An Electronic Nose as a Non-Destructive Analytical Tool to Identify the Geographical Origin of Portuguese Olive Oils from Two Adjacent Regions.

The geographical traceability of extra virgin olive oils (EVOO) is of paramount importance for oil chain actors and consumers. Oils produced in two adjacent Portuguese regions, Côa (36 oils) and Douro (31 oils), were evaluated and fulfilled the European legal thresholds for EVOO categorization. Compared to the Douro region, oils from Côa had higher total phenol contents (505 versus 279 mg GAE/kg) and greater oxidative stabilities (17.5 versus 10.6 h). The majority of Côa oils were fruity-green, bitter, and pungent oils. Conversely, Douro oils exhibited a more intense fruity-ripe and sweet sensation. Accordingly, different volatiles were detected, belonging to eight chemical families, from which aldehydes were the most abundant. Additionally, all oils were evaluated using a lab-made electronic nose, with metal oxide semiconductor sensors. The electrical fingerprints, together with principal component analysis, enabled the unsupervised recognition of the oils' geographical origin, and their successful supervised linear discrimination (sensitivity of 98.5% and specificity of 98.4%; internal validation). The E-nose also quantified the contents of the two main volatile chemical classes (alcohols and aldehydes) and of the total volatiles content, for the studied olive oils split by geographical origin, using multivariate linear regression models (0.981 ≤ R2 ≤ 0.998 and 0.40 ≤ RMSE ≤ 2.79 mg/kg oil; internal validation). The E-nose-MOS was shown to be a fast, green, non-invasive and cost-effective tool for authenticating the geographical origin of the studied olive oils and to estimate the contents of the most abundant chemical classes of volatiles.

Effect of Extraction Method on the Bioactive Composition, Antimicrobial Activity and Phytotoxicity of Pomegranate By-Products.

Pomegranate by-products can be an asset to the food industry due to the richness in bioactive and antimicrobial compounds. This work studied the influence of conventional solvent and sonication-assisted extraction methods on the bioactive profile, antimicrobial properties, and phytotoxicity effect of the peels and seeds extracts from Acco, Big Full, and Wonderful pomegranate cultivars. The bioactive composition of the extracts was evaluated for the content of total phenolics, total flavonoids, and antioxidant activity (expressed as the half-maximal inhibitory concentration-IC50) by spectrophotometric methods, while the tannins were determined by titration and the anthocyanins were estimated by the pH-differential method. For the evaluation of the antimicrobial activity, the disk diffusion method of Kirby-Bauer was adapted through inhibition halos against Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, Bacillus cereus, and Yarrowia lipolytica. The extracts' phytotoxicity was evaluated in vitro on garden-cress seeds. Extracts from conventional extraction were richer in total phenolics, expressed as gallic acid equivalents (0.16-0.73 mg GAE/mg extract), while those from sonication-assisted extraction had higher contents of total flavonoids, expressed as catechin equivalents (0.019-0.068 mg CATE/mg extract); anthocyanins, expressed as cyanidin-3-glucoside (0.06-0.60 µg C3G/mg, dry basis); and antioxidant activity (IC50, 0.01-0.20 mg/mL). All extracts were more effective against Gram-positive bacteria and yeasts than Gram-negative bacteria. In general, the sonication-assisted extracts led to higher inhibition halos (8.7 to 11.4 mm). All extracts presented phytotoxicity against garden-cress seeds in the tested concentrations. Only the lowest concentration (0.003 mg/mL) enabled the germination of seeds and root growth, and the sonication-assisted extracts showed the highest Munoo-Liisa vitality index (51.3%). Overall, sonication-assisted extraction obtained extracts with greater bioactive and antimicrobial potential and less phytotoxicity.

Pomegranate Peels and Seeds as a Source of Phenolic Compounds: Effect of Cultivar, By-Product, and Extraction Solvent.

