Machine learning-driven smart colorimetric sensor arrays for food freshness monitoring: Advances, challenges, and future prospects
Authors:
- 16 July 2026
- journal article
- review article
- Published by Elsevier in Food Chemistry
- Vol. 525 (Pt 2) , 150455
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (22278421)
This publication has 80 references indexed in Scilit:
- Frost-resistant hydrogel colorimetric sensing array for accurate detection of foodborne pathogens in cold chain systemsBiosensors and Bioelectronics, 2024
- A colorimetric paper based on curcumin-loaded CD-MOFs and CNFs for visual monitoring of strawberry freshnessChemical Engineering Journal, 2024
- Nanozyme-based colorimetric sensor arrays coupling with smartphone for discrimination and “segmentation-extraction-regression” deep learning assisted quantification of flavonoidsBiosensors and Bioelectronics, 2024
- Inspired by human olfactory system: Deep-learning-assisted portable chemo-responsive dye-based odor sensor array for the rapid sensing of shrimp and fish freshnessChemical Engineering Journal, 2024
- Colorimetric sensor array based on Au2Pt nanozymes for antioxidant nutrition quality evaluation in foodBiosensors and Bioelectronics, 2023
- A novel colorimetric sensor array for real-time and on-site monitoring of meat freshnessAnalytical and Bioanalytical Chemistry, 2022
- Pattern-based colorimetric sensor array to monitor food spoilage using automated high-throughput analysisBiosensors and Bioelectronics, 2022
- Portable Food‐Freshness Prediction Platform Based on Colorimetric Barcode Combinatorics and Deep Convolutional Neural NetworksAdvanced Materials, 2020
- Anaerobic digestion of food waste – Challenges and opportunitiesBioresource Technology, 2018
- Simple on package indicator label for monitoring of grape ripening process using colorimetric pH sensorJournal of Food Measurement and Characterization, 2017