Cooking surface temperatures, steak thickness, and quality grade effects on volatile aroma compounds

Beef flavor attributes were evaluated in USDA TopChoice and Select beef top loin steaks cut 1.3 cm (THIN) or 3.8 cm (THICK) andcooked on a commercial flat top grill at 177˚C (LOW) or 232˚C (HIGH) grillsurface temperature. Gas chromatography/mass spectrophotometry, was used toevaluate volatile aroma compounds.  USDASelect steaks had more 2-octene and less trimethyl pyrazine in (P<0.05) THINsteaks than THICK steaks, while Choice was unaffected by steak thickness(P>0.05).  Benzene acetaldehyde washigher and 4-hydroxybenzoic acid was higher in Select LOW grill temperaturescompared to Select HIGH grill temperatures, while 5-methyl-2-furancarboxaldehyde was only present in Choice HIGH grill temperatures (P<0.05).Two acid, three alcohol, one aldehyde, one alkane, and one ketone volatilearoma compounds were higher (P<0.05) for LOW compared to HIGH.  Conversely, five alcohols, two aldehyde, twoalkane, all four furans, six ketones, four pyrazines, along with 1H-indole, twopyrroles, two pyridines, and one benzene aroma compounds were higher (P<0.05)in HIGH compared to LOW.  Additionally,one alcohol, two aldehydes, one ketones, one sulfur-containing, and six othervolatile compounds were lower, while one acid, one alcohol, one aldehyde, twofurans, one ketone, three pyrazine, one sulfur-containing, and one othervolatile compounds were higher in the THIN compared to THICK.  Some aroma compounds like 2-butanone,4-methyl-2-pentanone, 1-ethyl-1H-pyrrole, 1-methyl-1H-pyrrole, and2-methyl-pyridine were only present in THICK cooked HIGH (P<0.05). Steakthickness and grill time are important factors to consider in the developmentof positive Maillard reaction products.@font-face{font-family:"Cambria Math";panose-1:2 4 5 3 5 4 6 3 2 4;mso-font-charset:0;mso-generic-font-family:roman;mso-font-pitch:variable;mso-font-signature:-536870145 1107305727 0 0 415 0;}@font-face{font-family:Calibri;panose-1:2 15 5 2 2 2 4 3 2 4;mso-font-charset:0;mso-generic-font-family:swiss;mso-font-pitch:variable;mso-font-signature:-536859905 -1073732485 9 0 511 0;}p.MsoNormal, li.MsoNormal, div.MsoNormal{mso-style-unhide:no;mso-style-qformat:yes;mso-style-parent:"";margin:0in;margin-bottom:.0001pt;mso-pagination:widow-orphan;font-size:12.0pt;font-family:"Calibri",sans-serif;mso-ascii-font-family:Calibri;mso-ascii-theme-font:minor-latin;mso-fareast-font-family:Calibri;mso-fareast-theme-font:minor-latin;mso-hansi-font-family:Calibri;mso-hansi-theme-font:minor-latin;mso-bidi-font-family:"Times New Roman";mso-bidi-theme-font:minor-bidi;}.MsoChpDefault{mso-style-type:export-only;mso-default-props:yes;font-family:"Calibri",sans-serif;mso-ascii-font-family:Calibri;mso-ascii-theme-font:minor-latin;mso-fareast-font-family:Calibri;mso-fareast-theme-font:minor-latin;mso-hansi-font-family:Calibri;mso-hansi-theme-font:minor-latin;mso-bidi-font-family:"Times New Roman";mso-bidi-theme-font:minor-bidi;}div.WordSection1{page:WordSection1;}@font-face{font-family:"MS Mincho";panose-1:2 2 6 9 4 2 5 8 3 4;mso-font-alt:"ＭＳ 明朝";mso-font-charset:128;mso-generic-font-family:modern;mso-font-pitch:fixed;mso-font-signature:-536870145 1791491579 134217746 0 131231 0;}@font-face{font-family:"Cambria Math";panose-1:2 4 5 3 5 4 6 3 2 4;mso-font-charset:0;mso-generic-font-family:roman;mso-font-pitch:variable;mso-font-signature:-536870145 1107305727 0 0 415 0;}@font-face{font-family:Calibri;panose-1:2 15 5 2 2 2 4 3 2 4;mso-font-charset:0;mso-generic-font-family:swiss;mso-font-pitch:variable;mso-font-signature:-536859905 -1073732485 9 0 511 0;}@font-face{font-family:Cambria;panose-1:2 4 5 3 5 4 6 3 2 4;mso-font-charset:0;mso-generic-font-family:roman;mso-font-pitch:variable;mso-font-signature:-536870145 1073743103 0 0 415 0;}@font-face{font-family:"\@MS Mincho";panose-1:2 2 6 9 4 2 5 8 3 4;mso-font-charset:128;mso-generic-font-family:modern;mso-font-pitch:fixed;mso-font-signature:-536870145 1791491579 134217746 0 131231 0;}p.MsoNormal, li.MsoNormal, div.MsoNormal{mso-style-unhide:no;mso-style-qformat:yes;mso-style-parent:"";margin:0in;margin-bottom:.0001pt;mso-pagination:widow-orphan;font-size:12.0pt;font-family:"Cambria",serif;mso-ascii-font-family:Cambria;mso-ascii-theme-font:minor-latin;mso-fareast-font-family:"MS Mincho";mso-fareast-theme-font:minor-fareast;mso-hansi-font-family:Cambria;mso-hansi-theme-font:minor-latin;mso-bidi-font-family:"Times New Roman";mso-bidi-theme-font:minor-bidi;}p.Major, li.Major, div.Major{mso-style-name:Major;mso-style-unhide:no;mso-style-qformat:yes;margin:0in;margin-bottom:.0001pt;text-align:center;line-height:200%;mso-pagination:widow-orphan;font-size:14.0pt;mso-bidi-font-size:12.0pt;font-family:"Times New Roman",serif;mso-fareast-font-family:"MS Mincho";mso-fareast-theme-font:minor-fareast;}.MsoChpDefault{mso-style-type:export-only;mso-default-props:yes;font-family:"Cambria",serif;mso-ascii-font-family:Cambria;mso-ascii-theme-font:minor-latin;mso-fareast-font-family:"MS Mincho";mso-fareast-theme-font:minor-fareast;mso-hansi-font-family:Cambria;mso-hansi-theme-font:minor-latin;mso-bidi-font-family:"Times New Roman";mso-bidi-theme-font:minor-bidi;}div.WordSection1{page:WordSection1;}