The nutraceutical properties of Punica granatum L. are not restricted to the edible portion of the fruit but also to the peels and seeds, flowers, leaves, and tree bark. The recovery and valorization of the peel and seeds (ca. 50% of the whole fruit), besides the positive environmental impact, can be viewed as a source of natural bioactive compounds. Thus, the bioactive properties of extracts of pomegranate peel and seeds from Acco and Wonderful known cultivars, as well as of the novel Big Full cultivar, were evaluated. The dried and ground pomegranate by-products were submitted to a conventional solid/liquid extraction with ethanol/water mixtures (0%, 25%, 50%, and 75% of EtOH, v/v). The obtained extracts were characterized in terms of total phenolic compounds (TPC), total flavonoids (TF), and antioxidant activity (AA), determined by the DPPH radical scavenging activity and expressed as IC50 (half maximum inhibitory concentration). With the exception of the Acco cultivar, the extraction yield (EY) was higher for peels, whose extracts showed higher TPC, TF, and IC50 (lower AA). The extracts obtained from the by-products of the Big Full cultivar had a statistically higher overall bioactive potential (TPC: 0.36 mg GAE/mg extract; TF: 0.031 mg CATE/mg extract; IC50: 0.51 mg/mL) compared to the other two studied cultivars. Furthermore, the EY was enhanced by solvents richer in ethanol (50-75%), allowing obtaining extracts richer in TPC and TF with higher AA. Finally, it was shown that EY combined with bioactive data allowed a satisfactory principal component unsupervised differentiation of the pomegranate extracts according to the type of by-product used.

Bioinspired Silk Fibroin-Based Composite Grafts as Bone Tunnel Fillers for Anterior Cruciate Ligament Reconstruction.

Anterior cruciate ligament (ACL) replacement is still a big challenge in orthopedics due to the need to develop bioinspired implants that can mimic the complexity of bone-ligament interface. In this study, we propose biomimetic composite tubular grafts (CTGs) made of horseradish peroxidase (HRP)-cross-linked silk fibroin (SF) hydrogels containing ZnSr-doped ß-tricalcium phosphate (ZnSr-ß-TCP) particles, as promising bone tunnel fillers to be used in ACL grafts (ACLGs) implantation. For comparative purposes, plain HRP-cross-linked SF hydrogels (PTGs) were fabricated. Sonication and freeze-drying methodologies capable of inducing crystalline ß-sheet conformation were carried out to produce both the CTGs and PTGs. A homogeneous microstructure was achieved from microporous to nanoporous scales. The mechanical properties were dependent on the inorganic powder's incorporation, with a superior tensile modulus observed on the CTGs (12.05 ± 1.03 MPa) as compared to the PTGs (5.30 ± 0.93 MPa). The CTGs presented adequate swelling properties to fill the space in the bone structure after bone tunnel enlargement and provide a stable degradation profile under low concentration of protease XIV. The in vitro studies revealed that SaOs-2 cells adhered, proliferated and remained viable when cultured into the CTGs. In addition, the bioactive CTGs supported the osteogenic activity of cells in terms of alkaline phosphatase (ALP) production, activity, and relative gene expression of osteogenic-related markers. Therefore, this study is the first evidence that the developed CTGs hold adequate structural, chemical, and biological properties to be used as bone tunnel fillers capable of connecting to the ACL tissue while stimulating bone tissue regeneration for a faster osteointegration.

Impact of fresh olive leaves addition during the extraction of Arbequina virgin olive oils on the phenolic and volatile profiles.

Leaves incorporation during the extraction of olive oils can enhance their chemical-sensory quality. Thus, leaves from cvs. Arbequina or Santulhana were added (1%, w/w) during the extraction of Arbequina oils using an Abencor system, being discussed the impacts on the phenolics and volatiles formation enzymatic pathways. Leaves addition contributed to a significant decrease (P-value < 0.05) of the contents of secoiridoids (-11%), C6-aldehydes (-16%), and ester compounds (-22%). This could be tentatively related to a reduction of the enzymatic activity of secoiridoids biosynthesis and lipoxygenase pathways, promoted by the leaves' addition. Moreover, in the presence of leaves, the oils' total contents of phenolics and volatiles were significantly reduced (-7 and -17%, respectively). Contrary, the incorporation of leaves significantly increased (P-value < 0.05) the contents of C6-alcohols (+37%) and the intensities of the green fruity (+25%) and apple (+30%) sensations.

Does water addition during the industrial milling phase affect the chemical-sensory quality of olive oils? The case of cv. Arbequina oils.

