Unique Texture Research Articles

Enhancing Organizing Pneumonia Diagnosis: A Novel Super-token Transformer Approach for Masson Body Segmentation.

In this study, we introduce an innovative deep-learning model architecture aimed at enhancing the accuracy of detecting and classifying organizing pneumonia (OP), a condition characterized by the presence of Masson bodies within the alveolar spaces due to lung injury. The variable morphology of Masson bodies and their resemblance to adjacent pulmonary structures pose significant diagnostic challenges, necessitating a model capable of discerning subtle textural and structural differences. Our model incorporates a novel architecture that integrates advancements in three key areas: Semantic segmentation, texture analysis, and structural feature recognition. We employed a dataset of whole slide imaging from 20 patients, totaling 100 slides of OP, segmented into training, validation, and testing sets to reflect real-world application scenarios. Our approach utilizes a modified multi-head self-attention mechanism combined with ResUNet for semantic segmentation, enhanced by superpixel concepts. This method facilitates the generation of representative token features through iterative super-token blocks, creating high-resolution token maps that leverage local and high-level feature information for improved accuracy. Benefiting from token features and distribution for enhanced texture alignment with fewer false-positives, the super-token transformer (STT) model achieved a mean intersection over union (mIOU) of 72.42%, with a sensitivity of 47.81%, specificity of 99.83%, positive predictive value of 64.03%, and negative predictive value of 99.94%, highlighting superior efficacy in Masson body segmentation in complex cross-tissue analyses. Our team developed an iterative learning model based on the STT approach, emphasizing token features of super token, including texture and distribution, that enable enhanced alignment with the unique textures of Masson bodies to improve sensitivity and mIOU, The development of this STT model presents a significant advancement in the field of medical image analysis for OP that offers a promising avenue for improving diagnostic precision and patient outcomes in pulmonary pathology.

M2Trans: Multi-Modal Regularized Coarse-to-Fine Transformer for Ultrasound Image Super-Resolution.

Ultrasound image super-resolution (SR) aims to transform low-resolution images into high-resolution ones, thereby restoring intricate details crucial for improved diagnostic accuracy. However, prevailing methods relying solely on image modality guidance and pixel-wise loss functions struggle to capture the distinct characteristics of medical images, such as unique texture patterns and specific colors harboring critical diagnostic information. To overcome these challenges, this paper introduces the Multi-Modal Regularized Coarse-to-fine Transformer (M2Trans) for Ultrasound Image SR. By integrating the text modality, we establish joint image-text guidance during training, leveraging the medical CLIP model to incorporate richer priors from text descriptions into the SR optimization process, enhancing detail, structure, and semantic recovery. Furthermore, we propose a novel coarse-to-fine transformer comprising multiple branches infused with self-attention and frequency transforms to efficiently capture signal dependencies across different scales. Extensive experimental results demonstrate significant improvements over state-of-the-art methods on benchmark datasets, including CCA-US, US-CASE, and our newly created dataset MMUS1K, with a minimum improvement of 0.17dB, 0.30dB, and 0.28dB in terms of PSNR. Our code and dataset will be available at: https://github.com/eezkni/M2Trans.

Date Fruit Classification using K-Nearest Neighbor with Principal Component Analysis and Binary Particle Swarm Optimization

Various cultivars of date fruits distributed throughout exhibit diverse complexity and unique attributes, including color, flavor, shape, and texture. These distinctive characteristics and appearance occasionally lack variability in date fruits, since various kinds of date fruit may have subtle differences in color, shape, and texture. To overcome the difficulty of sorting and classifying multiple types of date fruit, a classification model was developed to categorize date fruit according to their visual appearances and digital characteristics. This study proposes a classification system that categorizes date fruit into five distinct types. The system achieves this by extracting features related to date fruit images' color, shape, and texture. Specifically, color moments, HOG descriptors, and circularity are used for feature extraction. The resulting high-quality training data is then used to train a K-Nearest-Neighbor (KNN) classifier. Considering the parameters applied to develop the proposed classification model is essential. Therefore, the proposed KNN model will be optimized by Principal Component Analysis (PCA) and Binary Particle Swarm Optimization (BPSO). PCA is employed for dimensionality reduction, whereas BPSO is implemented to discover the optimal neighbors. The experimental results demonstrated that the classification model achieved an accuracy of 93.85%, a considerable improvement of 12% over barebone KNN.

