Wang Songlin, Liu Qingwei, Jia Wenshen, Lin Yawen, Bi Liang, Chen Dongdong, Lv Chi
College of Mechanical Engineering and Automation, Liaoning University of Technology, Jinzhou, Liaoning 121001, China.
Institute of Quality Standard and Testing Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China.
J Agric Food Chem. 2025 Jun 25;73(25):15480-15490. doi: 10.1021/acs.jafc.5c02460. Epub 2025 Jun 11.
Hyperspectral imaging (HSI), as a nondestructive testing method integrating spectral analysis and spatial imaging, has shown unique advantages in the dynamic monitoring of the core chemical components of fruits. In this paper, we focus on the application of HSI in the detection of core components of fruits, such as carbohydrates, organic acids, water, and polyphenols, and systematically analyze its chemical response mechanism and technical bottleneck. By comparison of the spectral differences of chemical bond vibration and electron jump features, the dynamic correlation between HSI and quality parameters such as sugar and acidity is revealed. Then, the problems and challenges faced by hyperspectral imaging technology in the nondestructive detection of the core chemical composition of fruits in terms of data processing, environmental interference, and equipment cost are discussed, and conclusions and outlook of the potential and prospect of hyperspectral imaging technology in the detection of the core chemical composition of fruits are presented to provide a powerful technical support for the detection of the core chemical composition of fruits.
高光谱成像（HSI）作为一种将光谱分析与空间成像相结合的无损检测方法，在水果核心化学成分的动态监测中显示出独特优势。本文聚焦于高光谱成像在水果核心成分如碳水化合物、有机酸、水分和多酚检测中的应用，系统分析其化学反应机理和技术瓶颈。通过比较化学键振动和电子跃迁特征的光谱差异，揭示了高光谱成像与糖度和酸度等品质参数之间的动态相关性。然后，讨论了高光谱成像技术在水果核心化学成分无损检测中在数据处理、环境干扰和设备成本方面面临的问题与挑战，并给出了高光谱成像技术在水果核心化学成分检测中的潜力和前景的结论与展望，为水果核心化学成分检测提供有力的技术支持。
