Effect of roasting on the antioxidant activity of coffee brews

Colombian Arabica coffee beans were roasted to give light, medium, and dark samples. Their aqueous extracts were analyzed by gel filtration chromatography, UV-visible spectrophotometry, capillary electrophoresis, and the ABTS(.+) assay. A progressive decrease in antioxidant activity (associated mainly with chlorogenic acids in the green beans) with degree of roasting was observed with the simultaneous generation of high (HMM) and low molecular mass (LMM) compounds possessing antioxidant activity. Maximum antioxidant activity was observed for the medium-roasted coffee; the dark coffee had a lower antioxidant activity despite the increase in color. Analysis of the gel filtration chromatography fractions showed that the LMM fraction made a greater contribution to total antioxidant activity than the HMM components.

Antioxidant activity of coffee model systems

Coffee model systems prepared from combinations of chlorogenic acid (CGA), N-alpha-acetyl-1-arginine (A), sucrose (S), and cellulose (C) were roasted at 240 degreesC for 4 min prior to analysis by UV-visible spectrophotometry, capillary zone electrophoresis (CZE), and the ABTS radical cation decolorization assay. The A/CGA/S/C and A/S/C systems were also fractionated by gel filtration chromatography. Antioxidant activity of the systems showed a positive, nonlinear relationship with the amount of CGA remaining after roasting. Sucrose degradation was a major source of color in the heated systems. There was no relationship between antioxidant activity and color generation.

The application of Near-Infrared Reflectance Spectroscopy (NIRS) to detect melamine adulteration of soya bean meal

Soya bean products are used widely in the animal feed industry as a protein based feed ingredient and
have been found to be adulterated with melamine. This was highlighted in the Chinese scandal of
2008. Dehulled soya (GM and non-GM), soya hulls and toasted soya were contaminated with melamine
and spectra were generated using Near Infrared Reflectance Spectroscopy (NIRS). By applying chemometrics
to the spectral data, excellent calibration models and prediction statistics were obtained. The coefficients
of determination (R2) were found to be 0.89–0.99 depending on the mathematical algorithm used,
the data pre-processing applied and the sample type used. The corresponding values for the root mean
square error of calibration and prediction were found to be 0.081–0.276% and 0.134–0.368%, respectively,
again depending on the chemometric treatment applied to the data and sample type. In addition, adopting
a qualitative approach with the spectral data and applying PCA, it was possible to discriminate
between the four samples types and also, by generation of Cooman’s plots, possible to distinguish
between adulterated and non-adulterated samples.

The feasibility of using near infrared and Raman spectroscopic techniques to detect fraudulent adulteration of chili powders with Sudan dye

Chili powder is a globally traded commodity which has been found to be adulterated with Sudan dyes from 2003 onwards. In this study, chili powders were adulterated with varying quantities of Sudan I dye (0.1-5%) and spectra were generated using near infrared reflectance spectroscopy (NIRS) and Raman
spectroscopy (on a spectrometer with a sample compartment modified as part of the study). Chemometrics were applied to the spectral data to produce quantitative and qualitative calibration models and prediction statistics. For the quantitative models coefficients of determination (R2) were found to be
0.891-0.994 depending on which spectral data (NIRS/Raman) was processed, the mathematical algorithm used and the data pre-processing applied. The corresponding values for the root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) were found to be 0.208-0.851%
and 0.141-0.831% respectively, once again depending on the spectral data and the chemometric treatment applied to the data. Indications are that the NIR spectroscopy based models are superior to the models produced from Raman spectral data based on a comparison of the values of the chemometric
parameters. The limit of detection (LOD) based on analysis of 20 blank chili powders against each calibration model gave 0.25% and 0.88% for the NIR and Raman data, respectively. In addition, adopting a qualitative approach with the spectral data and applying PCA or PLS-DA, it was possible to discriminate
between adulterated chili powders from non-adulterated chili powders.

The use of handheld near-infrared reflectance spectroscopy (NIRS) for the proximate analysis of poultry feed and to detect melamine adulteration of soya bean meal

The use of handheld near infrared (NIR) instrumentation, as a tool for rapid analysis, has the potential to be used widely in the animal feed sector. A comparison was made between handheld NIR and benchtop instruments in terms of proximate analysis of poultry feed using off-the-shelf calibration models and including statistical analysis. Additionally, melamine adulterated soya bean products were used to develop qualitative and quantitative calibration models from the NIRS spectral data with excellent calibration models and prediction statistics obtained. With regards to the quantitative approach, the coefficients of determination (R2) were found to be 0.94-0.99 with the corresponding values for the root mean square error of calibration and prediction were found to be 0.081-0.215 % and 0.095-0.288 % respectively. In addition, cross validation was used to further validate the models with the root mean square error of cross validation found to be 0.101-0.212 %. Furthermore, by adopting a qualitative approach with the spectral data and applying Principal Component Analysis, it was possible to discriminate between adulterated and pure samples.

Development of a novel continuous statistical modelling technique for detecting the adulteration of extra virgin olive oil with hazelnut oil by using spectroscopic data

The adulteration of extra virgin olive oil with other vegetable oils is a certain problem with economic and health consequences. Current official methods have been proved insufficient to detect such adulterations. One of the most concerning and undetectable adulterations with other vegetable oils is the addition of hazelnut oil. The main objective of this work was to develop a novel dimensionality reduction technique able to model oil mixtures as a part of an integrated pattern recognition solution. This final solution attempts to identify hazelnut oil adulterants in extra virgin olive oil at low percentages based on spectroscopic chemical fingerprints. The proposed Continuous Locality Preserving Projections (CLPP) technique allows the modelling of the continuous nature of the produced in house admixtures as data series instead of discrete points. This methodology has potential to be extended to other mixtures and adulterations of food products. The maintenance of the continuous structure of the data manifold lets the better visualization of this examined classification problem and facilitates a more accurate utilisation of the manifold for detecting the adulterants.