Volatile aroma component of natural and roasted hazelnut varieties using solid-phase microextraction gas chromatography/mass spectrometry

Hazelnut is a very important nutrient in terms of human health. It is widely consumed as natural and roasted. Aromatic components could be used as marker for export criteria in hazelnut. Thus, this study aimed preliminary to compare the aroma profile of some hazelnut varieties and to determine the effect of roasting on aroma component in natural hazelnuts. Hazelnut varieties (18 Turkish and 2 foreign varieties) were obtained and then roasted at 135°C for 30 min. The volatile aroma components of hazelnuts were characterized via solid phase microextraction-gas chromatography-mass spectrometry (SPME/GC-MS). A total of 20 and 29 aroma compounds were detected by SPME/GC-MS in natural and roasted hazelnuts, respectively. Concerning natural hazelnut samples, the highest values among the Turkish and foreign varieties were obtained from nonanal in ‛Kalınkara’, ‛Kan’ and ‛Negret-N9’, which are mainly characterized by citrus, rosy, fatty flavor. In roasted samples, 2(3H)-furanone was determined in highest level in ‛Cavcava’, ‛Mincane’ and ‛Negret-N9’ and the flavor attributes of these varieties were oily-nut-like. In particular, Turkish hazelnut varieties such as ‛Acı’ and ‛Kalınkara’ could be promising in terms of the highest amount of aromatic components in roasted hazelnuts.

