Characteristics Of Raw Materials Research Articles

Replacement of raw materials in the formulation of industrial products based on near-infrared spectroscopy and particle swarm optimization

The replacement of raw materials in formulations is a crucial but challenging issue in industrial production. The goal is to substitute the inadequate or costly raw materials or their combinations with the adequate or potentially adequate inventory but while still ensuring the consistency and stability of product quality. In the present study, near-infrared (NIR) technology is first used for rapid and non-destructive analysis and further comprehensive characterization of the chemical characteristics of different raw materials. Afterwards, the particle swarm optimization (PSO) method is modified for the processing of NIR data and formulation replacement. Under the conditions of optimal constraints, an integrated strategy for replacement and optimization of raw materials in formulation is fully established. This yields optimized results for replacements that meet real demands in formulation design. In addition, the simulation of NIR spectra is initially realized by combining multiple Gaussian functions, which constructs simulated datasets that are suitable for verifying the accuracy and reliability of the proposed method. The real example of the replacement of raw materials is applied to comprehensively demonstrate the effectiveness and capability of the strategies proposed in this study. Among the 3,000 combinations used for formulation replacement, the recommended results obtained through the PSO method exhibit a high targeted proportion, attaining 81.82%, in which the difference between the optimal and original formulation is less than 0.0005. The results of expert validation indicate that 83% of the evaluations are consistent with spectral similarity assessments, which shows that the replaced results effectively meet the requirements for objective, scientific and digitized requirements in product manufacturing. Furthermore, this proposed method is applicable to various analysis and application scenarios on the basis of NIR analysis and global optimization.

Development of bentonite-based organo-geopolymer hybrid wood binder

AbstractThe study addresses concerns associated with formaldehyde-based adhesives in wood panel board production by proposing geopolymer-based wood binders as promising, formaldehyde-free alternatives. Using bentonite, the research delves into the development and performance properties of this geopolymer wood binder. The BET method was employed for the surface characterization of precursor raw materials for binder preparation. Si and Al elements identified through XRF analysis were correlated with characteristic bands in the FTIR spectrum. Alkaline activation solutions, employing sodium silicate and sodium hydroxide with a molar ratio range of 0.5 to 2.5 (SiO2:Na2O), revealed that binders with a molar ratio of 2.5 exhibited lower pH and higher adhesion strength. Different geopolymer formulations at solution to powder ratios (s/p) of 1.33, 3, and 3.5 determined s/p 3.5 as optimal for bentonite-based organo-geopolymer binders. Viscosity, gel time, pH, and solids content were examined, showing the effectiveness of substituting 10% silica fume to enhance the geopolymerization process and improve adhesion. Modifications using citric acid, sucrose, paraffin, pMDI, triacetin, and resorcinol demonstrated wet bonding strength comparable to urea formaldehyde adhesive. Analytical techniques, including FTIR spectroscopy, XRD analysis, and SEM EDX analysis, provided insights into functional groups, crystallographic properties, and microstructural characteristics. The concentration of Si and Al compounds on the bonding line, coupled with Na element diffusion, was observed through these analyses. Light microscopy of lap shear samples revealed a thinner bonding line, affirming effective binder penetration into wood cell lumens in bentonite-based organo-geopolymer binder formulations.

Influence of TiO2 Nanoparticles on the Physical, Mechanical, and Structural Characteristics of Cementitious Composites with Recycled Aggregates.

