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In this study freeze-drying and oven-drying (at 50 and 65 °C) were applied for the preparation of dried pumpkin waste. The effect of drying methods on physical properties (moisture content, water activity, hygroscopicity, water solubility, bulk and tapped density, flowability and colour), content of bioactive compounds (carotenoids and phenolics) and antioxidant activity were investigated. Also, the influence of one-year storage at –20 °C on the bioactive compounds content and the antioxidant activity of dried pumpkin waste was examined. Results indicated that drying method showed a significant impact on the investigated characteristics. Bioactive compounds content and antioxidant activity by DPPH test of freeze-dried were higher than of oven-dried pumpkin waste, while higher antioxidant activity in reducing power assay was determined by oven-dried pumpkin waste. An artificial neural network model was developed, for the anticipation of antioxidant activity according to bioactive compounds content (phenolics and carotenoids), in oven-dried (at 50 and 65 °C) and in freeze-dried pumpkin waste after one-year storage. These models showed good prediction properties (the r2 value during training cycle for output variables was 0.999). It was demonstrated that pumpkin waste is potentially an important source of bioactive compounds, which can be used after extraction in suitable forms in the development of functional food products.

In this paper, zein-based films with the addition of shellac were synthesized by lamination on the existing dry zein film (L samples) and by adding shellac alcohol solution during the synthesis of zein film in a ratio of 50-50 by casting process (M samples). Zein films without the addition of shellac were designated as control samples. Physico-chemical (thickness, moisture content and solubility), mechanical (tensile strength and elongation at break) and barrier characteristics (water vapor permeability) were examined for all samples. The resulting films were transparent, glossy, light yellow (control) to ocher (samples with shellac), flexible, and non-sticky. The results showed significantly higher values of elongation at the break of the samples with shellac (11.49% for M and 18.99% for L) compared to the control (7.14%). Significantly lower water vapor permeability values were found, 10.04 g/(m²ꞏh) for L, and 18.41 g/(m²ꞏ h) for M, compared to the control pure zein film (40.33 g/(m² ꞏh)).

The machine learning technique for prediction and optimization of building material performances became an essential feature in the contemporary civil engineering. The Artificial Neural Network (ANN) prognosis of mortar behavior was conducted in this study. The model appraised the design and characteristics of seventeen either building or high-temperature mortars. Seven different cement types were employed. Seventeen mineral additives of primary and secondary origin were embedded in the mortar mixtures. Cluster Analysis and Principal Component Analysis designated groups of similar mortars assigning them a specific purpose based on monitored characteristics. ANN foresaw the quality of designed mortars. The impact of implemented raw materials on the mortar quality was assessed and evaluated. ANN outputs highlighted the high suitability level of anticipation, i.e., 0.999 during the training period, which is regarded appropriate enough to correctly predict the observed outputs in a wide range of processing parameters. Due to the high predictive accuracy, ANN can replace or be used in combination with standard destructive tests thereby saving the construction industry time, resources, and capital. Good performances of altered cement mortars are positive sign for widening of economical mineral additives application in building materials and making progress towards achieved carbon neutrality by reducing its emission.

The quality of protein is based on their amino acid composition, especially on the content and availability of essential amino acids. Cereals are important sources of protein for human nutrition, but are limited in the amounts of essential amino acids, notably lysine. The aim of this study was to analyze the chemical composition and amino acid profiles of different cereals that are important for nutritional purposes in human diet. The content of protein, moisture and crude fat in cereals varied significantly from 7.83 to 13.22%, 11.45 to 13.80%, and from 1.67 to 6.35%, respectively. The obtained results showed that oat had the highest contents of crude protein (13.22%), crude fat (6.35%) and crude cellulose (9.42%) compared to other cereals. Significant (p < 0.05) variation existed in the content of essential and nonessential amino acids among samples with the highest level in oat and wheat. Essential amino acids accounted for one-third of the total amino acids in the tested cereals. Glutamic acid was found to be the most abundant amino acid. It could be concluded that the amino acid composition of oat is the most favorable among cereals due to its high protein content and the content of lysine which can be found in limited amounts in most of the cereals.

Fresh fruit and vegetables contribute to almost 50% of food wasted by households in the EU. To understand the main reasons for wasteful behaviour among the consumers in Vojvodina (Serbia) cross-sectional data were collected through a self-administrated online survey of 711 correspondents. The questions presented in the study focused on the method of preserving the fruits and vegetables in domestic conditions before their consumption. Self-estimation of wasteful behaviour in the household and socio-demographic factors, including the respondents' self-estimated health status, were analysed using the correspondence analysis. The results showed that the first two dimensions explained for 95.06% of the total per cent of inertia (statistically significant at p

Although regular intake of fruits and vegetables has an essential role in a healthy diet and well-being, a majority of consumers in Serbia have a suboptimal intake of these groceries. To understand the main determinants of this unsatisfactory situation, the study tested an extended model of the theory of planned behavior intending to suggest necessary steps for improving fruits and vegetables daily intake. This theory, extended for the role of knowledge, was tested using structural equation modeling. Fit indices confirmed the utility of this extended model of the theory of planned behavior in explaining consumers' behavior as well as the mediating role of behavioral intentions. Serbia, as one of the central developing countries in the Balkans, was chosen to test the model with the possibility of applying it to other developing countries facing malnutrition. Data were collected in North Serbia, through an online survey (n=688). Despite consumers' high awareness of fruits and vegetables' beneficial health effects, the influence of consumers' knowledge only is not sufficient to trigger behavioral changes. Consumers' intentions and behavior should be influenced indirectly, by changing their attitudes and subjective norms. All custom-made activities promoting a higher fruit and vegetable intake should consider the present findings to achieve a bigger effect on behavioral changes among consumers.

Kombucha as a tea-based fermented beverage has become progressively widespread, mainly in the functional food market, because of health-improving benefits. As part of a daily diet for adults and children, kombucha was a valuable non-alcoholic drink containing beneficial mixtures of organic acids, minerals, vitamins, proteins, polyphenols, etc. The influence of the specific surface area of the vessel, the inoculum size, and the initial tea concentration as operating factors and fermentation time as output variable on the efficiency of kombucha fermentation was examined. The focus of this study is optimization and standardization of kombucha fermentation conditions using Box-Behnken experimental design and applying an artificial neural network (ANN) predictive model for the fermentation process. The Broyden-Fletcher-Goldfarb-Shanno iterative algorithm was used to accelerate the calculation. The obtained ANN models for the pH value and titratable acidity showed good prediction capabilities (the r2 values during the training cycle for output variables were 0.990 and 0.994, respectively). Predictive ANN modeling has been proven effective and reliable in establishing the optimum kombucha fermentation process using the selected operating factors.

