Optimization and Validation of a Headspace Solid-Phase Microextraction with Comprehensive Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometric Detection for Quantification of Trace Aroma Compounds in Chinese Liquor (Baijiu).

The detection of trace aroma compounds in samples with complex matrices such as Chinese liquor (Baijiu) requires a combination of several methods, which makes the analysis process very complicated. Therefore, a headspace solid-phase microextraction (HS-SPME) method coupled with two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) was developed for the quantitation of a large number of trace compounds in Baijiu. Optimization of extraction conditions via a series of experiments revealed that dilution of the alcohol content of 8 mL of Baijiu to 5%, followed by the addition of 3.

Three Extraction Methods in Combination with GC×GC-TOFMS for the Detailed Investigation of Volatiles in Chinese Herbaceous Aroma-Type Baijiu.

In this study, the detailed volatile compositions of Chinese herbaceous aroma-type Baijiu (HAB) were characterized by comprehensive two-dimensional gas chromatography-time of flight mass spectrometry (GC×GC-TOFMS). A total of 606 compounds were tentatively identified by similarity, mass spectral data, and retention indices, among which 247 compounds were positively verified by authentic standards. Esters were present in higher numbers (179), followed by aldehydes and ketones (111), and alcohols (81).

Emotion Recognition Based on Multichannel Physiological Signals with Comprehensive Nonlinear Processing.

Multichannel physiological datasets are usually nonlinear and separable in the field of emotion recognition. Many researchers have applied linear or partial nonlinear processing in feature reduction and classification, but these applications did not work well. Therefore, this paper proposed a comprehensive nonlinear method to solve this problem.