Sweeteners of natural sources, such as sugar alcohols, are in the centre of growing interest. Their impact on the phytochemicals, antioxidant and sensory properties of blackberry jams were investigated during a 9-months storage period. Measurements on jams prepared with different sugars and sugar alcohols (sucrose, fructose, xylitol and erythritol) were performed at the date of preparation and in the 1st, 3rd, 6th, 9th month. Total polyphenol content, individual polyphenols, antioxidant properties, anthocyanin content and CIE L*a*b* colour were determined. Sensory profiles were determined by a trained panel. Sensory attributes were compared by the results of the electronic tongue and nose. Sweeteners had a significant impact on physicochemical properties and sensory attributes. Storage time also affected the sensory and compositional properties of jams. Changes in antioxidant properties did not follow a clear trend during the storage period, and antioxidant capacity was not affected significantly by the sweetening agent, but showed a significant decline from the 6th month. A positive effect of xylitol was observed in terms of a low degradation rate of anthocyanins, while their decomposition was the fastest in the fructose-containing preparation. Jams sweetened with erythritol reached significantly lower values for some sensory attributes (blackberry flavour and general taste intensity), however, they showed more intense red colour. Multiple factor analysis enabled the identification of the effect of sweetener and storage time on the pattern of the sensory data matrix. Classification according to individual sweeteners was performed successfully by the electronic tongue, but not by electronic nose.

Monotony in a gluten-free (GF) diet can be a challenge because of a limited choice of acceptable cereal sources. This study investigates the potential of five types of differently coloured lentils in the development of GF cookies using rice flour as a reference. Raw materials (lentil flours) and cookies were characterised in terms of physicochemical parameters (e.g., crude protein content, total phenolics and flavonoids, antioxidant properties, colour, pH); additionally, geometry, baking loss and texture profile were determined for the cookies. A sensory acceptance test was also conducted to find out consumer preferences regarding rice versus different lentil cookies. Results showed that lentil cookies were superior to rice control in terms of higher crude protein (12.1–14.8 vs. 3.8 g/100 g), phenolic (136.5–342.3 vs. 61.5 mg gallic acid equivalents/100 g) and flavonoid (23.8–75.9 vs. 13.1 mg catechin equivalents/100 g) content and antioxidant capacity (0.60–1.81 vs. 0.35 mmol trolox equivalents/100 g), as well as lower hydroxymethyl-furfural content (<1 vs. 26.2 mg/kg). Consumers preferred lentil cookies to rice ones (overall liking: 6.1–7.0 vs. 5.6, significant differences for red and brown lentils), liking especially their taste (6.3–7.0 vs. 5.5). Depending on the target parameter, whether physicochemical or sensory, these lentil flours can be promising raw materials for GF bakery products.

No abstract

Honey is produced by honeybees and is used as a food and medical product. Adulteration of honey has been a problem for several years now because of the relatively high price of honey on the market according to its valuable composition. The aim of our study is to determine the physicochemical properties of authentic Hungarian linden and acacia honeys (pure samples or manipulated ones blended with sugar syrup) as well as commercially available blends of European Union (EU) non-European Union (non-EU) honeys. Authentic linden and acacia were blended with sugar syrup at 10%, 20% and 50% concentration levels, and physicochemical properties were determined according to the methods of the International Honey Commission. Our objectives also included testing of the performance of electronic sensory techniques (electronic tongue (ET) and electronic nose (EN)) in the detection of adulteration, and the results are compared to the sensory profile analysis. The results provide good average recognition and prediction abilities for the classification of adulterated and authentic honeys (>90% for ET and higher than >80 for EN). Misclassifications were found only in the case of honey with 10% added sugar syrup. The methods were also able to reveal adulteration of independently predicted samples.

The objective of the study was to check the authenticity of Hungarian honey using physicochemical analysis, near infrared spectroscopy, and melissopalynology. In the study, 87 samples from different botanical origins such as acacia, bastard indigo, rape, sunflower, linden, honeydew, milkweed, and sweet chestnut were collected. The samples were analyzed by physicochemical methods (pH, electrical conductivity, and moisture), melissopalynology (300 pollen grains counted), and near infrared spectroscopy (NIRS:740–1700 nm). During the evaluation of the data PCA-LDA models were built for the classification of different botanical and geographical origins, using the methods separately, and in combination (low-level data fusion). PC number optimization and external validation were applied for all the models. Botanical origin classification models were >90% and >55% accurate in the case of the pollen and NIR methods. Improved results were obtained with the combination of the physicochemical, melissopalynology, and NIRS techniques, which provided >99% and >81% accuracy for botanical and geographical origin classification models, respectively. The combination of these methods could be a promising tool for origin identification of honey.