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应用电子鼻和顶空固相微萃取/气相色谱-质谱联用技术测定新鲜墨西哥奶酪中的挥发性有机化合物。

Application of an Electronic Nose and HS-SPME/GC-MS to Determine Volatile Organic Compounds in Fresh Mexican Cheese.

作者信息

Lee-Rangel Héctor Aarón, Mendoza-Martinez German David, Diaz de León-Martínez Lorena, Relling Alejandro Enrique, Vazquez-Valladolid Anayeli, Palacios-Martínez Monika, Hernández-García Pedro Abel, Chay-Canul Alfonso Juventino, Flores-Ramirez Rogelio, Roque-Jiménez José Alejandro

机构信息

Centro de Biociencias, Universidad Autónoma de San Luis Potosí, Carretera Federal 57 km 14.5, Ejido Palma de la Cruz, Soledad de Graciano Sánchez 78321, San Luis Potosí, Mexico.

Departamento de Producción Animal, Universidad Autónoma Metropolitana-Xochimilco, CDMX, Mexico City 04960, Mexico.

出版信息

Foods. 2022 Jun 25;11(13):1887. doi: 10.3390/foods11131887.

DOI:10.3390/foods11131887
PMID:35804703
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9265309/
Abstract

Electronic devices have been used to describe chemical compounds in the food industry. However, there are different models and manufacturers of these devices; thus, there has been little consistency in the type of compounds and methods used for identification. This work aimed to determine the applicability of electronic nose (e-nose) Cyroanose 320 to describe the differentiation of volatile organic compounds (VOCs) in fresh Mexican cheese (F-MC) formulated with milk from two different dairy cattle breeds. The VOCs were described using a device manufactured by Sensigent and Solid-Phase Micro-extraction (SPME) coupled to GC-MS as a complementary method. The multivariate principal components analysis (PCA) and the partial least squares discriminant analysis (PLS-DA) were used to describe the relationships of VOCs to electronic nose data, sensory data, and response levels. In addition, variable importance in projection (VIP) was performed to characterize the e-nose signals to the VOCs. The e-nose distinguishes F-MC prepared with milk from two dairy breeds. Sensor number 31 correlated with carboxylic acids most in F-MC from Jersey milk. The HS-SPME/GC-MS identified eighteen VOCs in F-MC made with Holstein milk, while only eleven VOCs were identified for F-MC made with Jersey milk. The more significant peaks in both chromatogram analyses were Propanoic acid, 2-methyl-, 1-(1,1-dimethylethyl)-2-methyl-1,3-propanediyl ester in cheese made from Holstein milk and Propanoic acid, 2-methyl-, 3-hydroxy-2,4,4-trimethylpentyl ester in Jersey milk cheese. Both compounds are considered essential carboxylic acids in the dairy industry. Thus, sensor 31 in the electronic nose Cyranose 320 increased its response by essential carboxylic acids identified by HS-SPME/GC-MS as a complementary method. The e-nose Cyranose 320 is potentially helpful for evaluating fresh Mexican cheese authentication independent of cows' milk samples from different breeds.

摘要

电子设备已被用于食品工业中描述化合物。然而,这些设备有不同的型号和制造商;因此,用于识别的化合物类型和方法几乎没有一致性。这项工作旨在确定电子鼻(e-nose)Cyroanose 320用于描述由两种不同奶牛品种的牛奶制成的新鲜墨西哥奶酪(F-MC)中挥发性有机化合物(VOCs)差异的适用性。使用Sensigent制造的设备描述VOCs,并将固相微萃取(SPME)与气相色谱-质谱联用(GC-MS)作为补充方法。多元主成分分析(PCA)和偏最小二乘判别分析(PLS-DA)用于描述VOCs与电子鼻数据、感官数据和响应水平之间的关系。此外,进行了投影变量重要性(VIP)分析以表征电子鼻对VOCs的信号。电子鼻能够区分由两种奶牛品种的牛奶制成的F-MC。31号传感器与泽西牛奶制成的F-MC中的羧酸相关性最强。顶空固相微萃取/气相色谱-质谱联用(HS-SPME/GC-MS)在荷斯坦牛奶制成的F-MC中鉴定出18种VOCs,而在泽西牛奶制成的F-MC中仅鉴定出11种VOCs。两种色谱分析中较显著的峰分别是荷斯坦牛奶制成的奶酪中的2-甲基丙酸、1-(1,1-二甲基乙基)-2-甲基-1,3-丙二醇酯,以及泽西牛奶制成的奶酪中的2-甲基丙酸、3-羟基-2,4,4-三甲基戊酯。这两种化合物在乳制品工业中都被认为是重要的羧酸。因此,作为补充方法,电子鼻Cyranose 320中的31号传感器对HS-SPME/GC-MS鉴定出的重要羧酸的响应增强。电子鼻Cyranose 320对于评估新鲜墨西哥奶酪的真伪具有潜在帮助,且与不同品种奶牛的牛奶样本无关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/f5a0d00b7fb5/foods-11-01887-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/b8f9b2525efc/foods-11-01887-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/29b08f8cb188/foods-11-01887-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/c1054f62f3b5/foods-11-01887-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/30355d83ad8b/foods-11-01887-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/c6b7da738366/foods-11-01887-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/d45a8962d785/foods-11-01887-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/e7dc2398999f/foods-11-01887-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/4d1d301ae34b/foods-11-01887-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/f5a0d00b7fb5/foods-11-01887-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/b8f9b2525efc/foods-11-01887-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/29b08f8cb188/foods-11-01887-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/c1054f62f3b5/foods-11-01887-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/30355d83ad8b/foods-11-01887-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/c6b7da738366/foods-11-01887-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/d45a8962d785/foods-11-01887-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/e7dc2398999f/foods-11-01887-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/4d1d301ae34b/foods-11-01887-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10c3/9265309/f5a0d00b7fb5/foods-11-01887-g009.jpg

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