Olga Escuredo

Nutritional value and antioxidant activity of honeys produced in a European Atlantic area

One hundred eighty-seven honey samples from an Atlantic European area were studied to determine their nutritional compositions and antioxidant capacities, as well as the relationships between them. The results showed that heather, polyfloral, blackberry, and eucalyptus honeys had the highest carbohydrate contents, whereas honeydew and chestnut honeys had the lowest. There were some important differences among the honey types, which were related to the presence of minor components. The protein contents were significantly higher in honeydew and chestnut honeys, and the same results were obtained for mineral contents. Related to the presence of several antioxidant compounds, heather honey had the highest phenolic content, whereas honeydew and chestnut honeys had the highest flavonoid contents. Multivariate analysis showed that some variables, such as the amounts of flavonoids, minerals, proteins, and phenols, were significantly correlated with antioxidant activity. The regression analysis produced a significant model (R(2)=0.716; F=154.680; P<0.001) that related the antioxidant activity and the flavonoids, K, and P contents.

Contribution of botanical origin and sugar composition of honeys on the crystallization phenomenon.

The present work provides information regarding the statistical relationships among the palynological characteristics, sugars (fructose, glucose, sucrose, melezitose and maltose), moisture content and sugar ratios (F+G, F/G and G/W) of 136 different honey types (including bramble, chestnut, eucalyptus, heather, acacia, lime, rape, sunflower and honeydew). Results of the statistical analyses (multiple comparison Bonferroni test, Spearman rank correlations and principal components) revealed the valuable significance of the botanical origin on the sugar ratios (F+G, F/G and G/W). Brassica napus and Helianthus annuus pollen were the variables situated near F+G and G/W ratio, while Castanea sativa, Rubus and Eucalyptus pollen were located further away, as shown in the principal component analysis. The F/G ratio of sunflower, rape and lime honeys were lower than those found for the chestnut, eucalyptus, heather, acacia and honeydew honeys (>1.4). A lower value F/G ratio and lower water content were related with a faster crystallization in the honey.

Multivariate calibration by near infrared spectroscopy for the determination of the vitamin E and the antioxidant properties of quinoa

Quinoa is a pseudocereal that is grown mainly in the Andes. It is a functional food supplement and ingredient in the preparation of highly nutritious food. In this paper we evaluate the potential of near infrared spectroscopy (NIR) for the determination of vitamin E and antioxidant capacity in the quinoa as total phenol content (TPC), radical scavenging activity by DPPH (2,2-diphenyl-2-picryl-hydrazyl) and cupric reducing antioxidant capacity (CUPRAC) expressed as gallic acid equivalent (GAE). For recording NIR a fiber optic remote reflectance probe applied directly on the quinoa samples without treatment was used. The regression method used was modified partial least squares (MPLS). The multiple correlation coefficients (RSQ) and the standard prediction error corrected (SEP(C)) were for the vitamin E (0.841 and 1.70 mg 100 g(-1)) and for the antioxidants TPC (0.947 and 0.08 mg GAE g(-1)), DPPH radical (0.952 and 0.23 mg GAE g(-1)) and CUPRAC ( 0.623 and 0.21 mg GAE g(-1)), respectively. The prediction capacity of the model developed measured by the ratio performance deviation (RPD) for vitamin E (2.51), antioxidants TPC (4.33), DPPH radical (4.55) and CUPRAC (1.55) indicated that NIRS with a fiber optic probe provides an alternative for the determination of vitamin E and antioxidant properties of the quinoa, with a lower cost, higher speed and results comparable with the chemical methods.

Near infrared spectroscopy applied to the rapid prediction of the floral origin and mineral content of honeys

Consumers demand to know the floral origins of honeys. Therefore, the use of simple and reliable techniques for differentiating among honeys by their origins is necessary. Multivariate statistical techniques and near infrared spectroscopy applied to palynological and mineral characteristics make it possible to differentiate among the types of honey collected from Northwestern Spain. Prediction models using a modified partial least squares regression for the main pollen types (Castanea, Eucalyptus, Rubus and Erica) in honeys and their mineral composition (potassium, calcium, magnesium and phosphorus) were established. Good multiple correlation coefficients (higher than 0.700) and acceptable standard errors of cross-validation were obtained. The ratio performance deviation exhibited a good prediction capacity for Rubus pollen and for Castanea pollen, whereas for minerals, for Eucalyptus pollen and for Erica pollen the ratio performance deviation was excellent. Near infrared spectroscopy was established as a rapid and effective tool to obtain equations of prediction that contribute to the honey typification.

Assessment of physicochemical and antioxidant characteristics of Quercus pyrenaica honeydew honeys.

Consumers are exhibiting increasing interest in honeydew honey, principally due to its functional properties. Some plants can be sources of honeydew honey, but in north-western Spain, this honey type only comes from Quercus pyrenaica. In the present study, the melissopalynological and physicochemical characteristics and the antioxidant properties of 32 honeydew honey samples are described. Q. pyrenaica honeydew honey was defined by its colour, high pH, phenols and flavonoids. Multivariate statistical techniques were used to analyse the influence of the production year on the honeys physicochemical parameters and polyphenol content. Differences among the honey samples were found, showing that weather affected the physicochemical composition of the honey samples. Optimal conditions for oak growth favoured the production of honeydew honey.

Near infrared spectroscopy for prediction of antioxidant compounds in the honey.

