Comparative study of different Portuguese samples of propolis: pollinic, sensorial, physicochemical, microbiological characterization and antibacterial activity

The aim of this work was to study four propolis samples from Trás-os-Montes region of Portugal. The propolis samples’ color was different, which pollen analysis showed to be due to different botanical sources: Populus sp., Pinus sp., Quercus sp. and Castanea sativa. The data from physicochemical analysis (moisture, soluble and insoluble solids content, pH, conductivity, ash content, wax, total phenolics and flavonoids content) was treated using multivariate statistical tools as cluster heat map, principal components analysis and linear discriminant analysis with the purpose of classifying the sample accordingly to the botanical/geographical origin. The discriminant analysis was applied with stepwise to select the variables that most contribute to sample identification accordingly to pollinic profile. The cross-validation technique was applied, using the leave-one-out procedure, which showed good prediction capabilities of the samples. Microbiologically, the commercial quality was satisfactory, since the samples didn’t contain deterioration or pathogenic microorganisms. All the samples studied presented antimicrobial activity against Methicillin-resistant Staphylococcus aureus, in a dose dependent way. The antimicrobial activity was strictly related to the physicochemical composition. This work will allow connecting a particular chemical propolis type to a specific type of biological activity, what is essential for the use in therapeutic applications

Compostos fenólicos e actividade antifúngica do mel de Trás-os-Montes

A utilização de antibióticos, desde os anos 50, têm vindo a generalizar-se conduzindo ao aumento progressivo de resistência dos microrganismos a estes fármacos. Para obviar esta situação, tem vindo a ser efectuados estudos científicos no sentido de desenvolver novos compostos para substituir total ou parcialmente a terapia antibiótica convencional. Nos nossos dias, o mel parece ser visto como uma alternativa à utilização destas substâncias evidenciando um espectro de acção bastante alargado quer em bactérias gram positivas quer em bactérias negativas, muitas das quais multiresistentes às drogas. No entanto, os estudos sobre a sua actividade antimicótica são escassos. Assim, neste trabalho procedemos à determinação de compostos fenólicos de dois tipos de mel (escuro e claro) de Trás-os-Montes por HPLC/DAD e à avaliação da sua actividade em leveduras patogénicas (Candida albicans, Cryptococcus neoformans, e Candida krusei). Como referência utilizou-se a levedura Sacharomyces cerivisae. Os estudos da actividade biológica efectuaram-se em meio líquido ao qual foram adicionados os compostos fenólicos na concentração desejada. Os principais compostos fenólicos identificados foram o ácido p-cumárico e naringenina. Estes compostos induziram uma inibição do crescimento de todas as leveduras testadas, à excepção de S. cerevisae. No entanto, o efeito exercido foi variável quer com a estirpe quer com o tipo de mel utilizado, sendo a inibição do crescimento mais acentuada na presença dos compostos fenólicos extraídos do mel escuro. C. krusei revelou-se muito sensível, mesmo para concentrações baixas (CI 50 - 0,90 mg/mL – mel escuro; IC50 – 1,7 mg/mL – mel claro). Estes resultados sugerem que os compostos fenólicos extraídos do mel podem ser utilizados como agente terapêutico no tratamento de infecções fúngica

Antioxidant and antimicrobial effects of phenolic compounds extracts of Northeast Portugal honey

Phenolic compounds of dark and clear honeys from Trás-os-Montes of Portugal were extracted with Amberlite XAD-2 and evaluated for their antioxidant and antimicrobial activities. The antioxidant effect was studied using the in vitro test capacity of scavenge the 2,2-diphenyl-1-picryhydrazyl (DPPH) free radical and of reducing power of iron (III)/ferricyanide complex. The antimicrobial activity was screened using three Gram-positive bacteria (Bacillus subtilis, Staphylococcus aureus, Staphylococcus lentus) and three Gram-negative bacteria (Pseudomonas aeruginosa, Klebsiella pneumoniae and Escherichia coli). The results obtained from the partial identification of honey phenolic compounds by high-performance liquid chromatography with a diode array detector showed that p-hydroxibenzoic acid, cinnamic acid, naringe- nin, pinocembrin and chrysin are the phenolic compounds present in most of the samples analyzed. Anti- oxidant potential was dependent of honey extract concentration and the results showed that dark honey phenolic compounds had higher activity than the obtained from clear honey. In the biological assays, results showed that S. aureus were the most sensitive microrganisms and B. subtilis, S. lentus, K. pneumo- niae and E. coli were each moderately sensitive to the antimicrobial activity of honey extracts. Neverthe- less, no antimicrobial activity was observed in the test with P. aeruginosa

