Bonah Ernest, Huang Xingyi, Aheto Joshua Harrington, Osae Richard
1School of Food and Biological Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang, 212013 Jiangsu People's Republic of China.
Laboratory Services Department, Food and Drugs Authority, P. O. Box CT 2783, Cantonments - Accra, Ghana.
J Food Sci Technol. 2020 Jun;57(6):1977-1990. doi: 10.1007/s13197-019-04143-4. Epub 2019 Nov 5.
Food safety issues across the global food supply chain have become paramount in promoting public health safety and commercial success of global food industries. As food regulations and consumer expectations continue to advance around the world, notwithstanding the latest technology, detection tools, regulations and consumer education on food safety and quality, there is still an upsurge of foodborne disease outbreaks across the globe. The development of the Electronic nose as a noninvasive technique suitable for detecting volatile compounds have been applied for food safety and quality analysis. Application of E-nose for pathogen detection has been successful and superior to conventional methods. E-nose offers a method that is noninvasive, fast and requires little or no sample preparation, thus making it ideal for use as an online monitoring tool. This manuscript presents an in-depth review of the application of electronic nose (E-nose) for food safety, with emphasis on classification and detection of foodborne pathogens. We summarise recent data and publications on foodborne pathogen detection (2006-2018) and by E-nose together with their methodologies and pattern recognition tools employed. E-nose instrumentation, sensing technologies and pattern recognition models are also summarised and future trends and challenges, as well as research perspectives, are discussed.
全球食品供应链中的食品安全问题对于促进公众健康安全和全球食品行业的商业成功至关重要。尽管有最新技术、检测工具、法规以及关于食品安全和质量的消费者教育,但随着世界各地食品法规和消费者期望的不断提高,全球食源性疾病暴发事件仍呈上升趋势。电子鼻作为一种适用于检测挥发性化合物的非侵入性技术已被应用于食品安全和质量分析。电子鼻在病原体检测方面的应用已取得成功且优于传统方法。电子鼻提供了一种非侵入性、快速且几乎不需要或无需样品制备的方法,因此非常适合用作在线监测工具。本文对电子鼻在食品安全中的应用进行了深入综述,重点是食源性病原体的分类和检测。我们总结了近期(2006 - 2018年)关于食源性病原体检测以及电子鼻检测的数据和出版物,以及它们所采用的方法和模式识别工具。还总结了电子鼻仪器、传感技术和模式识别模型,并讨论了未来趋势、挑战以及研究展望。