47 resultados para Olive paste


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Extra virgin olive oil is produced in the form of a

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Using caffeic acid and p-hydroxybenzoic acid as templates, two molecularly imprinted polymers (MIPs) were prepared that were used for isolation of polyphenols from olive mill waste water samples (OMWWs) without previous pre-treatment. For the preparation of the caffeic acid MIPs 4-vinylpyridine, allylurea, allylaniline and methacrylic acid were tested as functional monomers, ethylene glycol dimethylacrylate (EDMA), pentaerythritol trimethylacrylate (PETRA) and divinylbenzene 80 (DVB80) as cross-linkers and tetrahydrofuran as porogen. For p-hydroxybenzoic acid 4-vinylpyridine, allylurea and allylaniline were tested as functional monomers, EDMA and PETRA as cross-linkers and acetonitrile as porogen. The performance of the synthesized polymers was evaluated against seven structurally related compounds by means of polymer-based HPLC. The two polymers that presented the most interesting properties were further evaluated by batch rebinding and from the derived isotherms their capacity and binding strength were determined. Using solid-phase extraction (SPE), their ability to recognize and bind the template molecule from an aqueous solution as well as the pH dependence of the binding strength were explored. After establishing the best SPE protocol, an aqueous model mixture of compounds and a raw OMWWs sample were loaded on the two best polymers. The result of the consecutive use of the two polymers on the same sample was explored. It was concluded that acidic conditions favour the recognition abilities of both polymers and that they can be used for a quick and efficient isolation of the polyphenol fraction directly from raw OMWW.

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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.

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Virgin olive oil is a high quality natural product obtained only by physical means. In addition to triacylglycerols it contains nutritionally important polar and non-polar antioxidant phenols and other bioactive ingredients. The polar fraction is a complex mixture of phenolic acids, simple phenols, derivatives of the glycosides oleuropein and ligstroside, lignans, and flavonoids. These compounds contribute significantly to the stability, flavor, and biological value of virgin olive. In the various stages of production, during storage and in the culinary uses, polar phenols and other valuable bioactive ingredients may be damaged. Oxidation, photo-oxidation, enzymic hydrolysis and heating at frying temperatures have a serious adverse effect. Due to the biological importance of the oil and its unique character, analytical methods have been developed to evaluate antioxidant activity or analyse complex phenol mixtures. These are based on radical scavenging assays and chromatographic techniques. Hyphenated methods are also used including liquid chromatography-mass spectrometry and liquid chromatography-nuclear magnetic resonance spectroscopy.

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The biosorption process of anionic dye Alizarin Red S (ARS) and cationic dye methylene blue (MB) as a function of solution pH, initial concentration and contact time onto olive stone (OS) biomass has been investigated. The main objectives of the current study are to: (i) study the chemistry and the mechanism of ARS and MB biosorption onto olive stone and the type of OS–ARS, MB interactions occurring, (ii) study the biosorption equilibrium and kinetic experimental data required for the design and operation of column reactors. Equilibrium biosorption isotherms and kinetics were also examined. Experimental equilibrium data were fitted to four different isotherms by non-linear regression method, however, the biosorption experimental data for ARS and MB dyes were well interpreted by the Temkin and Langmuir isotherms, respectively. The maximum monolayer adsorption capacity for ARS and MB dyes were 109.0 and 102.6 mg/g, respectively. The kinetic data of the two dyes could be better described by the pseudo second-order model. The data showed that olive stone can be effectively used for removing dyes from wastewater.

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In this work, olive stone (OS) was utilized to investigate its capacity as biosorbent for methylene blue (MB) and Cr(III), which are usually present in textile industry effluents. Equilibrium and kinetic experiments were performed in batch experiments. The biosorption process followed pseudo-second-order kinetics. The equilibrium data were fitted with several models, but Langmuir and Sips models best reproduced the experimental results. Maximum biosorption capacities were 3.296 mg/g (0.0116 mmol/g) and 4.990 mg/g (0.0960 mmol/g) for MB and Cr(III), respectively. Several operation variables, such as
biosorbent mass, flow rate, and initial concentration on the removal of dye and metal, were evaluated in column system. The removal efficiency improved as OS mass increased and decreased when flow rate and initial concentration increased. Also, MB uptake was substantially decreased by increasing the initial concentration of Cr(III), ranging from 6.09 to 2.75 mg/g. These results show that the presence of Cr(III) significantly modifies the biosorption capacity of MB by the OS. These results suggest that OS is a potential low-cost food industry waste for textile industry wastewater treatment.

