A critical review on the use of artificial neural networks in olive oil production, characterization and authentication.

Artificial neural networks (ANN) are computationally based mathematical tools inspired by the fundamental cell of the nervous system, the neuron. ANN constitute a simplified artificial replica of the human brain consisting of parallel processing neural elements similar to neurons in living beings. ANN is able to store large amounts of experimental information to be used for generalization with the aid of an appropriate prediction model. ANN has proved useful for a variety of biological, medical, economic and meteorological purposes, and in agro-food science and technology. The olive oil industry has a substantial weight in Mediterranean's economy. The different steps of the olive oil production process, which include olive tree and fruit care, fruit harvest, mechanical and chemical processing, and oil packaging have been examined in depth with a view to their optimization, and so have the authenticity, sensory properties and other quality-related properties of olive oil. This paper reviews existing literature on the use of bioinformatics predictive methods based on ANN in connection with the production, processing and characterization of olive oil. It examines the state of the art in bioinformatics tools for optimizing or predicting its quality with a view to identifying potential deficiencies or aspects for improvement.

Nitric oxide release from a cucurbituril encapsulated NO-donor.

Controlling S-nitrosothiol decomposition, with the consequent release of nitric oxide, is a topic of great research interest. The incorporation of nitrosomercaptopyridine (SNO+) into the cucurbit[7]uril cavity results in a large increase of its nitrosation equilibrium constant. This effect being a consequence of the preferential stabilization of organic cations by the formation of host : guest complexes with CB7 results in a drastic reduction of the SNO+ denitrosation rate constant. Moreover, SNO+ encapsulation also prevents its decomposition yielding disulfide and nitric oxide. The expulsion of SNO+ from the cucurbituril cavity through the application of a chemical stimulus (competitive binding) results in controlled nitric oxide release as was confirmed by using a NO selective electrode.

A critical review on the applications of artificial neural networks in winemaking technology.

Since their development in 1943, artificial neural networks were extended into applications in many fields. Last twenty years have brought their introduction into winery, where they were applied following four basic purposes: authenticity assurance systems, electronic sensory devices, production optimization methods, and artificial vision in image treatment tools, with successful and promising results. This work reviews the most significant approaches for neural networks in winemaking technologies with the aim of producing a clear and useful review document.

Is the tiger shark Galeocerdo cuvier a coastal species? Expanding its distribution range in the Atlantic Ocean using at-sea observer data.

The occurrence of tiger shark Galeocerdo cuvier in the Atlantic Ocean was assessed using at-sea observer data from multiple pelagic longline fisheries. Geographic positions of 2764 G. cuvier recorded between 1992 and 2013 and covering a wide area of the Atlantic Ocean were compared with the currently accepted distribution ranges of the species. Most records fell outside those ranges in both the Southern and Northern Hemispheres, which strongly suggests that the distribution range of G. cuvier in the open ocean is considerably larger than previously described.

Application of transit data analysis and artificial neural network in the prediction of discharge of Lor River, NW Spain.

Transit data analysis and artificial neural networks (ANNs) have proven to be a useful tool for characterizing and modelling non-linear hydrological processes. In this paper, these methods have been used to characterize and to predict the discharge of Lor River (North Western Spain), 1, 2 and 3 days ahead. Transit data analyses show a coefficient of correlation of 0.53 for a lag between precipitation and discharge of 1 day. On the other hand, temperature and discharge has a negative coefficient of correlation (-0.43) for a delay of 19 days. The ANNs developed provide a good result for the validation period, with R(2) between 0.92 and 0.80. Furthermore, these prediction models have been tested with discharge data from a period 16 years later. Results of this testing period also show a good correlation, with R(2) between 0.91 and 0.64. Overall, results indicate that ANNs are a good tool to predict river discharge with a small number of input variables.

Multilayer perceptron neural network for flow prediction.

Artificial neural networks (ANNs) have proven to be a tool for characterizing, modeling and predicting many of the non-linear hydrological processes such as rainfall-runoff, groundwater evaluation or simulation of water quality. After proper training they are able to generate satisfactory predictive results for many of these processes. In this paper they have been used to predict 1 or 2 days ahead the average and maximum daily flow of a river in a small forest headwaters in northwestern Spain. The inputs used were the flow and climate data (precipitation, temperature, relative humidity, solar radiation and wind speed) as recorded in the basin between 2003 and 2008. Climatic data have been utilized in a disaggregated form by considering each one as an input variable in ANN(1), or in an aggregated form by its use in the calculation of evapotranspiration and using this as input variable in ANN(2). Both ANN(1) and ANN(2), after being trained with the data for the period 2003-2007, have provided a good fit between estimated and observed data, with R(2) values exceeding 0.95. Subsequently, its operation has been verified making use of the data for the year 2008. The correlation coefficients obtained between the data estimated by ANNs and those observed were in all cases superior to 0.85, confirming the capacity of ANNs as a model for predicting average and maximum daily flow 1 or 2 days in advance.

