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Edible insects have been officially classified as food in the European Union since 2015. Currently, four insect species are approved for food use. However, no official method for detecting insects in food has been recognized to date. To establish a simple analytical method for insect detection in food, we developed an indirect sandwich (enzyme-linked lectin sorbent assay) ELLA specific for N-acetylglucosamine in chitin and chitosan polymers. The validation of the method demonstrated that the ELLA developed in this study is reliable for insect detection. The limit of detection (LOD) and quantification (LOQ) were 0.006 and 0.028 mg/mL, respectively. Intra-day precision ranged from 2.45% to 30.29%, and inter-day precision from 0.36% to 12.87%. Significant differences in the total amount of chitin and chitosan were observed among the insect products, processed insect products, and samples without any insect addition (p < 0.05).

The main objective of this work was to determine the significant physicochemical and bioactive parameters of honeys originating from Iraqi Kurdistan. For this purpose, honey samples (n = 16) were taken directly from Kurdish beekeepers from different places of Dohuk and Erbil Governorate in 2018 and 2022. The following parameters were analyzed: moisture content, electrical conductivity, diastase activity, hydroxymethylfurfural content, pH, free acidity, content of saccharides, total phenolic content, total flavonoid content, color, color intensity and DPPH, FRAP. Another objective of this work was to compare the properties of Kurdistan honeys with the requirements of European Union law and with the honeys of Central Europe. A total of 48 honey samples were included in the comparison. It was detected that the honeys produced in Iraqi Kurdistan met the strict quality criteria set by European law, which is important information for local beekeepers and experts in relation to honey production and an opportunity to set local limits of honey quality. Despite the different climatic and topographical conditions, the available flora, and the different species of bees, the properties of Iraqi Kurdistan honeys were similar to the properties of honeys from the Czech and Slovak Republics.

Honey contains a wide range of inorganic substances. Their content can be influenced, i.e., by the type of soil on which the bee pasture is located. As part of this study, the mineral profile of 32 samples of honey from hobby beekeepers from the Czech Republic wasevaluated and then compared with soil types in the vicinity of the beehive location. Pearson’s correlation coefficient was used to express the relationship between mineral substances and soil type. There was a high correlation between antroposol and Zn (R = 0.98), Pb (R = 0.96), then between ranker and Mn (0.95), then regosol and Al (R = 0.97) (p < 0.05). A high negative correlation was found between regosol and Mg (R = −0.97), Cr (R = −0.98) and between redzinas and Al (R = −0.97) (p < 0.05). Both positive and negative high correlations were confirmed for phaeozem. The CART method subsequently proved that the characteristic elements for individual soil types are B, Ca, Mg, Ni, and Mn. The soil types of cambisol, fluvisol, gleysol, anthrosol, and kastanozem had the closest relationship with the elements mentioned, and it can therefore be assumed that their occurrence indicates the presence of these soil types within the range of beehive location.

Pollen analysis is a method used for verification of the botanical and geographical honey origin. Currently, much effort is being made to introduce automated systems with the use of image analysis programs. The automatic analysis is impeded by the insufficient depth of field of objects when using a light microscope, however, this can be avoided by using image reconstruction from images obtained from different focal planes. In this method, testing was performed on the normal focus (NF) and extended-depth-of-focus (EDF) images. These two methods were compared and statistically evaluated. The number of pollen grains and selected morphometric characteristics were compared. For EDF images, a higher number of pollen grains was obtained for the analysis, and except for the length/width ratio, a statistically significant difference was observed in the characteristics of pollen grains between the compared NF and EDF methods.

Honeybees are important pollinators. As a side product of pollination, honeybees produce honey, as a natural sweetener. The source of honey depends on the hive location. In specific conditions honeybees produce monofloral honey, but more common are polyfloral kinds of honey. In this study honey from the Czech Republic in the 2019 season was evaluated by melissopalynology analysis. The common botanical taxa in the Czech Republic were determined and season impact to pollen taxa was compared for dominant pollen taxa. The taxonomic distribution of pollen in Czech honey was stable during the year. The average number of species was 11.52 taxa per sample. The dominant pollen source in Czech honey was the Brassicaceae family. The high pollen content in honey was confirmed also in the Rosacea family (fruit tree), Ubelliferacae family and Myosotis genus. During the year the pollen taxa were equally distributed in honey. Seasonal effects were confirmed only in Salix genus, Ubelliferacae family and Phacelia genus. Seasonal effects correspond with the blooming season and honeybee handling in the hive was also confirmed. High variability during the season and hive location was confirmed for other taxa.

