As a key link in the management of grain storage, quality inspection and evaluation has always been a hot research field of much concern among researchers. It plays a vital role in ensuring safe storage and product processing of grain. In order to better carry out relevant work in the future, this paper reviews the progress in research on conventional methods for the detection and evaluation of stored grain quality based on optical, acoustic, dielectric, physicochemical properties and volatile substances, and it also summarizes the application of the current new detection techniques such as strong magnetic field, laser-induced breakdown spectroscopy, nuclear magnetic resonance spectroscopy and scanning electron microscopy in the quality evaluation of stored grains. In addition, it compares and analyzes and the advantages and disadvantages of these techniques. This review concludes with an outlook on future research directions.

As an important part of food quality management, the detection of food hazard factors and safety risk prediction have always been a research hotspot. In order to better carry out related work in the future, this article reviews research progress on conventional methods for the detection of food hazard factors, and introduces new methods for the detection of food hazard factors such as nanozymes, clustered regularly interspaced short palindromic repeats/CRISPR-associated proteins (CRISPR/Cas) sensors and nuclear magnetic resonance (NMR) spectroscopy and the application of new materials such as magnetic covalent organic frameworks in this field. Then, it summarizes the application of subjective weighting, machine learning and deep learning in food safety risk prediction. Finally, the advantages and disadvantages of each method are analyzed, and future research directions are discussed.