Thermoplastic poly(urethane-siloxane)/organoclay nanocomposites (TPU NCs) with different hard segment content (20–55 wt. %) were prepared by in situ polymerization in the presence of organically modified montmorillonite as a nanofiller (Cloisite 30B; 1 wt. %). Hydroxyl-terminated ethoxypropyl- poly(dimethylsiloxane) was used as soft segment, while 4,4'-methylenediphenyl diisocyanate and 1,4-butanediol were the hard segment components. The study of the influence of the hard segment content on the functional properties of TPU NCs was performed by Fourier transform infrared (FTIR) spectroscopy, X-ray diffractometry (XRD), atomic force microscopy (AFM), scanning electron microscopy (SEM), dynamic mechanical thermal analyses (DMTA), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), water contact angle and water absorption tests. The results revealed that TPU NCs with the increasing hard segment content exhibit higher values of degree of microphase separation, melting temperature of the hard segments, degree of crystallinity, storage modulus (except for TPU NC-55), but lower thermal stability and hydrophobicity. TPU NC films were hydrophobic and their free surface energy was in the range from 17.7 to 24.9 mJ m-2. This work highlights how the composition of TPU NCs would affect their functional properties and provide an additional composition intended for designing advanced TPU NC materials for special biomedical applications.

A new type of functional food products-bread supplemented with yeast extract-was developed and optimized. In the next product development phase, samples of bread with yeast extract were tasted and evaluated by 536 randomly selected consumers, and their acceptability was analyzed.. The survey results showed that consumers in all groups had a high level of awareness about the importance of product labeling and the impact of food on health, while low requirements for special diets. Bread sensory characteristics were highly acceptable, while the final price of bread with yeast extract was 20% higher than regular bread. Correspondence analysis showed differentiation among categories of consumers and their responses. Despite the high importance of product price and lack of proper marketing, there was a high level of consumers' willingness to change their current bread, and buy this new type.

The objective of this study was to investigate the hydrodynamics and the gas-liquid mass transfer coefficient of an external-loop airlift reactor (ELAR). The ELAR was operated in three cases: different inlet velocities of fluids, different alcohols solutions (water, 0.5% methanol, 0.5% ethanol, 0.5% propanol and 0.5% butanol) and different concentration of methanol in solutions (0%, 0.5%, 1%, 2% and 5%). The influence of superficial gas velocity and various diluted alcohol solutions on hydrodynamics and the gas-liquid mass transfer coefficient of the ELAR was studied. Experimentally, the gas hold-up, liquid velocities and volumetric mass transfer coefficient values in the riser and the downcomer were obtained from the literature source. A computational fluid dynamics (CFD) model was developed, based on two-phase flow, investigating different liquids regarding surface tension, assuming the ideal gas flow, applying the finite volume method and Eulerian-Eulerian model. The volumetric mass transfer coefficient was determined using the CFD and artificial neural network model. The effects of liquid parameters and gas velocity on the characteristics of the gas-liquid mass transfer were simulated. These models were compared with the appropriate experimental results. The CFD model successfully simulates the influence of different alcohols regarding the number of C-atoms on hydrodynamics and mass transfer.

In this research, chicken meat was inoculated with selected microorganisms and subjected to the osmotic dehydration process in two osmotic solutions, in an effort to investigate the effect of storage time duration on its microbiological and chemical characteristics. Total viable counts, numbers of Enterobacteriaceae, Salmonella spp., Listeria monocytogenes, Escherichia coli, proteolytic bacteria, psychotropic bacteria, of microbiological, and biogenic amine content, TBARS and DPPH, and chemical analyses were conducted on meat samples stored at 22°C, during 14 days. During storage, the number of all tested microorganisms on meat samples decreased. The highest reduction occurred in the first 4 days. The meat dehydrated in molasses achieved better results of microbiological profile during storage. Results of TBARS and DPPH analyses indicated lipid oxidation after 14 days of storage, while the results after 10 days were satisfactory. Developed mathematical models allows good prediction of microbiological and chemical responses of dehydrated chicken meat during the investigated storage duration.

The aim of the present work is to determine the shelf life of osmodehydrated white cabbage in three different osmotic solutions. During 90 days of storage, chemical and color parameters were analysed together with the sensory acceptance and microbiological profile of the osmotic treated (OT) cabbage. Hybrid "Bravo" was considered within this research because of its high yield and wide cultivation in the Province of Vojvodina. Solutions of sucrose and chloride were applied so as sugar beet molasses in OT. OT cabbage was packed in MAP with variation in a gas mixture of 40:60/ CO2:N2 (atmosphere 1) and 80:20/CO2:N2 (atmosphere 2). The shelf-life evaluation had shown good sensorial acceptance and satisfying microbiological quality. The obtained principal component analysis (PCA) was able to present the experimental results. The PCA analysis is easy to implement and could be effectively used for predictive optimization of the osmotic treatment.

Amaranth seeds contain oil with important nutritional properties, in particular, because of the presence of essential fatty acids, high content of minerals, vitamins, lysine and squalene. In this study, the kinetics of the supercritical fluid extraction of oil from three amaranth seed varieties has been investigated. The average oil content in amaranth seed was 58.2 g/kg, ranging from 54.6 to 61.1 g/kg depends on varieties, while squalene content ranged from 3.3 to 3.8 g/kg with an average content of 3.5 g/kg dry seed. Five empirical kinetic equations were successfully applied for kinetic modeling of extraction. As indicated by the appropriate statistical "goodness of fit" tests (such as the sum of squared errors, the coefficient of determination and the average absolute relative deviation), empirical models show good agreement with experimental data. The mathematical modeling of a process is beneficial to predict the process conduct and furthermore extend the procedures from laboratory to industrial scales.

The effect of extrusion parameters, including feed rate (15-25 kg/h), screw speed (250-750 rpm) and feed moisture (15-25%) on the expansion index of spelt wholegrain snack products was investigated. Wholegrain spelt flour was extruded using co-rotating twinscrew extruder (Bühler BTSK 30/28D, 7 sections, length/diameter ratio = 28:1, Bühler, Uzwil, Switzerland). The obtained data demonstrate that increased feed moisture leads to a decrease in the expansion of extrudates. Increasing in screw speed resulted in higher elasticity, which has resulted in the greater expansion index. The following operating conditions: screw speed (750 rpm), feed moisture (20%) and feed rate (20kg/h) provided the highest expansion index (1.93). The screw speed has the greatest positive influence on the expansion index obtained by Yoon's model.