The aim of this study is to analyze the effect of the addition of TiO2 nanoparticles (NTs) on the physical and mechanical properties, as well as the microstructural changes, of cementitious composites containing partially substituted natural aggregates (NAs) with aggregates derived from the following four recycled materials: glass (RGA), brick (RGB), blast-furnace slag (GBA), and recycled textolite waste with WEEE (waste from electrical and electronic equipment) as the primary source (RTA), in line with sustainable construction practices. The research methodology included the following phases: selection and characterization of raw materials, formulation design, experimental preparation and testing of specimens using standardized methods specific to cementitious composite mortars (including determination of apparent density in the hardened state, mechanical strength in compression, flexure, and abrasion, and water absorption by capillarity), and structural analysis using specialized techniques (scanning electron microscopy (SEM) images and energy dispersive X-ray spectroscopy (EDS)). The analysis and interpretation of the results focused primarily on identifying the effects of NT addition on the composites. Results show a decrease in density resulting from replacing NAs with recycled aggregates, particularly in the case of RGB and RTA. Conversely, the introduction of TiO2 nanoparticles resulted in a slight increase in density, ranging from 0.2% for RTA to 7.4% for samples containing NAs. Additionally, the introduction of TiO2 contributes to improved compressive strength, especially in samples containing RTA, while flexural strength benefits from a 3-4% TiO2 addition in all composites. The compressive strength ranged from 35.19 to 70.13 N/mm2, while the flexural strength ranged from 8.4 to 10.47 N/mm2. The abrasion loss varied between 2.4% and 5.71%, and the water absorption coefficient varied between 0.03 and 0.37 kg/m2m0.5, the variations being influenced by both the nature of the aggregates and the amount of NTs added. Scanning electron microscopy (SEM) images and energy dispersive X-ray spectroscopy (EDS) analysis showed that TiO2 nanoparticles are uniformly distributed in the cementitious composites, mainly forming CSH gel. TiO2 nanoparticles act as nucleating agents during early hydration, as confirmed by EDS spectra after curing.

An innovative dryer for Arabica coffee (Coffea arabica L.) drying: Investigating heat and mass transfer

In the pursuit of advancing post-processing techniques for Arabica coffee, our research introduces a rotary dryer, known as a roto-aerated dryer, marking its first application in coffee drying and surpassing conventional methods. This study delves into the evaluation of heat and mass transfer dynamics between coffee and drying air within the innovative dryer. Characterization of raw materials precedes a series of drying experiments under varied conditions, forming the basis for a mathematical two-phase model elucidating the underlying dynamics of the drying process. Noteworthy is the significantly reduced material residence time (14.60–27.47 min) compared to conventional dryers. Drying rates (0.09–0.24 g water/100 g solid/min) surpass those achieved by other methods. Simulated results from the numerical solution of the two-phase model closely align with experiments (average error of 2.39% for moisture content and 0.89% for temperature). The effective preservation of material quality, particularly acidity, underscores the valuable insights offered for optimizing drying processes, holding substantial potential for advancing the specialty coffee industry.

Fixed position varying pore structure of weft-knitted seamless fabric and heat/moisture transfer mechanism

In this work, two functional superfine polyester yarns were selected as face yarns, three conventional yarns were selected as ground yarns, and 18 fabrics were designed by using a combination of three different plating structures. Then, through contact angle measurements, moisture management performance, thermal management performance, and breathability tests, we evaluated the effects of raw material, structure, and pore characteristics on the fabric’s hygrothermal comfort, and furthermore assessed the prioritization of the three factors using a range analysis. The results show that fabrics with face yarn of 75 D/288 F have better hydrophilicity, and fabrics with face yarn of 50 D/216 F have a better temperature control effect. The fabric with spandex/polyester covered yarn or spandex/nylon covered yarn has the best moisture transmission, and the unidirectional transfer index can reach 300%. The microstructure has a great influence on air permeability, and the surface porosity is positively correlated with air permeability. Combined with the heat and humidity division of the sports body, the development of efficient zonal positioning of heat and moisture management sports undershirts can provide certain theoretical support for the design of weft-knitted seamless sports products.

Physical and Chemical Characteristics of Liquid Organic Fertilizer from Shrimp Shell Waste and Old Coconut Water

The rapid growth of people and industry generates organic waste of 50-60% of production materials. These wastes can be used for agriculture, as human awareness of healthy consumption causes agriculture to start using organic materials. Organic waste from industry in the form of shrimp shells and old coconut water can be used as organic fertilizer for plant growth and development. This study aims to examine the dynamics of reactions that occur during the process of making organic fertilizer and test the physical and chemical quality of the resulting organic fertilizer. This research has a combination design of 2 factors. The first factor is the fermentation method (F) which consists of 2 levels, namely: F1 = container with air hose (aerobic), F2 = tightly closed container (anaerobic). The second factor is the organic fertilizer raw material (L) which consists of 3 levels, namely: L1 = shrimp shell waste, L2 = old coconut water, L3 = shrimp shell waste + old coconut water. The results showed on the physical characteristics, aerobic fermentation treatment is faster to produce organic fertilizer than anaerobic, and the speed of producing organic fertilizer is also influenced by the characteristics of raw materials. Wheareas based on the chemical properties, all treatments have not met the Indonesian national standards, but there are several chemical components that meet such as pH, C-organic and N-total. The treatments that are close to the standard are F1L1 and F1L3 treatment for N-total, F1L2 and F2L2 for C-organic.

