The effects of gums on macro and micro-structure of breads baked in different ovens

In this study, the effects of gums on macro and micro-structure of breads baked in different ovens (infrared (IR)-microwave combination and conventional) were investigated by the help of image and SEM analysis, respectively. The gums used were xanthan, guar, κ-carrageenan and xanthan-guar blend. The gums were added to the formulation at 0.5% concentration. As a control, no gum added formulations were used. Results of Image analysis demonstrated that xanthan-guar gum blend addition improved bread quality with increasing pore area fractions. It was seen that about 75% of the pores of control breads baked in infrared-microwave combination oven and about 63% of the pores of control breads baked in conventional oven had diameters of above 1000 μm. According to SEM analysis, pores in control breads baked in conventional oven were found to be smaller, and had spherical, oval-like shape as compared to the ones baked in IR-microwave combination oven. Moreover, more homogeneous closed-cell structure was observed for conventionally baked control breads. The pores of breads baked in IR-microwave combination oven were so close to each other which resulted in coalescence of the gas cells to form channels, then the pores were no longer spherical. The starch granules in conventionally baked breads were more distorted and seen as a continuous sheet of gelatinized starch. On the other hand, granular residues and continuous starch structure was observed together in IR-microwave combination heating.     

Classification of Italian honeys by mid-infrared diffuse reflectance spectroscopy (DRIFTS)

Diffuse reflectance mid-infrared Fourier transform spectroscopy (DRIFTS) and multivariate statistical analysis methods were used for the identification and classification of honey from different floral sources. The 82 honey samples (robinia, chestnut, citrus, polyfloral) were scanned by DRIFTS in the region 4000–600 cm⁻¹ and also transformed in 1st and 2nd derivatives. Spectral data were analyzed by principal component analysis, general discriminant analysis and classification tree analysis. Classification accuracy near 100% was obtained by discriminant and classification tree analyses. Classification models were successfully validated with one-third leave out method and a classification of about 100% were achieved.     

Geographical origin of imported and domestic teas (Camellia sinensis) from Turkey as determined by stable isotope signatures

In this study, stable isotope signatures (δ¹³C, δ¹⁵N, and δD) of both tea leaves and tea infusions were investigated to identify the geographical origin of Turkish domestic and imported tea samples. Sixteen domestic tea samples collected from different locations in the Black Sea Region, which produces almost 100% of tea in Turkey, and 11 imported tea samples (Kenya, India, Sri Lanka, Indonesia, and China) purchased from importers were studied. δ¹³C, δ¹⁵N, and δD in the samples were determined using isotope ratio mass spectrometry (IR-MS). δ¹³C in the samples ranged from ?29.18 ± 0.01 to ?25.7 ± 0.2, while δ¹⁵N ranged between 1.1 ± 0.2 and 5.2 ± 0.8. However, δD in the samples were found to be in the range from 56.5 ± 0.3 to 72 ± 1. The classifications of the tea samples into domestic and imported tea samples were achieved with 100% accuracy using multivariate statistical analyses (principal component analysis, PCA, and hierarchical cluster analysis, HCA). In conclusion, the domestic tea samples had a distinctive isotopic fingerprint and the isotopic ratios used in the study can be significant predictors in determination of the geographical source of Turkish tea.     

Characterisation of the geographical origin of Italian potatoes,based on stable isotope and volatile compound analyses

Headspace solid-phase microextraction/gas chromatography–mass spectrometry (HS-SPME/GC–MS) and isotope ratio mass spectrometry (IRMS), in combination with appropriate statistical techniques, were used for the prediction of the geographical origin of Italian potatoes cultivated in three different Italian locations: Sicily, Apulia, and Tuscany. An analysis of variance, performed on log transformed headspace volatile compounds and isotopic ratios, highlighted statistically significant differences (p < 0.05) in the values of 15 volatile compounds and for all isotopic parameters among the potatoes produced in the three different geographical areas. A Post-Hoc test showed that only the oxygen and nitrogen isotopic ratios distinguished the potatoes produced at the three sites. Applying discriminant function analysis (DFA), the classification results were 100% by using both volatile and complete data set (isotopic ratios and volatile compounds), whereas classification results were 91.7% for isotopic data; the prediction ability of 91.7%, evaluated by leave-one-out procedure, was the same by applying DFA both on single data sets (volatile compounds or isotopic ratios) and on all data together.     

