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Molecules ◽  
2019 ◽  
Vol 24 (18) ◽  
pp. 3377 ◽  
Author(s):  
Mohamed A. Farag ◽  
Asmaa M. Otify ◽  
Aly M. El-Sayed ◽  
Camilia G. Michel ◽  
Shaimaa A. ElShebiney ◽  
...  

Interest in developing coffee substitutes is on the rise, to minimizing its health side effects. In the Middle East, date palm (Phoenix dactylifera L.) pits are often used as a coffee substitute post roasting. In this study, commercially-roasted date pit products, along with unroasted and home-prepared roasted date pits, were subjected to analyses for their metabolite composition, and neuropharmacological evaluation in mice. Headspace SPME-GCMS and GCMS post silylation were employed for characterizing its volatile and non-volatile metabolite profile. For comparison to roasted coffee, coffee product was also included. There is evidence that some commercial date pit products appear to contain undeclared additives. SPME headspace analysis revealed the abundance of furans, pyrans, terpenoids and sulfur compounds in roasted date pits, whereas pyrroles and caffeine were absent. GCMS-post silylation employed for primary metabolite profiling revealed fatty acids’ enrichment in roasted pits versus sugars’ abundance in coffee. Biological investigations affirmed that date pit showed safer margin than coffee from its LD50, albeit it exhibits no CNS stimulant properties. This study provides the first insight into the roasting impact on the date pit through its metabolome and its neuropharmacological aspects to rationalize its use as a coffee substitute.


Foods ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 293 ◽  
Author(s):  
Sara Gaggiotti ◽  
Marcello Mascini ◽  
Paola Pittia ◽  
Flavio Della Pelle ◽  
Dario Compagnone

The performances of a quartz crystal microbalances (QCMs) based on an electronic nose (E-nose), modified with hairpin-DNA (hpDNA) for carrot aroma profiling has been evaluated. Solid phase micro-extraction (SPME) headspace sampling, combined with gas chromatography (GC), was used as a reference method. The changes in carrot aroma profiles stored at different temperatures (−18 °C, 4 °C, 25 °C, and 40 °C) were monitored during time up to 26 days. The principal component analysis of the data evidenced the different aroma patterns related to the presence of different key compounds. The output data achieved with the hpDNA-based E-nose were able to detect aroma patterns similar to gas chromatography with mass spectrometry (GC-MS). This work demonstrates that hpDNA has different sizes of loops that can be used for the development of sensor arrays able to detect aroma patterns in food and their changes with advantages in terms of easiness of usage, rapidity, and cost of analysis versus classical methods.


Molecules ◽  
2019 ◽  
Vol 24 (10) ◽  
pp. 1917 ◽  
Author(s):  
Ryan High ◽  
Phil Bremer ◽  
Biniam Kebede ◽  
Graham T. Eyres

Recent growth and diversification of sheep milk products means more sophisticated methods are required to ensure their flavour quality. The objective of this study was to compare four extraction techniques for the analysis of volatile compounds in sheep milk by gas chromatography-mass spectrometry (GC-MS). Solvent Assisted Flavour Evaporation (SAFE), Solid Phase Microextraction (SPME), Headspace Sorptive Extraction (HSSE) and Stir Bar Sorptive Extraction (SBSE) were evaluated for their sensitivity, selectivity, reproducibility, and overall efficiency. A total of 48 volatile compounds from nine compound classes were identified in the spray-dried sheep milk. Alcohols, aldehydes, alkanes, carboxylic acids, ketones, lactones, sulphur compounds, nitrogen compounds, and terpenes were all present, but the differences between the methods were most apparent for lactones. SBSE extracted eight lactones, SAFE extracted four lactones and HSSE and SPME only detected trace levels of two lactones. Six of the lactones—δ-hexa-lactone, δ-octalactone, γ-decalactone, γ-dodecalactone, δ-tetradecalactone, and δ-hexadeca-lactone—were identified for the first time in spray-dried sheep milk. The present work demonstrated that SBSE is an effective tool for the extraction and analysis of volatiles, especially lactones, in sheep milk and dairy products in general. A discussion of the benefits and limitations of each method is included.


2014 ◽  
Vol 22 (1) ◽  
pp. 77-84 ◽  
Author(s):  
Giulia Bianchi ◽  
Andrea Lovazzano ◽  
Alessandra Lanubile ◽  
Adriano Marocco

AbstractExpression profiles of flavour-related genes and the aroma quality of fruit headspace were investigated in the four strawberry genotypes ‘Reine des Vallées’ (Fragaria vesca), ‘Profumata di Tortona’ (F mos-chata), ‘Onda’ and VR 177 selection (F” x ananassa). Differences in the expression level of genes coding of strawberry alcohol acyltransferase (SAAT), F. x ananassa nerolidol synthase 1 (FaNESl) and F vesca monoterpene and sesquiterpene synthases (FvPINS and PINS1, respectively) were detected among these genotypes. In fruits of F. x ananassa the terpenoid profile was dominated by nerolidol, whereas wild spe–cies produced mainly monoterpenes. It was correlated with the higher induction of FaNES1 in cultivated and PINS gene in the wild Fragaria species. The flavour biogenesis in ripening fruits was determined by the expression of SAAT gene, especially visible for ‘Profumata di Tortona’ and ‘Onda’ strawberries. The fruit solid-phase microextraction (SPME) headspace was analysed using the Gas Chromatography-Olfac–tometry (GC-O), that allows for the chromatographic separation of volatiles together with their olfactomet-ric evaluation. ‘Reine des Vallées’ fruits have a peculiar profile characterized by high concentrations of limonene, linalool and mesifurane that resulted in “spiced”, “citrus, floral” and “sweet, baked” descriptors. The character impact compound in ‘Profumata di Tortona’ fruits was ethyl butanoate, responsible for “sweet” and “fruity, strawberry” descriptors. However, it was detected in lower amount in comparison to the data obtained for F. x ananassa strawberries. The sesquiterpene nerolidol was identified in both culti–vated strawberry genotypes.


2008 ◽  
Vol 7 (12) ◽  
pp. 1451-1457 ◽  
Author(s):  
Xiao-lei LI ◽  
Luan KANG ◽  
Jing-jing HU ◽  
Xue-fei LI ◽  
Xiang SHEN

2008 ◽  
Vol 11 (9) ◽  
pp. 1246-1251 ◽  
Author(s):  
Mourad Shonouda ◽  
Sergio Angeli ◽  
Stefan Schutz ◽  
Stefan Vidal

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