No abstract

Studies dealing with the development of edible/biodegradable packaging have been gaining popularity since these commodities are marked as being ecofriendly, especially when byproducts are incorporated. Consequently, this study aimed at the development of chitosan-based coatings with plant byproducts. Their sensory properties, colour attributes, occurrence of cracks in microstructure and biodegradability were analysed. Coatings containing grape and blueberry pomace had statistically significantly (p < 0.05) higher levels of colour intensity. Coating samples were characterised by lower aroma intensity (3.46–4.77), relatively smooth surface (2.40–5.86), and low stickiness (2.11–3.14). In the overall hedonic evaluation, the samples containing parsley pomace in all concentrations and a sample containing 5% grape pomace achieved a statistically significantly (p < 0.05) better evaluation (5.76–5.93). The lowest values of the parameter ΔE2000 were recorded for the sample containing 5% parsley pomace (3.5); the highest was for the sample with 20% blueberry pomace (39.3). An analysis of the coating surface microstructure showed the presence of surface cracks at an 80 K magnification but the protective function of the edible coating was not disrupted by the added plant pomace. The produced samples can be considered to have a high biodegradability rate. The results of our experimentally produced coatings indicate their possible application on a commercial scale.

Melissopalynology is an important analytical method to identify botanical origin of honey. Pollen grain recognition is commonly performed by visual inspection by a trained person. An alternative method for visual inspection is automated pollen analysis based on the image analysis technique. Image analysis transfers visual information to mathematical descriptions. In this work, the suitability of three microscopic techniques for automatic analysis of pollen grains was studied. 2D and 3D morphological characteristics, textural and colour features, and extended depth of focus characteristics were used for the pollen discrimination. In this study, 7 botanical taxa and a total of 2482 pollen grains were evaluated. The highest correct classification rate of 93.05% was achieved using the phase contrast microscopy, followed by the dark field microscopy reaching 91.02%, and finally by the light field microscopy reaching 88.88%. The most significant discriminant characteristics were morphological (2D and 3D) and colour characteristics. Our results confirm the potential of using automatic pollen analysis to discriminate pollen taxa in honey. This work provides the basis for further research where the taxa dataset will be increased, and new descriptors will be studied.

Respondents' perception about the possible changes of best before date (BBD) to the date of the highest quality was the main aim of the survey. The survey consisted out of 1,107 respondents who were grouped according to their demographic characteristics and food labelling preferences. The results of the survey are indicating high acceptance rate towards new labelling, but without clear connection with their preferences. Another aspect of the research emphasised the respondents' perception towards the price of healthier food commodities and revealed that education level has high impact (P < 0.05) on their opinion and considerations. The survey gave important answers on possibility of changes of food labelling by which it would be affected food waste quantities. Certainly, each food type shelf life should be checked and labelled according to food perishability and consumers safeness. The changing of the BBD to the date of the highest quality according to our survey would be broadly accepted among all socio-demographic groups.

Geographical and botanical origin of honeys can be characterized on the basis of physico-chemical composition, sensory properties and on the basis of melissopalynological analysis. No comprehensive description of the characteristics of Czech honey has been published so far. This study provides insights that are important for correct classification. The study analysed 317 samples of authentic honey from randomly selected localities. Due to the diversity of the landscape, the typical honey of the region is blend honey with a predominance of blossom honey. According to the pollen profile and electric conductivity, the honeys were sorted into the following: Brassica honey (BH), Floral honey (FH), Fruit tree honey (PH), Honeydew (HD), Lime tree honey (LH), Robinia pseudoacacia honey (RH), and Trifolium honey (TH). Physico-chemical properties, including higher carbohydrates, were determined for the honeys and their pollen profiles were examined. The physico-chemical properties and pollen profile are partially in compliance with the description of European monofloral honeys, except for RH and TH. Although they had the highest proportion of acacia pollen, amounting to >10% of all the Czech honeys, these RH honeys differ from the European standard, so they cannot be considered acacia honey. Further, PH honeys and FH polyfloral honeys were described. Most honeys contained a significant proportion of rapeseed pollen, which is one of the common agricultural crops grown in the Czech Republic. All the analysed honeys met the parameters defined by the legislation. Due to direct on-site sampling, honeys were characterized by a low 5-(hydroxymethyl)furfural (HMF) content (3.0 mg/kg) and high diastase activity (24.4 DN). Honeydew honeys had the highest proportion of higher carbohydrates, primarily of Melezitose (4.8 g/100 g) and Trehalose (1.3 g/100 g). The presence of higher carbohydrates was also confirmed in LH for Maltose (4.6 g/100 g) and Turanose (2.4 g/100 g).