@article{WANG2024, 
author = {Haitao WANG and Xiao SHEN and Lingyun YAO and Min SUN and Huatian WANG and Tao FENG},
title = {Analysis of Volatile Compounds in Three Milks with Different Fat Contents by GC × GC-TOFMS},
year = {2024},
journal = {Journal of Dairy Science and Technology},
volume = {47},
number = {1},
pages = {26-32},
keywords = {non-fat milk, flavor, headspace solid phase microextraction in combination with comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry, partial least squares discriminant analysis},
url = {https://www.sciopen.com/article/10.7506/rykxyjs1671-5187-20240415-021},
doi = {10.7506/rykxyjs1671-5187-20240415-021},
abstract = {In this study, headspace solid phase microextraction in combination with comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (HS-SPME-GC × GC-TOFMS) was used to analyze the volatile compounds in whole (WM), low-fat milk (LFM) and non-fat milk (NFM). Altogether 49 volatile compounds were detected, among which methyl ketones with odd-numbered carbon chain lengths such as 2-nonanone and 2-undecanone constituted the main flavor compounds of WM. Using partial least squares discriminant analysis (PLS-DA), a model which could well differentiate among the 3 milks was developed and it was found to have good variance and cross-validation predictive ability. Nine differential key aroma compounds were identified using variable importance in the projection (VIP) > 1, P ≤ 0.05 and their contents ≥ 1% as criteria, which may be the main factors contributing to the differences in flavor profiles among the 3 milks. The heatmap from clustering analysis indicated that NFM had poor sensory performance due to the presence of off-flavor compounds (e.g., hexadecanal), whereas WM and LFM contained more aroma compounds, having a full and rich sensory aroma profile. The HS-SPME-GC × GC-TOFMS method can provide theoretical guidance for dairy flavor improvement and dairy flavoring formulation.}
}