The selection of antioxidant variables in honey is first time considered applying the near infrared (NIR) spectroscopic technique. A total of 60 honey samples were used to develop the calibration models using the modified partial least squares (MPLS) regression method and 15 samples were used for external validation. Calibration models on honey matrix for the estimation of phenols, flavonoids, vitamin C, antioxidant capacity (DPPH), oxidation index and copper using near infrared (NIR) spectroscopy has been satisfactorily obtained. These models were optimised by cross-validation, and the best model was evaluated according to multiple correlation coefficient (RSQ), standard error of cross-validation (SECV), ratio performance deviation (RPD) and root mean standard error (RMSE) in the prediction set. The result of these statistics suggested that the equations developed could be used for rapid determination of antioxidant compounds in honey. This work shows that near infrared spectroscopy can be considered as rapid tool for the nondestructive measurement of antioxidant constitutes as phenols, flavonoids, vitamin C and copper and also the antioxidant capacity in the honey.

Fungal diversity in honeys from northwest Spain and their relationship to the ecological origin of the product

Abstract The microscopic analysis of honeys has led to the identification of different structures, including pollen grains, fungal spores, yeast, algae and soot particles. Pollen grains are the most studied elements, while others, like fungal spores and yeast, are less well known. Some of these elements come from primary sources and are associated with the presence of honey dew, such as Alternaria, Stemphylium, and Leptosphaeria. A variety of yeasts are regularly present in the floral nectar of many plant species where they frequently reach high densities. A melissopalynological method was used to identify some of these microscopic elements, their frequency in honeys and the relationships with the ecological origin of the product. The pollen types most frequently identified were Castanea sativa, Rubus, Cytisus type, Eucalyptus and Erica. Cladosporium conidia were identified in 64% of the samples, Metschnikowia cells were present in more than 50% of the honeys and some plant pathogenic fungi (Leptosphaeria, Stemphylium and Urediniospores among others) were also frequently present. The presence of Metschnikowia cells was associated with blossom honey and the presence of some fungal spores was associated with honey dew contributions.

Palynological evaluation of selected honeys from Romania

Abstract Fifty-four honey samples collected over two consecutive harvest seasons (2009–2010) from different floristic areas of Romania were analysed. A melissopalynological analysis including qualitative and quantitative analyses was carried out in order to identify the principal pollen types in Romanian honeys and therefore, the important plants exploited by Apis mellifera in this country. Seventy-seven pollen types from 35 botanical families were identified. The main pollen forms were: Brassica napus-type, Tilia, Helianthus annuus, Robinia pseudoacacia, Prunus, Castanea sativa, Fragaria-type and Plantago-type. Honey samples were classified as: acacia honey (Robinia pseudoacacia), lime honey (Tilia), rape honey (Brassica napus-type), sunflower honey (Helianthus annuus), cherry honey (Prunus). Three of them were honeydew honeys whereas the others were all polyfloral. The results from this study can be used as a palynological baseline data of Romanian artisanal honeys.

Determination of the Mineral Composition and Toxic Element Contents of Propolis by Near Infrared Spectroscopy

The potential of near infrared spectroscopy (NIR) with remote reflectance fiber-optic probes for determining the mineral composition of propolis was evaluated. This technology allows direct measurements without prior sample treatment. Ninety one samples of propolis were collected in Chile (Bio-Bio region) and Spain (Castilla-León and Galicia regions). The minerals measured were aluminum, calcium, iron, potassium, magnesium, phosphorus, and some potentially toxic trace elements such as zinc, chromium, nickel, copper and lead. The modified partial least squares (MPLS) regression method was used to develop the NIR calibration model. The determination coefficient (R2) and root mean square error of prediction (RMSEP) obtained for aluminum (0.79, 53), calcium (0.83, 94), iron (0.69, 134) potassium (0.95, 117), magnesium (0.70, 99), phosphorus (0.94, 24) zinc (0.87, 10) chromium (0.48, 0.6) nickel (0.52, 0.7) copper (0.64, 0.9) and lead (0.70, 2) in ppm. The results demonstrated that the capacity for prediction can be considered good for wide ranges of potassium, phosphorus and zinc concentrations, and acceptable for aluminum, calcium, magnesium, iron and lead. This indicated that the NIR method is comparable to chemical methods. The method is of interest in the rapid prediction of potentially toxic elements in propolis before consumption.

Chemical characteristics and mineral composition of quinoa by near‐infrared spectroscopy

BACKGROUND Quinoa (Chenopodium quinoa Willd.) has been traditionally used as a foodstuff in the Andes and it has gained increasing interest in recent years owing to its high nutritional value. The potential of near-infrared spectroscopy (NIRS) for estimating chemical compounds in quinoa was studied because of the possibility of conducting direct measurement without prior sample treatment. RESULTS The use of NIRS technology with a remote reflectance fiber-optic probe for the analysis of major compounds and mineral composition of 48 quinoa samples was studied. The calibration of the NIRS instrument was conducted using modified partial least squares (MPLS) analysis. This allowed the determination of protein (16.0-20.2 g 100g⁻¹), crude fiber (1.8-3.1 g 100g⁻¹), fat (4.4-7.5 g 100g⁻¹), calcium (298.8-1164.5 mg kg⁻¹), iron (0-948.5 mg kg⁻¹) and phosphorus (2735.0-4543.3 mg kg⁻¹). The correlation coefficients (RSQ) were 0.83 for protein, 0.73 for crude fiber, 0.93 for fat; 0.60 for calcium; 0.76 for iron and 0.75 for phosphorus. The robustness of the equations obtained was verified by external validation on unknown quinoa samples. CONCLUSIONS NIRS with fiber-optic probe provides an alternative for the determination of chemical compounds of quinoa, faster and at lower cost, with results comparable with chemical methods.