Cationic reverse micelles create water with super hydrogen-bond-donor capacity for enzymatic catalysis: hydrolysis of 2-naphthyl acetate by alpha-chymotrypsin.

Reverse micelles (RMs) are very good nanoreactors because they can create a unique microenvironment for carrying out a variety of chemical and biochemical reactions. The aim of the present work is to determine the influence of different RM interfaces on the hydrolysis of 2-naphthyl acetate (2-NA) by alpha-chymotrypsin (alpha-CT). The reaction was studied in water/benzyl-n-hexadecyldimethylammonium chloride (BHDC)/benzene RMs and, its efficiency compared with that observed in pure water and in sodium 1,4-bis-2-ethylhexylsulfosuccinate (AOT) RMs. Thus, the hydrolysis rates of 2-NA catalyzed by alpha-CT were determined by spectroscopic measurements. In addition, the method used allows the joint evaluation of the substrate partition constant K(p) between the organic and the micellar pseudophase and the kinetic parameters: catalytic rate constant k(cat), and the Michaelis constant K(M) of the enzymatic reaction. The effect of the surfactant concentration on the kinetics parameters was determined at constant W(0)=[H(2)O]/[surfactant], and the variation of W(0) with surfactant constant concentration was investigated. The results show that the classical Michaelis-Menten mechanism is valid for alpha-CT in all of the RMs systems studied and that the reaction takes place at both RM interfaces. Moreover, the catalytic efficiency values k(cat)/K(M) obtained in the RMs systems are higher than that reported in water. Furthermore, there is a remarkable increase in alpha-CT efficiency in the cationic RMs in comparison with the anionic system, presumably due to the unique water properties found in these confined media. The results show that in cationic RMs the hydrogen-bond donor capacity of water is enhanced due to its interaction with the cationic interface. Hence, entrapped water can be converted into "super-water" for the enzymatic reaction studied in this work.

The use of artificial neural networks to forecast biological atmospheric allergens or pathogens only as Alternaria spores.

The monitoring of atmospheric Alternaria spores is of major importance due to their adverse effects on crops and their role as human allergens. Most species act as plant pathogens, prompting considerable economic losses worldwide on important crops such as potato, tomato or wheat. Fungal spores can also have serious detrimental effects on human health, triggering respiratory diseases and allergenic processes. The aim of this study was not only to examine the relationship between the atmospheric Alternaria spore content and the prevailing meteorological parameters, but also to predict the atmospheric Alternaria spore content in the Northwest Spain using a novel data analysis technique, ANNs (Artificial Neural Networks). A Hirst-type LANZONI VPPS 2000 volumetric 7-day recording sampler was used to collect the airborne spores from 1997 to 2008. Neural networks provided us with a good tool for forecasting Alternaria airborne spore concentration, and thus could help the automation of the prediction system in the aerobiological information diffusion to the population suffering from allergic problems or the prevention of considerable economic worldwide losses on important crops. Our proposed model would be applied to different geographical areas; nevertheless, the adjustment of the model, by using the available and adequate variables, would be realised in each case.

Mitigation of emerging implications of climate change on food production systems.

Crops, livestock and seafood are major contributors to global economy. Agriculture and fisheries are especially dependent on climate. Thus, elevated temperatures and carbon dioxide levels can have large impacts on appropriate nutrient levels, soil moisture, water availability and various other critical performance conditions. Changes in drought and flood frequency and severity can pose severe challenges to farmers and threaten food safety. In addition, increasingly warmer water temperatures are likely to shift the habitat ranges of many fish and shellfish species, ultimately disrupting ecosystems. In general, climate change will probably have negative implications for farming, animal husbandry and fishing. The effects of climate change must be taken into account as a key aspect along with other evolving factors with a potential impact on agricultural production, such as changes in agricultural practices and technology; all of them with a serious impact on food availability and price. This review is intended to provide critical and timely information on climate change and its implications in the food production/consumption system, paying special attention to the available mitigation strategies.

Influence of n-alkyl acids on the percolative phenomena in AOT-based microemulsions.