COMPRESSIVE AND BENDING STRENGTH OF CHAMBO ARTISANAL BRICKS WITH ADDITION OF RECYCLED GLASS POWDER

This article describes the main findings obtained when implementing recycled glass powder as an ingredient in the production of artisanal bricks in the Chambo canton, with the aim of improving their mechanical properties. The characterization of the brick's raw material (soil and ash) was carried out, followed by the fabrication of bricks with the addition of glass powder (PV), using the artisanal procedure with only the modification of adding glass powder to the mixture. The results indicate that the soil used as the main raw material is classified, according to the SUCS methodology, as a well-graded sand with silt (SW-SM). Modified bricks with glass powder show up to 240% compressive strength and 220% flexural strength capability compared to traditional bricks when using 8% to 12% glass powder dosage in the mixture. Additionally, both traditional and modified bricks exhibit a water absorption percentage between 25% and 26%. The procedures, as well as the interpretation and contrast of the results, are based on the guidelines established by the Ecuadorian Institute of Standardization (INEN).

Prediction of bio-oil yield by machine learning model based on 'enhanced data' training

Bio-oil is widely used and has great application potential. With the development of artificial intelligence, machine learning has been gradually applied in the field of biomass, the data augmentation method is a common operation method for training models in the field of computer or data processing. In this study, the concept of 'enhanced data' was proposed for the first time. According to the composition characteristics of biomass raw materials, the sample data were divided into three different sample sets. Based on the light gradient boosting machine (Light GBM) and deep neural network (DNN) algorithm, a prediction model of bio-oil yield was established. Combined with the analysis of partial correlation, the influence of 'enhanced data' on the prediction accuracy of the model was explored. The results showed that the prediction accuracy of the model was improved to a certain extent after adding 'enhanced data'. The Light GBM model was more suitable for predicting bio-oil yield, and the Light GBM _ c model performed best, with R2 of 0.894, MAE of 3.622, and RMSE of 4.445. At the same time, this study also has certain reference significance for other prediction studies in the field of biomass thermochemical conversion.

Productivity of two Brassica oilseed crops in a Mediterranean environment and assessment of the qualitative characteristics of raw materials for bioenergy purposes

Rapeseed (Brassica napus var. oleifera D.C.) and Ethiopian mustard (Brassica carinata A. Braun) are promising industrial crops for cultivation in the Southern Mediterranean area due to profitable yields under semi-arid conditions. The exploitation of raw materials produced by these crops is very convenient for farmers to produce bioenergy directly on-farm and permits them to create a short agri-energy supply chain. The purpose of this study was to determine their yield performance under rainfed conditions and make an economic assessment of a combined heat and power plant (CHP) system operating on pure vegetable oil (PVO). Tests were conducted in Sicily (Italy) from 2012 to 2014. Seed and crop residue yields were detected. The analysis of seed, defatted seed meal and crop residue, and the chemical-physical aspects of PVO were carried out according to conventional protocols. A pilot CHP system was used for cogenerating electricity and heat. In general, rapeseed had the highest seed (2.27 t ha−1) and oil (1.11 t ha−1) yields. The average oil content ranged from 44.88 % (Ethiopian mustard) to 45.73 % dry matter (rapeseed). Ethiopian mustard performed better than rapeseed in terms of aboveground biomass yield (5.49 t ha−1), in both years. The two crops showed different fatty acid profiles of the oil mainly due to diverse content of erucic and oleic acids. The CHP system had an average consumption of 14.41 kg PVO h−1. These results confirm that the productivity of the species can be appreciable in the Southern Mediterranean area and indicate the use of raw materials of these crops as crucial to the development a sustainable short agri-energy supply chain.

