Colorimetric Sensor Arrays Technology in Food Quality and Safety Analysis

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Authors: Jie Cao, Ye Qiu, Yang Gao, Guanggui Cheng
Cited by: 1
References: 114

Abstract

Colorimetric sensor array (CSA) technology has been increasingly applied in food quality and safety analysis due to its advantages of low cost, visual readout, high sensitivity and suitability for on-site monitoring. However, a dedicated review that systematically integrates advances in sensing materials, application scenarios, analytical strategies and practical implementation of CSA technology for real food matrices is still lacking. This review summarizes the fundamental characteristics of CSA technology from the relevant studies published during the past 5 years. The literature was retrieved using keywords such as "colorimetric sensor array" and "food quality detection," and was filtered by predefined criteria prioritizing original research with verified sensing performance and practical validation in food applications. Emphasis is placed on the design and performance of sensitive materials. Furthermore, using a task-oriented framework, representative studies on CSA applications in food spoilage detection, adulteration identification, food composition analysis, contamination monitoring, food storage monitoring and volatile compound detection are discussed. In addition, the integration of CSA systems with portable devices, machine learning algorithms and intelligent detection platforms is critically analyzed. Finally, the detection characteristics, current challenges and future development prospects of CSA technology in food quality and safety analysis are highlighted. This review is expected to provide valuable insights for further development, optimization and practical implementation of intelligent CSA-based sensing systems in the food industry.

Fields of Study & Subjects

Advanced Chemical Sensor Technologies Spectroscopy and Chemometric Analyses Biosensors and Analytical Detection

Publication details

Journal / source
Micromachines
Publisher
MDPI AG
Volume
17
Issue
7
Pages
821–821
Publication date
9 July 2026
Language
EN