Insight into the Recent Application of Chemometrics in Quality Analysis and Characterization of Bee Honey during Processing and Storage

Exploring the role of NIR spectroscopy in quantifying and verifying honey authenticity: A review

Honey, recognized for its diverse flavors and nutritional benefits, confronts challenges in maintaining authenticity and quality due to factors like adulteration and mislabelling. This review undertakes a comprehensive exploration of the utility of Near-Infrared (NIR) spectroscopy as a non-destructive analytical method for concurrently evaluating both honey quantity and authenticity. The primary purpose of this investigation is to delve into the various applications of NIR spectroscopy in honey analysis, with a specific focus on its capability to identify and quantify significant quality parameters such as sugar content, moisture levels, 5-HMF, and proline content. Results from the study underscore the effectiveness of NIR spectroscopy, especially when integrated with advanced chemometrics models. This combination not only facilitates quantification of diverse quality parameters but also enhances the classification of honey based on geographical and botanical origin. The technology emerges as a potent tool for detecting adulteration, addressing critical challenges in preserving the authenticity and quality of honey products. The impact of this critical analysis extends to shedding light on the current state, challenges, and future prospects of applying NIR spectroscopy in the honey industry. This analysis outlines the current challenges and future prospects of NIR spectroscopy in the honey industry. Emphasizing its potential to improve consumer confidence and food safety, the research has broader implications for authenticity and quality assurance in honey. Integrating NIR spectroscopy into industry practices could establish stronger quality control measures, benefiting both producers and consumers globally.

Assessing the Impact of Botanical Origins, Harvest Years, and Geographical Variability on the Physicochemical Quality of Serbian Honey

This study summarized the physicochemical analysis of 609 honey samples originating from the Republic of Serbia. Variations among honey samples from different botanical origins, regions of collections, and harvest years were exposed to descriptive statistics and correlation analysis that differentiated honey samples. Furthermore, most of the observed physicochemical parameters (glucose, fructose, sucrose content, 5-hydroxymethylfurfural (5-HMF) levels, acidity, and electrical conductivity) varied significantly among different types of honey, years, and regions. At the same time, no noticeable difference was found in diastase activity, moisture content, and insoluble matter. Based on the obtained results, 22 honey samples could be considered adulterated, due to the irregular content of sucrose, 5-HMF, acidity, and diastase activity. In addition, 64 honey samples were suspected to be adulterated. Adulterated and non-compliant samples present a relatively low percentage (14.1%) of the total number of investigated samples. Consequently, a considerable number of honey samples met the required standards for honey quality. Overall, these findings provide insights into compositional and quality differences among various types of honey, aiding in understanding their characteristics and potential applications.

Intelligent Rapid Detection Techniques for Low-Content Components in Fruits and Vegetables: A Comprehensive Review

Fruits and vegetables are an important part of our daily diet and contain low-content components that are crucial for our health. Detecting these components accurately is of paramount significance. However, traditional detection methods face challenges such as complex sample processing, slow detection speed, and the need for highly skilled operators. These limitations fail to meet the growing demand for intelligent and rapid detection of low-content components in fruits and vegetables. In recent years, significant progress has been made in intelligent rapid detection technology, particularly in detecting high-content components in fruits and vegetables. However, the accurate detection of low-content components remains a challenge and has gained considerable attention in current research. This review paper aims to explore and analyze several intelligent rapid detection techniques that have been extensively studied for this purpose. These techniques include near-infrared spectroscopy, Raman spectroscopy, laser-induced breakdown spectroscopy, and terahertz spectroscopy, among others. This paper provides detailed reports and analyses of the application of these methods in detecting low-content components. Furthermore, it offers a prospective exploration of their future development in this field. The goal is to contribute to the enhancement and widespread adoption of technology for detecting low-content components in fruits and vegetables. It is expected that this review will serve as a valuable reference for researchers and practitioners in this area.

Implementation of Chemometrics and Other Techniques as Means of Authenticity and Traceability to Detect Adulteration in Foods for the Protection of Human Health

The authenticity of foods of plant and animal origin is key to safeguarding both quality and safety aspects without jeopardizing consumers' health [...].