Techniques for Dealcoholization of Wines: Their Impact on Wine Phenolic Composition, Volatile Composition and Sensory Characteristics

The attention of some winemakers and researchers over the past years has been drawn towards the partial or total dealcoholization of wines and alcoholic beverages due to trends in wine styles, and the effect of climate change on wine alcohol content. To achieve this, different techniques have been used at the various stages of winemaking, among which the physical dealcoholization techniques, particularly membrane separation (nanofiltration, reverse osmosis, evaporative perstraction, and pervaporation) and thermal distillation (vacuum distillation and spinning cone column), have shown promising results and hence are being used for commercial production. However, the removal of alcohol by these techniques can cause changes in color and losses of desirable volatile aroma compounds, which can subsequently affect the sensory quality and acceptability of the wine by consumers. Aside from the removal of ethanol, other factors such as the ethanol concentration, the kind of alcohol removal technique, the retention properties of the wine non-volatile matrix, and the chemical-physical properties of the aroma compounds can influence changes in the wine sensory quality during dealcoholization. This review highlights and summarizes some of the techniques for wine dealcoholization and their impact on wine quality to help winemakers in choosing the best technique to limit adverse effects in dealcoholized wines and to help meet the needs and acceptance among different targeted consumers such as younger people, pregnant women, drivers, and teetotalers.

Digital Smoke Taint Detection in Pinot Grigio Wines Using an E-Nose and Machine Learning Algorithms Following Treatment with Activated Carbon and a Cleaving Enzyme

The incidence and intensity of bushfires is increasing due to climate change, resulting in a greater risk of smoke taint development in wine. In this study, smoke-tainted and non-smoke-tainted wines were subjected to treatments using activated carbon with/without the addition of a cleaving enzyme treatment to hydrolyze glycoconjugates. Chemical measurements and volatile aroma compounds were assessed for each treatment, with the two smoke taint amelioration treatments exhibiting lower mean values for volatile aroma compounds exhibiting positive ‘fruit’ aromas. Furthermore, a low-cost electronic nose (e-nose) was used to assess the wines. A machine learning model based on artificial neural networks (ANN) was developed using the e-nose outputs from the unsmoked control wine, unsmoked wine with activated carbon treatment, unsmoked wine with a cleaving enzyme plus activated carbon treatment, and smoke-tainted control wine samples as inputs to classify the wines according to the smoke taint amelioration treatment. The model displayed a high overall accuracy of 98% in classifying the e-nose readings, illustrating it may be a rapid, cost-effective tool for winemakers to assess the effectiveness of smoke taint amelioration treatment by activated carbon with/without the use of a cleaving enzyme. Furthermore, the use of a cleaving enzyme coupled with activated carbon was found to be effective in ameliorating smoke taint in wine and may help delay the resurgence of smoke aromas in wine following the aging and hydrolysis of glycoconjugates.

A Rapid Gas-Chromatography/Mass-Spectrometry Technique for Determining Odour Activity Values of Volatile Compounds in Plant Proteins: Soy, and Allergen-Free Pea and Brown Rice Protein

Plant-based protein sources have a characteristic aroma that limits their usage in various meat-alternative formulations. Despite being the most popular plant-based protein, the allergenicity of soy protein severely restricts the potential adoption of soy protein as an animal substitute. Thereby, allergen-free plant-protein sources need to be characterized. Herein, we demonstrate a rapid solid-phase-microextraction gas-chromatography/mass-spectrometry (SPME-GC/MS) technique for comparing the volatile aroma profile concentration of two different allergen-free plant-protein sources (brown rice and pea) and comparing them with soy protein. The extraction procedure consisted of making a 1:7 w/v aqueous plant protein slurry, and then absorbing the volatile compounds on an SPME fibre under agitation for 10 min at 40 °C, which was subsequently injected onto a GC column coupled to an MS system. Observed volatile concentrations were used in conjunction with odour threshold values to generate a Total Volatile Aroma Score for each protein sample. A total of 76 volatile compounds were identified. Aldehydes and furans were determined to be the most dominant volatiles present in the plant proteins. Both brown rice protein and pea protein contained 64% aldehydes and 18% furans, with minor contents of alcohols, ketones and other compounds. On the other hand, soy protein consisted of fewer aldehydes (46%), but a more significant proportion of furans (42%). However, in terms of total concentration, brown rice protein contained the highest intensity and number of volatile compounds. Based on the calculated odour activity values of the detected compounds, our study concludes that pea proteins could be used as a suitable alternative to soy proteins in applications for allergen-free vegan protein products without interfering with the taste or flavour of the product.