At olive oil industrial extraction, water addition is a practice overcoming the formation of thick pastes. The effect of water addition (0 to 6.2%, kgadded water/kgolives), during the industrial milling of cv. Arbequina olives, on the oils' chemical-sensory quality, was evaluated. Despite the extra virgin olive oil classification, compared with the water incorporation (1.2-6.2%), extraction without water addition resulted into oils that showed less primary oxidation (lower peroxide values and K232), greater total phenolic content (+12-22%) and higher oxidative stability (+22-31%). No water addition increased the oils secoiridoids content (+5-13%), mainly oleacein (+27-79%). Oils extracted without water addition had a more intense ripe fruity sensation (≥ +11%) but lower fruit intensities (at least -4%). Thus, the quality and stability of the cv. Arbequina oils can be favoured if extracted without adding water during the olives industrial milling.

A Lab-Made E-Nose-MOS Device for Assessing the Bacterial Growth in a Solid Culture Medium.

The detection and level assessment of microorganisms is a practical quality/contamination indicator of food and water samples. Conventional analytical procedures (e.g., culture methods, immunological techniques, and polymerase chain reactions), while accurate and widely used, are time-consuming, costly, and generate a large amount of waste. Electronic noses (E-noses), combined with chemometrics, provide a direct, green, and non-invasive assessment of the volatile fraction without the need for sample pre-treatments. The unique olfactory fingerprint generated during each microorganism's growth can be a vehicle for its detection using gas sensors. A lab-made E-nose, comprising metal oxide semiconductor sensors was applied, to analyze solid medium containing Gram-positive (Enterococcus faecalis and Staphylococcus aureus) or Gram-negative (Escherichia coli and Pseudomonas aeruginosa) bacteria. The electrical-resistance signals generated by the E-nose coupled with linear discriminant analysis allowed the discrimination of the four bacteria (90% of correct classifications for leave-one-out cross-validation). Furthermore, multiple linear regression models were also established allowing quantifying the number of colony-forming units (CFU) (0.9428 ≤ R2 ≤ 0.9946), with maximum root mean square errors lower than 4 CFU. Overall, the E-nose showed to be a powerful qualitative-quantitative device for bacteria preliminary analysis, being envisaged its possible application in solid food matrices.

The Use of Electronic Nose as Alternative Non-Destructive Technique to Discriminate Flavored and Unflavored Olive Oils.

Cv. Arbequina extra virgin olive oils (EVOO) were flavored with cinnamon, garlic, and rosemary and characterized. Although flavoring significantly affected the physicochemical quality parameters, all oils fulfilled the legal thresholds for EVOO classification. Flavoring increased (20 to 40%) the total phenolic contents, whereas oxidative stability was dependent on the flavoring agent (a slight increase for rosemary and a decrease for cinnamon and garlic). Flavoring also had a significant impact on the sensory profiles. Unflavored oils, cinnamon, and garlic flavored oils had a fruity-ripe sensation while rosemary flavored oils were fruity-green oils. Fruit-related sensations, perceived in unflavored oils, disappeared with flavoring. Flavoring decreased the sweetness, enhanced the bitterness, and did not influence the pungency of the oils. According to the EU regulations, flavored oils cannot be commercialized as EVOO. Thus, to guarantee the legal labelling requirement and to meet the expectations of the market-specific consumers for differentiated olive oils, a lab-made electronic nose was applied. The device successfully discriminated unflavored from flavored oils and identified the type of flavoring agent (90 ± 10% of correct classifications for the repeated K-fold cross-validation method). Thus, the electronic nose could be used as a practical non-destructive preliminary classification tool for recognizing olive oils' flavoring practice.

Application of a lab-made electronic nose for extra virgin olive oils commercial classification according to the perceived fruitiness intensity.

An electronic nose, comprising nine metal oxide sensors, has been built aiming to classify olive oils according to the fruity intensity commercial grade (ripely fruity or light, medium and intense greenly fruity), following the European regulated complementary terminology. The lab-made sensor device was capable to differentiate standard aqueous solutions (acetic acid, cis-3-hexenyl, cis-3-hexen-1-ol, hexanal, 1-hexenol and nonanal) that mimicked positive sensations (e.g., fatty, floral, fruit, grass, green and green leaves attributes) and negative attributes (e.g., sour and vinegary defects), as well as to semi-quantitatively classify them according to the concentration ranges (0.05-2.25 mg/kg). For that, unsupervised (principal component analysis) and supervised (linear discriminant analysis: sensitivity of 92% for leave-one-out cross validation) classification multivariate models were established based on nine or six gas sensors, respectively. It was also showed that the built E-nose allowed differentiating/discriminating (sensitivity of 81% for leave-one-out cross validation) extra virgin olive oils according to the perceived intensity of fruitiness as ripely fruity, light, medium or intense greenly fruity. In conclusion, the gas sensor device could be used as a practical preliminary non-destructive tool for guaranteeing the correctness of olive oil fruitiness intensity labelling.

