science from 1991 to 2022 were included. The extracted data included information on the implementation of studies referring to the use of temporal methods (details related to subjects, products, descriptors, research design, data analysis, etc.), reasons why they were used and the conclusions they allowed to be drawn. Metadata analysis and critical appraisal were also carried out. A quantitative and qualitative synthesis of the results allowed the identification of trends in the way in which the methods were developed, refined, and disseminated. Overall, a large heterogeneity was noted in the way in which the temporal measurements were carried out and the results presented. Some critical research gaps in establishing the validity and reliability of temporal methods have also been identified. They were mostly related to the details of implementation of the methods (e.g., almost no justification for the number of consumers included in the studies, absence of report on panel repeatability) and data analysis (e.g., prevalence of use of exploratory data analysis, only 20% of studies using confirmatory analyses considering the dynamic nature of the data). These results suggest the need for general guidelines on how to implement the method, analyze and interpret data, and report the results. Thus, a template and checklist for reporting data and results were proposed to help increase the quality of future research.

Development and Evaluation of Cannabidiol Orodispersible Tablets Using a 23-Factorial Design

Orodispersible tablets (ODTs) are pharmaceutical formulations used to obtain fast therapeutic effects, usually recommended for geriatric and pediatric patients due to their improved compliance, bioavailability, ease of administration, and good palatability. This study aimed to develop ODTs with cannabidiol (CBD) phytocannabinoid extracted from Cannabis sativa used in the treatment of Lennox–Gastaut and Dravet syndromes. The tablets were obtained using an eccentric tableting machine and 9 mm punches. To develop CBD ODTs, the following parameters were varied: the Poloxamer 407 concentration (0 and 10%), the type of co-processed excipient (Prosolv^® ODT G2—PODTG2 and Prosolv^® EasyTab sp—PETsp), and the type of superdisintegrant (Croscarmellose—CCS, and Soy Polysaccharides—Emcosoy^®—EMCS), resulting in eleven formulations (O1–O11). The following dependent parameters were evaluated: friability, disintegration time, crushing strength, and the CBD dissolution at 1, 3, 5, 10, 15, and 30 min. The dependent parameters were verified according to European Pharmacopoeia (Ph. Eur.) requirements. All the tablets obtained were in accordance with quality requirements in terms of friability (less than 1%), and disintegration time (less than 180 s). The crushing strength was between 19 N and 80 N. Regarding the dissolution test, only four formulations exhibited an amount of CBD released higher than 80% at 30 min. Taking into consideration the results obtained and using the Modde 13.1 software, an optimal formulation was developed (O12), which respected the quality criteria chosen (friability 0.23%, crushing strength of 37 N, a disintegration time of 27 s, and the target amount of CBD released in 30 min of 99.3 ± 6%).

Bootstrap Resampling of Temporal Dominance of Sensations Curves to Compute Uncertainties

In the last decade, temporal dominance of sensations (TDS) methods have proven to be potent approaches in the field of food sciences. Accordingly, thus far, methods for analyzing TDS curves, which are the major outputs of TDS methods, have been developed. This study proposes a method of bootstrap resampling for TDS tasks. The proposed method enables the production of random TDS curves to estimate the uncertainties, that is, the 95% confidence interval and standard error of the curves. Based on Monte Carlo simulation studies, the estimated uncertainties are considered valid and match those estimated by approximated normal distributions with the number of independent TDS tasks or samples being 50-100 or greater. The proposed resampling method enables researchers to apply statistical analyses and machine-learning approaches that require a large sample size of TDS curves.