This study analyzed the last 20 years` data available on power plant coal ashes used in clay brick production. The statistical analysis has been carried out for a total of 302 cases based on the relevant parameters reported in the literature. The chemical composition of the clays and coal ashes, percentage incorporation and maximum particle size of ash, size of fired samples, peak firing temperature, and the corresponding soaking time were selected as inputs for modeling. The product characteristics i.e. open porosity, water absorption, and compressive strength was taken as output parameters. An artificial neural network model has been developed and showed a satisfactory fit to experimental data and predicted the observed output variables with the overall coefficient of determination (r2) of 0.972 during the training period. Besides, the reduced chi-square, mean bias error, root mean square error, and mean percentage error were utilized to check the correctness of the obtained model, which proved the network generalization capability. The sensitivity analysis of the model suggested that the quantity of Na2O coming from brick clays, the percentages of SiO2 and K2O coming from ashes, and MgO coming from clays were the most influential parameters in descending order for the ash-clay composite bricks` quality, mostly owing to the influence of fluxes during firing.

The aim of this study was the prediction model of retention indices of compounds from the aboveground parts of Achillea clypeolata Sibth. & Sm. essential oil, obtained by hydrodistillation and analysed by GC–MS. The quantitative structure–retention relationship analysis was applied in order to anticipate the retention time of the obtained compounds. The selection of the seven molecular descriptors was done by a genetic algorithm. The chosen descriptors were uncorrelated and were used to construct an artificial neural network. A total of 40 experimentally obtained retention indices was used to build this prediction model. The coefficient of determination for the training, testing and validation cycles were: 0.950, 0.825 and 1.000, respectively, indicating that this model could be used for prediction of retention indices for A. clypeolata, essential oil compounds.

Rare earth elements (REE) are frequently referred to as ingredients for enhancements in modern industry, as they are extensively applied in many industrial branches due to their accented electro-magnetic and optical properties. REE have end-utilizations as catalysts, magnets, and as dopants for ceramic materials. Rare earth minerals are scarce therefore the unconventional REE-containing resources such as waste materials and industrial byproducts are continuously being investigated. Coal combustion products comprise REE concentrations varying between 200 ppm and 1500 ppm. This quantity can be isolated though the extraction procedure. In this study, the five stages extraction was conducted on the coal combustion ash from the selected landfill site. The extractions of 32 elements (As, Ga, Ce, Be, Ge, Nd, Cr, Zr, Eu, Cu, Nb, Gd, Co, Mo, Dy, Li, Ag, W, Mn, Cd, Au, Ni, In, Hg, Pb, Sn, Tl, V, Sb, Th, Zn, and La) were conveyed. Chemical analyses were conducted via XRF, ICP-OES, ICP-MS, and AAS techniques. The complexity of the obtained data was examined by Principal component analysis and Cluster analysis in order to derive interconnections between quantity of elements and landfill characteristics, as well as mutual relationships among the elements of interest, and to assess the accomplishment of REE recovery from the coal ash.

As one of the main non-covalent relations in microbiological-based systems, cell surface hydrophobicity (CSH) can be observed as a relevant parameter for biodegradation capability and suggested bacterial behaviour and biofilm formation during a bioremediation process. On the other hand, the role of ureolytic bacteria in bioremediation has subsequently led to the examination of this bacterial type in different engineering fields. In order to optimize the operating parameters of microbial adhesion to hydrocarbons test (MATH) for ureolytic bacteria, Box–Behnken experimental design was conducted for five ureolytic bacteria isolated from soils, as well as for the reference strain Sporosarcina pasteurii DSM 33. The optimization was completed with and without the essential substrate for the targeted metabolic reaction, with the aim to compare differences in bacterial hydrophobicity. A vortex time of 2 min, a hydrocarbon volume of 0.5 mL, and a phase separation time of 15 min are recommended as MATH operating parameters for all tested ureolytic bacteria. Although all bacteria are hydrophobic, lower CSH values in the presence of urea were observed for the same bacterium, which could be explained by the interaction of urea with the organic phase of the separation system, as well as a rapid ureolysis process that also occurs during the application of ureolytic bacteria in biotechnology systems.

Ecological conditions of the growing areas, growing practices as well as harvest and postharvest processing influence the yield and quality of chamomile. The aim of this research was to determine the influence of chamomile separation methods, as postharvest treatments, on the essential oil quality and content, with a view to improve current primary processing of this valuable medicinal plant. In order to explain the structure of laboratory data that would give deeper assessment of similarities among various samples of chamomile essential oil, PCA was employed. Tested results showed that separation of chamomile plant material, as postharvest and pre-drying treatment, had significant influence on the number of identified compounds in the chamomile essential oil. The highest content of individual essential oil compounds had chamomile flowers with short stems, especially a-bisabolol, chamazulene, Z-spiroether and E-b-famesene. In the essential oil obtained from chamomile flowers with long stems, content of a-bisabolol and chamazulene were significantly lower, while E-b-famesene and Z-spiroether contents were significantly higher. Furthermore, in the essential oil obtained from chamomile plant material without separation, the lowest content of abisabolol and Z-spiroether, and the highest content of E-b-farnesene were recorded. The correlation analysis was performed to investigate the likeness in the amounts of the active compounds of essential oil from differently processed chamomile samples. All these results indicate the importance of precise and controlled postharvest treatments, since it clearly affects the essential oil quality and content in the primary processing of this valuable medicinal plant.

In the essential oil of yarrow (Achillea millefolium L. sensu lato) collected from natural population on Mt. Rtanj (Serbia) and distilled by Clevenger apparatus 104 compounds were detected, and the most abundant were camphor (9.8%), caryophyllene oxide (6.5%), terpinen-4-ol (6.3%) and 1,8- cineole (5.6%). The quantitative structure-retention relationship (QSRR) model was employed to predict the retention indices, using four molecular descriptors selected by factor analysis and a genetic algorithm. The coefficients of determination reached the value of 0.862, demonstrating that this model could be used for prediction purposes.