Impact of the malaxation temperature on the phenolic profile of cv. Cobrançosa olive oils and assessment of the related health claim.

Phenolic compounds contribute to the bioactive properties of olive oil. However, olive oils can only support a health claim concerning the protection against oxidative stress depending on the polyphenolic concentration, requiring effective measures during extraction to preserve/enhance their concentrations. The effect of the malaxation temperature (22, 28 and 34 °C) on the phenolic profile was studied for industrially extracted cv. Cobrançosa oils. Higher malaxation temperatures decreased the contents of the majority of the chromatographically detected compounds (P < 0.05, one-way ANOVA), enabling oils' differentiation. This decreasing trend was observed for hydroxytyrosol and tyrosol bound forms, determinant for the health claim, which were also negatively affected by temperature, despite revealing that all the industrially extracted oils tested supported the health claim. The observed constant free to bound forms ratio showed that the temperature range tested had a minor effect on bound-forms hydrolysis, being both free and bound forms equally affected by temperature.

An electronic tongue as a classifier tool for assessing perfume olfactory family and storage time-period.

The identification of more than three perfumes is difficult and no analytical tool can completely replace the human olfactory system for fragrance classification. Indeed, no analytical system can mimic the human fragrance perception, being the recognition of perfume aroma patterns by conventional or sensor-based analytical tools a challenging task. For the perfume sector, the possibility of applying fast, cost-effective and green analytical devices for perfume analysis would represent a huge economic revenue. Since the perfume aroma pattern will depend on the composition of the liquid phase and on the diffusion properties of their volatile components, this work aimed to apply a potentiometric electronic tongue, comprising non-specific cross-sensitive lipid polymeric membranes, combined with chemometric techniques, as a novel perfume classifier. The multisensors device allowed establishing perfumes' unique fingerprints, which were successfully used to discriminate men from women perfumes, to identify the perfume aroma family (Citric-Aromatic, Floral, Floral-Fruity, Floral-Oriental, Floral-Woody, Woody-Oriental and Woody-Spicy) and, assessing the perfume storage time-period (≤ 9 months; 9-24 months; and, ≥ 24 months). The established linear discriminant models were based on single-run potentiometric profiles gathered by sub-sets of sensors selected using the simulated annealing algorithm, which enabled achieving correct classification rates of 93-100% (for leave-one-out cross-validation procedure). The satisfactory performance of the electronic tongue demonstrates the versatility of the proposed approach as a practical perfume preliminary classifier sensor device, which industrial application may be foreseen in a near future, contributing to a green-sustained economic growth of the perfume industry.

Dataset on free amino acids contents of Serra da Estrela PDO cheeses determined by UPLC-DAD-MS/MS.

The composition of Serra da Estrela PDO cheeses (total fat, total protein, salt and free amino acids) was assessed using NIR spectrophotometry and UPLC-DAD-MS/MS. In total, 24 cheeses were acquired from 6 certified cheesemakers located in 5 different municipalities within the delimited PDO geographical region. Cheeses were produced from raw ewe milk of two autochthonous Portuguese sheep breeds, between November 2017 and March 2018, and were acquired after 45 days of maturation. The data include the mean (and respective standard deviations) levels of moisture (%), total fat (%), total protein (%) and salt (%), obtained by NIR spectrophotometry. As well the mean (and respective standard deviations) of free amino acids contents (mg/100 g of cheese, in wet basis) evaluated using a UPLC-DAD-MS/MS method are shown. The latter data include information regarding 8 essential free amino acids (histidine, leucine-isoleucine, lysine, methionine, phenylalanine, threonine, tryptophan and valine) and 9 non-essential free amino acids (arginine, asparagine, aspartic acid, cysteine, glutamine, glutamic acid, proline, tyrosine and serine). Leucine and isoleucine, being isomers, were quantified together. Leucine-isoleucine, phenylalanine and serine were the most abundant essential free amino acids and cysteine, proline and asparagine were the most abundant non-essential free amino acids. Free amino acids contents depended on the cheese producer as well as on the production time-period.