Interaction between affordance and handedness recognition: a chronometric study

The visualization of tools and manipulable objects activates motor-related areas in the cortex, facilitating possible actions toward them. This pattern of activity may underlie the phenomenon of object affordance. Some cortical motor neurons are also covertly activated during the recognition of body parts such as hands. One hypothesis is that different subpopulations of motor neurons in the frontal cortex are activated in each motor program; for example, canonical neurons in the premotor cortex are responsible for the affordance of visual objects, while mirror neurons support motor imagery triggered during handedness recognition. However, the question remains whether these subpopulations work independently. This hypothesis can be tested with a manual reaction time (MRT) task with a priming paradigm to evaluate whether the view of a manipulable object interferes with the motor imagery of the subject's hand. The MRT provides a measure of the course of information processing in the brain and allows indirect evaluation of cognitive processes. Our results suggest that canonical and mirror neurons work together to create a motor plan involving hand movements to facilitate successful object manipulation

Antioxidant properties, total phenols and pollen analysis of propolis samples from Portugal

Pollen analysis, total phenols content and antioxidant activity were studied for the first time in Portuguese propolis samples from Bornes and Fundão regions. Total phenols content was determined by colorimetric assay and their amount was of 329 mg/g of GAE in Bornes sample and 151 mg/g of GAE in Fundão propolis. The antioxidant capacity of propolis extracts was assessed through the scavenging effects on DPPH (2,2- diphenyl-1-picrylhydrazyl) and reducing power of iron (III)/ ferricyanide complex assays. A concentration- dependent antioxidative capacity was verified in DPPH and reducing power assays. Low values of EC50 on DPPH scavenging assay were obtained for Bornes and Fundão propolis (of 6.22 lg/mL and 52.00 lg/mL, respectively). For reducing power the values were 9.00 lg/mL, for Bornes propolis, and 55.00 lg/mL, for Fundão propolis. The high activity of propolis from Bornes could be related with their different pollen composition. The results obtained indicate that Portuguese propolis is an important source of total phenols showing antioxidant properties that could be beneficial for human health

Propolis: antimicrobial activity, phenolic compounds and role in the inflammation

Propolis is a beehive product prepared by bees of the Apis mellifera species, using resinous substances collected from various plants. These substances are mixed with β-glycosidase enzyme of their saliva, partially digested and added to bee wax to form the final product. In the present study, it was evaluated the antimicrobial activity against multi-resistant microorganisms and the anti-inflammatory activity, assessed by the effect on the hyaluronidase enzyme, of propolis samples from Portugal. Simultaneously, it was studied the effect of extraction solvents on this biological activities. It was chosen the hydro-alcoholic extract because this was the most effective for extracting phenolic compounds. The antimicrobial activity was accessed in Gram-positive (Staphylococcus aureus) and Gram-negative bacteria (Pseudomonas aeruginosa, Escherichia coli) and yeasts (Candida albicans), isolated from different biological fluids and the results were then compared with the obtained for reference microorganisms. Regarding the pollen profiles, marked differences were found among the samples from the different regions under study. In the propolis from Bragança the dominant pollen was Erica sp., whereas the dominant species in Coimbra and Beja were Populus tremula and Eucalyptus sp., respectively. The propolis from Bragança was the one that possessed the highest polyphenols’ content. It was verified that all the extracts inhibited the hyaluronidase enzyme in a dose-dependent manner. The propolis that showed higher inhibitory activity was the one from Bragança and the product from Beja was the less effective. Despite the differences amongst the polyphenols concentrations, the anti-inflammatory activity of the samples did not differ significantly, suggesting that polyphenols are not the only factor responsible for the bioactive properties of this beehive product. Concerning the antimicrobial activity, Candida albicans was the most resistant and Staphylococcus aureus the most sensitive. Propolis showed greater activity against Gram-positive bacteria than Gram-negative ones, something that may be explained by structural differences of the cell wall of these two types of bacteria. In addition, the reference microorganisms were more sensitive than the ones isolated from biological fluids. This study suggests that the simultaneous use of propolis and antibiotics may reduce the acquisition of resistances and consequently avoid the use of more powerful therapies, even though further studies are required

Application of a potentiometric electronic tongue for assessing phenolic and volatile profiles of Arbequina extra virgin olive oils

The capability of determining the phenolic and volatile profiles of olive oils is of major relevance since these compounds are known to greatly influence the gustatory and olfactory positive attributes of olive oils. An electronic tongue with multiple linear regression models was used to evaluate both profiles based on olive oils potentiometric data generated during a single assay. The proposed electronic tongue-chemometric procedure enabled the quantification of flavonoids, phenolic acids and phenol alcohols of Arbequina extra-virgin olive oils with a similar accuracy of UPLC-MS (0.93 ± 0.03≤R2≤0.98 ± 0.08 for the repeated K-fold cross-validation procedure). Also, it was verified that the potentiometric device should not be applied to evaluate volatile compounds in solution (0.80 ± 0.14≤R2≤0.94 ± 0.05 for the repeated K-fold cross-validation procedure), showing a lower accuracy than HS-SPME-GS-MS. The overall satisfactory results showed that electronic tongue could be used as a practical sensing instrument to generate a chemical profile of the compounds known to influence the positive sensory attributes of olive oils.The authors would like to thank Consejo Regulador de Denominación de Origen (DOP) Estepa and DOP Les Garrigues; Casas Hualdo, Castillo Canena, Cortijo de Jara, Quaryat Dilar, EPAMIG and Olivas do Sul for the donation of samples. We would like to dedicate this work to the memory of Carmen Cabrera-Vique. We are grateful to the CAPES Foundation, (Ministry of Education, Brazil), for scholarship support provided to Thays Helena Borges (grant number 6073/13-1), being presently a Ph.D. student from the Official Doctoral Program ‘‘Nutrition and Food Sciences” of the Granada University. This work was also financially supported by Project POCI-01–0145-FEDER- 006984–Associate Laboratory LSRE-LCM, strategic project PEst-OE/ AGR/UI0690/2014 –CIMO all funded by FEDER - Fundo Europeu de Desenvolvimento Regional through COMPETE2020-Programa Operacional Competitividade e Internacionalização (POCI) – and by national funds through FCT - Fundação para a Ciência e a Tecnologia, Portugal.info:eu-repo/semantics/publishedVersio