This paper examines the effect of starch coating and the osmotic dehydration in sugar beet molasses on the microbiological stability of apples. One-half of the osmotically treated/untreated apples were protected by starch coating, resulting in four sample groups (namely the K, P, OD and OD+P sample groups). E. coli, Salmonella spp. and Listeria monocytogenes were not detected in any of the samples. Enterobacteria were present in the K and P samples in the first four days (indicating a downward trend), but were not subsequently detectable. The total number of microorganisms (TVC) was found to be uniform in each sample group. However, the TVC values were significantly higher in the K and P sample groups than those of the OD and OD + P samples. Yeasts and molds were detected in the K and P samples, whereas the presence of yeasts and molds in the OD and OD+P samples was confirmed only after four days of storage. The results obtained indicate that osmotic dehydration is a suitable method for maintaining microbial stability, whereas starch coating did not justify its purpose.

The paper presents the results of testing the effect of pyrophyllite shale (pyrophyllite) on the quality of maize plant silage, primarily on the production of organic acids, pH value, quality assessment and microbiological safety. The ensiling was done in plastic containers which allowed the storage of 10 kg of chopped green mass. Tested pyrophyllite doses were: 0% in the control treatment (I), 0.5 and 1.0% in experimental treatments (II and III, respectively). Granulated pyrophyllite (100 µm), originating from Parsovići, Konjic site, AD Harbi Ltd., Sarajevo, Bosnia and Herzegovina, was manually incorporated. The chopped green mass of the maize plant came from FAO 600 hybrids. The green mass containing 37.17% of dry matter (final waxy ripening phase) was compressed in the same manner in all three treatments during the filling of the vessels. The containers were then covered with nylon foil (0.2 mm) above which a layer of fine sand (approx. 5 cm) was placed in toward the silage protection from air passage. The silages were opened after 7 weeks and organoleptic, chemical and microbiological analyses were performed. The organoleptic properties of silages (colour and odour) were better in silages containing 0.5 and 1.0% pyrophyllite. The silage temperature at the moment of opening of the containers was lower in the treatments with 0.5 and 1.0% added pyrophyllite (13.7 and 13.2 °C, respectively) while in the control treatment it was 14.6 °C. The addition of pyrophyllite to silage affected the production of volatile fatty acids (p ≤ 0.05). The highest amount of lactic acid was found in the silage sample without the addition of pyrophyllite, and acetic acid in the silage treated with 0.5 and 1.0% of pyrophyllite. The lowest amount of butyric acid was determined in the silage with the addition of 1% pyrophyllite. Based on the content and interrelationship of lactic, acetic and butyric acid, as well as the pH values, all three silages were rated as the highest (I) class. The number of aerobic mesophilic bacteria, as well as the number of yeasts, was lower in the silages with the addition of 0.5 and 1.0% pyrophyllite. In future, particular attention should be paid on the possibility of pyrophyllite enrichment (e.g. with nitrogen) and more appropriate physical formulation (e.g. granules) that would allow more efficient practical application.

The use of natural zeolite – clinoptilolite, to protect wheat grain from storage insects within environmentally-friendly storage techniques can lead to the presence of small amounts of zeolite residues in flour. This study investigated the influence of as-received zeolite clinoptilolite (Z) and sodium-rich clinoptilolite (NaZ) in wheat dough on the dough rheological properties. Zeolites were added to dough at 0.5-1.5 wt.% flour basis level, which is a range expected to remain in the grain (flour) after treatment to control storage pests. The effects were studied in two types of wheat, conventional (Triticum aestivum) and spelt (T. aestivum spp. spelta) because they initially differ in rheological properties. NaZ was used to discern whether the presence of increased concentration of Na+ in the zeolite was able to exert a higher strengthening effect as compared to as-received zeolite (Z). NaZ exerted the highest dough strengthening effect which was mainly reflected as decreased dough softening and increased water absorption. The fact that the presence of NaZ was the most effective factor in improving the dough rheological profile suggested that the presence of movable cations in the zeolite lattice might have a pronounced role in the mechanism by which zeolite affects dough behaviour.

A modification of an analytical procedure for the energy-dispersive X-ray fluorescence (EDXRF) quantification of ten chemical elements (As, Ba, Cd, Co, Cr, Cu, Mo, Ni, Pb and Zn) in the leachates obtained from cement binders was developed. Twenty-nine testing samples were used in the experiment. All samples were based on Portland cement. Fly ash of different origin, zeolite and bentonite were employed as mineral additives in the cement binders. Distilled water was used as the leachate. Validation of the modified EDXRF procedure was conducted in terms of limits of detection and quantification, working range, linearity, selectivity, precision, trueness, and robustness. Traceability of the procedure was established using certified reference materials. Uncertainty of measurement was confirmed via an “in-house” laboratory validation approach. The expanded uncertainties for the ten analysed elements were obtained for the entire working range of the EDXRF method. Robustness of the modified EDXRF procedure was assessed by means of a chemometric in-house approach. The results obtained by the modified X-ray fluorescence method were additionally correlated to those acquired by inductively coupled plasma optical emission spectrometry to confirm that EDXRF could be used as an effective and reliable alternative method for analysis of cement leachates.

In the past decades, the bioremediation process based on denitrification by aerobic heterotrophic bacteria was extensively studied for different engineering approaches. Besides the fact that only non-pathogenic and non-biofilm forming bacteria must be used, it is very important to isolate bacteria or a group of bacteria in nature with the capacity to remove completely nitrate without accumulation of nitrogen oxides or ammonia as intermediates. In this article, the denitrification capacity of 43 bacterial strains isolated from slightly alkaline and calcite soils along the Danube River were investigated by artificial neural network (ANN) modelling. According to the obtained results, an ANN model was developed for the prediction of denitrification capacity of bacterial soil strains based on six signification denitrification indicators: biomass and N2 gas production, nitrate and nitrite concentration as well as nitrite and ammonia formation. The ANN model showed a reasonably good predictive capability of the outputs (overall R2 for prediction was 0.958). In addition, the experimental verification of the ANN in laboratory testing indicated that the ANN could predict the denitrification capacity of soil bacteria during the denitrification process in laboratory conditions.

