Application of a novel S3 nanowire gas sensor device in parallel with GC-MS for the identification of Parmigiano Reggiano from US and European competitors

被引：11

作者：

Abbatangelo, Marco ^{[1
]}

Nunez-Carmona, Estefania ^{[1
]}

Sberveglieri, Veronica ^{[2
,3
]}

机构：

[1] Univ Brescia, Dept Informat Engn, Via Branze 38, I-25123 Brescia, Italy

[2] CNR IBBR, Inst Biosci & Bioresources, Via Madonna del Piano 10, I-50019 Sesto Fiorentino, FI, Italy

[3] Nano Sensor Syst Srl, Via Branze 38, I-25123 Brescia, Italy

来源：

JOURNAL OF FOOD ENGINEERING | 2018年 / 236卷

关键词：

Nanowire sensors; S3; GC-MS; Parmigiano reggiano; Discrimination; PLS-DA; SOLID-PHASE MICROEXTRACTION; ELECTRONIC NOSE; AROMA COMPOUNDS; MASS SPECTROMETRY; PARMESAN CHEESE; PLS-DA; SPECTROSCOPY; HEADSPACE; MILK; MICROORGANISMS;

D O I：

10.1016/j.jfoodeng.2018.05.009

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

Parmigiano Reggiano is a typical Italian product known all over the world. Appreciated for its qualities, it is also one of the most counterfeit foods. To avoid this, two different techniques has been used: GC-MS with SPME and S3 gas sensor. With the first one, characteristic VOCs of different cheeses has been found. The most present classes are alcohols, aldehydes, hydrocarbons, esters and ketones, for a total of 58 compounds. Statistical analysis has shown that only 6 of them could be used to distinguish between Parmigiano Reggiano and its competitors. Instead, S3 is a new, rapid, economic and user-friendly approach. Assessing the variation of sensors resistances, it has been possible to discriminate between different kind of cheeses with an accuracy higher than 80%. Data analysis was performed considering PLS to have a visual representation of samples, the SFS algorithm for features selection and PLS-DA as classifier.

引用

页码：36 / 43

页数：8