Harvest maturity stage affects watercore dissipation and postharvest quality deterioration of watercore 'Fuji' apples

Watercore 'Fuji' apples, with their special watercore shape and unique flavor and texture, are a very popular specialty fruit in the Asian markets. However, watercore disappearance and quality deterioration of apples during postharvest storage are serious problems. In this study, we compared the differences among three harvest maturity stages of apples in watercore dissipation and fruit quality deterioration. In this study, the physiochemical attributes (visual quality, watercore incidence, and firmness), flavor substances (TSS content, TA content, and TSS/TA), aroma volatiles, and cellular structure were analyzed in 'Fuji' apple fruits of low maturity (LM) at early harvest stage, medium maturity (MM) at mid harvest stage, and high maturity (HM) at late harvest stage, during a cold storage at 0 ± 1 °C for 120 d. The results showed that harvest maturity stage had a significant effect on postharvest storage quality parameters of watercore 'Fuji' apples. Specifically, L*, b*, firmness, and TA values of the flesh decreased significantly from the LM to the HM levels. However, the watercore incidence of apples significantly increased from LM to HM levels. Moreover, the parameters including L*, b*, firmenss, TA, and watercore incidence of apples with different harvest maturity stages gradually decreased as the storage time increased. In contrast, the TSS, TSS/TA, and a* values showed an increasing trend from LM to HM apples. In particular, the TSS tended to increase first and decrease after 60 d of storage. Moreover, the microstructure and cellular structure gradually deformed as the structural porosity and cell size decreased from LM to HM apples. Furthermore, the microstructure of the watercore and non-watercore sites is significantly different. Meanwhile, the content of soluble sugars and aroma volatiles increased with the advancing maturity. Non-watercore sites of apples with the same level of maturity contained higher levels of sucrose, fructose, maltose, and sorbitol than watercore sites. Furthermore, the MM apples maintained better sensory qualities during the shelf life after cold storage. Overall, the MM apples showed higher quality and were more acceptable to consumers, which suggested watercore 'Fuji' apples from mid harvest stage showed the optimal harvest-ready maturity for post-harvest long-term cold storage.

Biofouling and Corrosion Protection of Aluminum Alloys Through Ultrafast Laser Surface Texturing for Marine Applications

AbstractSurface biofouling, corrosion, and wettability are important parameters to understand and characterize aluminum alloys to prevent the failure in marine environments. Antifouling technologies predominantly encompass chemical and biocidal approaches with negative environmental consequences. Therefore, this study focuses on a new method of producing non‐toxic and effective antifouling and corrosion‐resistant surfaces. In this study, ultrafast laser texturing is used to modify the surface of an aluminum alloy using a femtosecond laser system. Five different unique texture patterns are designed and fabricated using 3 W laser power, 100 kHz pulse repetition rate, and 4 mm s−1 scanning speed in order to make the aluminum surface antifouling and corrosion resistant. The non‐textured sample has a contact angle of 85° while the textured samples have contact angles of up to 157°. The contact angle increased with time up to 90 days of aging. Biofouling assessment is conducted using marine algae Nitzschia ovalis as a marine fouling test organism. A reduction of biofilm coverage of 79% is recorded from the laser‐produced star pattern texture. This study demonstrates that laser‐textured surfaces have the potential to mitigate the formation of biofilms on the surfaces while also providing a mechanism to control the relative level of corrosion.

Sourdoughs as Natural Enhancers of Bread Quality and Shelf Life: A Review

Sourdough is a key component in traditional and artisanal bread making. It imparts unique flavors and textures to bread, which are highly sought after by consumers. The use of sourdoughs to prepare bakery products has been researched for more than 30 years, and accumulated research shows the performance of sourdoughs as an alternative to improve the organoleptic characteristics of bread and its shelf life. The purpose of this review is to present an overview of the research carried out on the use of sourdoughs from lactic acid bacteria and their benefits in the quality characteristics of bread, as well as to present relevant and recent information on the use of sourdoughs and their aqueous extracts for the preservation of bakery products. Also, the advances in the identification of antifungal compounds have been revised. In general, it has been shown that incorporating sourdoughs into the bread formulation positively impacts the product’s flavor and helps slow down the bread’s aging process and spoilage. Also, it has been observed that the bioactive compounds formed by lactic acid bacteria (LAB) during sourdough fermentation and their extracts have an antimicrobial, especially antifungal, capacity that significantly helps increase bread’s shelf life. Studying sourdough as part of fermentation processes and product development is essential to improve bread production’s quality, diversity, and sustainability, and to advance our understanding of the science behind this food tradition.