One of the options to determine botanical origin of trees or honey is the analysis of pollen grains. The characteristics of pollen grains in Czech flora has not been sufficiently described yet. Within this work, fruit trees pollen of Czech origin was characterized on the basis of morphological and spectral description of pollen grains produced by fruit species of M. domestica, P. armenica, P. persica, P. domestica, P. avium and P. cerasus. The morphological characterization results of the studied fruit species are consistent with results by other authors, but certain differences between the pollen grains of some fruit trees were confirmed. Most morphological differences were confirmed among the Malus and Prunus genera. Results of morphological and spectral analyzes further confirmed the differences between some types of fruit trees, but homogeneity remained for individual species even in mixed samples. Morphological and spectral analysis can therefore be used for botanical identification of pollen. If this knowledge is applied to pollen analysis in honey, these methods can also be used to verify the botanical origin of honey.

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.

Carrageenan is a substance widely used as an additive in the food industry. Among other things, it is often added to processed cheese, where it has a positive effect on texture. Processing of such cheese involves grinding, melting and emulsifying the cheese. There is currently no official method by which carrageenan can be detected in foodstuffs, but there are several studies describing its negative health impact on consumers. Lectin histochemistry is a method that is used mainly in medical fields, but it has great potential to be used in food analysis as well. It has been demonstrated that lectin histochemistry can be used to detect carrageenan in processed cheese by Human Inspection and Computer-Assisted Analysis (CIE L*a*b*). The limit of detection (LoD) was established at 100 mg kg−1 for Human Inspection and 43.64 for CIE L*a*b*. The CIE L*a*b* results indicate that Computer-Assisted Analysis may be an appropriate alternative to Human Inspection. The most suitable parameter for Computer-Assisted Analysis was the b* parameter in the CIE L*a*b* color space.

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).

Fat is an irreplacable ingredient in the production of sausages and it determines the appearance of the resulting cut to a significant extent. When shopping, consumers choose a traditional product mostly according to its appearance, based onwhat they are used to. Chemical analysis is capable to determine the total fat content in the product, but it cannot accurately describe the shape and size of fat grains which the consumer observes when looking at the product. The size of fat grains considered acceptable by consumers can be determined using sensory analysis or image analysis. In recent years, image analysis has become widely used when examining meat and meat products. Compared to the human eye, image analysis using a computer system is highly effective, since a correctly adjusted computer program is able to evaluate results with lower error rate. The most commonly monitored parameter in meat products is the aforementioned fat. The fat is located in the cut surface of the product in the form of dispersed particles which can be fairly reliably identified based on color differences in the individual parts of the product matrix. The size of the fat grains depends on the input raw material used as well as on the production technology. The present article describes the application of image analysis when evaluating fat grains in the appearance of cut of the Gothaj sausage whose sensory requirements are set by Czech legislation, namely by Decree No. 326/2001 Coll., as amended. The paper evaluates the size of fat mosaic grains in Gothaj sausages from different manufacturers. Fat grains were divided into ten size classes according to various size limits; specifically, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 5.0, 8.0 and over 8 mm. The upper limit of up to 8 mm in diameter was chosen based on the limit for the size of individual fat grains set by the legislation. This upper limit was not exceeded by any of the products. On the other side the mosaic had the hightest representation of 0.25 mm fat grains.

With the growing popularity of various plant proteins used as raw materials for meat production, interest of manufacturers to extend the range of such raw materials is increasing as well. Manufacturers are trying to minimize the cost of manufacturing their products with simultaneous preserving the nutritional value of their products to the maximum extent possible. Such cheaper raw materials, which are also nutritionally rich, include pea protein. Another advantage for manufacturers is the fact that legislation does not order them to indicate pea protein presence in case of its addition, as it does for other allergenic ingredients, although this legume contains storage proteins which can cause a variety of allergic reactions, just like other legumes. Currently no method used for its qualitative determination has been described in literature, let alone its quantitative determination. Our work describes a possible method that can be applied for its quantification. It is a stereological method applied to microscopic sections stained by immunohistochemical staining based on the avidin-biotin complex using monoclonal legumin (1H9) as the primary antibody. The stereological method is based on geometry, it applies knowledge of geometry to analyze a sample of diverse origin, size and internal structure. Despite potential shortcomings in staining microscopic preparations, stereology allows us to perform quantification based on knowledge of morphology of the observed structures. This work describes a procedure of a known pea protein addition quantification in model meat products by means of Ellipse software. Pea protein quantification was performed in two ways. In the first case ten microimages of all sections prepared were examined, while in the second case one scan of the entire section was analyzed. Based on the results, Spearman's correlation coefficient was calculated, which confirmed our assumption of correlation between the protein added into the product and the measured area in microimages. In both ways Spearman's correlation coefficient was rSp = 1000. We obtained regression equations in MS Excel, which can be used for calculation of pea protein addition based on measured area of this protein in microscopic section.

