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This research investigates the impact of various fertilization methods on the bioactive compound content and antioxidant activity of celery ( Apium graveolens L.) root and leaf. Mineral fertilizer, poultry manure, cattle manure, sheep manure, supercompost, and molasses were applied. Total dry weight, phenolic and flavonoid compounds, and antioxidant activity were assessed, along with fiber, protein, fat, sugar, and starch in celery root. Principal component analysis (PCA) and cluster analysis were used to correlate production conditions with the parameters. The highest fiber and protein contents were found in mineral-fertilized roots, while total fat and sugar were highest in cattle-manure-fertilized roots, and starch was highest in supercompost-fertilized roots. Fertilization with supercompost yielded the highest total phenolic and flavonoid contents in leaves, while mineral fertilizer resulted in the highest antioxidant activity in roots. Notably, the highest dry weight in leaves and the highest total phenolic and flavonoid contents in roots were also observed with supercompost. PCA and cluster analysis demonstrated significant correlations between plant parts, i.e., the celery root and leaf samples, cultivation conditions, and the observed parameters, emphasizing the importance of selecting suitable cultivation methods to optimize celery's nutritional properties. Also, these findings suggest that supercompost, a byproduct of breweries, could potentially replace animal-based organic fertilizers, addressing the problem of reduced availability due to declining livestock numbers.

Drying is one of the most commonly used methods for food preservation, and in spice processing, it has a significant impact on quality. In this paper, the influences of drying at room temperature, 60 °C, and 90 °C and freeze-drying on celery and parsley roots and turmeric rhizomes were examined. The highest content of total phenolics was found in celery dried at 60 °C (C60), parsley at room temperature (PRT), and freeze-dried turmeric (TFD) (1.44, 1.58, and 44.92 mg GAE/g dm , respectively). Celery dried at room temperature (CRT), PRT, and TFD showed the highest antioxidant activity regarding the DPPH and ABTS radicals and FRAP. The analysis of color parameters revealed that celery dried at 90 °C (C90); PFD and TFD showed the most similar values to control samples. The drying process was optimized using a combination of standard score (SS) and artificial neural network (ANN) methods. The ANN model effectively evaluated the significance of drying parameters, demonstrating high predictive accuracy for total phenolics, total flavonoids, total flavonols, total flavan-3-ols, IC 50 ABTS , and FRAP. TFD showed the strongest α-glucosidase inhibitory potential. Also, TFD extract showed good antibacterial activity against Staphylococcus aureus but not against Escherichia coli . C90 and PFD extracts did not show antibacterial activity against the tested microorganisms.

Novel probiotic yoghurt was produced using the combination of bacterial cultures Lactobacillus plantarum HA119 and Bifidobacterium animalis subsp. lactis B94 and yoghurt bacteria Lactobacillus delbrueckii subsp. bulgaricus and Streptococcus thermophilus . Its basic nutritional composition, colour, texture, rheological properties, and sensory profile were compared with yoghurt produced using the same technological process and standard yoghurt cultures (control sample), as well as other commercially available yoghurts with different milk fat contents. Despite the fat content of the yoghurt made with the new probiotic cultures being 1.44%, its apparent viscosity was similar to that of high-fat yoghurt (2.99%). Other results from rheological measurements indicate that the new yoghurt had a stronger protein network, presumably due to the higher number of exopolysaccharides compared to both control and commercial yoghurts. Sensory analysis revealed that there were no statistically significant differences between the novel probiotic yoghurt and high-fat yoghurt as perceived by panellists. In conclusion, this combination of probiotic cultures can be used to produce yoghurt with rheological and sensory properties similar to high-fat yoghurts, without the need for hydrocolloids or changes in the production process.

In the production of refined sunflower oil, waxes are removed during the winterization stage, and wax crystals are separated through filtration assisted by filtration aids. Commonly used filtration aids in oil refining include perlite and diatomaceous earth. After winterization, a significant amount of filter cake remains as a by-product and is treated as waste. Today, natural cellulose fibers are being promoted as filtration aids. Their advantages are numerous, both in the production process and from an environmental perspective. However, their only disadvantage is their higher cost. Therefore, in this study, 57 filtration cycles during the industrial sunflower oil winterization step using cellulose-based filtration aids were monitored. Different process parameters, including the pressure differential on the filter, the flow rate of filtered oil, constant pressure period, the quantity of filtered oil, filtration time, the quantity of pre-coating and dosing filtration aids, the volume of filtered oil, the concentration of dosing filtration aid, as well as the mass of separated waxes, were observed. Additionally, artificial neural networks were applied to predict process parameters, optimize the process, and, above all, determine the dosage of filtration aids, which will make the process more economical. The optimal filtration process is performed at a pressure differential of 3.3 bar, lasting a total of 39 h, with 32 h at constant pressure, resulting in 322,503 kg of filtered oil and 90.41 kg of waxes. The optimal quantity of cellulose-based filtration aids employed for pre-coat was 80 kg, and for dosing, 375 kg, with an optimal concentration of 0.12% w/w .

Around 20-30% of the horned melon's weight is peel. This peel is often discarded or underutilized despite containing valuable bioactive compounds. Conventional methods for extracting polyphenols and carotenoids from horned melon peel are typically inefficient, environmentally harmful, or require significant time and energy. The potential of green cloud point extraction (CPE) or green surfactant-based extraction for recovering bioactives with different polarities from this kind of by-product has not been thoroughly investigated. Therefore, this study focused on optimizing CPE process parameters using a one-variable-at-a-time (OVAT) approach. Optimal CPE demonstrated superior yields compared to conventional, ultrasound, microwave, ultrasound-assisted CPE, and microwave-assisted CPE methods. Further, a Plackett-Burman design identified key factors influencing optimal CPE conditions, while artificial neural network (ANN) analysis assessed each input variable's impact on outcomes. Maximum extraction efficiency for total phenolics (352.49 mg GAE/100 g), total carotenoids (16.59 mg β-carotene/100 g), and antioxidant activity (989.02 μmol TE/100 g) was achieved under conditions of: surfactant type = Tween 80, surfactant concentration = 2%; solid:liquid ratio = 1:100; pH = 6612; equilibration temperature = 35 °C; equilibration time = 60 min; salt type = NaCl; salt concentration = 16.4%; centrifugation speed = 7906× g ; centrifugation time = 13.358 min; and No. of CPE steps = Step 1. This comprehensive approach aimed to enhance the understanding and optimization of CPE for maximizing the recovery of bioactives from the horned melon peel, addressing the inefficiencies of traditional extraction methods.