Potensi Daya Tarik Gastronomi Wisata Kuliner sebagai Faktor Kunci dalam Mengembangkan Pariwisata Kuliner Pempek 26 Ilir Palembang

Gastronomy tourism is an important aspect of the tourism industry which is able to attract the attention of visitors from various corners of the world. One of the special foods that stands out in Palembang is pempek, especially Pempek 26 Ilir. This research aims to reveal the potential gastronomic of Pempek 26 Ilir Palembang as the main attraction for tourists. The theories used are Symbolic Communication Theory and Tourist Experience Theory. The research method used involved surveys, interviews, and direct observation of visitors and owners of pempek culinary businesses in the Pempek 26 Ilir area. The research results show that Pempek 26 Ilir has a strong appeal in various gastronomic aspects. The unique taste and texture of pempek, as well as the variety of cuko (gravy) and accompaniments, make visitors come back again to enjoy this dish. Apart from that, the local culinary potential and the pempek raw materials quality are also added value to the culinary experience. The comfortable atmosphere of the stall, the closeness between the owner and visitors, as well as various special promotional programs also enrich the gastronomic experience of tourists. The potential gastronomic attraction of Pempek 26 Ilir Palembang can be a basis for related parties to develop and promote culinary tourism in Palembang. Thus, it can increase tourist visits and contribute to the local economy.

Microscopic growth mechanism and edge states of monolayer 1T′-MoTe2

Transition metal ditellurides (TMTDs) have versatile physical properties, including non-trivial topology, Weyl semimetal states and unique spin texture. Controlled growth of high-quality and large-scale monolayer TMTDs with preferred crystal phases is crucial for their applications. Here, we demonstrate the epitaxial growth of 1T′-MoTe2 on Au (111) and graphitized silicon carbide (Gr/SiC) by molecular beam epitaxy (MBE). We investigate the morphology of the grown 1T′-MoTe2 at the atomic level by scanning tunnelling microscopy (STM) and reveal the corresponding microscopic growth mechanism. It is found that the unique ordered Te structures preferentially deposited on Au (111) regulate the growth of monolayer single crystal 1T′-MoTe2, while the Mo clusters were preferentially deposited on the Gr/SiC substrate, which impedes the ordered growth of monolayer MoTe2. We confirm that the size of single crystal 1T′-MoTe2 grown on Au (111) is nearly two orders of magnitude larger than that on Gr/SiC. By scanning tunnelling spectroscopy (STS), we observe that the STS spectrum of the monolayer 1T′-MoTe2 nano-island at the edge is different from that at the interior, which exhibits enhanced conductivity.

Solid-State Fermented Plant Foods as New Protein Sources.

The current animal-based production of protein-rich foods is unsustainable, especially in light of continued population growth. New alternative proteinaceous foods are therefore required. Solid-state fermented plant foods from Africa and Asia include several mold- and Bacillus-fermented foods such as tempeh, sufu, and natto. These fermentations improve the protein digestibility of the plant food materials while also creating unique textures, flavors, and taste sensations. Understanding the nature of these transformations is of crucial interest to inspire the development of new plant-protein foods. In this review, we describe the conversions taking place in the plant food matrix as a result of these solid-state fermentations. We also summarize how these (nonlactic) plant food fermentations can lead to desirable flavor properties, such as kokumi and umami sensations, and improve the protein quality by removing antinutritional factors and producing additional essential amino acids in these foods.

Exploring the Potential of Blockchain Data as Pseudorandom Numbers for Microtonal Algorithmic Composition. A Case Study on Blockchain Music 2.5

This study explores the utilization of blockchain data as a set of pseudorandom numbers in the context of microtonal algorithmic composition. Conventional methods of generating indiscriminate numbers often lack the desired levels of unpredictability and uniqueness necessary for an intricate musical piece. By harnessing the hash parameter of several blockchains, we propose an innovative approach for obtaining pseudorandom numbers that offer heightened randomness and diversity. Moreover, the ensuing structure ensures the preservation of all composition data on servers, facilitating the re-generation of the piece and enabling listeners to revisit its past fragments. Additionally, leveraging blockchain technology allows the audience to actively interact with the composition, fostering a more engaging and participatory musical experience. Through a comprehensive case study of a self-written, self-generating piece (Blockchain Music 2.5, 2023), we demonstrate the practical implementation of blockchain-generated numbers, showcasing their potential in exploring new post-tonal dimensions and producing unique sonic textures based on the predetermined set of rules. We also discuss the implications, challenges, and potential future directions of incorporating blockchain-generated numbers in algorithmic music composition. The research expands the landscape of digital music composition techniques and offers new avenues for leveraging blockchain technology in the domain of creative expression.