The objective of this research was to determine chemical composition and to evaluate the antifungal activity of essential oil of Mentha piperita. By the application of GC/MS analysis of essential mint oil, 27 components were identified. The major components were menthol (39.9 %), menton (23.51 %), menthyl acetate (7.29 %), 1.8-cineol (5.96 %), isomenton (5.24 %), isomenthol (3.17 %), trans-caryophyllene (2.88 %), limonene (2.14 %), pulegon (1.38 %), beta-pinene (1.14 %) and piperiton (1.03 %). The quantitative structure– retention relationship (QSRR) was employed to predict the retention time (RT) of Mentha piperita essential oil compounds obtained in GC/MS analysis, using twelve molecular descriptors selected by genetic algorithm. The selected descriptors were used, as inputs of an artificial neural network, to build an RT predictive QSRR model. The coefficient of determination was 0.983, during training cycle, indicating that this model could be used for prediction of RT values for essential oil compounds in Mentha piperita essential oil extracts. Essential oil of Mentha piperita showed antifungal activity on all tested isolates in the minimal inhibitory concentration range of 0.2–1.7 μl/ml and a minimal fungicidal concentration (MFC) range of 1.7–454.5 μl/ml. The most powerful antifungal activity of mint was observed in C. cladosporioides of MFC value 1.7 μl/ml. P. aurantiogriseum showed the lowest sensitivity of MFC value 454.5 μl/ml. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. 31029]

Serbian aromatized wine “Bermet” from grapes grown on Fruška Gora Mountain has been in production since the 15th century. Ten commercial Bermets produced according to the traditional procedure by different manufacturers, and six prepared within the scope of this study were assessed for antioxidant (AO) activity using electrochemical, chemiluminescent and spectrophotometric AO assays. Direct current polarographic assay based on the decrease of anodic current of [hydrogen(peroxido)(1-)]hydroxidomercury(II) complex formation in alkaline H2O2 solution at potential of mercury oxidation, chemiluminescent H2O2 scavenging assay, as well as commonly used spectrophotometric assays (2,2’-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid (ABTS) based Trolox equivalent antioxidant capacity (TEAC), 2,2-diphenyl-1- picrylhydrazyl (DPPH) and ferric reducing antioxidant power (FRAP)) were used. Total phenolic content (TPC) was determined by Folin–Ciocalteu assay. The results obtained were correlated using regression analysis, ANOVA and F-test. An integrated approach to AO capacity determination allowed a more comprehensive comparison between samples. The approach is based on the introduction of the relative antioxidant capacity index, calculated by assigning each AO assay equal weight, and by PCA analysis. In addition, the introduction of phenolic antioxidant coefficients, calculated as the ratio between individual AO capacity and TPC, enabled a better understanding of their relation. [Projects of the Serbian Ministry of Education, Science and Technological Development, Grant no. 43010 and Grant no. 31093]

This work aimed to obtain a validated model for prediction of retention time of terpenoids isolated from sage herbal dust using supercritical fluid extraction. In total 32 experimentally obtained retention time of terpenes, which were separated and detected by GC–MS were further used to build a prediction model. The quantitative structure–retention relationship was employed to predict the retention time of essential oil compounds obtained in GC–MS analysis, using six molecular descriptors selected by a genetic algorithm. The selected descriptors were used as inputs of an artificial neural network, to build a retention time predictive quantitative structure–retention relationship model. The coefficient of determination for training cycle was 0.837, indicating that this model could be used for prediction of retention time values for essential oil compounds in sage herbal dust extracts obtained by supercritical fluid extraction due to low prediction error and moderately high r2. Results suggested that a 2D autocorrelation descriptor AATS0v was the most influential parameter with an approximately relative importance of 25.1 %. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. TR 31013]

New global tendencies for waste materials reusing in building materials are imposing the request for improved performances of chemical analysis methods and the improvements of matrices used. A new method for optical emission spectrometry with inductively coupled plasma (ICP-OES) is developed and validated for the chemical analysis (35 elements: Al, Be, Cd, So, Cr, Cu, Fe, Mn, Mo, Ni, V, Mo, Zn, Pb , Bi, Si, Zr, W, As, Se, Sb, Sn, Ti, Ba, B, Ag, Mg, Ca, K, Na, S, P, Ga, In, Li) in leachate of fly ash. Validation performances and the uncertainty оf measurement were resolved. Uncertainty оf measurements were resolved by three routes: validation procedure, participation in proficiency testing (PT) schemes and standard method. The obtained method is a new simple and effective analyzing route for determination of undesired trace elements and their quantity comprised in leachates of fly ash, and leachates of building materials with addition of fly ash (cement binders and mortars). In order to prove its accuracy and precision, the developed method was employed on laboratory samples of cement binders and mortars. Results were compared with limit values provided in the standard. Multivariate analyses, i.e. cluster analysis and principal component analysis, were applied to establish interrelations between analyzed samples, and to certify the developed ICP-OES method. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. III 45008 and Grant no. OI 172057]

In the past few decades the diet preparation in feed production has evolved towards more complicated technological operations, which include different liquid addition. A wide scale of different liquids is used in contemporary animal feed production, from oils and glycerol to more expensive products in a liquid form, such as enzymes, flavourings, amino acids, vitamins and others. In the presented study the liquid addition in feed production was observed, with a specific goal to investigate the spraying systems in order to better understand the effects of fluids, such as soybean oil and glycerol, on feed production. The dispersion angles of spraying nozzle for glycerol and soybean oil were determined as an indicator of the uniform application of liquids during feed production. Dispersion of the material was accomplished using the two-fluid nozzle. The performance of Artificial Neural Network (ANN) was compared with experimental data in order to develop rapid and accurate method for prediction of dispersion angle. The ANN model showed high prediction accuracy (r2 = 0.945). [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. III46012]

Table eggs can play an important role as functional food, especially if specially designed mixtures enriched with o-3 fatty acids, natural pigments and vitamins are used for their production. Thus, the aim of this study was to investigate the effects of inclusion of flax-corn meal co-extrudate (FCM) in combination with natural pigments in hens' diet on physical properties, yolk colour and fatty acid composition of eggs. One hundred and twenty Lohmann Brown laying hens were fed corn-soybean meal based diet with the addition of FCM at different levels: 0% (control C1 and C2), 13.50% experimental treatment (E1) and 22.50% experimental treatment (E2). The control treatment (C1) contained up to 3% fat, without added pigments while the control treatment (C2) contained up to 5% fat and synthetic pigments. Experimental treatments E1 and E2 (3% and 5% fat, respectively) had the same amount of natural pigments (1% carrot and 0.5% paprika). When compared with control eggs, no significant changes (p>0.05) in the egg quality characteristics were observed for E1 and E2 eggs. Desirable egg yolk colour of 12.78 RYCF (Roche Yolk Colour Fan scale) was achieved in the treatments E1 and E2. Eggs from hens fed FCM had significantly higher level (p

Agricultural production is a Serbian main economic sector, presenting a base for the food industry. By analysing the public available data of the agriculture sector, applying a newly developed business model it is possible to assess the current situation and to realize the relation between variables, which can also be used for prediction of future trends in agricultural production and food industry. Within this paper an attempt was made to develop a novel artificial neural network model for better understanding the relation between the observed parameters and to estimate the efficiency in sustainability achievement and sector potential the well-known Cobb-Douglas production model was compared to the newly developed model. The presented models could be used to achieve the transformation towards a circular bioeconomy, by developing the national strategies for sustainable agricultural production, with the aim of better utilization of resources and reduction of wastes.