Using natural plant extracts as food additives is a promising approach for improving food products' quality, nutritional value, and safety, offering advantages for both consumers and the environment. Therefore, the main goal of this study was to develop a sustainable method for extracting polyphenols and carotenoids from horned melon peel using the cloud point extraction (CPE) technique, intending to utilize it as a natural food additive. CPE is novel promising extraction method for separation and pre-concentration of different compounds while being simple, inexpensive, and low-toxic. Three parameters within the CPE approach, i.e., pH, equilibrium temperature, and equilibrium time, were investigated as independent variables through the implementation of Box-Behnken design and statistical analyses. The optimized conditions for the maximum recovery of both polyphenols and carotenoids, reaching 236.14 mg GAE/100 g and 13.80 mg β carotene/100 g, respectively, were a pH value of 7.32, an equilibrium temperature of 55 °C, and an equilibrium time of 43.03 min. The obtained bioactives' recovery values under the optimized conditions corresponded to the predicted ones, indicating the suitability of the employed RSM model. These results highlight the effectiveness of CPE in extracting bioactive compounds with varying polarities from agricultural by-products, underscoring its potential for enhancing the value of food waste and advancing sustainable practices in food processing. According to microbiological food safety parameters, the optimal CPE extract is suitable for food applications, while its storage under refrigerated and dark conditions is particularly beneficial. The CPE extract's enhanced stability under these conditions makes it a more viable option for long-term storage, preserving both safety and quality.

Helichrysum italicum (Roth) G. Don is a typical Mediterranean plant, with limited distribution on the islands of Sardinia, Corsica, and the Iberian Peninsula, as well as the islands of the Adriatic Sea and the Balkan Peninsula. In these regions, H. italicum is mainly collected from spontaneous nature, while in recent years, there has been a pronounced cultivation trend due to increased demand and market requirements for constant quality of raw materials. Bearing in mind that biological activity is linked with chemical composition, this review aimed to collect data from different scientific databases (Scopus, PubMed, Web of Science, and Google Scholar) on the antimicrobial activity of essential oil and its chemical composition. A total of 20 papers investigating the antibacterial, antibiofilm, and antifungal activities of H. italicum essential oil were found. Furthermore, in these samples, several compounds occurred as dominant: neryl acetate, α-pinene, and γ-curcumene. These compounds are known for their antimicrobial properties, which likely contribute to the essential oil's efficacy against various microbial strains.

This study analyzed the phenolic compounds, organic acids, sugars, and antioxidant activity in different conventional apple cultivars ( Malus domestica ) from the Serbian market. Polyphenol profiles, sugars, and organic acid contents were analyzed by HPLC, and antioxidant activity was examined by DPPH and FRAP. Notable findings included variations in phenolic compound presence, with certain compounds detected only in specific cultivars. 'Red Jonaprince' exhibited the highest arbutin (0.86 mg/kg FW) and quercetin-3-rhamnoside content (22.90 mg/kg FW), while 'Idared' stood out for its gallic acid content (0.22 mg/kg FW) and 'Granny Smith' for its catechin levels (21.19 mg/kg FW). Additionally, malic acid dominated among organic acids, with 'Granny Smith' showing the highest content (6958.48 mg/kg FW). Fructose was the predominant sugar across all cultivars. Chemometric analysis revealed distinct groupings based on phenolic and organic acid profiles, with 'Granny Smith' and 'Golden Delicious' exhibiting unique characteristics. Artificial neural network modeling effectively predicted antioxidant activity based on the input parameters. Global sensitivity analysis highlighted the significant influence of certain phenolic compounds and organic acids on antioxidant activity.

Helichrysum italicum (immortelle) essential oil is one of the most popular essential oils worldwide and it has many beneficial properties, including antimicrobial. However, in this plant, the chemical diversity of the essential oil is very pronounced. The aim of this work was to process the GC-MS results of four samples of H. italicum essential oil of Serbian origin by chemometric tools, and evaluate the antimicrobial activity in vitro and in silico. Overall, 47 compounds were identified, the most abundant were γ -curcumene, α -pinene, and ar -curcumene, followed by α -ylangene, neryl acetate, trans -caryophyllene, italicene, α -selinene, limonene, and italidiones. Although the four samples of H. italicum essential oil used in this study were obtained from different producers in Serbia, they belong to the type of essential oil rich in sesquiterpenes ( γ -curcumene and ar -curcumene chemotype). In vitro antimicrobial potential showed that five were sensitive among ten strains of tested microorganisms: Staphylococcus aureus , Listeria monocytogenes , Bacillus cereus , Saccharomyces cerevisiae, and Candida albicans . Therefore, these microorganism models were used further for in silico molecular docking through the mechanism of ATP-ase inhibitory activity. Results showed that among all compounds from H. italicum essential oil, neryl acetate has the highest predicted binding energy. Artificial neural network modeling (ANN) showed that two major compounds γ -curcumene and α -pinene, as well as minor compounds such as trans - β -ocimene, terpinolene, terpinene-4-ol, isoitalicene, italicene, cis - α -bergamotene, trans - α -bergamotene, italidiones, trans - β -farnesene, γ -selinene, β -selinene, α -selinene, and guaiol are responsible for the antimicrobial activity of H. italicum essential oil. The results of this study indicate that H. italicum essential oil samples rich in γ -curcumene, α -pinene, and ar -curcumene cultivated in Serbia (Balkan) have antimicrobial potential both in vitro and in silico. In addition, according to ANN modeling, the proportion of neryl acetate and other compounds detected in these samples has the potential to exhibit antimicrobial activity.