Traditional and New Microorganisms in Lactic Acid Fermentation of Food

Lactic acid fermentation is one of the oldest and most commonly used methods of bioconservation. This process is widely used for food preservation and also for a production technique that relies on the metabolism of lactic acid bacteria (LAB) to convert carbohydrates into lactic acid. This fermentation imparts unique flavors and texture of foods, extends their shelf life, and can offer health benefits. There are both traditional and new microorganisms involved in the lactic acid fermentation of food. The current review outlines the issues of fermented foods. Based on traditional fermentation methods, a broad panorama of various food products is presented, with the microorganisms involved. The methods of both traditional fermentation (spontaneous and back-slopping) as well as the importance and application of starter cultures in mass food production are presented. Currently, based on the results of scientific research, the health-promoting effect of fermented foods is becoming more and more important. This is due to the presence of probiotic microorganisms that are naturally presented or may be added to them, as starter cultures or additives, and from the presence of prebiotics and postbiotics. New innovative methods of using probiotic microorganisms open up new and broad perspectives for fermented functional foods.

Effect of alternative pre-treatments and fermentation on quality characteristics of oyster mushrooms

AbstractBesides their unique taste and texture, mushrooms are a promising source of important nutrients, including dietary fiber, amino acids, minerals, and vitamins. Fresh mushrooms, however, can only endure for a brief time, typically up to three days at ambient conditions. Different methods have been used to preserve mushrooms for a prolonged period, such as drying, cooking, frying, irradiation and fermentation. The objective of the current study is to investigate the effect of different pre-treatments and fermentation on physicochemical, textural, and microbial properties of oyster mushrooms. The fresh oyster mushroom was considered as control and 6 alternative pre-treatment methods were used as; blanching in water, steaming, oven cooking, microwave, High Hydrostatic Pressure and UV Light treatment. Moisture, pH, yield, color, texture, and microbiological analyses were performed on each pre-treatment group before and after fermentation. Our results showed that the quality attributes of oyster mushrooms were significantly affected by the usage of different pre-treatments.

Mechanistic insights into the enhanced texture of potato noodles by incorporation of small granule starches

Potato noodles are a popular food due to their unique texture and taste, but native potato starch often fails to meet consumer demands for precise textural outcomes. The effect of blending small granule (waxy amaranth, non-waxy oat and quinoa) starch with potato starch on the properties of noodles was investigated to enhance quality of noodles. Morphological results demonstrated that small granule starch filled gaps between potato starch granules, some of which gelatinized incompletely. Meanwhile, XRD and FTIR analysis indicated that more ordered structures and hydrogen bonding among starch granules increased with addition of small granule starch. The addition of oat or quinoa starch increased gel elasticity, decreased viscosity of the pastes, and increased the tensile strength of noodles, while addition of 30 % and 45 % waxy amaranth starch did not increase G′ value of gel or tensile strength of noodles. These results indicated that amylose molecules played an important role during retrogradation, and may intertwine and interact with each other to enhance the network structure of starch gel in potato starch blended with oat or quinoa starch. This study provides a natural way to modify potato starch for desirable textural properties of noodle product.

Correlation analysis on the quality indicators of intensified dry-aged beef and microbial succession during fermentation

Dry aging is a historic and common-used preservation and increment method for meat processing, giving the meat product unique mouthfeel and attracted flavor. In this work, less time-consuming intensified dry aging was conducted by using specified strains (all selected from “List of Strains Allowed to Be Used in Food” issued by National Health Commission of the People's Republic of China) mixed of Staphylococcus sarcosa, Debaryomyces hansenii and Pediococcus pentose (1:1:1). The taste, aroma, texture and microbiota of intensified dry-aged beef were investigated and correlatively analyzed. Results showed that the contents and varieties of main taste and aromatic compounds in final products were significantly increased by intensified dry aging, along with unique texture formation and improved palatability of beef. Most importantly, the above-mentioned quality changes were confirmed to be closely correlated with microbial succession during fermentation. All the 3 strains had extremely significant positive correlations with springiness, and Debaryomyces hansenii positively correlated with taste components, and both Pediococcus and Debaryomyces had significant positive correlations with volatile flavor substances. Additionally, 3 selected strains for intensified dry aging could inhibit the growth of spoilage organisms to an extent. This work provides valuable reference both for the industrialization and standardization of dry-aged meat products.