A comprehensive strategy to detect the fraudulent adulteration of herbs: The oregano approach

Fraud in the global food supply chain is becoming increasingly common due to the huge profits associated with this type of criminal activity. Food commodities and ingredients that are expensive and are part of complex supply chains are particularly vulnerable. Both herbs and spices fit these criteria perfectly and yet strategies to detect fraudulent adulteration are still far from robust. An FT-IR screening method coupled to data analysis using chemometrics and a second method using LC-HRMS were developed, with the latter detecting commonly used adulterants by biomarker identification. The two tier testing strategy was applied to 78 samples obtained from a variety of retail and on-line sources. There was 100% agreement between the two tests that over 24% of all samples tested had some form of adulterants present. The innovative strategy devised could potentially be used for testing the global supply chains for fraud in many different forms of herbs.

Continuous statistical modelling for rapid detection of adulteration of extra virgin olive oil using mid infrared and Raman spectroscopic data

The main objective of this work was to develop a novel dimensionality reduction technique as a part of an integrated pattern recognition solution capable of identifying adulterants such as hazelnut oil in extra virgin olive oil at low percentages based on spectroscopic chemical fingerprints. A novel Continuous Locality Preserving Projections (CLPP) technique is proposed which allows the modelling of the continuous nature of the produced in-house admixtures as data series instead of discrete points. The maintenance of the continuous structure of the data manifold enables the better visualisation of this examined classification problem and facilitates the more accurate utilisation of the manifold for detecting the adulterants. The performance of the proposed technique is validated with two different spectroscopic techniques (Raman and Fourier transform infrared, FT-IR). In all cases studied, CLPP accompanied by k-Nearest Neighbors (kNN) algorithm was found to outperform any other state-of-the-art pattern recognition techniques.

Is childhood type 1 diabetes a wealth-related disease? An ecological analysis of European incidence rates

Aims/Hypothesis: To describe the epidemiology of childhood-onset Type 1 (insulin-dependent) diabetes in Europe, the EURODIAB collaborative group has established prospective, geographically-defined registers of children diagnosed under 15 years. A total of 16,362 cases were registered by 44 centres during the period 1989-1994. The registers cover a population of approximately 28 million children with most European countries represented. Methods In most centres a primary and a secondary source of ascertainment were used so that the completeness of registration could be assessed by the capture-recapture method. Ecological correlation and regression analyses were used to study the relationship between incidence and various environmental, health and economic indicators. Findings: The standardised average annual incidence rate during the period 1989-94 ranged from 3.2 cases per 100,000 per annum in the Former Yugoslavian Republic of Macedonia to 40.2 cases per 100,000 per annum in Finland. Indicators of national prosperity such as infant mortality (r= -0.64) and gross domestic product (r= 0.58) were most strongly and significantly correlated with incidence rate, and previously-reported associations with coffee consumption (r= 0.51), milk consumption (r= 0.58) and latitude (r= 0.40) were also observed. Conclusion/Interpretation: The wide variation in childhood type 1 diabetes incidence rates within Europe could be partially explained by indicators of national prosperity. These indicators could reflect differences in environmental risk factors such as nutrition or lifestyle that are important in determining a country's incidence rate.

High-dose adenosine overcomes the attenuation of myocardial perfusion reserve caused by caffeine.

Objectives:
We studied whether an increase in adenosine dose overcomes caffeine antagonism on adenosine-mediated coronary vasodilation.

Background:
Caffeine is a competitive antagonist at the adenosine receptors, but it is unclear whether caffeine in coffee alters the actions of exogenous adenosine, and whether the antagonism can be surmounted by increasing the adenosine dose.

Methods:
Myocardial perfusion scintigraphy (MPS) was used to assess adenosine-induced hyperemia in 30 patients before (baseline) and after coffee ingestion (caffeine). At baseline, patients received 140 µg/kg/min of adenosine combined with low-level exercise. For the caffeine study, 12 patients received 140 µg/kg/min of adenosine (standard) and 18 patients received 210 µg/kg/min (high dose) after caffeine intake (200 mg). Myocardial perfusion was assessed semiquantitatively and quantitatively, and perfusion defect was characterized according to the presence of reversibility.

Results:
Caffeine reduced the magnitude of perfusion abnormality induced by standard adenosine as measured by the summed difference score (SDS) (12.0 ± 4.4 at baseline vs. 4.1 ± 2.1 after caffeine, p < 0.001) as well as defect size (18% [3% to 38%] vs. 8% [0% to 22%], p < 0.01), whereas it had no effect on the abnormalities caused by high-dose adenosine (SDS, 7.7 ± 4.0 at baseline vs. 7.8 ± 4.2 after caffeine, p = 0.7). There was good agreement between baseline and caffeine studies for segmental defect category (kappa = 0.72, 95% confidence interval: 0.65 to 0.79) in the high-dose group. An increase in adenosine after caffeine intake was well tolerated.

Conclusions:
Caffeine in coffee attenuates adenosine-induced coronary hyperemia and, consequently, the detection of perfusion abnormality by adenosine MPS. This can be overcome by increasing the adenosine dose without compromising test tolerability.