This study investigates the applicability of the Peleg model to the osmotic dehydration of various sweet potato variety samples in sugar beet molasses, addressing a notable gap in the existing literature. The osmotic dehydration was performed using an 80% sugar beet molasses solution at temperatures of 20 °C, 35 °C, and 50 °C for periods of 1, 3, and 5 h. The sample-to-solution ratio was 1:5. The objectives encompassed evaluating the Peleg equation's suitability for modeling mass transfer during osmotic dehydration and determining equilibrium water and solid contents at various temperatures. With its modified equation, the Peleg model accurately described water loss and solid gain dynamics during osmotic treatment, as evidenced by a high coefficient of determination value (r 2 ) ranging from 0.990 to 1.000. Analysis of Peleg constants revealed temperature and concentration dependencies, aligning with previous observations. The Guggenheim, Anderson, and de Boer (GAB) model was employed to characterize sorption isotherms, yielding coefficients comparable to prior studies. Effective moisture diffusivity and activation energy calculations further elucidated the drying kinetics, with effective moisture diffusivity values ranging from 1.85 × 10 -8 to 4.83 × 10 -8 m 2 /s and activation energy between 7.096 and 16.652 kJ/mol. These findings contribute to understanding the complex kinetics of osmotic dehydration and provide insights into the modeling and optimization of dehydration processes for sweet potato samples, with implications for food processing and preservation methodologies.

This study summarized the physicochemical analysis of 609 honey samples originating from the Republic of Serbia. Variations among honey samples from different botanical origins, regions of collections, and harvest years were exposed to descriptive statistics and correlation analysis that differentiated honey samples. Furthermore, most of the observed physicochemical parameters (glucose, fructose, sucrose content, 5-hydroxymethylfurfural (5-HMF) levels, acidity, and electrical conductivity) varied significantly among different types of honey, years, and regions. At the same time, no noticeable difference was found in diastase activity, moisture content, and insoluble matter. Based on the obtained results, 22 honey samples could be considered adulterated, due to the irregular content of sucrose, 5-HMF, acidity, and diastase activity. In addition, 64 honey samples were suspected to be adulterated. Adulterated and non-compliant samples present a relatively low percentage (14.1%) of the total number of investigated samples. Consequently, a considerable number of honey samples met the required standards for honey quality. Overall, these findings provide insights into compositional and quality differences among various types of honey, aiding in understanding their characteristics and potential applications.

This study focuses on predicting and optimizing the quality parameters of cookies enriched with dehydrated peach through the application of Support Vector Machine (SVM) and Artificial Neural Network (ANN) models. The purpose of the study is to employ advanced machine learning techniques to understand the intricate relationships between input parameters, such as the presence of dehydrated peach and treatment methods (lyophilization and lyophilization with osmotic pretreatment), and output variables representing various quality aspects of cookies. For each of the 32 outputs, including the parameters of the basic chemical compositions of the cookie samples, selected mineral contents, moisture contents, baking characteristics, color properties, sensorial attributes, and antioxidant properties, separate models were constructed using SVMs and ANNs. Results showcase the efficiency of ANN models in predicting a diverse set of quality parameters with r 2 up to 1.000, with SVM models exhibiting slightly higher coefficients of determination for specific variables with r 2 reaching 0.981. The sensitivity analysis underscores the pivotal role of dehydrated peach and the positive influence of osmotic pretreatment on specific compositional attributes. Utilizing established Artificial Neural Network models, multi-objective optimization was conducted, revealing optimal formulation and factor values in cookie quality optimization. The optimal quantity of lyophilized peach with osmotic pretreatment for the cookie formulation was identified as 15%.

In this study, an Artificial Neural Network (ANN) model is used to solve the complex task of producing fresh cheese with the desired quality parameters. The study focuses on kombucha fresh cheese samples fortified with ground wild thyme, supercritical fluid extract of wild thyme, ground sage and supercritical fluid extract of sage and optimizes the parameters of chemical composition, antioxidant potential and microbiological profile. The ANN models demonstrate robust generalization capabilities and accurately predict the observed results based on the input parameters. The optimal neural network model (MLP 6-10-16) with 10 neurons provides high r2 values (0.993 for training, 0.992 for testing, and 0.992 for validation cycles). The ANN model identified the optimal sample, a supercritical fluid extract of sage, on the 20th day of storage, showcasing specific favorable process parameters. These parameters encompass dry matter, fat, ash, proteins, water activity, pH, antioxidant potential (TP, DPPH, ABTS, FRAP), and microbiological profile. These findings offer valuable insights into producing fresh cheese efficiently with the desired quality attributes. Moreover, they highlight the effectiveness of the ANN model in optimizing diverse parameters for enhanced product development in the dairy industry.

This study delved into the impact of two extrusion processing parameters-screw speed ( SS at 400, 600, 800 RPM) and material moisture content in the extruder barrel ( M at 12, 15, 18%) at constant feed rate (50 kg/h)-on reducing the content of alternariol (AOH), alternariol monomethyl ether (AME), tenuazonic acid (TeA), and tentoxin (TEN) in whole-grain red sorghum flour. Ultra-performance liquid chromatography combined with a triple-quadrupole mass spectrometer (UPLC-MS/MS) was employed for the determination of Alternaria toxin levels. The extruder die temperature fluctuated between 136 and 177 °C, with die pressures ranging from 0.16 to 6.23 MPa. The specific mechanical energy spanned from 83.5 to 152.3 kWh/t, the torque varied between 88 and 162.8 Nm, and the average material retention time in the barrel ranged from 5.6 to 13 s. The optimal parameters for reducing the concentration of all Alternaria toxins with a satisfactory quality of the sorghum snacks were: SS = 400 RPM, M = 12%, with a reduction of 61.4, 76.4, 12.1, and 50.8% for AOH, AME, TeA, and TEN, respectively., Competing Interests: The authors declare no conflicts of interest.