Developing a data-driven operational guide for the texturized yarn production process: data mining and intelligence approach

PurposeThe textile industry holds immense significance in the economy of any nation, particularly in the production of synthetic yarn and fabrics. Consequently, the pursuit of acquiring high-quality products at a reduced cost has become a significant concern for countries. The primary objective of this research is to leverage data mining and data intelligence techniques to enhance and refine the production process of texturized yarn by developing an intelligent operating guide that enables the adjustment of production process parameters in the texturized yarn manufacturing process, based on the specifications of raw materials.Design/methodology/approachThis research undertook a systematic literature review to explore the various factors that influence yarn quality. Data mining techniques, including deep learning, K-nearest neighbor (KNN), decision tree, Naïve Bayes, support vector machine and VOTE, were employed to identify the most crucial factors. Subsequently, an executive and dynamic guide was developed utilizing data intelligence tools such as Power BI (Business Intelligence). The proposed model was then applied to the production process of a textile company in Iran 2020 to 2021.FindingsThe results of this research highlight that the production process parameters exert a more significant influence on texturized yarn quality than the characteristics of raw materials. The executive production guide was designed by selecting the optimal combination of production process parameters, namely draw ratio, D/Y and primary temperature, with the incorporation of limiting indexes derived from the raw material characteristics to predict tenacity and elongation.Originality/valueThis paper contributes by introducing a novel method for creating a dynamic guide. An intelligent and dynamic guide for tenacity and elongation in texturized yarn production was proposed, boasting an approximate accuracy rate of 80%. This developed guide is dynamic and seamlessly integrated with the production database. It undergoes regular updates every three months, incorporating the selected features of the process and raw materials, their respective thresholds, and the predicted levels of elongation and tenacity.

Agricultural waste as a sustainable source for nanoparticle synthesis and their antimicrobial properties for food preservation

Traditional agriculture from cropping to harvesting is contributing to climate change by increasing global greenhouse emissions. Circular economy approaches and biorefinery technologies based on the reuse, recycling, and remanufacturing might result in the valorization of wastes that consequently would avoid environmental pollution. Nanoparticles synthesis using bio-waste such as stems, leaves, seeds, pulp, stubble, and bagasse is considered a green approach with low energy consumption, and low-cost production. Characteristics of raw materials influence the final application of nanoparticles in edible coatings, and films. Therefore, the preparation of nanoparticles based on cellulose, pectin, metal (titanium oxide, silver, zinc oxide), or silica are considered organic, inorganic, or hybrid nanocomposites, are resulted in several benefits including shelf-life extension and broad-spectrum antimicrobial properties by its capacity to encapsulate active compounds that greatly improve food preservation. For considering agro-waste-based nanoparticles in food, challenges in homogenization and synthesis, yield, and toxicity are mainly described. Therefore, this review examines the employment of agro-industrial waste for the development of sustainable nanoparticles and their synthesis methods (top-down and bottom-up). Moreover, it discusses their incorporation and role in active edible coatings and films by highlighting their bioactive properties, mechanisms of action, and applications in food group preservation.

Characteristics of secondary dairy raw material obtained during dairy processing

This study focuses on by-products of dairy processing and the effectively utilization to reduce environmental problems. The existing traditional technology of producing sour cream, butter, natural cheeses and cottage cheese receives huge amount of by-products such as skim milk, buttermilk and whey is called “secondary dairy raw material”. Enzymatic hydrolysis of kappa-casein is the particular process that starts the coagulation of milk and the casein micelles’ characteristics change and become unstable and begin to combine. A 3-dimensional network of casein micelles eventually emerges as aggregation continues. The amount of nutrients and the chemical elements to be taken into consideration for further processing would lower the cost of manufacturing and increase corporate profit, according to tests conducted on the samples’ protein, lactose content, titratable acidity, and pH. It could be used as a product for functional purpose and processing of whey and the production of whey drinks which has dietary and therapeutic nutrition. They can significantly increase the biological value of nutrition and due to lipotropic and antioxidant components (phospholipids, choline, leucine, vitamin E and other substances) mitigate the manifestation of latent forms of vitamin deficiency. Therefore, whey should be more fully processed for food purposes.

