Volatiles Composition and Antimicrobial Activities of Areca Nut Extracts Obtained by Simultaneous Distillation–Extraction and Headspace Solid-Phase Microextraction

The volatile components of areca nuts were isolated by headspace solid-phase microextraction (HS-SPME, DVB/CAR/PDMS fiber extraction) and simultaneous hydrodistillation–extraction (SHDE) and analyzed by gas chromatography/mass spectrometry. Furthermore, all SHDE fractions were tested for antimicrobial activity using the disk diffusion method on nine Gram-negative and Gram-positive bacteria (Bacillus subtilis, Enterococcus faecalis, Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, Streptococcus agalactiae, Streptococcus canis, Streptococcus pyogenes, and Candida albicans). In total, 98 compounds (mainly alcohols, carbonyl compounds, fatty acids, esters, terpenes, terpenoids, and aliphatic hydrocarbons) were identified in SHDE fractions and by using SPME extraction Fatty acids were the main group of volatile constituents detected in all types of extracts. The microorganism most sensitive to the extract of the areca nut was Streptococcus canis. The results can provide essential information for the application of different treatments of areca nuts in the canning industry or as natural antibiotics.

Method Validation and Evaluation of Safrole Persistence in Cowpea Beans Using Headspace Solid-Phase Microextraction and Gas Chromatography

Bioinsecticides are regarded as important alternatives for controlling agricultural pests. However, few studies have determined the persistence of these compounds in stored grains. This study aimed at optimizing and validating a fast and effective method for extraction and quantification of residues of safrole (the main component of Piper hispidinervum essential oil) in cowpea beans. It also sought to assess the persistence of this substance in the grains treated by contact and fumigation. The proposed method used headspace solid-phase microextraction (HS-SPME) and gas chromatography with a flame ionization detector (GC/FID). Factors such as temperature, extraction time and type of fiber were assessed to maximize the performance of the extraction technique. The performance of the method was appraised via the parameters selectivity, linearity, limit of detection (LOD), limit of quantification (LOQ), precision, and accuracy. The LOD and LOQ of safrole were 0.0057 and 0.019 μg kg−1, respectively and the determination coefficient (R2) was >0.99. The relative recovery ranged from 99.26 to 104.85, with a coefficient of variation <15%. The validated method was applied to assess the persistence of safrole residue in grains, where concentrations ranged from 1.095 to 0.052 µg kg−1 (contact) and from 2.16 to 0.12 µg kg −1 (fumigation). The levels measured up from the fifth day represented less than 1% of the initial concentration, proving that safrole have low persistence in cowpea beans, thus being safe for bioinsecticide use. Thus, this work is relevant not only for the extraction method developed, but also for the possible use of a natural insecticide in pest management in stored grains.

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 3.0 g of NaCl and subsequent SPME extraction with DVB/CAR/PDMS fiber coating over 45 min at 45 °C was the most suitable. To check the matrix effects, various model Baijiu matrices were investigated in detail. The quantitative method was established through an optimized model synthetic solution, which can identify 119 aroma compounds (esters, alcohols, fatty acids, aldehydes and ketones, furans, pyrazines, sulfur compounds, phenols, terpenes, and lactones) in the Baijiu sample. The developed procedure provided high recovery (86.79–117.94%), good repeatability (relative standard deviation < 9.93%), high linearity (R2 > 0.99), and lower detection limits than reported methods. The method was successfully applied to study the composition of volatile compounds in different types of Baijiu. This research indicated that the optimized HS-SPME–GC×GC-TOFMS method was a valid and accurate procedure for the simultaneous determination of different types of trace compounds in Baijiu. This developed method will allow an improved analysis of other samples with complex matrices.