The global impact of the COVID-19 pandemic has significantly influenced individuals' dietary choices and food-buying behavior. Present research specifically delves into the alterations in fruit and vegetable (F&V) consumption among consumers in Serbia during the pandemic. The study employs an extended model of the theory of planned behavior (TPB), incorporating the construct of consumers' knowledge to comprehensively explore behavioral changes. Conducted in the first half of 2020, the study engaged 479 participants from Serbia, using an online questionnaire for data collection. Structural equation modelling was employed for a thorough analysis of the gathered responses. The main outcome revealed a noteworthy connection between consumers' knowledge and their attitudes, subjective norms, and intentions regarding F&V consumption. Subjective norms significantly influenced consumers' desire to increase F&V intake during and after the outbreak. These intentions aligned with actual behavior changes, indicating a shift toward higher F&V consumption. Consumer knowledge also notably shaped attitudes and behaviors regarding F&V intake. Notably, the TPB proved valuable in predicting and understanding these dietary shifts during global crises like the pandemic. These insights not only bolster healthier eating habits but also have broader implications for public health. Understanding consumer behavior dynamics during crises like COVID-19 is crucial for crafting effective strategies to promote overall human health and well-being., Competing Interests: The authors declare no conflict of interest.

This study explores the unexploited potential of Artificial Neural Network (ANN) optimization techniques in enhancing different drying methods and their influence on the characteristics of various sweet potato varieties. Focusing on the intricate interplay between drying methods and the unique characteristics of white, pink, orange, and purple sweet potatoes, the presented experimental study indicates the impact of ANN-driven optimization on food-related characteristics such as color, phenols content, biological activities (antioxidant, antimicrobial, anti-hyperglycemic, and anti-inflammatory), chemical, and mineral contents. The results unveil significant variations in drying method efficacy across different sweet potato types, underscoring the need for tailored optimization strategies. Specifically, purple sweet potatoes emerge as robust carriers of phenolic compounds, showcasing superior antioxidant activities. Furthermore, this study reveals the optimized parameters of dried sweet potato, such as total phenols content of 1677.76 mg/100 g and anti-inflammatory activity of 8.93%, anti-hyperglycemic activity of 24.42%. The upgraded antioxidant capability is presented through DPPH ● , ABTS ●+ , RP, and SoA assays with values of 1500.56, 10,083.37, 3130.81, and 22,753.97 μg TE/100 g, respectively. Additionally, the moisture content in the lyophilized sample reached a minimum of 2.97%, holding favorable chemical and mineral contents. The utilization of ANN optimization proves instrumental in interpreting complex interactions and unlocking efficiencies in sweet potato drying processes, thereby contributing valuable insights to food science and technology.

The following article describes new research about the design, construction and installation of the new prototype of a vacuum dryer with an ejector system. Moreover, the testing of this new prototype involved comparing the qualities of fruit dried in a vacuum drier with an ejector system to fruit dried in a convectional vacuum drier. The data obtained were then analyzed and presented. Due to their economic relevance and highly valuable nutritional value and sensory properties, sour cherries and apricots have been chosen to be the subjects for the testing. The most appropriate quality indicators for analyzing were moisture content, a w value, share and penetration force, total phenol, flavonoid and anthocyanin content and antioxidant activity (FRAP, DPPH and ABTS test). The main results of this study were achieved by designing, constructing, installing and testing the usage of the innovative prototype of a vacuum dryer with an ejector system in the laboratory of the Technology of fruit and vegetable products of the Faculty of Technology Novi Sad, University of Novi Sad. Based on our analyses of the obtained data, it was concluded that vacuum dryer with an ejector system are similar to vacuum dryer with a vacuum pump in terms of all tested physical, chemical and biological properties of dried samples. We observed similarities in some of the most important parameters, including product safety and quality, such as the a w value and the total phenol content, respectively. For example, in dried sour cherry, the a w values ranged from 0.250 to 0.521 with the vacuum pump and from 0.232 to 0.417 with the ejector system; the total phenol content ranged from 2322 to 2765 mg GAE/100 g DW with the vacuum pump and from 2327 to 2617 mg GAE/100 g DW with the ejector system. In dried apricot, the a w ranged from 0.176 to 0.405 with the vacuum pump and from 0.166 to 0.313 with the ejector system; total phenol content ranged from 392 to 439 mg GAE/100 g DW with the vacuum pump and from 378 to 428 mg GAE/100 g DW with the ejector system.

The kinetic properties and thermal characteristics of fresh pork meat proteins ( Longissimus dorsi ), as well as osmotically dehydrated meat proteins, were investigated using differential scanning calorimetry. Two isoconversional kinetical methods, namely the differential Friedman and integral Ortega methods, were employed to analyze the data. The obtained kinetic triplet, activation energy, pre-exponential factor, and extent of conversion, has been discussed. The resulting activation energy for proteins of fresh meat ranges between 751 kJ·mol -1 for myosin, 152 kJ·mol -1 for collagen and sarcoplasmic proteins, and 331 kJ·mol -1 for actin at a conversion degree of 0.1 to 0.9. For osmotically dried pork meat proteins, the values range from 307 kJ·mol -1 for myosin 272 kJ·mol -1 for collagen and sarcoplasmic proteins, and 334.83 kJ·mol -1 for actin at a conversion degree from 0.1 to 0.9. The proteins of the dry meat obtained by osmotic dehydration in molasses could be described as partly unfolded as they retain the characteristic protein denaturation transition. Concerning the decrease in enthalpies of proteins denaturation, thermodynamic destabilization of dried meat proteins occurred. On the contrary, dried meat proteins were thermally stabilized with respect to increase in the temperatures of denaturation. Knowledge of the nature of meat protein denaturation of each kind of meat product is one of the necessary tools for developing the technology of meat product processing and to achieve desired quality and nutritional value. The kinetic analysis of meat protein denaturation is appropriate because protein denaturation gives rise to changes in meat texture during processing and directly affects the quality of product.

