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使用近红外光谱和化学计量学检测粉末状食品中的掺假物:最新进展、挑战与未来展望

Detection of Adulterants in Powdered Foods Using Near-Infrared Spectroscopy and Chemometrics: Recent Advances, Challenges, and Future Perspectives.

作者信息

Vera William, Salvador-Reyes Rebeca, Quispe-Santivañez Grimaldo, Kemper Guillermo

机构信息

Programa de Doctorado en Ingeniería Agroindustrial Mención Transformación Avanzada de Granos y Tubérculos Andinos, Universidad Nacional del Santa, Nuevo Chimbote 02711, Ancash, Peru.

Facultad de Ingeniería, Universidad Tecnológica del Perú, Lima 150101, Lima, Peru.

出版信息

Foods. 2025 Sep 13;14(18):3195. doi: 10.3390/foods14183195.

DOI:10.3390/foods14183195
PMID:41008169
Abstract

Powdered foods are matrices transformed into fine, loose solid particles through dehydration and/or milling, which enhances stability, storage, and transport. Due to their high commercial value and susceptibility to fraudulent practices, detecting adulterants in powdered foods is essential for ensuring food safety and protecting consumer health and the economy. Food fraud in powdered products, such as spices, cereals, dairy-based powders, and dietary supplements, poses an increasing risk to public health and consumer trust. These products were selected as representative matrices due to their high nutritional and economic relevance, which also makes them more susceptible to adulteration and hidden potential health risks from hidden contaminants. Recent studies highlight the potential of spectroscopic techniques combined with chemometrics as rapid, non-destructive, and cost-effective tools for authentication. This narrative review synthesizes recent literature (2020-2025) on the application of near-infrared (NIR) spectroscopy combined with chemometric techniques for adulterant detection in powdered foods. Advances in spectral preprocessing, variable selection, classification, and regression models are discussed alongside the most common adulterants and their nutritional and toxicological implications. Furthermore, the applicability of portable versus benchtop NIR devices is compared. The main contribution of this review lies in critically analyzing methodological frameworks, mapping current gaps, and identifying emerging trends, such as digital integration, self-adaptive chemometric models, and real-time on-site authentication, positioning NIR spectroscopy as a promising tool for food authentication and quality control.

摘要

粉末状食品是通过脱水和/或研磨转化为细小、松散固体颗粒的基质,这提高了其稳定性、储存性和运输性。由于其高商业价值以及易受欺诈行为影响,检测粉末状食品中的掺假物对于确保食品安全、保护消费者健康和经济至关重要。粉末状产品中的食品欺诈,如香料、谷物、乳基粉末和膳食补充剂,对公众健康和消费者信任构成了越来越大的风险。由于这些产品具有很高的营养和经济相关性,因此被选为代表性基质,这也使它们更容易受到掺假以及隐藏污染物带来的潜在健康风险的影响。最近的研究强调了光谱技术与化学计量学相结合作为快速、无损且经济高效的认证工具的潜力。这篇叙述性综述综合了近期文献(2020 - 2025年)中关于近红外(NIR)光谱结合化学计量技术在粉末状食品掺假物检测中的应用。讨论了光谱预处理、变量选择、分类和回归模型的进展,以及最常见的掺假物及其营养和毒理学影响。此外,还比较了便携式和台式近红外设备的适用性。本综述的主要贡献在于批判性地分析方法框架、梳理当前差距并识别新兴趋势,如数字集成、自适应化学计量模型和实时现场认证,将近红外光谱定位为食品认证和质量控制的一种有前景的工具。

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Research on Rapid and Non-Destructive Detection of Coffee Powder Adulteration Based on Portable Near-Infrared Spectroscopy Technology.基于便携式近红外光谱技术的咖啡粉掺假快速无损检测研究
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Near-infrared spectroscopy combined with support vector machine for the identification of Tartary buckwheat (Fagopyrum tataricum (L.) Gaertn) adulteration using wavelength selection algorithms.基于波长选择算法的近红外光谱结合支持向量机鉴别鞑靼荞麦(Fagopyrum tataricum (L.) Gaertn)掺伪
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