Nicola Caporaso

Olive oil phenolic compounds affect the release of aroma compounds.

Twelve aroma compounds were monitored and quantified by dynamic headspace analysis after their addition in refined olive oil model systems with extra virgin olive oil (EVOO) biophenols to simulate EVOO aroma. The influence of polyphenols on aroma release was studied under simulated mouth conditions by using human saliva, and SPME-GC/MS analysis. While few differences were observed in orthonasal assay (without saliva), interesting results were obtained for retronasal aroma. Biophenols caused generally the lowest headspace release of almost all volatile compounds. However, only ethyl esters and linalool concentrations were significantly lower in retronasal than orthonasal assay. Saliva also caused higher concentration of hexanal, probably due to hydroperoxide lyase (HPL) action on linoleyl hydroperoxides. Epicatechin was compared to EVOO phenolics and the behaviour was dramatically different, likely to be due to salivary protein-tannin binding interactions, which influenced aroma headspace release. These results were also confirmed using two extra virgin olive oils.

Protein content prediction in single wheat kernels using hyperspectral imaging

Highlights • HSI was applied for non-destructive prediction of total protein content in wheat kernels.• Above 2100 wheat kernels were taken from ~200 batches and individually analysed.• PLS regression models had R2 = 0.82 and prediction error lower than 0.93%.• Protein distribution had wide range (6–20%) and was visualised by applying the calibration.• The performance of HgGcTe was superior to the one built by simulating InGaAs sensors.

Influence of Olive Oil Phenolic Compounds on Headspace Aroma Release by Interaction with Whey Proteins

The release of volatile compounds in an oil-in-water model system obtained from olive oil-whey protein (WP) pairing was investigated by considering the effect of phenolic compounds. Human saliva was used to simulate mouth conditions by retronasal aroma simulator (RAS) analysis. Twelve aroma compounds were quantified in the dynamic headspace by SPME-GC/MS. The results showed significant influences of saliva on the aroma release of virgin olive oil (VOO) volatiles also in the presence of WP. The interaction between WP and saliva leads to lower headspace release of ethyl esters and hexanal. Salivary components caused lower decrease of the release of acetates and alcohols. A lower release of volatile compounds was found in the RAS essay in comparison to that in orthonasal simulation of only refined olive oil (without addition of saliva or WP), with the exception of hexanal and 1-penten-3-one, where a significantly higher release was found. Our results suggest that the extent of retronasal odor (green, pungent) of these two volatile compounds is higher than orthonasal odor. An extra VOO was used to verify the release in model systems, indicating that WP affected aroma release more than model systems, while saliva seems to exert an opposite trend. A significant increase in aroma release was found when phenolic compounds were added to the system, probably due to the contrasting effects of binding of volatile compounds caused by WP, for the polyphenol-protein interaction phenomenon. Our study could be applied to the formulation of new functional foods to enhance flavor release and modulate the presence and concentrations of phenolics and whey proteins in food emulsions/dispersions.

Non-destructive analysis of sucrose, caffeine and trigonelline on single green coffee beans by hyperspectral imaging

Hyperspectral imaging (HSI) is a novel technology for the food sector that enables rapid non-contact analysis of food materials. HSI was applied for the first time to whole green coffee beans, at a single seed level, for quantitative prediction of sucrose, caffeine and trigonelline content. In addition, the intra-bean distribution of coffee constituents was analysed in Arabica and Robusta coffees on a large sample set from 12 countries, using a total of 260 samples. Individual green coffee beans were scanned by reflectance HSI (980–2500 nm) and then the concentration of sucrose, caffeine and trigonelline analysed with a reference method (HPLC-MS). Quantitative prediction models were subsequently built using Partial Least Squares (PLS) regression. Large variations in sucrose, caffeine and trigonelline were found between different species and origin, but also within beans from the same batch. It was shown that estimation of sucrose content is possible for screening purposes (R2 = 0.65; prediction error of ~ 0.7% w/w coffee, with observed range of ~ 6.5%), while the performance of the PLS model was better for caffeine and trigonelline prediction (R2 = 0.85 and R2 = 0.82, respectively; prediction errors of 0.2 and 0.1%, on a range of 2.3 and 1.1% w/w coffee, respectively). The prediction error is acceptable mainly for laboratory applications, with the potential application to breeding programmes and for screening purposes for the food industry. The spatial distribution of coffee constituents was also successfully visualised for single beans and this enabled mapping of the analytes across the bean structure at single pixel level.