Serra da Estrela cheese's free amino acids profiles by UPLC-DAD-MS/MS and their application for cheese origin assessment.

Serra da Estrela cheese is a high-value Portuguese Protected Designation of Origin cheese, produced with raw ewe milk. Thus, information regarding its composition is of utmost relevance for both consumers and certified producers. In this work, the chromatographic profiles of free amino acids in cheeses (45 days of maturation, 6 producers located in 5 municipalities and produced from November 2017 to March 2018) were established by UPLC-DAD-MS/MS. The proposed method allowed detecting 19 free amino acids and cystine with overall limits of detection and quantification lower than 44 µmol/L (1.4 mg/100 g cheese, wet matter) and than 134 µmol/L (4.2 mg/100 g cheese, wet matter), respectively. In all cheeses, 17 free amino acids were quantified including 8 essential amino acids (histidine, leucine-isoleucine, lysine, methionine, phenylalanine, threonine, tryptophan and valine) and 9 non-essential amino acids (arginine, asparagine, aspartic acid, cysteine, glutamic acid, glutamine, proline, serine and tyrosine). The amounts of the free amino acids, essential free amino acids, branched chain free amino acids (leucine, isoleucine and valine) plus the free amino acids ratios (mg/g protein) were further used to identify the producer of Serra da Estrela cheeses. Linear discriminant analysis coupled with the simulated annealing variable selection algorithm was used allowing the correct classification of 96% and 90 ±â€¯8% of the samples, for leave-one-out and repeated K-fold cross-validation procedures, respectively. The satisfactory predictive performance pointed out the possibility of using cheeses' amino acids profiles as origin biomarkers for authenticity control, warranting the correctness identification of the cheese producer/brand, which is quite relevant for ensuring the consumer confidence and satisfaction when purchasing this high-value dairy food.

Application of an electronic tongue as a single-run tool for olive oils' physicochemical and sensory simultaneous assessment.

Olive oil is highly appreciated due to its nutritional and organoleptic characteristics. However, a huge compositional variation is observed between olive oils, requiring the use of diverse analytical techniques for its classification including titration, spectrophotometry and chromatography, as well as sensory analysis. Chemical analysis is usually time-consuming, expensive and require skilled technicians, while the sensorial ones are dependent upon individual subjective evaluations, even if performed by trained panellists. This work evaluated and demonstrated the feasibility of using a potentiometric electronic tongue, comprising non-specific lipid polymeric and cross-sensitive sensor membranes, coupled with chemometric tools based on different sub-sets of sensors (from 11 to 14 sensors), to predict key quality parameters of olive oils based on single-run assays. The multivariate linear models established for 23 centenarian olive trees from different cultivars allowed predicting peroxide value, oxidative stability, total phenols and tocopherols contents, CIELAB scale parameters (L*, a* and b* values), as well as 11 gustatory-retronasal positive attributes (green, sweet, bitter, pungent, tomato and tomato leaves, apple, banana, cabbage, fresh herbs and dry fruits) with satisfactory accuracy (0.90 ±â€¯0.07 ≤ R2 ≤ 0.98 ±â€¯0.02 for the repeated K-fold-CV procedure, which ensured that 25% of the data was used for internal-validation purposes). The electronic tongue device had an accuracy statistically similar to that achieved with standard analytical techniques, pointing out the versatility of the device for the fast and simultaneous chemical and sensory analysis of olive oil.

Perception of olive oils sensory defects using a potentiometric taste device.

