Authentication of an Italian PDO hazelnut ("Nocciola Romana") by NIR spectroscopy.

Common hazelnuts are widely present in human diet all over the world, and their beneficial effects on the health have been extensively investigated and demonstrated. Different in-depth researches have highlighted that the harvesting area can define small variations in the chemical composition of the fruits, affecting their quality. As a consequence, it has become relevant to develop methodologies which would allow authenticating and tracing hazelnuts.

Simultaneous quantification of caffeine and chlorogenic acid in coffee green beans and varietal classification of the samples by HPLC-DAD coupled with chemometrics.

A chromatographic procedure (HPLC-DAD) using a relatively rapid gradient has been combined with a chemometric curve deconvolution method, multivariate curve resolution-alternating least squares (MCR-ALS), in order to quantify caffeine and chlorogenic acid in green coffee beans. Despite that the HPLC analysis (at these specific operating conditions) presents some coeluting peaks, MCR-ALS allowed their resolution and, consequently, the creation of a calibration curve to be used for the quantification of the analytes of interest; this procedure led to a high accuracy in the quantification of caffeine and chlorogenic acid present in the samples. In a second part of this study, the possibility of classifying the green coffee beans on the basis of their cultivar (Arabica or Robusta), by partial least squares discriminant analysis (PLS-DA) and soft independent modeling of class analogies (SIMCA), has been explored.

Geographical characterization by MAE-HPLC and NIR methodologies and carbonic anhydrase inhibition of Saffron components.

A microwave-assisted extraction method was optimised for the recovery of bioactive compounds from Crocus sativus L. stigmas with the use of water/ethanol mixture. HPLC-DAD was employed to evaluate the extraction parameters, in particular, solvent type and volume, and the duration of the procedure.

Combined effects of reduced malaxation oxygen levels and storage time on extra-virgin olive oil volatiles investigated by a novel chemometric approach.

Combined effects of oxygen level reduction in the malaxation headspace and storage time up to 6 months on the volatile composition of a monovarietal extra-virgin olive oil (EVOO), obtained from cv. Carboncella olives, were investigated by applying a full factorial design approach (4 oxygen levels × 4 storage times) on EVOOs extracted on an industrial scale in two mills, equipped with "two-phase" and "three-phase" centrifugation systems, respectively. The outcoming data were analysed by the chemometric technique called ANOVA-simultaneous component analysis (ASCA).

Data-fusion for multiplatform characterization of an Italian craft beer aimed at its authentication.

Five different instrumental techniques: thermogravimetry, mid-infrared, near-infrared, ultra-violet and visible spectroscopies, have been used to characterize a high quality beer (Reale) from an Italian craft brewery (Birra del Borgo) and to differentiate it from other competing and lower quality products. Chemometric classification models were built on the separate blocks using soft independent modeling of class analogies (SIMCA) and partial least squares-discriminant analysis (PLS-DA) obtaining good predictive ability on an external test set (75% or higher depending on the technique). The use of data fusion strategies - in particular, the mid-level one - to integrate the data from the different platforms allowed the correct classification of all the training and validation samples.

Chemometric classification techniques as a tool for solving problems in analytical chemistry.

Supervised pattern recognition (classification) techniques, i.e., the family of chemometric methods whose aim is the prediction of a qualitative response on a set of samples, represent a very important assortment of tools for solving problems in several areas of applied analytical chemistry.

Application of near infrared (NIR) spectroscopy coupled to chemometrics for dried egg-pasta characterization and egg content quantification.

Dried egg pasta is an important and traditional food in the Italian cuisine, and the eggs in pasta improve its nutritional value and organoleptic properties. For this reason the percentage of eggs present in the products sold as "egg pasta" has to always be clearly reported in the label. In this respect, the present research addresses the possibility of developing a method which would allow fast, simple and economic determination of egg content in dried egg-pasta, using near-infrared spectroscopy and chemometric analysis.

Tracing the origin of extra virgin olive oils by infrared spectroscopy and chemometrics: a case study.

In this paper, the potential of coupling mid- and near-infrared spectroscopic fingerprinting techniques and chemometric classification methods for the traceability of extra virgin olive oil samples from the PDO Sabina was investigated. To this purpose, two different pattern recognition algorithm representative of the discriminant (PLS-DA) and modeling (SIMCA) approach to classification were employed. Results obtained after processing the spectroscopic data by PLS-DA evidenced a rather high classification accuracy, NIR providing better predictions than MIR (as evaluated both in cross-validation and on an external test set).

