Carbon dots based ratiometric fluorescent sensing platform for food safety.

Carbon dots fluorescent detection food safety nanohybrid nanosensor ratiometric fluorescence

Journal

Critical reviews in food science and nutrition
ISSN: 1549-7852
Titre abrégé: Crit Rev Food Sci Nutr
Pays: United States
ID NLM: 8914818

Informations de publication

Date de publication:
2022
Historique:
pubmed: 3 9 2020
medline: 25 12 2021
entrez: 3 9 2020
Statut: ppublish

Résumé

Food safety has become a major global concern and the rapid detection of food nutritional ingredients and contaminants has aroused much more attention. Nanomaterials-based fluorescent sensing holds great potential in designing highly sensitive and selective detection strategies for food safety analysis. Carbon dots (CDs) possess tremendous prospects in fluorescent sensing food ingredients and contaminants due to their superior properties of chemical and photostability, highly fluorescence with tunability, and no/low-toxicity. Numerous endeavors are demanded to contribute to overcoming the challenge of lower sensitivity and selectivity of the sensors interfered by various components in intricate food matrices to ensure food safety and human health. Nanohybrid CDs based ratiometric fluorescent sensing with self-calibration is regarded as an efficient strategy for the CDs based sensors for the specific recognition of target analyte in the food matrices. This work is devoted to reviewing the development of nanohybrid CDs based ratiometric fluorescent sensing platform and the perspectives of the platform for food safety. The applications of nanohybrid CDs in sensing are summarized and the sensing mechanisms are briefly discussed.

Identifiants

pubmed: 32876496
doi: 10.1080/10408398.2020.1814197
doi:

Substances chimiques

Fluorescent Dyes 0
Carbon 7440-44-0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

244-260

Auteurs

Yong Han (Y)

College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi, PR China.

Weixia Yang (W)

College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi, PR China.

Xueli Luo (X)

College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi, PR China.

Xie He (X)

College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi, PR China.

Haiping Zhao (H)

College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi, PR China.

Wenzhi Tang (W)

College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi, PR China.

Tianli Yue (T)

College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi, PR China.
Laboratory of Quality & Safety Risk Assessment for Agro-products (Yangling), Ministry of Agriculture, Yangling, Shaanxi, PR China.

Zhonghong Li (Z)

College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi, PR China.
Laboratory of Quality & Safety Risk Assessment for Agro-products (Yangling), Ministry of Agriculture, Yangling, Shaanxi, PR China.

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Classifications MeSH