The aim of this study is to compare the efficacy of selected food disinfectants on planktonic populations of Staphylococcus aureus and Escherichia coli and on the same microorganisms (MOs) incorporated in a biofilm. Two disinfectants were used for treatment: peracetic acid-based disinfectant (P) and benzalkonium chloride-based disinfectant (D). Testing of their efficacy on the selected MO populations was performed using a quantitative suspension test. The standard colony counting procedure was used to determine their efficacy on bacterial suspensions in tryptone soy agar (TSA). The germicidal effect (GE) of the disinfectants was determined based on the decimal reduction ratio. For both MOs, 100% GE was achieved at the lowest concentration (0.1%) and after the shortest exposure time (5 min). Biofilm production was confirmed with a crystal violet test on microtitre plates. Both E. coli and S. aureus showed strong biofilm production at 25 °C with E. coli showing significantly higher adherence capacity. Both disinfectants show a significantly weaker GE on 48 h biofilms compared to the GE observed after application of the same concentrations on planktonic cells of the same MOs. Complete destruction of the viable cells of the biofilms was observed after 5 min of exposure to the highest concentration tested (2%) for both disinfectants and MOs tested. The anti-quorum sensing activity (anti-QS) of disinfectants P and D was determined via a qualitative disc diffusion method applied to the biosensor bacterial strain Chromobacterium violaceum CV026. The results obtained indicate that the disinfectants studied have no anti-QS effect. The inhibition zones around the disc therefore only represent their antimicrobial effect.

Waxes, phospholipids, free fatty acids, peroxides, aldehydes, soap, trace metals and moisture present in crude sunflower oil have a negative effect on the oil quality and are, therefore, removed during the refining process. Waxes crystallizing at low temperatures are removed during winterization by cooling and filtration. Waxes have poor filtration characteristics and an industrial filtration process must be enhanced by the use of filtration aids, which improve filter cake structure and properties, and consequently prolong the filtration cycle. Today, traditional filtration aids (diatomite, perlite, etc.) being used in the industry are frequently replaced by cellulose-based aids. The aim of this study is to examine the effect of oil filtration assisted by two cellulose-based filtration aids on the chemical parameters (wax, moisture, phospholipids, soaps, and fatty acids), oil transparency, carotenoids, and Fe and Cu content of sunflower oil obtained in an industrial horizontal pressure leaf filter. In order to investigate the mentioned parameters, the following techniques were used: gravimetric (waxes and moisture content), spectrophotometric (phospholipids and carotenoid content and oil transparency), volumetric (soaps and free fatty acids content) as well as inductively coupled plasma mass spectrometry (ICP-MS) for Fe and Cu content. An artificial neural network model (ANN) was employed for the prediction of removal efficiency based on the chemical quality, oil transparency, Fe and Cu content in oils before filtration, as well as filtration aid quantity and filtration time. Cellulose-based filtration aids had multiple beneficial effects; on average, 99.20% of waxes, 74.88% of phospholipids, 100% of soap, 7.99% of carotenoids, 16.39% of Fe and 18.33% of Cu were removed.

The problem of microbial biofilms has come to the fore alongside food, pharmaceutical, and healthcare industrialization. The development of new antibiofilm products has become urgent, but it includes bioprospecting and is time and money-consuming. Contemporary efforts are directed at the pursuit of effective compounds of natural origin, also known as "green" agents. Mushrooms appear to be a possible new source of antibiofilm compounds, as has been demonstrated recently. The existing modeling methods are directed toward predicting bacterial biofilm formation, not in the presence of antibiofilm materials. Moreover, the modeling is almost exclusively targeted at biofilms in healthcare, while modeling related to the food industry remains under-researched. The present study applied an Artificial Neural Network (ANN) model to analyze the anti-adhesion and anti-biofilm-forming effects of 40 extracts from 20 mushroom species against two very important food-borne bacterial species for food and food-related industries- Listeria monocytogenes and Salmonella enteritidis . The models developed in this study exhibited high prediction quality, as indicated by high r 2 values during the training cycle. The best fit between the modeled and measured values was observed for the inhibition of adhesion. This study provides a valuable contribution to the field, supporting industrial settings during the initial stage of biofilm formation, when these communities are the most vulnerable, and promoting innovative and improved safety management.

The main objective of this study is to determine the possibility of predicting the impact of land use and soil type on concentrations of heavy metals (HMs) and phthalates (PAEs) in soil based on an artificial neural network model (ANN). Qualitative analysis of HMs was performed with inductively coupled plasma-optical emission spectrometry (ICP/OES) and Direct Mercury Analyzer. Determination of PAEs was performed with gas chromatography (GC) coupled with a single quadrupole mass spectrometry (MS). An ANN, based on the Broyden-Fletcher-Goldfarb-Shanno (BFGS) iterative algorithm, for the prediction of HM and PAE concentrations, based on land use and soil type parameters, showed good prediction capabilities (the coefficient of determination ( r 2 ) values during the training cycle for HM concentration variables were 0.895, 0.927, 0.885, 0.813, 0.883, 0.917, 0.931, and 0.883, respectively, and for PAEs, the concentration variables were 0.950, 0.974, 0.958, 0.974, and 0.943, respectively). The results of this study indicate that HM and PAE concentrations, based on land use and soil type, can be predicted using ANN.

