Review and meta-analysis of the short-term effects of a vegetable oil emulsion on food intake

Several short-term studies have investigated the effects of a vegetable oil emulsion on subsequent food intake, although findings have been inconsistent. This work aimed to review all studies, and investigate differences in study outcomes based on methodology. All known studies were identified. Data were abstracted from published studies (n = 7). Details of unpublished studies were gained from investigators/sponsors (n = 5), or were unavailable for reasons of confidentiality (n = 4). Available data were combined using meta-analyses. A combined appetite suppressant effect of the emulsion compared with control was found for test meal intake at approximately 4, 12 and 36 h post-treatment: smallest combined mean difference (random effects model) = 0.53 MJ (95% confidence interval 0.20, 0.86), P < 0.01. However, considerable heterogeneity (variability) between study results was also found (smallest I2 = 94%, P < 0.01), questioning the predictive validity of the above findings. Meta-regression suggested this heterogeneity to be related to differences in the processed nature of the product, treatment dose and in particular year of study (smallest B = 0.54, 95% confidence interval 0.06, 1.03, P = 0.04), although again heterogeneity was found. The only consistent finding was a lack of effect on food intake 4 h post-preload in studies conducted after 2003. These results suggest a small but inconsistent appetite suppressant effect of the vegetable oil emulsion. However, due to the large heterogeneity, no definitive conclusions can be drawn.

Evaluation of methodologies to determine vegetable oil species present in oil mixtures: Proposition of an approach to meet the EU legislation demands for correct vegetable oils labelling

Refined vegetable oils are widely used in the food industry as ingredients or components in many processed food products in the form of oil blends. To date, the generic term 'vegetable oil' has been used in the labelling of food containing oil blends. With the introduction of new EU Regulation for Food Information (1169/2011) due to take effect in 2014, the oil species used must be clearly identified on the package and there is a need for development of fit for purpose methodology for industry and regulators alike to verify the oil species present in a product. The available methodologies that may be employed to authenticate the botanical origin of a vegetable oil admixture were reviewed and evaluated. The majority of the sources however, described techniques applied to crude vegetable oils such as olive oil due to the lack of refined vegetable oil focused studies. Nevertheless, DNA based typing methods and stable isotopes procedures were found not suitable for this particular purpose due to several issues. Only a small number of specific chromatographic and spectroscopic fingerprinting methods in either targeted or untargeted mode were found to be applicable in potentially providing a solution to this complex authenticity problem. Applied as a single method in isolation, these techniques would be able to give limited information on the oils identity as signals obtained for various oil types may well be overlapping. Therefore, more complex and combined approaches are likely to be needed to identify the oil species present in oil blends employing a stepwise approach in combination with advanced chemometrics. Options to provide such a methodology are outlined in the current study.

Identification of vegetable oil botanical speciation in refined vegetable oil blends using an innovative combination of chromatographic and spectroscopic techniques

European Regulation 1169/2011 requires producers of foods that contain refined vegetable oils to label the oil types. A novel rapid and staged methodology has been developed for the first time to identify common oil species in oil blends. The qualitative method consists of a combination of a Fourier Transform Infrared (FTIR) spectroscopy to profile the oils and fatty acid chromatographic analysis to confirm the composition of the oils when required. Calibration models and specific classification criteria were developed and all data were fused into a simple decision-making system. The single lab validation of the method demonstrated the very good performance (96% correct classification, 100% specificity, 4% false positive rate). Only a small fraction of the samples needed to be confirmed with the majority of oils identified rapidly using only the spectroscopic procedure. The results demonstrate the huge potential of the methodology for a wide range of oil authenticity work.

A new analytical approach for the detection of palm oil in vegetable oil blends

The new Food Information Regulation (1169/2011), dictates that in a refined vegetable oil blend, the type of oil must be clearly identified in the package in contract with current practice where is labelled under the generic and often misleading term “vegetable oil”. With increase consumer awareness in food authenticity, as shown in the recent food scandal with horsemeat in beef products, the identification of the origin of species in food products becomes increasingly relevant. Palm oil is used extensively in food manufacturing and as global demand increases, producing countries suffer from the aftermath of intensive agriculture. Even if only a small portion of global production, sustainable palm oil comes in great demand from consumers and industry. It is therefore of interest to detect the presence of palm oil in food products as consumers have the right to know if it is present in the product or not, mainly from an ethical point of view. Apart from palm oil and its derivatives, rapeseed oil and sunflower oil are also included. With DNA-based methods, the gold standard for the detection of food authenticity and species recognition deemed not suitable in this analytical problem, the focus is inevitably drawn to the chromatographic and spectroscopic methods. Both chromatographic (such as GC-FID and LC-MS) and spectroscopic methods (FT-IR, Raman, NIR) are relevant. Previous attempts have not shown promising results due to oils’ natural variation in composition and complex chemical signals but the suggested two-step analytical procedure is a promising approach with very good initial results.