A study was carried out on the influence of the n-alkyl acid addition on the electric percolation of AOT/iso-octane/water microemulsions ([AOT] = 0.5 M and W= [H(2)O]/[AOT] = 22.2). The observed influence has been explained taking into account the organic nature of these molecules and, hence, their capacity of disturbing the structure of the AOT-film. For these reasons, relationships with their molecular structure (chain length) were analysed.

Simultaneous effect of microemulsions and phase-transfer agents on aminolysis reactions.

The catalytic effect of triethylene glycol dimethyl ether (glyme) on the butylaminolysis of 4-nitrophenylcaprate (NPC) in water/AOT/chlorobenzene microemulsions has been studied. Experimental results show the existence of four simultaneous reaction pathways. One of them takes place at the microemulsion interphase where the rate-determining step of butylaminolysis is the formation of the addition intermediate, T+/-. The locus of the other three pathways is the continuous medium of the microemulsion. These three pathways consist of the decomposition of the addition intermediate catalyzed by butylamine, by glyme, and by both of them. The kinetic model allows us to obtain the value of every rate and distribution constant involved in the overall reaction mechanism. We must emphasize that the reactions located in the continuous medium exhibit a kinetic behavior similar to the corresponding one found in pure chlorobenzene. On the basis of the pseudophase model, the percentage of reaction in each of the microdomains of the microemulsion has been calculated. Likewise, changes in the loci of reaction from the interphase to the continuous medium as a function of catalyst concentration have been proved.

Determination of pyridine-2-azo-p-dimethylaniline acidity constants by spectra resolution methodology.

The influence of acidity upon the pyridine-2-azo-p-dimethylaniline (PADA) absorption spectrum has been studied. The obtained results allowed us to calculate the acidity constants of PADA. The spectra resolution method has been used to determinate the constants. The absorption spectrum was decomposed in two sub-bands for the neutral form of the indicator, one for the monoprotonated molecule and another more for the diprotonated structure. The quantitative analysis of relative areas variation with the medium acidity allows us to obtain the equilibrium constants of PADA prolongation. The obtained values are in good agreement with the values reported in the literature.

In search of fully uncomplexed cyclodextrin in the presence of micellar aggregates.

The chemical behavior of beta-cyclodextrin/nonionic surfactant mixed systems has been investigated using the basic hydrolysis of N-methyl-N-nitroso-p-toluenesulfonamide as a chemical probe. The experimental results prove that at the cmc, there are significant quantities of uncomplexed beta-CD in equilibrium with the micellar aggregates. In contrast to the expected situation, the percentage of uncomplexed beta-CD in equilibrium with the micellar system increases on increasing the hydrophobicity of the surfactant molecule. This behavior is due to the existence of two simultaneous processes: complexation of surfactant monomers by cyclodextrin and the process of self-assembly to form micellar aggregates. The autoaggregation of surfactant monomers is expected to be more important than the complexation process in this mixed system. Varying the hydrophobicity of the surfactant monomer enabled us to determine that the percentages of uncomplexed cyclodextrin in equilibrium with the micellar system were in the range of 5-95%.

Ester aminolysis by morpholine in AOT-based water-in-oil microemulsions.

A kinetic study of the aminolysis of p-nitrophenyl acetate (NPA) by morpholine (MOR) in AOT/isooctane/water (w/o) microemulsions was conducted. Based on the solubilities of NPA and MOR in water and isooctane, both compounds partition between the continuous medium, interface and water microdroplets of the microemulsion. Because the rate of the aminolysis reaction decreases with decreasing polarity of the solvent, the reaction must take place to a negligible extent in the continuous medium relative to the interface and the aqueous microdroplets. We used the pseudo-phase model to determine the rate constants at the interface, k(2)(i), and in the water microdroplets, k(2)(w). Both k(2)(i) and k(2)(w) were found to be independent of W in the aminolysis of NPA by MOR. This is a result of the expected increase in k(2)(w) on decreasing W being offset by the decrease in k(2)(i) with increase in the water content of the system. Based on the results, the reaction takes place to an extent of only 16% in the water microdroplets at W=40, the proportion decreasing with decreasing water content.

Influence of aza crown ethers on the electric percolation of AOT/isooctane/water (w/o) microemulsions.

