Current Application of Advancing Spectroscopy Techniques in Food Analysis: Data Handling with Chemometric Approaches

Abstract

In today’s era of increased food consumption, consumers have become more demanding in terms of safety and the quality of products they consume. As a result, food authorities are closely monitoring the food industry to ensure that products meet the required standards of quality. The analysis of food properties encompasses various aspects, including chemical and physical descriptions, sensory assessments, authenticity, traceability, processing, crop production, storage conditions, and microbial and contaminant levels. Traditionally, the analysis of food properties has relied on conventional analytical techniques. However, these methods often involve destructive processes, which are laborious, time-consuming, expensive, and environmentally harmful. In contrast, advanced spectroscopic techniques offer a promising alternative. Spectroscopic methods such as hyperspectral and multispectral imaging, NMR, Raman, IR, UV, visible, fluorescence, and X-ray-based methods provide rapid, non-destructive, cost-effective, and environmentally friendly means of food analysis. Nevertheless, interpreting spectroscopy data, whether in the form of signals (fingerprints) or images, can be complex without the assistance of statistical and innovative chemometric approaches. These approaches involve various steps such as pre-processing, exploratory analysis, variable selection, regression, classification, and data integration. They are essential for extracting relevant information and effectively handling the complexity of spectroscopic data. This review aims to address, discuss, and examine recent studies on advanced spectroscopic techniques and chemometric tools in the context of food product applications and analysis trends. Furthermore, it focuses on the practical aspects of spectral data handling, model construction, data interpretation, and the general utilization of statistical and chemometric methods for both qualitative and quantitative analysis. By exploring the advancements in spectroscopic techniques and their integration with chemometric tools, this review provides valuable insights into the potential applications and future directions of these analytical approaches in the food industry. It emphasizes the importance of efficient data handling, model development, and practical implementation of statistical and chemometric methods in the field of food analysis.

FT-MIR-ATR Associated with Chemometrics Methods: A Preliminary Analysis of Deterioration State of Brazil Nut Oil

“…Only batches C3, C4, M10, M11, and M12 can be sent to the food sector, as they comply with the legislation in terms of AI and PI parameters. In a study by Kharbach, Alaoui, and Taabouz [44], various processed food products were analyzed. They found a strong correlation between the peroxide and acidity indexes and the sensory acceptability of the products.…”

AI Classification of Eggs’ Origin from Mycoplasma synoviae-Infected or Non-Infected Poultry via Analysis of the Spectral Response

“…By employing machine learning algorithms, the researchers were able to differentiate tested samples of various origins with a reasonable probability. In the case of white eggshells, the F-scores reached 95.75%, while for brown eggshells, the F-scores reached 86.21% [31]. When using modified machine learning algorithms, the F-scores for white eggshells were 86% while for brown eggshells, they were 96% [27].…”

“…Moreover, spectral data may also vary depending on what kind of spectral response is measured: transmittance, reflectance, absorption, scattering, fluorescence, etc. Principal Component Analysis (PCA) is one of the most popular data analysis methods [29][30][31][32][33]. However, due to factors like subraces, age of hens, egg colouring, diet, and climate, eggshells' diversity is so extensive that standard PCA algorithms prove ineffective.…”

Rapid analysis technologies with chemometrics for food authenticity field: A review

“…Recently, spectroscopy, mass spectrometry, electronic sensor technology and DNA technology have been widely used in food analysis. The rapid and non-destructive analytical characteristics of spectroscopic techniques and the low analytical cost and high analytical efficiency of electronic sensor techniques are compatible with the technological needs in the food authenticity field, and have been used to identify the authenticity of a wide range of food products in recent years ( Kharbach et al, 2023 ; Tan and Xu, 2020 ). Mass spectrometry and DNA analysis have the advantages of high sensitivity and wide range of application ( Huang et al, 2010 ; Scarano and Rao, 2014 ).…”