Kharbach Mourad, Alaoui Mansouri Mohammed, Taabouz Mohammed, Yu Huiwen
Department of Food and Nutrition, University of Helsinki, 00014 Helsinki, Finland.
Department of Computer Sciences, University of Helsinki, 00560 Helsinki, Finland.
Foods. 2023 Jul 19;12(14):2753. doi: 10.3390/foods12142753.
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.
在当今食品消费增加的时代,消费者对他们所消费产品的安全性和质量要求越来越高。因此,食品监管部门正在密切监测食品行业,以确保产品符合规定的质量标准。食品特性分析涵盖多个方面,包括化学和物理描述、感官评估、真实性、可追溯性、加工、作物生产、储存条件以及微生物和污染物水平。传统上,食品特性分析依赖于传统分析技术。然而,这些方法通常涉及破坏性过程,既费力、耗时、昂贵,又对环境有害。相比之下,先进的光谱技术提供了一种很有前景的替代方法。诸如高光谱和多光谱成像、核磁共振、拉曼光谱、红外光谱、紫外光谱、可见光谱、荧光光谱以及基于X射线的方法等光谱方法,为食品分析提供了快速、无损、经济高效且环保的手段。然而,如果没有统计和创新的化学计量学方法的辅助,解释光谱数据,无论是以信号(指纹)还是图像的形式,都可能很复杂。这些方法涉及预处理、探索性分析、变量选择、回归、分类和数据整合等多个步骤。它们对于提取相关信息和有效处理光谱数据的复杂性至关重要。本综述旨在探讨、讨论和审视在食品产品应用和分析趋势背景下,关于先进光谱技术和化学计量工具的最新研究。此外,它侧重于光谱数据处理、模型构建、数据解释以及统计和化学计量方法在定性和定量分析中的一般应用的实际方面。通过探索光谱技术的进展及其与化学计量工具的整合,本综述为这些分析方法在食品工业中的潜在应用和未来方向提供了有价值的见解。它强调了在食品分析领域高效数据处理、模型开发以及统计和化学计量方法实际应用的重要性。