In recent years, various protein additives intended for manufacture of meat products have increasing importance in the food industry. These ingredients include both, plant-origin as well as animal-origin proteins. Among animal proteins, blood plasma, milk protein or collagen are used most commonly. Collagen is obtained from pork, beef, and poultry or fish skin. Collagen does not contain all the essential amino acids, thus it is not a full protein in terms of essential amino acids supply for one's organism. However, it is rather rich in amino acids of glycine, hydroxyproline and proline which are almost absent in other proteins and their synthesis is very energy intensive. Collagen, which is added to the soft and small meat products in the form of isolated porcine protein, significantly affects the organoleptic properties of these products. This work focused on detection of isolated porcine protein in model meat products where detection of isolated porcine protein was verified by histological staining and light microscopy. Seven model meat products from poultry meat and 7 model meat products from beef and pork in the ratio of 1:1, which contained 2.5% concentration of various commercially produced isolated porcine proteins, were examined. These model meat products were histologically processed by means of cryosections and stained with hematoxylin-eosin staining, toluidine blue staining and Calleja. For the validation phase, Calleja was utilized. To determine the sensitivity and specificity, five model meat products containing the addition of isolated porcine protein and five model meat products free of it were used. The sensitivity was determined for isolated porcine protein at 1.00 and specificity was determined at 1.00. The detection limit of the method was at the level of 0.001% addition. Repeatability of the method was carried out using products with addition as well as without addition of isolated porcine protein and detection was repeated 10 times. Repeatability in both, positive and negative samples, for isolated porcine protein was determined at 100%. The results show that the histological processing of cryosections stained using Calleja is suitable for detecting isolated porcine protein in meat products.

To increase production efficiency of meat products, milk protein additives are often used. Despite a number of advantages, use of dairy ingredients involves a certain risk, namely the allergenic potential of milk proteins. A number of methods have been developed to detect milk-origin raw materials in foodstuffs, including immunological reference methods. This study presents newly developed immunohistochemical (IHC) methods for casein detection in meat products. Casein was successfully detected directly in meat products where sensitivity was determined at 1.21 and specificity at 0.28. The results obtained from the IHC were compared with the Enzyme-Linked Immuno Sorbent Assay (ELISA) and there was no statistically significant difference between the IHC and ELISA methods (p > 0.05). The correspondence between the methods was 72% in total. The highest correspondence was reached in frankfurters (90%), the lowest in canned pâté (44%).

The aim of the study was to analytically evaluate quantum dots in immunohistofluorescence (IHF-QD) microscopic imaging as detectors of food allergens—peanut and wheat. The experiment was designed as two in silico experiments or simulations: (a) models of pastry samples were prepared with the addition of allergenic components (peanut and wheat protein components) and without the addition of allergenic components, and (b) positive and negative commercial samples underwent food allergen detection. The samples from both simulations were tested by the ELISA and IHF-QD microscopic methods. The primary antibodies (secondary antibodies to a rabbit Fc fragment with labeled CdSe/ZnS QD) were labelled at 525, 585, and 655 nm emissions. The use of quantum dots (QDs) has expanded to many science areas and they are also finding use in food allergen detection, as shown in the study. The study indicated that differences between the ELISA and IHF-QD microscopic methods were not observable among experimentally produced pastry samples with and without allergenic components, although differences were observed among commercial samples. The important value of the study is certainly the differences found in the application of different QD conjugates (525, 585, and 655). The highest contrast was found in the application of 585 QD conjugates that can serve for the possible quantification of present food allergens—peanuts and wheat. The study clearly emphasized that QD can be used for the qualitative detection of food allergens and can represent a reliable analytical method for food allergen detection in different food matrixes.

Fiber, a suitable additive to meat products with water-holding capacity, reduces curing losses and maintains juiciness of the meat. The risk is the use of excessive amounts of flour or other ingredients of vegetable origin, in which the fiber is contained. In some cases, sensory characteristics of products can be affected. Detection of fiber may be prevention of adulteration in some meat products. It is therefore very important to regularly detect the amount of fiber in meat products and check its contents. Fiber in meat products can be detected by various methods, applied are for example gravimetric, spectroscopic, histochemical, and microscopic methods. For this reason, a model meat product (Vysočina salami) was prepared in our experiment with the addition of bamboo fiber of selected concentrations of 0%, 2%, and 3%. Subsequently, a series of microscopic sections was made on different days of curing (day no. 7, 14 of the drying phase and 28, 42 of storage). Individual sections were examined and captured using a polarization microscope, the amounts of fiber in individual sections were analyzed by means of image analysis software and the values obtained were compared with each other. Also the influence of drying on the measured area of fiber in sections was monitored. The results indicate a noticeable reduction in the area of fiber until the seventh day of ripening, which is caused by the rapid loss of water in the product. In contrast, sections of products from the following days of drying contained mildly increased concentrations of fiber, which was caused by gradual drying of the products, while the area of fiber refrained form becoming smaller. Between the individual days of drying, a difference that was statistically significant was demonstrated from the 14th day of (storage or drying). Correlation was observed between the date of (storage or drying) and amount of added fiber. Among the tested mean values for the sample with the addition of fiber concentration of 2 % an insignificant difference was found. The difference between test values (day/fiber) in the sample with addition of 3% fiber was, however, statistically significant.