A study was carried out on the influence of different aza crown ethers on the electric percolation of AOT/isooctane/water microemulsions. A dual behavior of the aza crown ethers with regard to the percolative phenomenon was observed: low additive concentration causes an increase in the percolation temperature, whereas at high additive concentration a reduction in the percolation temperature of the system was observed. This dual behavior allowed us to define the compensation concentration, which corresponds the aza crown ether concentration at which there is no effect on the percolative phenomenon. We observed a correlation between the effect exerted by the aza crown ethers and the size of the cavity. This shows the importance of the capacity to complexate Na(+) and solubilize it in the interface and the continuous medium on the electric percolation. We also observed a correlation between the effect of the aza crown ethers on the percolation temperature and their external size. This shows the importance of their inclusion in the interface on the percolative phenomenon. Such an inclusion modifies the properties of the AOT film, facilitating the exchange of matter between droplets. A satisfactory multiparametric correlation between the compensation concentration, the distribution of the aza crown ether between water and 1-octanol, and the number of electron-donor atoms (O and N) in the crown ether was obtained. The effects have been compared with those corresponding to the crown ethers.

Retention of phosphorus by iron and aluminum-oxides-coated quartz particles.

The capacity of adsorption of P on Fe and Al-oxides-coated quartz sand has been studied. The adsorption process has been described as Freundlich and Langmuir isotherms. In all cases Langmuir equation yields better fits than Freundlich equation. The covering quartz particles with Fe and Al oxides provide a high capacity adsorption and immobilization of P from natural and waste waters. The values obtained for adsorption, desorption and adsorption/desorption cycles show that Al oxides particles provide an excellent material for construction of a P removal system for waste waters. The characteristics of this material would allow the design of a complementary filtration system to reduce P levels in the effluent, reducing contamination risks and combating eutrophication of nearby watercourses.

Airborne castanea pollen forecasting model for ecological and allergological implementation.

Castanea sativa Miller belongs to the natural vegetation of many European deciduous forests prompting impacts in the forestry, ecology, allergological and chestnut food industry fields. The study of the Castanea flowering represents an important tool for evaluating the ecological conservation of North-Western Spain woodland and the possible changes in the chestnut distribution due to recent climatic change. The Castanea pollen production and dispersal capacity may cause hypersensitivity reactions in the sensitive human population due to the relationship between patients with chestnut pollen allergy and a potential cross reactivity risk with other pollens or plant foods. In addition to Castanea pollen's importance as a pollinosis agent, its study is also essential in North-Western Spain due to the economic impact of the industry around the chestnut tree cultivation and its beekeeping interest. The aim of this research is to develop an Artificial Neural Networks for predict the Castanea pollen concentration in the atmosphere of the North-West Spain area by means a 20years data set. It was detected an increasing trend of the total annual Castanea pollen concentrations in the atmosphere during the study period. The Artificial Neural Networks (ANNs) implemented in this study show a great ability to predict Castanea pollen concentration one, two and three days ahead. The model to predict the Castanea pollen concentration one day ahead shows a high linear correlation coefficient of 0.784 (individual ANN) and 0.738 (multiple ANN). The results obtained improved those obtained by the classical methodology used to predict the airborne pollen concentrations such as time series analysis or other models based on the correlation of pollen levels with meteorological variables.

Influence of glymes upon percolative phenomena in AOT-based microemulsions.

A study was carried out on the influence of different polyethylene glycol dimethyl ethers (glymes) on the conductance percolation of AOT/isooctane/water microemulsions. The glymes used were chosen on the basis of this chain length (the number of polymeric units). In all cases we observed a decrease in the percolation threshold on increasing the amount of a glyme added to the microemulsion. We observed a correlation between the effect exerted by the glyme and its chain length, which shows the importance of including them in the interface for the percolative phenomenon. Such inclusion modifies the properties of the AOT film, facilitating the exchange of matter between droplets.

Mixed micelles of alkylamines and cetyltrimethylammonium chloride.

The influence of chain length and the nature of the head group on the composition of micelles of a binary mixture of cetyltrimethylammonium chloride with both unsubstituted and N-substituted n-octyl, n-decyl, and n-lauryl amines was established from the variation of the critical micelle concentration (cmc) as a function of the solution composition. A synergistic effect was observed in all instances that were found to be correlated with chain length and the type of N-substituent on the alkylamine head group. Experimental data were compared with theoretical predictions based on the equilibrium between micelles and monomers in solution. The Motomura treatment was used to determine the composition of each compound in the mixed micelles (Xi(m)). Mixing nonideality was expressed in terms of the molecular interaction parameter (beta12) as determined using the theory of Holland and Rubingh. Finally, the molecular thermodynamic model for mixed surfactant systems developed by Puvvada and Blankschtein was used to estimate the micellization free energy (DeltaGM) and to evaluate the synergistic phenomenon.