Amino acid profile of four honey types - two monofloral (acacia and sunflower), one polyfloral (meadow honey) and forest honey (honeydew honey) collected from the Autonomous Province of Vojvodina (Republic of Serbia) was determined using ion exchange chromatography. The results showed that proline was the dominant amino acid in all analyzed samples. Other amino acids present in substantial amounts were glutamic acid ˃ phenylalanine ˃ glycine ˃ serine in acacia and meadow honey samples, while sunflower was characterized by the presence of higher content of alanine compared to serine. Forest honey samples possessed the highest proline content and also the highest total amino acid content. Based on the amino acid contents, honey samples were classified using chemometric methods (cluster analysis (CA) and principal component analysis (PCA)). CA of different honey types could be applied to group honey types. According to the PCA, honey samples are clearly distinguished and form the specific groups. Therefore, amino acid profile could give an indication of honey botanical origin.

Mineral additives are extensively applied as cement replacement materials in both construction concrete and mortar. Fly ash is one of the most commonly utilized additives which improve rheological properties, as well as thermal and mechanical behavior of mortar, and as such it has been widely investigated. This industrial byproduct comprises heavy metals in its composition; therefore further research is needed to optimize its effective dosage. Moreover, certain sorptive clays, such as natural zeolite and bentonite, can prevent migration of toxic elements from fly ash by immobilizing them in their structure. Ten experimental mortars are prepared with Portland cement, river sand and addition of fly ash, zeolite and/or bentonite in accordance with chemometric experimental design rules. The aim of the study was to investigate the effect of mineral additives on thermal and mechanical performances of mortar. Thermal characteristics were monitored via dilatometric analysis and DTA method. Principal component analysis was used on the results of physico-mechanical testing (workability, bulk density, water absorption, shrinkage, compressive and flexural strength) to enable the divisions of the observed samples into groups in the factor space. The performance of Artificial Neural Network was compared with the experimental data in order to develop rapid and accurate method for prediction of mechanical parameters of mortar. The ANN model showed high overall prediction accuracy (r2 = 0.989, during training cycle). The test results indicate that incorporation of the mineral additives gave cost effective mortars with sufficiently good properties. However, tools of analytical modeling highlighted mortar with zeolite and fly ash as the optimal composition regarding its mechanical performance. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. III 45008 and Grant no. ON 172057]

New 48 wheat varieties, harvested in 2016 are classified in four wheat quality groups (improvers, bread varieties, basic varieties, poor quality varieties), based on minimum level of crude protein content, sedimentation value, flour extraction, yield of bread volume and bread crumb quality.22.9 % of analyzed varieties met all the prescribed parameter values for grading into defined quality groups. The objective of the presented study was to evaluate the quality of the different wheat varieties by integrating physicochemical, rheological and bread characteristics of wheat. Following 13 parameters: test weight, 1000 kernel weight, vitreousness, flour extraction, crude protein content, sedimentation value, wet gluten content, falling number, absorption, farinograph number of quality, extensograph area, yield of bread volume and bread crumb quality were subjected to score analysis. Outcomes may help in better differentiation the quality of wheat varieties. Score analysis has been estimated as a helpful mathematical tool for wheat grading.

The purpose of this paper is the synthesis and characterization of biodegradable composite films based on whole sunflower oil cake, as well as the effect of process parameters (pH and temperature)on the film properties obtained. Films were synthesized at different temperatures (room temperature, 60 °C and 90 °C) and pH values (10 and 12). The film samples obtained were characterized by the mechanical, barrier and physicochemical properties determination. The experimental results showed that the tensile strength values increased with temperature and pH value increments, whereas the sample with the highest elongation at break value was 60 °C/pH12. The water vapour permeability values were uniform (8.62 g/m2h - 11.63 g/m2h), and lower values were recorded in samples synthesized at higher temperatures. The results obtained relative to light transmission were uniform, and the maximum transmission value was reached at 800 nm (24.1- 35.7 %). The values obtained for swelling and solubility parameters are characteristic of the nature of biopolymer films.

For many years, linseed has been attracted a great attention in animal nutrition because of its exceptionally favourable fatty acid composition and high content of essential α-linolenic acid. However, the presence of antinutritive components, cyanogenic glycosides, limits its inclusion in the animal's diet. Several ways of linseed detoxification were observed in literature, emphasizing extrusion as one of the most effective processes. In the presented study, the application of Artificial Neural Network (ANN) has been observed, as a tool for prediction of process influence on the deterioration of cyanogenic glycosides during the extrusion process of linseed-sunflower meal co-extrudate. The content of hydrogen cyanide (HCN) was determined according to the AOAC method as an indicator of cyanogenic glycosides in the produced co-extrudate. Extrusion of the material was performed on a laboratory single screw extruder. The performance of ANN model was compared with experimental data in order to develop rapid and accurate method for prediction of HCN content in co-extrudate. According to the experimental results, the highest HCN content (126 mg/kg) was determined at the lowest moisture content (7%) and the lowest screw speed (240 rpm). With the increase of moisture content and temperature during extrusion, the content of HCN drastically decreased. The ANN model showed high prediction accuracy (r2> 0.999), which indicates that the model could be easily and reliably applied in practice.

