Recently, researchers from Food Nutrition and Functional Foods Innovation Team at the Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences (IFST-CAAS), published a systematic review on the design of metal-organic framework, or MOF, based composite sensing materials and their applications in the selective recognition and visual detection of nitrogen-containing compounds in food spoilage and environmental systems. The paper was published in Coordination Chemistry Reviews (JCR Q1, IF = 23.5). Qian Luo, a doctoral student, is the first author of the paper. Prof. Jinhui Zhou and Prof. Fengzhong Wang, from IFST-CAAS, together with Xinran Wang, associate researcher from the Institute of Quality Standards and Testing Technology for Agro-Products, Beijing Academy of Agriculture and Forestry Sciences, are the corresponding authors.

Nitrogen-containing compounds such as total volatile basic nitrogen and biogenic amines are not only important indicators of spoilage in high-protein foods, but also common pollutants in environmental systems. In practical detection, two major challenges remain. First, different amines often have highly similar molecular size, polarity, and functional group characteristics, which can easily lead to cross-interference. Second, high-humidity conditions are common in food packaging and complex environments, and the competitive adsorption of water molecules at active sites can reduce both recognition accuracy and signal stability.

This review systematically examines the design principles and sensing mechanisms of MOFs and MOF-based composite sensing materials. At the molecular recognition level, it shows how MOF materials use open metal sites, organic ligands, and pore environments to selectively capture target molecules through hydrogen bonding, acid-base interactions, electrostatic attraction, and coordination. At the signal transduction level, it clarifies the full sensing pathway, from precise pore screening of target molecules and enhanced specific capture at open sites to the conversion of interfacial interactions into colorimetric, fluorescent, or electrochemical signals. The review also highlights the role of narrow pore windows and well-defined pore sizes in achieving efficient molecular sieving. In terms of intelligent applications, the authors address key bottlenecks, including low material development efficiency, limited performance in complex systems, and insufficient device integration, and propose a systematic route toward data-driven smart material development and integrated sensor-recognition design.

This review deepens current understanding of the structure-regulation principles governing MOF-based sensing materials and provides both theoretical insight and practical guidance for trace pollutant detection and the development of smart sensing devices. It is expected to support advances in early warning of food spoilage and intelligent, precise monitoring of nitrogen-containing pollutants in the environment.

This work was supported by the National Natural Science Foundation of China

Article link: https://doi.org/10.1016/j.ccr.2026.217912