Department of Analytical Chemistry, Faculty of Chemistry, Gdańsk University of Technology, 80-233 Gdańsk, Poland
Department of Chemical and Process Engineering, Faculty of Chemistry, Gdańsk University of Technology, 80-233 Gdańsk, Poland
Sensors (Basel). 2017 Nov 24;17(12):2715. doi: 10.3390/s17122715.
The steady increase in global consumption puts a strain on agriculture and might lead to a decrease in food quality. Currently used techniques of food analysis are often labour-intensive and time-consuming and require extensive sample preparation. For that reason, there is a demand for novel methods that could be used for rapid food quality assessment. A technique based on the use of an array of chemical sensors for holistic analysis of the sample's headspace is called electronic olfaction. In this article, a prototype of a portable, modular electronic nose intended for food analysis is described. Using the SVM method, it was possible to classify samples of poultry meat based on shelf-life with 100% accuracy, and also samples of rapeseed oil based on the degree of thermal degradation with 100% accuracy. The prototype was also used to detect adulterations of extra virgin olive oil with rapeseed oil with 82% overall accuracy. Due to the modular design, the prototype offers the advantages of solutions targeted for analysis of specific food products, at the same time retaining the flexibility of application. Furthermore, its portability allows the device to be used at different stages of the production and distribution process.
全球消费的稳步增长给农业带来了压力,可能导致食品质量下降。目前使用的食品分析技术通常劳动强度大、耗时耗力,需要进行广泛的样品制备。因此,人们需要新的方法来快速评估食品质量。一种基于使用数组化学传感器对样品顶空进行整体分析的技术称为电子嗅觉。本文描述了一种用于食品分析的便携式模块化电子鼻原型。使用 SVM 方法,可以 100%准确地对根据保质期分类的禽肉样本进行分类,也可以 100%准确地对根据热降解程度分类的油菜籽油样本进行分类。该原型还用于检测特级初榨橄榄油中掺入油菜籽油的情况,总体准确率为 82%。由于采用模块化设计,该原型具有针对特定食品分析的解决方案的优势,同时保持了应用的灵活性。此外,其便携性允许该设备在生产和分销过程的不同阶段使用。