Instrumental and multivariate statistical analyses for the characterisation of the geographical origin of Apulian virgin olive oils

In this paper, virgin olive oils (VOOs) coming from three different geographic origins of Apulia, were analysed for free acidity, peroxide value, spectrophotometric indexes, chlorophyll content, sterol, fatty acid, and triacylglycerol compositions. In order to predict the geographical origin of VOOs, different multivariate approaches were applied. By performing principal component analysis (PCA) a modest natural grouping of the VOOs was observed on the basis of their origin, and consequently three supervised techniques, i.e., general discriminant analysis (GDA), partial least squares-discriminant analysis (PLS-DA) and soft independent modelling of class analogy (SIMCA) were used and the results were compared. In particular, the best prediction ability was produced by applying GDA (average prediction ability of 82.5%), even if interesting results were obtained also by applying the other two classification techniques, i.e., 77.2% and 75.5% for PLS-DA and SIMCA, respectively.     

Characterisation of the geographical origin of Western Greek virgin olive oils based on instrumental and multivariate statistical analysis

In this work, measurements of free acidity, peroxide content, spectrophotometric parameters, chlorophyll content, phenol, sterol, fatty acid and triacylglycerol composition, were carried out on samples of virgin olive oils (VOOs) coming from four different Greek Ionian islands, i.e. Zakynthos, Kefalonia, Lefkada and Kerkyra. An analysis of variance (ANOVA) highlighted statistically significant differences (p < 0.01) in the values of 26 analytical parameters amongst the VOOs produced in the four different geographical regions but a post-hoc test showed that no variable was able to distinguish all four origins. Analogously, a Principal Component Analysis (PCA) showed a modest grouping of VOOs according to geographical origin except for Kerkyra samples which were more distinct from others. Applying discriminant function analysis (DFA) a good separation of the four geographical groups was achieved with classification and prediction abilities equal to 97.7% and 95.3%, respectively. Moreover, the analysis of the standardised coefficients showed that the fatty acids and triacylglycerols were the most discriminant variables. This last outcome was confirmed by comparison of the prediction performances obtained applying DFA on four subdatasets containing fatty acids (69.8%), triacylglycerols (76.7%), sterols (62.8%), and remaining parameters (65.1%) together, respectively. As the results showed, the multidisciplinary approach that combines different types of analytical determinations improved the discrimination of geographical origin for Greek virgin olive oils.     

Use of a toasted durum whole meal in the production of a traditional Italian pasta: chemical, mechanical, sensory and image analyses

The characterisation of traditional Italian pasta obtained by mixing amounts of toasted whole meal with re-milled semolina and other ingredients was obtained by means of physico-chemical, rheological, mechanical, sensory and image analyses. The toasted meal showed higher ash, fibre and protein contents than re-milled semolina. The replacement of percentages of re-milled semolina with the toasted meal and soft flour increased tenacity and decreased extensibility and strength, making the dough less suitable for pasta-making. The P / L values were indices of high starch damage. The replacement of part of re-milled semolina and water with toasted whole wheat meal, soft flour and eggs increased the optimal cooking time and the amount of water absorbed during cooking but made the other cooking parameters worse. The image analysis provided evidence of the changes induced by the use of toasted wholemeal, soft flour and eggs in the microscopic structure of pasta protein and starch.     

Classification of olive oils according to geographical origin by using H NMR fingerprinting combined with multivariate analysis

Authentic extravirgin olive oils from 7 different regions (Italy – 3 regions, Greece – 4 regions) have been investigated by ¹H Nuclear Magnetic Resonance (NMR) fingerprinting in combination with multivariate statistical analysis. In order to cover the dominating lipid signals as well as signals from compounds of low abundance in the oil, both a simple one pulse experiment and an experiment with multiple saturation of the lipid signals was applied to each sample. Thus, the dynamic range of concentrations covered by the two experiments was of the order of 100,000 allowing for a more comprehensive NMR assessment of the samples. Monte-Carlo embedded cross-validation was used to demonstrate that a combination of principal component analysis, canonical analysis, and classification via nearest class mean can be used to predict the origin of olive oil samples from ¹H NMR data. Given the rather limited number of samples tested, correct prediction probabilities of 78% were achieved with region specific correct predictions between 53% and 100%.     

