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基于植物性食品监测的超声诊断技术的机遇与挑战:原理、机器系统及应用策略

Opportunities and challenges of ultrasonic diagnostic techniques for plant-based food monitoring: principle, machine system, and application strategies.

作者信息

Yan Jing, Zhang Yingling, Jiao Zibin, Song Lifan, Wang Zhijun, Zhang Qing, Liu Yaowen, Qin Wen

机构信息

College of Food Science, Sichuan Agricultural University, Sichuan, People's Republic of China.

School of Biosystems and Food Engineering, University College Dublin, Belfield, Dublin, Ireland.

出版信息

Crit Rev Food Sci Nutr. 2024 Oct 25:1-20. doi: 10.1080/10408398.2024.2418891.

Abstract

Plant-based food consumption has increased substantially owing to its positive effects on human and global health. However, ensuring the quality and safety of plant-based foods remains a challenge. Diagnostic ultrasonic technology is widely used for rapid and nondestructive determination owing to its ability to penetrate optically opaque materials, strong directivity, rapid detection capabilities, low equipment costs, and ease of operation. This review provides a comprehensive understanding of diagnostic ultrasonic technology by summarizing the principles of food characterization, factors that influence detection accuracy and methods to mitigate their impact, composition of ultrasonic machine systems, and application of diagnostic ultrasound for monitoring plant-based foods. The detection principle of ultrasonic technology is based on empirical equations that establish a relationship between the ultrasonic and physicochemical indicators of food. To improve the detection accuracy, a compensation mechanism for the temperature and pressure should be established, measurement distances should be set in the far-field region, and liquid samples should be degassed. Furthermore, the sample platform design and the choice of detection mode depend on the nature of the food. Combining ultrasonic technology with machine learning techniques presents promising prospects for real-time process monitoring in the food and beverage industries.

摘要

由于植物性食品对人类健康和全球健康具有积极影响,其消费量已大幅增加。然而,确保植物性食品的质量和安全仍然是一项挑战。诊断超声技术因其能够穿透光学不透明材料、具有强方向性、检测速度快、设备成本低且操作简便等特点,而被广泛用于快速无损检测。本文综述通过总结食品特性表征原理、影响检测准确性的因素及减轻其影响的方法、超声机器系统的组成以及诊断超声在监测植物性食品方面的应用,全面介绍了诊断超声技术。超声技术的检测原理基于经验方程,该方程建立了食品超声指标与物理化学指标之间的关系。为提高检测准确性,应建立温度和压力补偿机制,测量距离应设置在远场区域,液体样品应进行脱气处理。此外,样品平台设计和检测模式的选择取决于食品的性质。将超声技术与机器学习技术相结合,在食品和饮料行业的实时过程监测方面具有广阔的前景。

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