Classification of olive cultivars using artificial neural networks

Olive fruit classification according to their cultivar is of major importance to guarantee varietal authenticity. Usually, non-supervised or supervised statistical tools (such as Principal Component Analysis or Linear Discriminant Analysis, respectively) are used for this purpose, based on several physico-chemical data, namely table olive fatty acids profiles, dietary fiber, sugar, organic acids and mineral nutrient contents. In this work, quantitative morphological parameters of fruit and endocarp were evaluated. Seventy samples, containing each one around 40 olives, of the six most representative olive cultivars of Portuguese northeast region (Cobrançosa, Cordovil, Madural, Negrinha de Freixo, Santulhana and Verdeal Transmontana) were selected. The samples were collected in different groves and during four crop years. The biometrical data was used together with a Multi layer Perceptron Artificial Neural Network allowing the implementation and validation of a classification model. Its performance was compared with that obtained using a linear discriminant analysis. The best results were obtained using artificial neural networks, especially for the external validation procedure implemented. The satisfactory results achieved, even when compared with previous published works, regarding olive cultivar's classification, show that the neural networks could be used by olive oil producers as a preventive and effective tool for avoiding adulterations o f Protected Designation of Origin or monovarietal olive oils with olives of non-allowed cultivars

Olive oils qualitative evaluation using a potentiometric electronic tongue: a review of practical applications

Olive oil is a food product highly prone to fraud, including mislabeling of olive oil commercial category, geographical or olive cultivar origin. Several analytical techniques have been reported to assess olive oil quality, authenticity as well as to detect possible adulterations, namely gas-, liquid- and mass-spectrometry chromatography, DNA and spectroscopy based methods. However, in general, these techniques require expensive pre-sample treatments, are time-consuming and need cost equipments and high skilled technicians. So, fast and more cost-effective methods are still needed and their development a challenge. Among these, electrochemical sensors have been proposed within this field of research, including both voltammetric and potentiometric electronic noses and electronic tongues, individually or as a fused methodology. In this study it is intended to review some of the most recent applications described in the literature including those of the research team regarding the application of a potentiometric electronic tongue, containing cross-sensitive lipidic membranes, to discriminate single-cultivar extra-virgin olive oils by cultivar or sensory intensity, showing its range of applicability and the possibility of using this artificial taste sensor as a complementary/alternative methodology for olive oil sensory analysis.info:eu-repo/semantics/publishedVersio

Chemometric classification of several olive cultivars from Trás-os-Montes region (Northeast of Portugal) using artificial neural networks

This work aimed to use artificial neural networks for fruit classification according to olive cultivar, as a tool to guarantee varietal authenticity. So, 70 samples, each one containing, in general, 40 olives, belonging to the six most representative olive cultivars of Trás-os-Montes region (Cobrançosa, Cordovil, Madural, Negrinha de Freixo, Santulhana and Verdeal Transmontana) were collected in different groves and during four crop years. Five quantitative morphological parameters were evaluated for each fruit and endocarp, respectively. In total, ten biometrical parameters were used together with a multilayer perceptron artificial neural network allowing the implementation of a classification model. Its performance was compared with that obtained using linear discriminant analysis. The best results were obtained using artificial neural networks. In fact, the external validation procedure for linear discriminant analysis, using olive data from olive trees not included in the model development, showed an overall sensibility and specificity in the order of 70% and varying between 45 and 97% for the individual cultivars. On the other hand, the artificial neural network model was able to correctly classify the same unknown olives with a global sensibility and specificity around 75%, varying from 58 and 95% for each cultivar. The predictive results of the artificial neural network model selected was further confirmed since, in general, it correctly or incorrectly classified the unknown olive fruits in each one of the six cultivars studied with, respectively, higher and lower probabilities than those that could be expected by chance. The satisfactory results achieved, even when compared with previous published works, regarding olive cultivar's classification, show that the neural networks could be used by olive oil producers as a preventive and effective tool for avoiding adulterations of Protected Designation of Origin or monovarietal olive oils with olives of non-allowed cultivars.PRODER Programme, Ministério da Agricultura de Desenvolvimento Rural e das Pescas and União Europeia – Fundo Europeu Agrícola de Desenvolvimento Rural