Meat productivity and functional properties of meat from Kazakh white-headed bulls with the introduction of an adaptogen system into the diet

This article provides research on the use of a system of adaptogens of plant and animal origin, such as Leuzea safflower, drone homogenate, and pantocrine. The use of adaptogens in diets stimulates the development of animals, improves biochemical parameters, increases meat productivity and the characteristics of meat raw materials. To assess the effectiveness of adaptogens in diets, control and experimental groups of animals were compiled. Adaptogen preparations were fed to animals for 12 months. During the experiments, meat productivity indicators were determined. At the final stage of the research, an assessment of raw meat obtained from the control and experimental groups was carried out in order to determine its functional and technological properties. During the research, it was found that the use of the adaptogen system increases the meat productivity of animals, improves the quality and technological parameters of meat.

Hardness Prediction of WC-Co Cemented Carbide Based on Machine Learning Model

The hardness of cemented carbides is a fundamental property that plays a significant role in their design, preparation, and application evaluation. This study aims to identify the critical factors affecting the hardness of WC-Co cemented carbides and develop a high-throughput predictive model for hardness. A dataset consisting raw material composition, sintering parameters and characterization results of cemented carbides was constructed in which the hardness of cemented carbide was set as the target variable. By analyzing the pearson correlation coefficient, shapley additive explanations(SHAP) results, WC grain size and Co content were determined to be the key characteristics influencing the hardness of cemented carbide. Subsequently, machine learning models such as support vector regression (SVR), polynomial regression (PR), gradient boosting decision tree (GBDT), and random forest (RF) were optimized to construct prediction models for hardness. Evaluations using 10-fold cross-validation demonstrated that the GBDT algorithm model exhibits the highest accuracy and strong generalization ability, making it most suitable for predicting and analyzing the hardness of cemented carbides. Based on predictions from GBDT algorithm model, PR algorithm model was established to achieve high-precision interpretable prediction of the hardness of cemented carbides. As a result, a quantitative relationship between hardness and Co content and WC grain size were obtained, which show that reducing grain size and Co content is the key to obtain high hardness of cemented carbide. This research provides a data-driven method for accurately and efficiently predicting cemented carbide properties, offering valuable insights for the design and development of high-performance cemented carbide materials.

Deep Concrete Flow: Deep learning based characterisation of fresh concrete properties from open-channel flow using spatio-temporal flow fields

The global production of concrete, being one of the most commonly utilised materials in the world, is associated with significant CO2-emissions and a substantial depletion of mineral resources. In order to improve sustainability, concretes thus are increasingly produced using recipes containing a large variety of different raw materials, including e.g. CO2 reduced cements or recycled materials and industrial wastes. However, these actions result in heightened susceptibility of the concrete to variations in raw material characteristics, consequently diminishing the concrete’s resilience and decreasing the concrete’s robustness. Against this background, the quality control of fresh concrete before casting becomes of significant importance. However, current quality control is mainly conducted based on analogous, empirical, and often subjective test approaches. In this paper, a novel method is introduced for automatically and comprehensively evaluating the quality of fresh concrete at construction sites. In particular, the paper presents an end-to-end trainable framework for the image-based characterisation of fresh concrete properties. More specifically, a camera-based setup is proposed, in which image sequences of the discharge process of a mixing truck are acquired, on the basis of which the fresh concrete properties such as the consistency and rheology are determined. In this context, this paper introduces the concept of Spatio-Temporal Flow Fields, which provide a compact representation of the concrete’s flow behaviour and serve as input to a multi-task convolutional neural network (CNN) predicting the target parameters describing the fresh concrete’s properties. A thorough examination of the performance of the suggested method is carried out using highly challenging real-world data, showcasing extremely compelling outcomes with average prediction errors for the concrete properties of only about 6%.

