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Dairy Science & Technology

, Volume 92, Issue 4, pp 321–333 | Cite as

Application of HS-SPME–GC-MS-derived variables for monitoring ripening-induced changes in cheese volatile compounds

  • Nebojša P. Milosavljević
  • Polina D. Blagojević
  • Dragiša S. Savić
  • Niko S. RadulovićEmail author
Original Paper

Abstract

Headspace solid-phase microextraction–gas chromatography-mass spectrometry (HS-SPME–GC-MS) and multivariate statistical analysis (MVA) are widely employed in the analyses/comparison of cheese volatiles. One shortcoming of this approach is that the SPME fiber-coat polarity has a significant effect on the adsorption of volatiles and thus, on the results of MVA. The aim of this study was to test the applicability of different sets of MVA variables, obtained from HS-SPME–GC-MS experiments using the non-polar polydimethylsiloxane (PDMS) and the polar polyacrylate (PA) fibers, in the profiling of cheese volatile compounds and tracking ripening-induced changes. The volatile profiles and ripening-induced changes of two different types of Pasta-Filata “Pirotski kačkavalj” cheese (prepared from raw ewe’s or cow’s milk) were assessed at four different stages of ripening (1, 5, 20, and 30 days). The HS-SPME–GC-MS–MVA results showed that the distribution of volatile compounds into classes gives valuable information concerning cheese type and ripening phase. The extraction with a PA fiber gives a more realistic cheese volatile profile when the relative ratio of the constituent classes is in question, whereas the PDMS fiber is better in recognizing the contribution/concentration of single dominant volatile compounds. For a better and more complete description/profiling of cheese volatiles, we propose the use of combined (transformed) variables that include the information obtained from both PA and PDMS extraction experiments.

Keywords

Volatile profiles Principal component analysis Agglomerative hierarchical cluster analysis Cheese ripening Pasta-Filata “Pirotski kačkavalj” cheese 

利用HS-SPME-GC-MS监测干酪成熟过程中挥发性化合物的变化

摘要

顶空固相微萃取-气质联用(HS-SPME-GC-MS)和多元统计分析(MVA)广泛应用于分析和比较干酪的挥发性化合物。该方法的一个缺点是SPME 纤维外套的极性对挥发性化合物的吸附影响较大,因此也影响了MVA分析的结果。本论文目的是应用不同组合的MVA变量,这些变量是通过HS-SPME-GC-MS实验并采用非极性聚二甲硅氧烷(PDMS)和极性聚丙烯酸酯(PA)纤维萃取跟踪干酪成熟过程中引发的挥发性化合物变化。分析了两种不同类型的Pasta-Filata 和“Pirotski kačkavalj干酪(来自羊奶和牛奶)在四个不同成熟阶段(1,5,20和30 d)所产生挥发性化合物的变化。HS-SPME-GC-MS-MVA实验结果对干酪的类型和成熟阶段挥发性化合物的分布给出了非常重要的信息。利用PA纤维萃取对需要讨论干酪中各种挥发性化合物组分的相对比例给出了更理想的结果。然而PDMS纤维萃取对了解单个主要的挥发性化合物的分布和浓度方面更有优势。为了更好更全面的描述干酪的挥发性化合物,建议将PA和PDMS两种萃取实验的信息结合起来分析干酪成熟过程中挥发性化合物的变化。

关键词

挥发性成分 主成分分析 凝聚层次聚类分析 干酪的成熟 帕斯塔费拉塔乳酪 

Notes

Acknowledgments

The research has been supported by the Ministry of Education and Science of Serbia (Project 172061).

Supplementary material

13594_2012_70_MOESM1_ESM.doc (466 kb)
ESM 1 (DOC 466 kb)

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Copyright information

© INRA and Springer-Verlag, France 2012

Authors and Affiliations

  • Nebojša P. Milosavljević
    • 1
  • Polina D. Blagojević
    • 2
  • Dragiša S. Savić
    • 3
  • Niko S. Radulović
    • 2
    Email author
  1. 1.College of Agriculture and Food TechnologyProkupljeSerbia
  2. 2.Department of Chemistry, Faculty of Science and MathematicsUniversity of NišNišSerbia
  3. 3.Faculty of TechnologyUniversity of NišLeskovacSerbia

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