The capability of perceiving olive oils sensory defects and intensities plays a key role on olive oils quality grade classification since olive oils can only be classified as extra-virgin if no defect can be perceived by a human trained sensory panel. Otherwise, olive oils may be classified as virgin or lampante depending on the median intensity of the defect predominantly perceived and on the physicochemical levels. However, sensory analysis is time-consuming and requires an official sensory panel, which can only evaluate a low number of samples per day. In this work, the potential use of an electronic tongue as a taste sensor device to identify the defect predominantly perceived in olive oils was evaluated. The potentiometric profiles recorded showed that intra- and inter-day signal drifts could be neglected (i.e., relative standard deviations lower than 25%), being not statistically significant the effect of the analysis day on the overall recorded E-tongue sensor fingerprints (P-value = 0.5715, for multivariate analysis of variance using Pillai's trace test), which significantly differ according to the olive oils' sensory defect (P-value = 0.0084, for multivariate analysis of variance using Pillai's trace test). Thus, a linear discriminant model based on 19 potentiometric signal sensors, selected by the simulated annealing algorithm, could be established to correctly predict the olive oil main sensory defect (fusty, rancid, wet-wood or winey-vinegary) with average sensitivity of 75 ± 3% and specificity of 73 ± 4% (repeated K-fold cross-validation variant: 4 folds×10 repeats). Similarly, a linear discriminant model, based on 24 selected sensors, correctly classified 92 ± 3% of the olive oils as virgin or lampante, being an average specificity of 93 ± 3% achieved. The overall satisfactory predictive performances strengthen the feasibility of the developed taste sensor device as a complementary methodology for olive oils' defects analysis and subsequent quality grade classification. Furthermore, the capability of identifying the type of sensory defect of an olive oil may allow establishing helpful insights regarding bad practices of olives or olive oils production, harvesting, transport and storage.

Sensory classification of table olives using an electronic tongue: Analysis of aqueous pastes and brines.

Table olives are highly appreciated and consumed worldwide. Different aspects are used for trade category classification being the sensory assessment of negative defects present in the olives and brines one of the most important. The trade category quality classification must follow the International Olive Council directives, requiring the organoleptic assessment of defects by a trained sensory panel. However, the training process is a hard, complex and sometimes subjective task, being the low number of samples that can be evaluated per day a major drawback considering the real needs of the olive industry. In this context, the development of electronic tongues as taste sensors for defects' sensory evaluation is of utmost relevance. So, an electronic tongue was used for table olives classification according to the presence and intensity of negative defects. Linear discrimination models were established based on sub-sets of sensor signals selected by a simulated annealing algorithm. The predictive potential of the novel approach was first demonstrated for standard solutions of chemical compounds that mimic butyric, putrid and zapateria defects (≥93% for cross-validation procedures). Then its applicability was verified; using reference table olives/brine solutions samples identified with a single intense negative attribute, namely butyric, musty, putrid, zapateria or winey-vinegary defects (≥93% cross-validation procedures). Finally, the E-tongue coupled with the same chemometric approach was applied to classify table olive samples according to the trade commercial categories (extra, 1st choice, 2nd choice and unsuitable for consumption) and an additional quality category (extra free of defects), established based on sensory analysis data. Despite the heterogeneity of the samples studied and number of different sensory defects perceived, the predictive linear discriminant model established showed sensitivities greater than 86%. So, the overall performance achieved showed that the electrochemical device could be used as a taste sensor for table olives organoleptic trade successful classification, allowing a preliminary quality assessment, which could facilitate, in the future, the complex task of sensory panelists.

Sensory intensity assessment of olive oils using an electronic tongue.

Olive oils may be commercialized as intense, medium or light, according to the intensity perception of fruitiness, bitterness and pungency attributes, assessed by a sensory panel. In this work, the capability of an electronic tongue to correctly classify olive oils according to the sensory intensity perception levels was evaluated. Cross-sensitivity and non-specific lipid polymeric membranes were used as sensors. The sensor device was firstly tested using quinine monohydrochloride standard solutions. Mean sensitivities of 14±2 to 25±6 mV/decade, depending on the type of plasticizer used in the lipid membranes, were obtained showing the device capability for evaluating bitterness. Then, linear discriminant models based on sub-sets of sensors, selected by a meta-heuristic simulated annealing algorithm, were established enabling to correctly classify 91% of olive oils according to their intensity sensory grade (leave-one-out cross-validation procedure). This capability was further evaluated using a repeated K-fold cross-validation procedure, showing that the electronic tongue allowed an average correct classification of 80% of the olive oils used for internal-validation. So, the electronic tongue can be seen as a taste sensor, allowing differentiating olive oils with different sensory intensities, and could be used as a preliminary, complementary and practical tool for panelists during olive oil sensory analysis.