Developments, applications, and trends of molecular gastronomy among food scientists and innovative chefs

ABSTRACT Molecular gastronomy (MG) is a relatively new scientific discipline, which focuses on food preparation mainly at domestic and restaurant levels. The number of scientific papers on MG has increased in the past few years. It is, however, difficult to differentiate specifically between the MG discipline or other research areas in food science and technology. Otherwise, molecular cooking, i.e., an application of MG principles, seems limited to a few “fancy” techniques supported by famous chefs. This paper aims to critically review the recent developments of MG, the most interesting applications, and the outcomes obtained from the fruitful collaboration among food scientists and innovative chefs. The controversies and merits associated with MG are also presented, e.g., the principle of food pairing and consumers’ appreciation of innovative dishes, and a few research papers promising exciting future developments.

The “True” Neapolitan Pizza: Assessing the Influence of Extra Virgin Olive Oil on Pizza Volatile Compounds and Lipid Oxidation

The aim of our research was to evaluate the effect of different types of vegetable oils, namely extra virgin olive oil (EVOO), olive oil, and sunflower oil, on the chemical properties and volatile profile of traditional Neapolitan pizza, produced by using tomato sauce and EVOO. The quality indices and polyphenols in vegetable oils were analyzed to assess the lipid oxidation as affected by cooking in traditional wood-fired ovens. Peroxide value significantly increased in all vegetable oils, particularly in sunflower oil. EVOO polyphenols decreased about 30% their initial level, particularly simple phenolics. Total individual phenolic compounds decreased from 254.6 to 172.0 mg/kg. Pizza cooking caused the development of some neo-formation volatile compounds caused by lipid oxidation and Maillard reaction. Some positive key odor compounds were found in pizza cooked with EVOO, and the addition of tomato sauce and EVOO caused a dramatic change in its volatile pattern.

Hyperspectral imaging for non-destructive prediction of fermentation index, polyphenol content and antioxidant activity in single cocoa beans

Highlights • Measurements of single cocoa beans were made by NIR HSI.• PLS regression models were built for several chemical properties.• Fermentation (FI), total phenolics (TP) and antioxidant activity (AA) were predicted.• Prediction performance was suitable for screening purposes.

Fruit position within the canopy affects kernel lipid composition of hazelnuts

BACKGROUND The aim of this research was to study the variability in kernel composition within the canopy of hazelnut trees. RESULTS Kernel fresh and dry weight increased linearly with fruit height above the ground. Fat content decreased, while protein and ash content increased, from the bottom to the top layers of the canopy. The level of unsaturation of fatty acids decreased from the bottom to the top of the canopy. Thus, the kernels located in the bottom layers of the canopy appear to be more interesting from a nutritional point of view, but their lipids may be more exposed to oxidation. The content of different phytosterols increased progressively from bottom to top canopy layers. CONCLUSION Most of these effects correlated with the pattern in light distribution inside the canopy. The results of this study indicate that fruit position within the canopy is an important factor in determining hazelnut kernel growth and composition.

Variability of single bean coffee volatile compounds of Arabica and robusta roasted coffees analysed by SPME-GC-MS

We report on the analysis of volatile compounds by SPME-GC-MS for individual roasted coffee beans. The aim was to understand the relative abundance and variability of volatile compounds between individual roasted coffee beans at constant roasting conditions. Twenty-five batches of Arabica and robusta species were sampled from 13 countries, and 10 single coffee beans randomly selected from each batch were individually roasted in a fluidised-bed roaster at 210 °C for 3 min. High variability (CV = 14.0–53.3%) of 50 volatile compounds in roasted coffee was obtained within batches (10 beans per batch). Phenols and heterocyclic nitrogen compounds generally had higher intra-batch variation, while ketones were the most uniform compounds (CV < 20%). The variation between batches was much higher, with the CV ranging from 15.6 to 179.3%. The highest variation was observed for 2,3-butanediol, 3-ethylpyridine and hexanal. It was also possible to build classification models based on geographical origin, obtaining 99.5% and 90.8% accuracy using LDA or MLR classifiers respectively, and classification between Arabica and robusta beans. These results give further insight into natural variation of coffee aroma and could be used to obtain higher quality and more consistent final products. Our results suggest that coffee volatile concentration is also influenced by other factors than simply the roasting degree, especially green coffee composition, which is in turn influenced by the coffee species, geographical origin, ripening stage and pre- and post-harvest processing.