Identification of oil mixtures in extracted and refined vegetable oils

Identification of adulteration in mechanically extracted oils or the botanical origin of refined vegetable oil blends can be effectively achieved through the combination of spectroscopic methods and chemometric techniques. Chromatographic methods remain highly relevant but suffer from various limitations which derive from natural compositional variation. Modern multivariate techniques have demonstrated that it is possible to identify patterns and effectively classify unknown samples in both cases. Development of robust analytical methodologies requires however vigorous validation. Spectroscopic methods combined with chemometric techniques lack established validation protocols and this might hinder their use by law enforcement authorities. 

CsF and alumina: A mixed homogeneous-heterogeneous catalytic system for the transesterification of sunflower oil with methanol

The activity and nature (i e heterogeneous and/or homogeneous) of catalysts based on CsF supported on alpha-Al2O3 were investigated for the transesterification of vegetable oil with methanol. The effect of the activation temperature, CsF loading and the reusability in a recirculating reactor were first studied CsF/alpha-Al2O3 exhibited the highest activity for a CsF loading of 0 6 mmol/g and when activated at 120 degrees C An important aspect of this study is the effect of CsF leaching into the reaction mixture, which is attributed to the high solubility of CsF in methanol, leading to a complete loss of activity after one run It was Identified that the activity of the catalyst resulted from a synergy between alumina and dissolved CsF, the presence of both compounds being absolutely necessary to observe any conversion The use of an alumina with a higher surface area resulted in a far greater reaction rate, showing that the concentration of surface site on the oxide (probably surface hydroxyl) was rate-limiting in the case of the experiments using the low surface area alpha-Al2O3 This work emphasizes that combined homogeneous-heterogeneous catalytic systems made from the blending of the respective catalysts can be used to obtain high conversion of vegetable oil to biodiesel. Despite the homogeneous/heterogeneous dual character, such a catalytic system may prove valuable in developing a simple and cost-effective continuous catalytic process for biodiesel production (C) 2010 Elsevier B V All rights reserved

Identifying oil species in oil mixtures

Detection of adulteration of non-processed vegetable oil with lesser value seed oils (classic example is hazelnut in virgin olive oil) has been in the centre of scientific attention for many years and several chemical methods were proposed. The recent EC Regulation 1169/2011, however, introduces necessity for different analytical method in a more complicated matrix. From the end of 2014, food businesses required to declare the composition of the refined oil mixture in the food product label. This creates a gap since there is no analytical method currently available to perform such analysis. In the first phase the work focused on 100% oil blends of various oil species of palm oil (and derivatives), sunflower and rapeseed oil before expanding to foodstuffs. Chromatographic methods remain highly relevant although suffer from various limitations which derive from natural compositional variation. Modern multivariate techniques based on machine learning algorithms, however, when applied in FTIR, Raman spectroscopic data have a strong potential in tackling the problem.

Selective Hydrogenation of Acetylene over Pd-Boron Catalysts: A Density Functional Theory Study

Boron-modified Pd catalysts have shown excellent performance for the selective hydrogenation of alkynes experimentally. In the current work, we investigated the hydrogenation of acetylene on boron-modified Pd(111) and Pd(211) surfaces, utilizing density functional theory calculations. The activity of acetylene hydrogenation has been studied by estimating the effective barrier of the whole process. The selectivity of ethylene formation is investigated from a comparison between the desorption and the hydrogenation of ethylene as well as comparison between the ethylene and the 1,3-butadiene formation. Formation of subsurface carbon and hydrogen on both boron-modified Pd(111) and Pd(211) surfaces has also been evaluated, since these have been reported to affect both the activity and the selectivity of acetylene hydrogenation to produce ethylene on Pd surfaces. Our results provide some important insights into the Pd B catalysts for selective hydrogenation of acetylene and also for more complex hydrogenation systems, such as stereoselective hydrogenation of longer chain alkynes and selective hydrogenation of vegetable oil.