An insight into the quality formation of egg-white sufu based on the dynamic changes of protease activity, physicochemical properties and texture

Sufu is a delicious traditional Chinese food, mainly produced by fermentation using soybeans as raw material. Egg white is rich in protein and is theoretically an excellent material for sufu processing, however there are few reports on egg-white sufu (EWS) currently, and no such product is available on the market. In this paper, a novel sufu was processed with egg white as main material, and the formation mechanism of its unique quality was explored by monitoring the dynamic changes in the pre-fermentation and post-fermentation stages. The dynamic change curve of protease activity showed an “S” shape, with a peak of 32.33 U/mL on the 4th day of pre-fermentation stage. After a 4-day pre-fermentation and 90-day post-fermentation, most of the proteins in the EWS had been hydrolyzed, and the sufu was moderately soft and delicate in texture, with a hardness of 950.3 g and a total free amino acid content of 19.863 mg/g. SEM and SDS-PAGE detections suggested that the proteins in EWS had been extensively degraded, which led to the formation of its unique texture and flavor. The EWS was slightly better than soybean sufu in terms of texture, fragrance and mouthfeel, with flavor compounds mainly composed of aldehydes and alcohols, resulting in a slightly higher total sensory evaluation score.

Investigation of 3D printing product of powder-based white mushroom incorporated with soybean protein isolate as dysphagia diet

The elderly people are prone to dysphagia due to weakened muscle strength. 3D food printing could modify the nutritional ratio and shape design to produce personalized nutritious food suitable for patients with dysphagia. White mushroom (Agaricus bisporus) is rich in a variety of active ingredients such as polysaccharides and polyphenols which are beneficial to human body, but its unique texture is not suitable for patients with dysphagia to chew. This study investigated the impact of different concentrations of soybean protein isolate (SPI, 3%, 5%, 7%, w/w) on 3D food printing of white mushroom powder and carried out the hierarchical representation of dysphagia diet within the framework of International Dysphagia Diet Standardization Initiative (IDDSI). The results illustrated that SPI addition to white mushroom gel reduced water mobility and promoted hydrogen bond formation, which significantly improved the mechanical strength and cohesiveness of printing inks, including yield stress, viscosity and hardness. IDDSI tests showed that the SPI addition of 3% and 5% helped the printing ink pass the spoon tilt test and the fork drip test, which could be classified as level 5 minced and moist food under the consideration of the fork pressure test. The 3D printing results indicated that the 7% SPI addition made the yield stress too high and was not easy for extrusion, resulting in the appearance defects of the printed sample. The addition of 3% SPI could make the printed sample have smooth surface and excellent self-supporting capacity. This work provides insights of white mushroom 3D printing technology as a more visually appealing dysphagia diet.

Ultrahigh initial coulombic efficiency for deep sodium storage enabled by carbon-free vanadium-doping MoS2 hierarchical nanostructure

Molybdenum disulfide (MoS2) has garnered attention as a promising anode material for sodium-ion batteries due to its high theoretical capacity and unique lamellar texture. Nevertheless, unmodified MoS2 suffers from inferior electrical conductivity, poor reaction reversibility, and suboptimal cycle life upon repeated sodiation/desodiation. In this study, a novel carbon-free V-heteroatom doping MoS2 composite (abbr. VMS) with hierarchical laurustinus-like structure was synthesized by a facile one-step hydrothermal process. Specifically, the rational doping of V-atoms can effectively modulate the intrinsic electronic structure of pure MoS2, resulting in enhanced Na-ion diffusion rate, improved reaction kinetics and reduced activation energy compared to bare MoS2. Additionally, the hierarchical structure of the VMS composite, with sufficient spacing, effectively mitigates mechanical stress and ensures the integrity of active materials. Consequently, the prepared VMS composite possesses exceptional reaction reversibility (average ICE value of 92 %) and remarkable capacity retention (92.1 % after 450 cycles at 10 A/g). These findings contribute valuable insights into the development of advanced MoS2-based anode for sodium ion batteries.