Stinging nettle ( Urtica dioica L.) is one fantastic plant widely used in folk medicine, pharmacy, cosmetics, and food. This plant's popularity may be explained by its chemical composition, containing a wide range of compounds significant for human health and diet. This study aimed to investigate extracts of exhausted stinging nettle leaves after supercritical fluid extraction obtained using ultrasound and microwave techniques. Extracts were analyzed to obtain insight into the chemical composition and biological activity. These extracts were shown to be more potent than those of previously untreated leaves. The principal component analysis was applied as a pattern recognition tool to visualize the antioxidant capacity and cytotoxic activity of extract obtained from exhausted stinging nettle leaves. An artificial neural network model is presented for the prediction of the antioxidant activity of samples according to polyphenolic profile data, showing a suitable anticipation property (the r 2 value during the training cycle for output variables was 0.999).

The main challenge in controlling the microbiological contamination of historical paper is finding an adequate method that includes the use of cost-effective, harmless, and non-toxic biocides whose effectiveness is maintained over time and without adverse effects on cultural heritage and human health. Therefore, this study demonstrated the possibility of using a non-invasive method of historical paper conservation based on plant essential oils (EOs) application. Evaluation of antimicrobial effects of different EOs (lemongrass, oregano, rosemary, peppermint, and eucalyptus) was conducted against Cladosporium cladosporoides , Aspergillus fumigatus , and Penicillium chrysogenum , which are commonly found on archive papers. Using a mixture of oregano, lemongrass and peppermint in ratio 1:1:1, the lower minimal inhibition concentration (0.78%) and better efficiency during a vapour test at the highest tested distance (5.5 cm) compared with individual EOs was proven. At the final step, this EOs mixture was used in the in situ conservation of historical paper samples obtained from the Archives of Vojvodina. According to the SEM imaging, the applied EOs mixture demonstrates complete efficiency in the inhibition of fungi colonization of archive papers, since fungal growth was not observed on samples, unlike the control samples.

This study aimed to investigate the impact of chicory root addition (20-40%) and extrusion conditions (moisture content from 16.3 to 22.5%, and screw speed from 500 to 900 rpm) on bioactive compounds content (inulin, sesquiterpene lactones, and polyphenols) of gluten-free rice snacks. Chicory root is considered a potential carrier of food bioactives, while extrusion may produce a wide range of functional snack products. The mineral profiles were determined in all of the obtained extrudates in terms of Na, K, Ca, Mg, Fe, Mn, Zn, and Cu contents, while antioxidative activity was established through reducing capacity, DPPH (2,2-diphenyl-1-picrylhydrazyl) and ABTS (2,2-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) tests. Chicory root addition contributed to the improvement of bioactive compounds and mineral contents, as well as antioxidative activities in all of the investigated extrudates in comparison to the pure-rice control sample. An increase in moisture content raised sesquiterpene lactones and minerals, while high screw speeds positively affected polyphenols content. The achieved results showed the important impact of the extrusion conditions on the investigated parameters and promoted chicory root as an attractive food ingredient in gluten-free snack products with high bioactive value.

Predicting yield is essential for producers, stakeholders and international interchange demand. The majority of the divergence in yield and essential oil content is associated with environmental aspects, including weather conditions, soil variety and cultivation techniques. Therefore, aniseed production was examined in this study. The categorical input variables for artificial neural network modelling were growing year (two successive growing years), growing locality (three different locations in Vojvodina Province, Serbia) and fertilization type (six different treatments). The output variables were morphological and quality parameters, with agricultural importance such as plant height, umbel diameter, number of umbels, number of seeds per umbel, 1000-seed weight, seed yield per plant, plant weight, harvest index, yield per ha, essential oil (EO) yield, germination energy, total germination, EO content, as well as the share of EOs compounds, including limonene, cis -dihydro carvone, methyl chavicol, carvone, cis -anethole, trans -anethole, β-elemene, α-himachalene, trans -β-farnesene, γ-himachalene, trans -muurola-4(14),5-diene, α-zingiberene, β-himachalene, β-bisabolene, trans -pseudoisoeugenyl 2-methylbutyrate and epoxy-pseudoisoeugenyl 2-methylbutyrate. The ANN model predicted agricultural parameters accurately, showing r 2 values between 0.555 and 0.918, while r 2 values for the forecasting of essential oil content were between 0.379 and 0.908. According to global sensitivity analysis, the fertilization type was a more influential variable to agricultural parameters, while the location site was more influential to essential oils content., Competing Interests: The authors declare no conflict of interest.

Winter savory ( Satureja montana L.) is a well-known spice and medicinal plant with a wide range of activities and applications. Two subspecies of S. montana , subsp. montana and subsp. variegata , were used for the preparation of seven different extracts: steam distillation (essential oil (EO) and hydrolate (HY)), subcritical water (SWE), ultrasound-assisted (UAE-MeOH and UAE-H 2 O), and microwave-assisted (MAE-MeOH and MAE-H 2 O) extraction. The obtained EOs, HYs, and extracts were used for an in vitro evaluation of the antioxidant activity (DPPH, ABTS, reducing power, and superoxide anion methods) and in vitro antimicrobial activity against Bacillus cereus , Staphylococcus aureus , Enterococcus faecalis , Escherichia coli , Salmonella Typhimurium, Saccharomyces cerevisiae , and Candida albicans . The antimicrobial screening was conducted using disk-diffusion assessment, minimal inhibitory concentration, time-kill kinetics modeling, and pharmacodynamic study of the biocide effect. The total phenolic content (TPC) was highest in EO, followed by SWE, MAE, and UAE, and the lowest was in HY. The highest antimicrobial activity shows EO and SWE for both varieties, while different UAE and MAE extracts have not exhibited antimicrobial activity. The natural antimicrobials in the S. montana extract samples obtained by green extraction methods, indicated the possibility of ecologically and economically better solutions for future in vivo application of the selected plant subspecies.