Generating Data Augmented Spectroscopic Data For Performance Enhancement

The application of chemometrics in food science has revolutionized the field by allowing the creation of models able to automate a broad range of applications such as food authenticity and food fraud detection. In order to create effective and general models able to address the complexity of real life problems, a vast amount of varied training samples are required. Training dataset has to cover all possible types of sample and instrument variability. However, acquiring a varied amount of samples is a time consuming and costly process, in which collecting samples representative of the real world variation is not always possible, specially in some application fields. To address this problem, a novel framework for the application of data augmentation techniques to spectroscopic data has been designed and implemented. This is a carefully designed pipeline of four complementary and independent blocks which can be finely tuned depending on the desired variance for enhancing model's robustness: a) blending spectra, b) changing baseline, c) shifting along x axis, and d) adding random noise.
This novel data augmentation solution has been tested in order to obtain highly efficient generalised classification model based on spectroscopic data. Fourier transform mid-infrared (FT-IR) spectroscopic data of eleven pure vegetable oils (106 admixtures) for the rapid identification of vegetable oil species in mixtures of oils have been used as a case study to demonstrate the influence of this pioneering approach in chemometrics, obtaining a 10% improvement in classification which is crucial in some applications of food adulteration.

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.

Analytical strategies for the early quality and safety assurance in the global feed chain. Approaches for nitrogen adulterants in soybean meal and mineral and transformer oils in vegetable oils.

In the past decade, several major food safety crises originated from problems with feed. Consequently, there is an urgent need for early detection of fraudulent adulteration and contamination in the feed chain. Strategies are presented for two specific cases, viz. adulterations of (i) soybean meal with melamine and other types of adulterants/contaminants and (ii) vegetable oils with mineral oil, transformer oil or other oils. These strategies comprise screening at the feed mill or port of entry with non-destructive spectroscopic methods (NIRS and Raman), followed by post-screening and confirmation in the laboratory with MS-based methods. The spectroscopic techniques are suitable for on-site and on-line applications. Currently they are suited to detect fraudulent adulteration at relatively high levels but not to detect low level contamination. The potential use of the strategies for non-targeted analysis is demonstrated.

Deactivation of Oxidation Catalysts by Oil-Derived Sulphur

The most common mode of deactivation suffered by catalysts fitted to two-stroke engines has traditionally been thermal degradation, or even meltdown, of the washcoat and substrate. The high temperatures experienced by these catalysts are caused by excessively high concentrations of HC and CO in the exhaust gas which are, in turn, caused by a rich AFR and the loss of neat fuel to the exhaust during the scavenging period. The effects of catalyst poisoning due to additives in the oil is often regarded as a secondary, or even negligible, deactivating mechanism in two-stroke catalysts and has therefore received little attention. However, with the introduction of direct in-cylinder fuel injection to some larger versions of this engine, the quantities of HC escaping to the exhaust can be reduced to levels similar to those found on four-stroke gasoline engines. Under these conditions, the effects of poisoning are much more significant to catalyst durability, particularly for crankcase scavenged derivatives which allow considerable quantities of oil to escape into the exhaust in a neat, or partially burned form. In this paper the effects of oil-derived sulphur on catalyst performance are examined using specialised test apparatus. The oil used throughout the study was formulated specifically for a two-stroke engine fitted with direct in-cylinder fuel injection. The sulphur content of this oil was 0.21% by mass and particular attention was paid to the role of this element in the resulting deactivation. The catalyst was also designed for two-stroke applications and contained a high palladium loading of 300g/ft3 (28g/l) to prolong the life of the catalyst. It was found that the sulphur caused permanent deactivation of the CO reaction and increased the light-off temperature by around 40oC after oiling for 60 hours. This deactivation was progressive and led to a reduction in surface area of the washcoat, particularly in the micropores of around 5Å diameter. By using a validated catalyst model the change in surface area of the precious metal was estimated. It was found that the simulated palladium surface area had to be reduced by a factor of around 7.5 to produce the light-off temperature of the deactivated catalyst. Conversely, the light-off temperature of the C3H6 reaction was barely affected by the deactivation.