Use of near infrared reflectance and transmittance coupled to robust calibration for the evaluation of nutritional value in naked oats.

A rapid accurate and precise method for simultaneous determination of β-glucan and protein content in naked oat samples, based on the coupling of near-infrared spectroscopy and chemometrics, is presented. In particular, three different spectroscopic approaches [near infrared reflectance (NIR) and transmittance (NIT) on flour and NIT on whole grains] and various spectral pretreatments were considered. To account for the possibility of outlying samples, a robust version of the PLS algorithm (namely partial robust M-regression) was used.

UV-vis spectrophotometric method for the quantitation of all the components of Italian general denaturant and its application to check the conformity of alcohol samples.

A simple, fast and relatively inexpensive spectrophotometric method for the identification and the quantification of the individual components of the Italian general denaturant in alcohol samples is proposed. In particular, it is shown that bitrex (a quaternary ammonium salt), whose UV spectrum is completely masked by those of the other denaturant components, can be identified using its reaction with disulphine blue VN-150 (an anionic dye indicator), which leads to the formation of an intensely colored ion-association complex (mole ratio 1:1), easily extractable in chloroform. As far as the quantitative detection is involved, it is however necessary to shake the chloroform phase in the presence of 1 mol L(-1) NaClO(4) aqueous solution because of the fast adsorption of the ion pair on the walls of the glass cell.

Proton NMR relaxation study of swelling and gelatinisation process in rice starch-water samples.

Proton transverse magnetization decay curves of rice flour starch-water samples were measured and analysed for the presence of four components in the relaxation curve. T2 values were interpreted on the basis of the diffusive and chemical exchange model that provided evidence for extra granular bulk water and three more water populations whose relaxation rate is governed by diffusive and chemical exchange with starch components. The analysis of relaxation data provided information on dynamics of water molecules as well as on the size and dispersion of diffusive domains.

Use of different artificial neural networks to resolve binary blends of monocultivar Italian olive oils.

The problem of authenticating extra virgin olive oil varieties is particularly important from the standpoint of quality control. After having shown in our previous works the possibility of discriminating oils from a single variety using chemometrics, in this study a combination of two different neural networks architectures was employed for the resolution of simulated binary blends of oils from different cultivars. In particular, a Kohonen self-organizing map was used to select the samples to include in the training, test and validation sets, needed to operate the successive calibration stage, which has been carried out by means of several multilayer feed-forward neural networks.

Comparison of three spectrophotometric methods for the determination of gamma-oryzanol in rice bran oil.

A comparison of the results obtained by applying three spectrophotometric methods (at fixed wavelength, second-derivative and multicomponent analysis) to the determination of gamma-oryzanol in rice bran oil is reported. At fixed wavelength the results are more accurate when using isopropyl alcohol, rather than n-heptane, to dilute the oil samples, because the absorption bands of gamma-oryzanol are red-shifted and the absorbance, measured at lambda(max)=327 nm, is less affected by the interference of the oil "matrix" (lambda(max)=314 nm in n-heptane).However, to obtain accurate results also in oils with a low content of gamma-oryzanol, it is necessary to perform the analysis using second-derivative ((2)D330.

Structural analysis of the solid amorphous binuclear complexes of iron(III) and aluminum(III) with chromium(III)-DTPA chelator using energy dispersive X-ray diffraction.

This paper is concerned with the structural data obtained for two amorphous binuclear complexes of iron(III) and aluminum(III) with chromium(III)-diethylentriaminepentaacetic acid (chromium(III)-DTPA, CrL(2)(-)) using the energy-dispersive X-ray diffraction technique. Fe(OH)CrL(H(2)O)(6) and Al(OH)CrL(H(2)O)(6) are binuclear complexes, the metals ions being bridged via oxygen atoms. The metal ions are all octahedrally coordinated.

Chemical authentication of extra virgin olive oil varieties by supervised chemometric procedures.

This work has focused on discriminating extra virgin olive oils from Sabina (Lazio, Italy) by olive fruit variety (cultivar). A set of oils from five of the most widespread cultivars (Carboncella, Frantoio, Leccino, Moraiolo, and Pendolino) in this geographical area was analyzed for chemical composition using only the Official Analytical Methods, recognized for the quality control and commercial classification of this product. The obtained data set was converted into a computer-compatible format, and principal component analysis (PCA) and a method based on the Fisher F ratio were used to reduce the number of variables without a significant loss of chemical information.