A novel approach for honey pollen profile assessment using an electronic tongue and chemometric tools.

Nowadays the main honey producing countries require accurate labeling of honey before commercialization, including floral classification. Traditionally, this classification is made by melissopalynology analysis, an accurate but time-consuming task requiring laborious sample pre-treatment and high-skilled technicians. In this work the potential use of a potentiometric electronic tongue for pollinic assessment is evaluated, using monofloral and polyfloral honeys. The results showed that after splitting honeys according to color (white, amber and dark), the novel methodology enabled quantifying the relative percentage of the main pollens (Castanea sp., Echium sp., Erica sp., Eucaliptus sp., Lavandula sp., Prunus sp., Rubus sp. and Trifolium sp.). Multiple linear regression models were established for each type of pollen, based on the best sensors' sub-sets selected using the simulated annealing algorithm. To minimize the overfitting risk, a repeated K-fold cross-validation procedure was implemented, ensuring that at least 10-20% of the honeys were used for internal validation. With this approach, a minimum average determination coefficient of 0.91 ± 0.15 was obtained. Also, the proposed technique enabled the correct classification of 92% and 100% of monofloral and polyfloral honeys, respectively. The quite satisfactory performance of the novel procedure for quantifying the relative pollen frequency may envisage its applicability for honey labeling and geographical origin identification. Nevertheless, this approach is not a full alternative to the traditional melissopalynologic analysis; it may be seen as a practical complementary tool for preliminary honey floral classification, leaving only problematic cases for pollinic evaluation.

Separation and quantification of the major casein fractions by reverse-phase high-performance liquid chromatography and urea-polyacrylamide gel electrophoresis. Detection of milk adulterations.

The separation and quantification of bovine kappa-, alpha- and beta-caseins by HPLC-UV using an RP column which contained polystyrene-divinilbenzene copolymer based packing was optimized and validated. Gradient elution was carried out at a flow-rate of 1 ml/min and a temperature of 46 degrees C, using a mixture of two solvents. Solvent A was 0.1% trifluoroacetic acid in water and solvent B was acetonitrile-water-trifluoroacetic acid (95:5:0.1). The effluent was monitored by a UV detector at 280 nm. The determinations were performed in the linear range of 0.038-0.377 mg/ml for kappa-casein, 0.188-1.883 mg/ml for alpha-casein and 0.151-1.506 mg/ml for beta-casein. The detection limits were 0.006, 0.019 and 0.015 mg/ml for kappa-casein, alpha-casein and beta-casein, respectively. The validity of the method was verified. The recoveries ranged from 91 to 100% for bovine milk. The precision of the method was also evaluated, the RSD being less than 3.67%. The same HPLC procedure was used for the separation of caprine and ovine caseins. Different chromatographic profiles were obtained for bovine, ovine and caprine milks, although it was only possible to detect and quantify additions of 5% or more of bovine milk to caprine milk. With respect to detection of milk adulterations, electrophoresis using urea-polyacrylamide gel electrophoresis (PAGE) analysis was more sensitive. The evolution of casein proteolysis in cheeses made from bovine milk and cheeses made from ovine milk, during 30 days of ripening was followed by HPLC-UV and urea-PAGE methodologies. The results obtained by these techniques were similar.

Evaluation of healthy and sensory indexes of sweetened beverages using an electronic tongue.

Overconsumption of sugar-sweetened beverages may increase the risk of health problems and so, the evaluation of their glycemic load and fructose-intolerance level is essential since it may allow establishing possible relations between physiologic effects of sugar-rich beverages and health. In this work, an electronic tongue was used to accurately classify beverages according to glycemic load (low, medium or high load) as well to their adequacy for people suffering from fructose malabsorption syndrome (tolerable or not): 100% of correct classifications (leave-one-out cross-validation) using linear discriminant models based on potentiomentric signals selected by a meta-heuristic simulated annealing algorithm. These results may be partially explained by the electronic tongue's capability to mimic the human sweetness perception and total acid flavor of beverages, which can be related with glycemic load and fructose-intolerance index. Finally, the E-tongue was also applied to quantify, accurately, healthy and sensory indexes using multiple linear regression models (leave-one-out cross-validation: Radj>0.99) in the following dynamic ranges: 4.7