Preparation of a highly-sensitive intelligent label based on MOFs and its application in visual monitoring of pork freshness

To achieve non-destructive and real-time monitoring of pork freshness, an intelligent indicator label was developed using nanoparticles of cyclodextrin metal–organic frameworks (CD-MOFs) loaded with curcumin (Cur), referred to as CC-MOFs. The study investigated its application in the visual monitoring of pork freshness. The microstructures, chemical compositions, and thermal stability of CC-MOFs, as well as the responsiveness of the intelligent indicator label, were explored. Additionally, the feasibility of the indicator label for monitoring pork freshness was studied. The results demonstrated that in the CC-MOFs particles prepared via the green synthesis method, Cur was successfully embedded into the CD-MOFs pores via hydrogen bonding. This induced local reconstruction of the MOF framework, forming a porous structure with a rough surface, which significantly improved color persistence and stability. The CC-MOFs label responded sensitively to volatile ammonia, performing significantly better than the pure Cur label. In the pork storage model, the CC-MOFs label changed from khaki to orange-red and then to reddish-brown. The color changes were highly correlated with spoilage indicators such as TVB-N value, pH value, and electrical conductivity, and were consistent with electronic nose detection results. In summary, this intelligent indicator label can accurately distinguish three freshness levels of pork, providing a non-toxic and efficient visual solution for real-time food freshness monitoring.

Authors

Institutions

Publication Details

Journal
Food Production Processing and Nutrition
Published
2026-04-16
DOI
https://doi.org/10.1186/s43014-026-00383-y
Primary Topic
Nanocomposite Films for Food Packaging
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Preparation of a highly-sensitive intelligent label based on MOFs and its application in visual monitoring of pork freshness

Qianshuo Shao, Xinyao Quan, Y ZHAO, Yuning Wang et al.
Food Production Processing and Nutrition
Nanocomposite Films for Food Packaging
article

Preparation of a highly-sensitive intelligent label based on MOFs and its application in visual monitoring of pork freshness

Qianshuo Shao, Xinyao Quan, Y ZHAO, Yuning Wang, Siyao Sui, Haocong Li, Jing Pei, Tian Zhong
article en

Abstract

To achieve non-destructive and real-time monitoring of pork freshness, an intelligent indicator label was developed using nanoparticles of cyclodextrin metal–organic frameworks (CD-MOFs) loaded with curcumin (Cur), referred to as CC-MOFs. The study investigated its application in the visual monitoring of pork freshness. The microstructures, chemical compositions, and thermal stability of CC-MOFs, as well as the responsiveness of the intelligent indicator label, were explored. Additionally, the feasibility of the indicator label for monitoring pork freshness was studied. The results demonstrated that in the CC-MOFs particles prepared via the green synthesis method, Cur was successfully embedded into the CD-MOFs pores via hydrogen bonding. This induced local reconstruction of the MOF framework, forming a porous structure with a rough surface, which significantly improved color persistence and stability. The CC-MOFs label responded sensitively to volatile ammonia, performing significantly better than the pure Cur label. In the pork storage model, the CC-MOFs label changed from khaki to orange-red and then to reddish-brown. The color changes were highly correlated with spoilage indicators such as TVB-N value, pH value, and electrical conductivity, and were consistent with electronic nose detection results. In summary, this intelligent indicator label can accurately distinguish three freshness levels of pork, providing a non-toxic and efficient visual solution for real-time food freshness monitoring.

Food Production Processing and NutritionVol. 8(1)
Macau University of Science and Technology (MO), Changchun Observatory (CN), Suzhou Academy of Agricultural Sciences (CN)
Government of Jiangsu Province
Openalex Percentile: Top 21%
Nanocomposite Films for Food Packaging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.