Food Quality Assessed by Chemometrics

Abstract

<jats:p>Food market globalization, food security as well as increasing consumer demand for safe, minimally processed and healthy food impose the need to establish new approaches for identifying and assessing food quality markers. Nowadays, food industry stakeholders are challenged to assure food quality and safety without compromising several prerequisites such as sustainable and ecologically resilient food production, prolonged shelf life, satisfactory sensory quality, enhanced nutritional value and health-promoting properties. In addition, food fraud related to deliberate product mislabeling or economically intended adulteration is of major concern for both industry and regulatory authorities due to cost and public health implications. Notwithstanding the great number of state-of-the-art analytical tools available for quantifying food quality markers, their implementation results in highly complex and big datasets, which are not easily interpretable. In this context, chemometrics e.g., supervised and unsupervised multivariate exploratory analyses, design-of-experiment methodology, univariate or multivariate regression modelling etc., are commonly implemented as part of food process optimization and food quality assessment. In this Special Issue, we aimed to publish innovative research and perspective papers on chemometric-assisted case studies relating to food quality assessment, food authenticity, mathematical modelling and optimization of processes involved in food manufacturing.</jats:p>

D-α-Tocopherol-Based Micelles for Successful Encapsulation of Retinoic Acid

“…Multivariate analysis (MVA) is a rapid and efficient chemometric tool suitable to study complex instrumental data sets and able to unveil the hidden information in them [ 45 ]. There are more than 20 different ways to perform MVA depending on the type of data and the objectives to be achieved, including principal component analysis (PCA).…”

The Application of Chemometrics in Metabolomic and Lipidomic Analysis Data Presentation for Halal Authentication of Meat Products

“…It allows controlling the number of variables involved in the analysis [ 42 , 43 ] and providing accurate and significant results in a short time [ 44 ], besides having a good sensitivity and robustness [ 45 ]. There are two general types of chemometric methods, the unsupervised classifications and supervised classifications [ 46 ]. Unsupervised classifications include hierarchical clustering analysis (HCA) or clustering analysis.…”

Foodomics: Analytical Opportunities and Challenges

“…In addition, it is also increasing the concern of consumers about the relevance of food products on health and, consequently, their interest in knowing and understanding information about diet and food products. Hence, great efforts must be done in order to ensure the safety of consumers and guarantee the quality of food, improving current regulations, searching for new control strategies and good quality markers, and providing adequate information to the general population. , …”