A fine-grained recognition technique for identifying Chinese food images

As a crucial area of research in the field of computer vision, food recognition technology has become a core technology in many food-related fields, such as unmanned restaurants and food nutrition analysis, which are closely related to our healthy lives. Obtaining accurate classification results is the most important task in food recognition. Food classification is a fine-grained recognition process, which involves extracting features from a group of objects with similar appearances and accurately classifying them into different categories. In a such usage environment, the network is required to not only overview the overall image, but also capture the subtle details within it. In addition, since Chinese food images have unique texture features, the model needs to extract texture information from the image. However, existing CNN methods have not focused on and processed this information. To classify food as accurately as possible, this paper introduces the Laplace pyramid into the convolution layer and proposes a bilinear network that can perceive image texture features and multi-scale features (LMB-Net). The proposed model was evaluated on a public dataset, and the results demonstrate that LMB-Net achieves state-of-the-art classification performance.

Face deblurring based on regularized structure and enhanced texture information

Image deblurring is an essential problem in computer vision. Due to highly structured and special facial components (e.g. eyes), most general image deblurring methods and face deblurring methods failed to yield more explicit structure and facial details, resulting in too smooth, uncoordinated and distorted face structure. Considering the unique face texture and sufficient facial details, we present an effective face deblurring network by exploiting more regularized structure and enhanced texture information (RSETNet). We first incorporate the face parsing network with fine-tuning to obtain more accurate face structure, and we present the feature adaptive denormalization (FAD) to regularize the facial structure as a condition of auxiliary to generate more harmonious and undistorted face structure. Meanwhile, to improve the generated facial texture information, we propose a new Laplace depth-wise separable convolution (LDConv) and multi-patch discriminator. Compared with existing methods, our face deblurring method could restore face structure more accurately and with more facial details. Experiments on two public face datasets have demonstrated the effectiveness of our proposed methods in terms of qualitative and quantitative indicators.

Bioengineering research on sesame anti-alimentary factors inactivation for confectionery industry

The object of research. The process of inactivation of inhibitors of proteolytic enzymes of sesame seeds for use in the confectionery industry.
 Investigated problem. The use of sesame seeds in the confectionery industry is very popular, as it adds a unique taste and texture to products. However, inhibitors of seed proteolytic enzymes can limit the absorption of nutrients such as proteins. This can be a problem in terms of nutritional value and efficient use of sesame seeds in the food industry. Inactivation of inhibitors of proteolytic enzymes in sesame seeds will contribute to the stability and uniformity of the quality of raw materials, which is an important aspect in the confectionery industry. This allows enterprises to ensure high sustainable quality of products containing sesame seeds and competitive advantages of such products.
 The main scientific results. The features of the inactivation of anti-alimentary factors of sesame were studied, namely the influence of the initial humidity and the time of treatment with ultra high frequency (UHF) radiation on the inactivation degree of inhibitors of proteolytic enzymes of the seeds. Rational conditions for pre-treatment of sesame seeds for inactivation of anti-alimentary factors were established: moisture to 10–13 %, treatment time with UHF radiation 220–240 s. The peculiarities of the use of crushed sesame seeds with an inactivated anti-alimentary complex in the technology of high-nutrition chocolate pastes were studied. Organoleptic evaluation of test samples with different content of sesame seeds was carried out, during which the products were evaluated according to their appearance, uniformity, plasticity, color, taste and aroma. The effect of the content of crushed sesame seeds with an inactivated anti-alimentary complex on the consumer properties of chocolate pastes was determined.
 The area of practical use of research results. Taking into account the results of the research can contribute not only to the improvement of technological processes in confectionery production, but also to the development of new products that meet the modern requirements of consumers.
 Innovative technological product. As a result of research, an innovative food product was created, which is an innovative approach to the use of sesame seeds in the technology of chocolate pastes with increased nutritional value.
 Scope of the innovative technological product. The developed innovative technological product can be implemented in food technology. In particular, the use of sesame seeds with an inactivated anti-alimentary complex in the production of chocolate pastes should become an additional advantage for manufacturers in the market, especially in the context of increased demand for health food products.