Background: Anemia represents a significant cause of maternal and perinatal mortality, as well as child mortality. The aim of the research was to determine the serum concentration of hepcidin in children aged 6 months to 2 years and adolescents aged 11 to 19 years which suffer from iron deficiency anemia and compare it with the serum concentration of hepcidin in the control groups, as well as to determine its connection with the parameters of the iron metabolism. Methods: The research included 173 examinees, 89 of them suffered from iron deficiency anemia and 84 did not suffer from iron deficiency anemia (the latter represented the control group). Blood samples were collected from all study participants. The samples were analyzed for complete blood count and parameters of iron metabolism. ELISA method was used for establishing serum hepcidin levels. Results: The research showed that the concentration of hepcidin is statistically lower in children (4.4 ng/mL) and adolescents (4.1 ng/mL) who suffer from iron deficiency anemia in comparison with the control group (14 ng/mL, 10 ng/mL, respectively). The positive correlation between serum hepcidin level and iron in the serum, ferritin, the mean corpuscular volume and transferrin saturation was confirmed, but the negative one occurred in serum hepcidin level, transferrin and reticulocytes. Conclusions: The age of the examinees does not influence the level of serum hepcidin which makes it a more sensitive indicator of the level of iron in the body. Besides this, serum hepcidin is a reliable biological marker for the assessment of iron deficiency anemia.

In the territory of Kosovo and Metohija there are important preconditions for the development of tourism as a specific economic activity. However, the premise for the development of pertaining plans is the preservation of cultural and historical heritage of Serbian and other ethnic groups in this area. Tourist valorisation is certainly one of the most important issues of tourism theory. The paper highlights the importance of protecting Serbian heritage and the heritage of other ethnic groups living in the territory of Kosovo and Metohija. The paper has significant pragmatic value as it provides the foundation for defining the strategy of the necessary valorization of cultural and historical heritage from cultural and economic perspectives. Valorisation is important in order to clearly define the priorities in preserving the rich cultural heritage for future generations, while acknowledging the unresolved political issue regarding the status of the province. In the process of normalising relations between Belgrade and Priština with the help of international community there is a clear and urgent need to create adequate models for protection of the Serbian heritage. The paper concludes that the process of valorisation in the current conditions of Kosovo is a very expensive and complicated task, which will make it difficult to implement in the near future. The paper calls for a wider discussion, one that will satisfy all interested parties, about tourist valorisation of rich cultural and historical heritage in this territory.

This research describes a study of 11 selected samples of brick clays applied in roofing tile production, by using simultaneous thermal analysis. Additionally, the laboratory-sized samples were prepared and fired (850-950 °C) and technological properties were determined. Mathematical analysis was applied to sum all the experimental results and help discriminate the samples by their behavior during firing. The samples, very similar according to mineralogical and chemical content, as well as granulometry tests, were successfully grouped using principal component analysis (PCA). The PCA was used to explore and easily visualize the differences between samples. The PCA performed for differential thermal analysis (DTA), differential scanning calorimetry (DSC) and differential thermogravimetry (DTG) curves clearly showed that the heat flow was mainly influenced by carbonate content and its grain size, while DTG discriminated samples according to the contents of clay minerals and carbonates. In addition, dilatometry analysis revealed which samples underwent the highest densification during the firing process. The PCA analysis of fired products properties showed that the highest correlations were between water absorption with firing shrinkage and compressive strength. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. III45008, Grant no. TR31055 and Grant no. III45007]

Various cultivars of different cereal and pseudocereal species (9 wheat, 8 barley, 1 rye, 3 oat, 2 triticale, 3 spelt, 12 corn, 3 amaranth and 9 buckwheat cultivar samples) were milled into flour, extracted using n-hexane, derivatized with trimethylsulfonium hydroxide solution, and subjected to GC– –MS analysis. Fatty acid methyl esters and non-saponifiable compounds (phytosterols, α-tocopherol and squalene) were identified by comparing mass spectra with the Wiley MS library. A binary system was applied in further data processing: the presence or the absence of a particular lipid component in each sample was coded with either (1) or (0). Major lipid components that were present in all analyzed flour samples were removed from further data analysis, leaving only those that represent a good pattern to differentiate the flour samples according to corresponding cereal/pseudocereal species. Pattern recognition tools (cluster analysis and principal component analysis) were applied to visualize groupings and separations among the samples. The presented approach enables the rapid differentiation of flour samples made from various cereal/pseudocereal species according to their botanical origin and gluten content, thereby, successfully avoiding exact quantitative determinations. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. TR31066]

Water stability of eight samples of extruded salmon feeds was first determined by applying two gravimetric methods developed by the authors: gravimetric static and wet sieving method. Then, the conductometric method, primarily developed for investigation of nutrient leaching of feed into the water by the authors, was used for each sample. The aim of this study was to evaluate the potential of the conductometric measurement as a technique for determining water stability of extruded fish feed. In order to find any correlation between the results of two gravimetric tests and conductometric method, correlation analysis was employed. The results of static and wet sieving method were expressed as water stability index, which was expressed as the percent of remained dry matter of sample after being disintegrated in the water. The results of conductometric method were shown as conductivity curves for each sample, giving the insight in rate of nutrient leaching during the time. The obtained values of water conductivity showed no significant (p < 0.05) correlation with the results of static water method, while there was a negative significant (p < 0.05) correlation with the results of wet sieving method during first four hours of pellets soaking in water. The highest correlation coefficients were obtained within the first hour of conductivity measurement, demonstrating that proposed conductometric method had a potential to be applied as a rapid and simple method for determination and relative comparison of salmon feed water stability.[ Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. III46012 and Grant no. TR31011]

The aim of this study was to compare the sensitivity of two analytical methods for the prediction of the shelf-life of unpacked and packed gluten-free rice–buckwheat cookies kept at ambient (23±1°C) and elevated (40±1°C) temperature during storage, namely the static headspace gas chromatographic method with flame ionisation detection (SHS-GC-FID) for volatile saturated aldehydes (propanal (C3), pentanal (C5), hexanal (C6), heptanal (C7) and octanal (C8)) and the HPLC method for malondialdehyde (MDA) determination. Both methods resulted in obtaining the same end-points of cookie shelf-life, i.e., 3 and 5 months for unpacked and packed cookies kept at elevated temperature, respectively, and 11 and 14 months for unpacked and packed cookies kept at ambient temperature, respectively. Two computational approaches, i.e., the second order polynomial (SOP) and artificial neural network (ANN) models, were used accordingly. The calculations of the contents of aldehydes and MDA could be predicted with an overall coefficient of determination of 0.722 using the ANN model compared to 0.312–0.773 for SOP models. According to sensitivity analysis, it might be suggested that the relevant parameter for the prediction of the end-point of cookie shelf-life is the MDA rather than the C3, C5, C6, C7 and C8 content. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. TR-31029]