A combined approach for characterisation of fresh and brined vine leaves by X-ray powder diffraction,NMR spectroscopy and direct infusion high resolution mass spectrometry

X-ray powder diffraction was combined, for the first time, with Nuclear Magnetic Resonance spectroscopy and direct infusion mass spectrometry to characterise fresh and brined grape leaves. Covariance analysis of data generated by the three techniques was performed with the aim to correlate information deriving from the solid part with those obtained for soluble metabolites. The results obtained indicate that crystalline components can be correlated to the metabolites contained in the grape leaves, paving the way to the use of X-ray diffraction analysis for food fingerprinting purposes. Moreover it was ascertained that, differently from most of the metabolites present in the fresh vine leaves, linolenic acid (an omega-3-fatty acid) and quercetin-3-O-glucuronide (a polyphenol metabolite) do not undergo sensible degradation during the brining process, which is used as preservative method for the grape leaves.     

Study by means of H nuclear magnetic resonance of the oxidation process undergone by edible oils of different natures submitted to microwave action

The oxidation processes of virgin olive, corn and linseed oils, repeatedly submitted to the effect of microwave heating until the temperature reached 190 °C, have been studied by means of ¹H nuclear magnetic resonance. These oxidation processes are very different to those produced at 70 °C with aeration; differences have been found not only in the rate of degradation and in the oxidation mechanisms but also in the nature and proportions of the aldehydes generated. It has also been shown that these oxidative conditions affect the three oils studied in very different ways; virgin olive oil is the least affected by this process and in addition its degradation produces lower proportions of harmful aldehydes.     

Void structure in textiles by nuclear magnetic resonance,Part I. Imaging of imbibed fluids and image analysis by calculation of fluid density autocorrelation functions

Void structure in textiles may be characterized by a variety of methods, including many based on nuclear magnetic resonance (NMR). The NMR techniques are based on the measurement of fluid distribution or diffusion within porous media, and are therefore particularly relevant for characterizing the void space that governs fluid interactions and movement within textile substrates. In this article, we describe the use of NMR imaging, also known as magnetic resonance imaging, to measure average void dimensions in textile fabrics. In addition to direct visualization using NMR images, void space may be analyzed by calculating the fluid density autocorrelation function. The advantages of both types of data analysis are discussed. These NMR techniques are applied to a water-saturated nylon fabric and the results compared to void sizes measured from optical microscopy.     

Relationships between volatile production,fruit quality and sensory evaluation of Fuji apples stored in different atmospheres by means of multivariate analysis

Aroma compounds, quality parameters and sensory characteristics of Fuji apples were analysed after 3, 5 and 7 months of storage at 1 °C in normal air (AIR; 210 l m^?3 O₂/0.3 l m^?3 CO₂) and in controlled atmospheres with O₂/CO₂ ratios of 10 l m^?3/10 l m^?3 (ULO1), 10 l m^?3/20 l m^?3 (ULO2) and 30 l m^?3/20 l m^?3 (SCA). After storage the apples were kept at 20 °C for 1, 5 and 10 days. The components that contributed most to the characteristic aroma of Fuji apples were ethyl 2‐methylbutanoate, 2‐methylbutyl acetate and hexyl acetate. The highest aroma compound production was found in ULO1 fruits after 5 months of cold storage and 1 day of shelf‐life. After 3 and 5 months of storage, ULO1 fruits showed the highest firmness after both 1 day and 10 days at 20 °C. After 7 months of storage plus 1 day at 20 °C, ULO2 fruits showed higher titratable acidity and soluble solid content; fruit firmness was also maintained throughout the shelf‐life period. Generally, background and superficial colour were not influenced by storage conditions. A statistically significant correlation was found between aroma compounds, quality parameters and sensory evaluation. Copyright © 2003 Society of Chemical Industry     

Characterization of marama bean (Tylosema esculentum) by comparative spectroscopy: NMR, FT-Raman, FT-IR and NIR

The marama bean from Southern Africa has proven to be a source for production of various healthy food products. In order to exploit its commercial potential, it is important to know its chemical composition in more detail. In this study, marama beans from different geographical sites and harvest years were analyzed by use of infrared, near infrared, Raman, and ¹H as well as ¹³C nuclear magnetic resonance spectroscopy. These techniques can measure single beans in a rapid and non-destructive manner. By comparative application, the qualitative composition of the marama bean was explored in detail, revealing large amounts of protein, dietary fiber and unsaturated fat. The carbohydrate fraction was largely present as pectins and a minor fraction of smaller water soluble carbohydrates were tentatively assigned to raffinose. It is characteristic that the beans do not contain starch or ??-glucans and that the water soluble part of the proteins/peptides have a high content of the aromatic amino acid tyrosine.