Верификация оптимальных условий и параметров биотрансформации мышечной ткани филе рыб бактериальными заквасочными культурами

The article describes the relevance and expediency of using a method of biotechnological processing, namely biotransformation of fish raw materials by bacterial starter cultures, which is a priority of developing areas according to the Strategy of improving the quality of food products in the Russian Federation until 2030. The studied method of processing will positively affect the shelf life of fish products, its organoleptic properties and nutritional value due to the formation of metabolites of the vital activity of bacterial starter cultures, which are the main factor of bioconservation, synthesis of vitamins and other biologically active substances. Probiotic properties of bacterial starter cultures will have a significant impact on the optimization of the internal microflora of the gastrointestinal tract, thereby strengthening the human body and its immune system as a whole, which supports the principles of a healthy lifestyle. In accordance with this, studies have been conducted to study the possibility of using bacterial starter cultures for the biotransformation of fish raw materials in order to further obtain a probiotic food product based on it. Data on the effect of bacterial starter cultures on organoleptic microstructural, physico-chemical and functional-technological characteristics of fish raw materials are presented. The number of residual cells of bacterial starter cultures in the muscle tissue of fish fillets, which meets the requirements for probiotic products, was revealed. The survival rate under the influence of temperatures and the dynamics of changes in the number of bacterial starter cultures during storage in fish fillet muscle tissue samples were determined, the data on which will be used to develop and adjust the thermal treatment modes of the final product. The influence of bacterial starter cultures on the changes in total viable count after biotransformation and during storage is analyzed, on the basis of which the effect of bioconservation is justified. The results of the conducted studies became the basis for the selection of the most suitable bacterial starter cultures, as well as verification of optimal conditions and parameters predicted by mathematical modeling algorithms for biotransfor-mation of the muscle tissue of fish fillets. At the next stage, research will be conducted to study the possibility of using fish raw materials treated with bacterial starter cultures in the formulations of “fast food” products containing functional components, which is justified by the accelerated rhythm of life and the desire of modern society to monitor their nutrition by eating foods that correspond to a healthy lifestyle.

CLIMATIC FACTORS CHARACTERIZING THE MOISTURE SUPPLY OF THE TERRITORY AND THEIR EFFECT ON THE QUALITY INDICATORS OF GRAPES

The study of scientific problem, to which this research is devoted, is due to planetary climate change, manifested in an increase in the average annual air temperature, rapid changes in winter and summer temperatures, and a lack of precipitation.
 For today, there is a serious problem of adapting plants to climate change due to an increase in water deficiency in many regions of the world. Climate change creates significant uncertainty in the potential adaptability of grape plants, as well as in the prospects for viticulture development in general.
 The study and generalization of territorial distribution of climatic factors that characterize a particular region, as well as their effect on the quality characteristics of raw materials and finished products, are attractive from the point of better understanding and forecasting the potential impact on agricultural systems. The obtained data consumption will allow improving the forecast of climate change consequences in the medium term, and in relation to particular terroirs.
 The goal is to study the effect of climatic factors that characterize the moisture supply of the territory on the quality indicators of grapes.
 Materials and methods. The objects of the study were grapes of white and red cultivars, different in agroecological aspect, and growing in micro regions of Crimea. To identify the effect of factors characterizing the moisture supply of the territory on the quality indicators of raw materials for winemaking products, the amount of precipitation from the beginning of growing season to the harvesting, the amount of precipitation for the last month before harvest, and hydrothermal coefficient of Selyaninov were selected. The assessment of grapes was carried out according to the indicators of carbohydrate-acid complex (mass concentration of sugars, titratable acids, pH value, profile of organic acids), as well as the glucoacidimetric indicator revealing the degree of grape ripeness.
 Results and conclusion. Climatic factors characterizing the moisture supply of viticultural and winemaking regions of Crimea were assessed. The studies carried out made it possible to reveal variations in the concentration of carbohydrate-acid complex components depending on the changing ability of environmental factors. A significant precipitation deficiency was observed on the Peninsula. According to the value of hydrothermal coefficient of Selyaninov (did not exceed 1), most of the territory was classified as an arid or very arid zone. A correlation between the hydrothermal coefficient and mass concentration of grape sugars (r=-0.63) was established for red grapevine cultivars. The data obtained indicate that an increase in the amount of precipitation during growing season contributes to a moderation of sugar accumulation in grapes. Similar pattern was not established for white grapevine cultivars. There was a direct correlation of the mass concentration of malic acid on the amount of precipitation in the last month before harvest (r=0.78).