A novel rice-based snack enriched with chicory root flour (CRF) was developed by twin-screw extrusion. Chicory ( Cichorium intybus L.) is one of the promising medicinal plants for the development of innovative food and may be considered a functional food ingredient. Central composite design (CCD) was employed to generate snack formulations by varying feed moisture (M, 16.3-22.5%), screw speed (SS, 500-900 rpm) and CRF content (20-40%). The optimization according to artificial neural network modeling and a genetic algorithm was applied to define optimal process conditions (17.6% moisture, 820 rpm and 24.1% of CRF) for obtaining the product with the highest expansion (3.34), crispiness (3.22 × 10 -3 ), volume (2040 m 3 ), degree of gelatinization (69.70%) and good color properties. Bulk density (110.33 g/L), density (250 kg/m 3 ), and hardness (98.74 N) resulted in low values for the optimal sample. The descriptive sensory analysis evaluated low hardness and bitterness, with high crispiness for the optimal extrudate. This study points to the possibility of a novel chicory enriched extrudate production with desirable physicochemical and sensory properties.

The osmotic dehydration (OD) of celery root in sugar beet molasses was studied at three temperatures (20, 35, and 50 °C) and three immersion periods (1, 3, and 5 h) in order to examine the changes in antioxidant potential and phenolic profile of celery root throughout the process. The antioxidant capacity (AOC) of dehydrated samples was evaluated by spectrophotometric and polarographic assays, the total phenolic content by the Folin-Ciocalteu method, and the individual phenolic compounds by HPLC-DAD. As a result of OD in molasses, the AOC and phenols content in samples increased proportionally to the augmentation of temperature and the immersion time. Vanillic acid, syringic acid, and catechin were detected in dehydrated samples as a result of transfer from molasses. Compared to fresh celery root, the content of identified phenols in osmodehydrated samples was improved from 1.5 to 6.2 times. Strong correlations between applied assays were obtained, except for the DPPH. Based on the correlation analysis chlorogenic acid, gallic acid, chrysin, catechin, and kaempferol showed the greatest contribution to the overall AOC of osmodehydrated celery root. Molasses, an agro-industrial waste from sugar production, could be valorized as a valuable osmotic solution.

The present study investigated the effect of incorporating 10, 20, and 30% apple powder obtained by freeze-drying, and apple powder produced with osmotic pre-treatment in sugar beet molasses solution, into muffins. The powder was freeze-dried and introduced as a whole spelt wheat flour replacement in muffins. The obtained products were investigated for their chemical composition and technological properties, and were subjected to a sensory analysis as well as a consumer acceptance test. Increasing the substitution level from 0 to 30% apple powder lowered the protein, starch, and fat content, while moisture content, sugar, and cellulose showed the opposite trend. The sensory analysis results indicated that the addition of apple powder or apple powder with osmotic pre-treatment (apple OT+Lyo powder) to the ingredients of muffins positively affected the taste, smell, mastication, and appearance of the final product. Consumers rated the muffins with 30% apple OT+Lyo powder as the most acceptable. Principal component analysis, an artificial neural network, and global sensitivity analysis were utilized to differentiate among muffin samples, and to estimate the corresponding influence of the substitution of spelt flour with apple powder or apple OT powder on the observed quality and nutritional parameters of the muffins.

Artificial neural intelligence was established for the estimation, prediction, and optimization of many agricultural and food processes to enable enhanced and balanced utilization of fresh and processed fruits. The predictive capabilities of artificial neural networks (ANNs) are evaluated to estimate the phytochemical composition and the antioxidant and antimicrobial activity of horned melon (Cucumis metuliferus) pulp, peel, and seed. Using multiobjective optimization, the main goals were successively achieved through analysis of antimicrobial potential against sensitive microorganisms for peel (Bacillus cereus, Pseudomonas aeruginosa, Aspergillus brasiliensis, and Penicillium aurantiogriseum), pulp (Salmonella enterica subsp. enterica serotype Typhimurium), and seed samples (Saccharomyces cerevisiae and Candida albicans), and its connection with phytochemical and nutritional composition and antioxidant activity. The highly potent extracts were obtained from peels which represent a waste part with strong antioxidant and antifungal capacity. Briefly, the calculated inhibition zone minimums for sensitive microorganisms were 25.3−30.7 mm, while the optimal results achieved with carotenoids, phenolics, vitamin C, proteins, lipids, DPPH, ABTS, and RP were: 332.01 mg β-car/100 g, 1923.52 mg GAE/100 g, 928.15 mg/100 g, 5.73 g/100 g, 2.3 g/100 g, 226.56 μmol TE/100 g, 8042.55 μmol TE/100 g, and 7526.36 μmol TE/100 g, respectively. These results imply the possibility of using horned melon peel extract as an antioxidant and antifungal agent for food safety and quality.

Red beetroot is well known for its high proportion of betalains, with great potential as functional food ingredients due to their health-promoting properties. The objective of this study was to investigate the influence of processing techniques such as Soxhlet, cold, ultrasound and supercritical fluid extraction on the betalains content and its antioxidant, anti-inflammatory and antihyperglycemic activities. Whilst Soxhlet extraction with water has provided the highest yield, the highest content of total phenolics was found in an extract prepared using Soxhlet extraction with 50% ethanol. Amongst eight phenolic compounds detected in the extracts, protocatechuic acid was the most abundant. The concentrations of total phenolics ranged from 12.09 mg/g (ultrasound extraction with 30% methanol) to 18.60 mg/g (Soxhlet extraction with 50% ethanol). The highest anti-inflammatory activity was observed for cold extraction with 50% methanol extract. The high radical scavenging activity of supercritical fluid extracts could be a consequence of nonphenolic compounds. The chemometrics approach was further used to analyse the results to find the "greenest" method for further possible application in the processing of beetroot in the food and/or pharmaceutical industry. According to the standard score, the best extraction method was determined to be Soxhlet extraction with 50% ethanol.