This paper investigates the effects of simultaneous addition of sunflower (3, 6 or 9 g/100 g of sample) and dry residue of wild oregano (0.5 or 1 g/100 g of sample) on the essential amino acids pattern and antioxidant potential of flake products. The accepted experimental design plan was 34. Data point that Score and PDCAAS values in flake products increase with increasing share of sunflower. Maximum value of phenolic compounds and antioxidant activity were experienced of TPC 2.84 mg/g, DPPH 0.75 mg/ml, FRAP 1.57 mg/g with the product having maximum shares of sunflower and dry residue of wild oregano. Tukey’s HSD test showed statistically significant differences between most of the mean values of amino acids content and antioxidant activity in the observed corn flakes. The response surface method has been applied for evaluation of amino acid content and antioxidative potential of corn flakes. Sunflower in flake products positively contributed to the protein nutritive value and dry residues of wild oregano elevated antioxidant potential of flake products and also contributed to the food waste valorisation in the food industry. Corn flakes are new products with improved essential amino acid pattern, antioxidant activity and functional properties due to added dry residue of wild oregano and sunflower. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. III 46005 and Grant no. TR 31027]

Osmotic treatment of celery root was studied in two osmotic solutions (sugar beet molasses and a ternary solution of water, sucrose and salt), at three temperatures (20, 35 and 50°C), and three different immersion periods (1, 3 and 5 h), at atmospheric pressure. The aim was to examine the influence of the type of the used hypertonic agent, the temperature and the immersion time on the water loss, solid gain, water activity, dry matter content, antioxidant activity (expressed by DPPH) and colour attributes (described by CIELAB coordinates L*, a* and b*). During the experiments, the antioxidant activity of celery root was increased in sugar beet molasses, while the DPPH value tended to decrease in the ternary solution. The experimental data of osmotic dehydration was used for PCA modelling. The standard scores analysis revealed that the optimum process parameters were gained with an immersion time of 5 h and a temperature of 35°C. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. TR-31055]

The limestone, as an economically sustainable and easily available basic raw material, is frequently utilized in the building industry for resolving of the environmental protection issues. The limestone is incorporated in a cementitious system either by grinding with cement clinker, or by blending with the binder during concrete production. The employing of powdery limestone as partial cement replacement gives the construction composites with properties comparable to that of conventional concrete. The study of limestone thermal behavior and its chemistry is crucial for the prognosis of the designed composites properties. In this work, the instrumental techniques (atomic emission spectroscopy, differential thermal and thermo-gravimetric analysis, Fourier transform infrared spectroscopy) and the Principal component analysis were employed to discriminate and classify 22 limestone types. The PCA statistical method, as a means of spectra and experimental data fingerprinting, grouped the samples in a multi-dimensional factor space producing four graphical prognosis - one for each instrumental method. DTA/TG peak values varied the most in a short range between 830-870°C, while FTIR spectra showed the highest diversity in the 867-887 cm-1 and 1237-1647 cm-1 ranges. This research was governed by an idea to reveal whether it is possible to differentiate various limestone types and to predict the possibility of their employment in construction composites on the basis of the results of instrumental and mathematical analyses. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. ON 172057, III 45008, TR 31055, TR 34006, and TR 34013]

The coal fly ash mechano-chemical activation conducted via high energy ultra-centrifugal mill was optimized using mathematical and statistical tools. The aim of the investigation was to accent the merits of alternations in ash processing schemes with a referral regarding the enhancement of the ash reactivity that will lead to its higher volume utilization as a cement replacement in concrete design. The impact of the processing parameters sets (number of rotor revolutions, current intensity, activation period, circumferential rotor speed, mill capacity) on the on the product’s quality factors (grain size distribution, average grain size, micronization level, agglomeration tendency, specific surface area) was assessed via Response surface method, Standard score analysis and Principal component analysis in order to obtain the most favorable output. Developed models were able to meticulously predict quality parameters in an extensive range of processing parameters. The calculated r2 values were in the range of 0.846-0.999. The optimal ash sample, that reached the Standard Score as high as 0.93, was produced using a set of processing parameters appropriate to experimental sequence with applied 120 μm sieve mesh. The microstructural characteristics were assessed using image-processing values and histogram plots of the activated fly ash SEM images. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. ON 172057, Grant no. III 45008, Grant no. TR 31055 and Grant no. TR 34006]

This study investigated properties of starch-based edible films with oregano and black cumin essential oil addition. Essential oils addition positively affected film swelling (decreased due to essential oil addition), mechanical properties (tensile strength decreased while elongation at break increased), and water vapor barrier properties (decreased along with essential oils addition). Control film did not have any biological activity, which proves the need for essential oils addition in order to obtain active packaging. Oregano oil was more effective in terms of biological activity. Endothermal peak, above 200°C, represents total thermal degradation of edible films. Diffraction pattern of control film showed significant destruction of A-type crystal structure. Addition of essential oils resulted in peak shape change: diffraction peaks became narrower. Principal Component Analysis has been used to assess the effect of essential oils addition on final starch-based edible films characteristics with the aim to reveal directions for the film characteristics improvement, since the next phase will be optimal film application for food packaging.

Fifteen horizontal single-pitch screw conveyors with modified geometry and the different lengths were investigated for premixing action, during the transport of materials. All investigations were performed experimentally and numerically, by using Discrete Element Method (DEM). The influences of screw length, observed geometry variations and different types of screw design, on the performances of the screw conveyor-mixer during material transport were explored. The auxiliary mixing action was achieved during the transport of the material. The geometry of the screw conveyor is changed by adding three complementary helices oriented in the same or the opposite direction from screw blades. The particles of the material being transported tumble down from the top of the helix to the next free surface, and that segment of helix was used for additional mixing action. According to DEM analysis, particle path length is increased, and the improved geometry could be determined for increasing the quality of mixing.

Static mixer is used for premixing action before the main mixing process, for significant reduction of mixing time and energy consumption. In this article, the novel numerical approach called Discrete Element Method is used for modeling of granular flow in multiple static mixer applications, while the Computational Fluid Dynamic method was chosen for fluid flow modeling. The main aim of this article is to predict the behaviour of granules being gravitationally transported in different mixer configuration and to choose the best configuration of the mixer taking into account the total particle path, the number of mixing elements and the quality of the obtained mixture. The results of the numerical simulations in the static mixers were compared to experimental results, the mixing quality is examined by relative standard deviation criterion. The effects of the mixer type and the number of mixing elements on mixing process were studied using analysis of variance (ANOVA).