Общее содержание и фракционный состав белка в семенах сортов сои селекции ФГБНУ ФНЦ ВНИИМК

The use of high-protein soybean cultivars is one of the most important reserves for solving the problem of protein deficiency in the production of feed and food products. In recent years, soybean cultivars with high productivity potential and improved biochemical composition of seeds have been developed in the V.S. Pustovoit All-Russian Research Institute of Oil Crops. The cultivars approved for usage in various regions of the Russian Federation were assessed by the total protein content in seeds and its fractional composition as the main biochemical characteristics of raw materials. The cultivars with a high content of water-soluble (albumin) and stable indicators of salt- and alkali-soluble (globulins and glutelins) fractions, respectively, were noted. It was established that the studied indicators depended not only on the genetic properties of the cultivars, but also on the characteristics of the conditions of the reproduction year. Thus, in soybean seeds of the 2021 harvest, the cultivars Iney (39.0%), Triada (39.9%) and Graya (42.0%) stood out with the highest protein content; in terms of albumin content in protein – Graya and Bars (91.8 and 92.0%, respectively). And in the seeds of the 2022 harvest, the maximum protein content was observed in the cultivars Puma (38.9%), Graya (39.4%) and Gnom (40.2%), albumin content – Barguzin (92.7%), Bars (94.5%) and Puma (95.1%). A weakly positive correlation was noted between the total protein content and the proportion of the water-soluble fraction in it (r = +0.33).

Mulberry silkworm biotechnology as the basis of a bioindustrial platform. Improvements on the upstream processing stage (USP)

Molecular engineering is an upstream engineering method for creating functional materials and devices using molecules, and atoms as building blocks. In 2000, Japan became the first country to genetically modify silkworms (Bombyx mori, hereinafter referred to as B. mori). The subsequent research in the development of new materials expanded the possibilities of using sericulture products, characterizing this situation as a "sericulture revolution". In the Russian Federation, molecular engineering in life sciences is aimed at solving the tasks of developing world-class technological platforms to create tools to produce new molecules (biopolymers, proteins, enzymes), bioproducts, cells and organisms. The main "bottom-up" approaches applied in the upstream process (USP) stage of silk production to improve the production and economic performance and quality characteristics of raw materials have been studied. The variety of improvement methods includes: the possibility of using artificial nutrient medium, molecular engineering based on transient expression techniques or stable germline transformation, genetic selection methods, breeding management, etc. The advantages of the mulberry silkworm (B. mori) such as low breeding costs, significantly higher production yield compared to other protein expression systems, favor its use as an effective producer of recombinant proteins, antimicrobial peptides and biologically active substances. USP stage biotechnologies enable the production of new raw materials for downstream processing (DSP) to produce a wide range of products that contribute to improving the quality of human life. A set of biotechnological solutions forms the modern basis of the mulberry silkworm bioindustrial platform.

The utilisation of thermally treated poultry farm waste for energy recovery and soil application

The thermal treatment was analysed of poultry farm waste, excrement and litter, and their mixture. Two thermal treatment methods were chosen: Torrefaction at 300 °C and hydrothermal carbonisation (HTC) at 250 °C. The characterisation of raw materials and solid products was performed by proximate and ultimate analysis, and analysis of the high heating value. Thermogravimetric analysis (TGA) was performed of the combustion of raw materials and solid products in an air atmosphere. The kinetic and thermodynamic parameters were determined according to the Flynn–Wall–Ozawa (FWO) kinetic model. The contents of total organic carbon, chemical oxygen demand, total nitrogen and total phosphorus, as well as the content of total phenols, were determined in the process fluids. In addition, a germination test was performed with garden cress.The results show that the torrefied biomass had a higher carbon (C) content and a higher calorific value than raw biomass. The FWO kinetic model proved to be suitable for describing the kinetic of combustion of the tested samples' high fitting coefficients. The Eα for torrefied litter, excrement and their mixture ranged between 129 and 338, 108–550 and 136–489 kJ/mol, while for the HTC-treated samples generally lower Eα values were measured, 187–364, 121–229 and 126–428 kJ/mol, respectively. Germination tests with garden cress and analysis of nutrients showed that the tested products of torrefaction and HTC have a perspective for agricultural use at a sample concentration of up to 10 wt% in the substrate.