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The biosorption process of anionic dye Alizarin Red S (ARS) and cationic dye methylene blue (MB) as a function of contact time, initial concentration and solution pH onto olive stone (OS) biomass has been investigated. Equilibrium biosorption isotherms in single and binary systems and kinetics in batch mode were also examined. The kinetic data of the two dyes were better described by the pseudo second-order model. At low concentration, ARS dye appeared to follow a two-step diffusion process, while MB dye followed a three-step diffusion process. The biosorption experimental data for ARS and MB dyes were well suited to the Redlich-Peterson isotherm. The maximum biosorption of ARS dye, qmax = 16.10 mg/g, was obtained at pH 3.28 and the maximum biosorption of MB dye, qmax = 13.20 mg/g, was observed at basic pH values. In the binary system, it was indicated that the MB dye diffuses firstly inside the biosorbent particle and occupies the biosorption sites forming a monodentate complex and then the ARS dye enters and can only bind to untaken sites; forms a tridentate complex with OS active sites.

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The growth of the construction industry worldwide poses a serious concern on the sustainability of the building material production chain, mainly due to the carbon emissions related to the production of Portland cement. On the other hand, valuable materials from waste streams, particularly from the metallurgical industry, are not used at their full potential. Alkali activated concrete (AAC) has emerged in the last years as a promising alternative to traditional Portland cement based concrete for some applications. However, despite showing remarkable strength and durability potential, its utilisation is not widespread, mainly due to the lack of broadly accepted standards for the selection of suitable mix recipes fulfilling design requirements, in particular workability, setting time and strength. In this paper, a contribution towards the design development of AAC synthetized from pulverised fuel ash (60%) and ground granulated blast furnace slag (40%) activated with a solution of sodium hydroxide and sodium silicate is proposed. Results from a first batch of mixes indicated that water content influences the setting time and that paste content is a key parameter for controlling strength development and workability. The investigation indicated that, for the given raw materials and activator compositions, a minimum water to solid (w/s) ratio of 0.37 was needed for an initial setting time of about 1 hour. Further work with paste content in the range of 30% to 33% determined the relationship between workability and strength development and w/s ratio and paste content. Strengths in the range of 50 - 60 MPa were achieved.

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Alkali activated binders, based on ash and slag, also known as geopolymers, can play a key role in reducing the carbon footprint of the construction sector by replacing ordinary Portland cement in some concretes. Since 1970s, research effort has been ongoing in many research institutions. In this study, pulverized fuel ash (pfa) from a UK power plant, ground granulated blast furnace slag (ggbs) and combinations of the two have been investigated as geopolymer binders for concrete applications. Activators used were sodium hydroxide and sodium silicate solutions. Mortars with sand/binder ratio of 2.75 with several pfa and ggbs combinations have been mixed and tested. The optimization of alkali dosage (defined as the Na2O/binder mass ratio) and modulus (defined as the Na2O/SiO2 mass ratio) resulted in strengths in excess of 70 MPa for tested mortars. Setting time and workability have been considered for the identification of the best combination of pfa/ggbs and alkali activator dosage for different precast concrete products. Geopolymer concrete building blocks have been replicated in laboratory and a real scale factory trial has been successfully carried out. Ongoing microstructural characterization is aiming to identify reaction products arising from pfa/ggbs combinations.

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Natural pozzolans are raw materials from geological deposits with a range of chemical compositions that when combined with suitable alkali activators can be converted to geopolymer cement for concrete production. In this paper the concept of adding mineral additives to enhance the properties of geopolymer cement is introduced. Taftan andesite, a natural Iranian pozzolan, was used to study the effect of adding mineral additives such as kaolinite, lime and other calcined pozzolans on the compressive strength of geopolymer cement under both normal and autoclave curing. Scanning electron microscopy (SEM)/energy dispersive X-ray (EDX) was used to determine the composition of the gel phase in both alkali-activated Taftan pozzolan with and without mineral additions. The work has shown that deficiencies in SiO2, Al2O3 and CaO content in the raw natural pozzolan can be compensated for by adding mineral additives for enhanced properties.

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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.