China’s liquor industry continues to steadily expand and develop. The industry is currently transforming, shifting its focus from scale to quality and efficiency. This transformation is significantly increasing the demand for quality and safety testing. Currently, the testing system relies mainly on manual operation or traditional mechanical equipment. Technical bottlenecks include low testing efficiency, a significant imbalance in the cost–benefit ratio, and difficulty meeting the modern industry’s dual technical index requirements of testing accuracy and systematicity. In this context, the innovative research and development of new detection technology is key to promoting technological upgrades in the liquor industry. Near-infrared (NIR) spectroscopy is a core, competitive analytical method for non-destructive wine quality testing due to its technical advantages, such as non-destructive analysis, real-time online detection, and the absence of sample pretreatment requirements. This study systematically elaborates on the optical principle and detection mechanism of NIR spectroscopy and explores the application paradigm of chemometrics in spectral data analysis. This study covers the quantitative analysis of alcoholic strength, the determination of main ingredient content (sugar, acidity, esters, etc.), the construction of trace flavor substance fingerprints, the authentication and origin tracing of alcoholic products, and the monitoring of wine aging quality dynamics, among other key technology areas. Additionally, we review the fusion and innovation trends of artificial intelligence and big data technology, the R&D progress of miniaturized testing equipment, and the technical bottlenecks of spectral modeling and algorithm optimization. We also make scientific predictions about the evolution path of this technology and its industrial application prospects.
Qi et al. (2025) studied this question.