Consumer knowledge about pasta quality differs around the world. Modern consumers are more sophisticated compared to past times, due to the availability of information on pasta types and quality. Therefore, this study investigated the nutritional, physical, textural, and morphological quality of durum wheat pasta enriched with carrot waste encapsulates (10 and 20% freeze-dried encapsulate (FDE) and 10 and 20% spray-dried encapsulate (SDE)), as well as determining consumer preferences for this type of product. Replacement of semolina with FDE and SDE contributed to changes in the pasta nutritional quality, which was reflected in the increased protein, fat, and ash content. Additionally, changes in cooking quality, color, and texture were within satisfactory limits. The uncooked pasta enriched with 10 and 20% SDE was characterized by a lighter yellow intensity with color saturation, as well as an imperceptible waxy appearance compared to the control and enriched pasta with 10 and 20% FDE. After cooking, the yellow color was more intense in all the enriched pasta samples which can be linked to the raw cereal which was significantly greater in the control in comparison to the FDE and SDE containing samples. Overall, carrot waste can be a promising material for the food industry to produce high-quality pasta.

Steam distillation was used for the isolation of Dracocephalum moldavica L. (Moldavian dragonhead) essential oil (DMEO). This aromatic herbaceous plant is widespread across the Northern Hemisphere regions and has been utilized in health-improving studies and applications. In addition to the DMEO, the hydrolate (DMH), a byproduct of the distillation process, was also collected. The DMEO and DMH were analyzed and compared in terms of their chemical composition, as well as their in vitro biological activities. The main component in DMEO was geranyl acetate, while geranial was dominant in DMH. The DMEO demonstrated better antioxidant and antimicrobial activities compared with the DMH against Staphylococcus aureus , Escherichia coli , Salmonella Typhimurium, and Listeria monocytogenes , which represent sources of food-borne illness at the global level. The DMEO and DMH show promise as antioxidant and antimicrobial additives to various products.

The influence of different extrusion parameters, including screw speed (250-750 rpm), feed rate (15-25 kg/h) and feed moisture content (15-25%), on the textural and color properties of spelt wholegrain snack products produced on a co-rotating twin-screw extruder with added betaine was investigated. In order to determine the relative influence of input variables in the artificial neural network (ANN) model, Yoon's interpretation method was used, and it was concluded that feed moisture content has the greatest influence on L* values, while screw speed has the greatest influence on a* and b* values. The softest samples were obtained at the lowest moisture content. Sensory analysis was carried out on selected samples, and it showed that betaine addition did not intensify the bitter taste. The sample with the largest expansion exhibited the lowest hardness and chewiness before and after immersion in milk, and this sample is the most suitable for enrichment with betaine.

Microbiologically induced CaCO 3 precipitation (MICP) is a well-known bio-based solution with application in environmental, geotechnical, and civil engineering. The significance of the MICP has increased explorations of process efficiency and specificity via natural bacterial isolates. In this study, comprehensive profiling of five soil ureolytic Bacillus strains was performed through a newly formed procedure that involved six steps from selection and identification, through kinetic study, to the characterization of the obtained precipitates, for the first time. To shorten the whole selection procedure of 43 bioagents with the MICP potential, Standard Score Analysis was performed and five selected bacteria were identified as Bacillus muralis , B. lentus , B. simplex , B. firmus , and B. licheniformis by the MALDI-TOF mass spectrometry. Despite following the targeted activity, kinetic studies were included important aspects of ureolysis and the MICP such as cell concentration, pH profiling, and reduction in calcium ion concentration. At the final step, characterization of the obtained precipitates was performed using FTIR, XRD, Raman, DTA/TGA, and SEM analysis. Although all tested strains showed significant potential in terms of precipitation of calcite or calcite and vaterite phase, the main differences in the MICP behavior can be observed at the bacterial strain level. B. licheniformis showed favorable behavior compared to the reference Sporosarcina pasteurii DSM 33.

This study was primarily focused on the supercritical fluid extraction (SFE) of cherry seed oil and the optimization of the process using sequential extraction kinetics modeling and artificial neural networks (ANN). The SFE study was organized according to Box-Behnken design of experiment, with additional runs. Pressure, temperature and flow rate were chosen as independent variables. Five well known empirical kinetic models and three mass-transfer kinetics models based on the Sovová's solution of SFE equations were successfully applied for kinetics modeling. The developed mass-transfer models exhibited better fit of experimental data, according to the calculated statistical tests ( R 2 , SSE and AARD). The initial slope of the SFE curve was evaluated as an output variable in the ANN optimization. The obtained results suggested that it is advisable to lead SFE process at an increased pressure and CO 2 flow rate with lower temperature and particle size values to reach a maximal initial slope., Competing Interests: The authors declare no conflict of interest.

Marrubium vulgare is a cosmopolitan medicinal plant from the Lamiaceae family, which produces structurally highly diverse groups of secondary metabolites. A total of 160 compounds were determined in the volatiles from Serbia during two investigated years (2019 and 2020). The main components were E -caryophyllene, followed by germacrene D, α -humulene and α -copaene. All these compounds are from sesquiterpene hydrocarbons class which was dominant in both investigated years. This variation in volatiles composition could be a consequence of weather conditions, as in the case of other aromatic plants. According to the unrooted cluster tree with 37 samples of Marrubium sp. volatiles from literature and average values from this study, it could be said that there are several chemotypes: E -caryophyllene, β -bisabolene, α-pinene, β-farnesene, E -caryophyllene + caryophyllene oxide chemotype, and diverse (unclassified) chemotypes. However, occurring polymorphism could be consequence of adaptation to grow in different environment, especially ecological conditions such as humidity, temperature and altitude, as well as hybridization strongly affected the chemotypes. In addition, this paper aimed to obtain validated models for prediction of retention indices (RIs) of compounds isolated from M. vulgare volatiles. A total of 160 experimentally obtained RIs of volatile compounds was used to build the prediction models. The coefficients of determination were 0.956 and 0.964, demonstrating that these models could be used for predicting RIs, due to low prediction error and high r 2 .

The aim of this study was to investigate the fate of the most common Alternaria toxins found in wheat-tenuazonic acid (TeA), alternariol (AOH), and alternariol monomethyl ether (AME) during sourdough processing. For this purpose, spiked whole wheat flour, 3% sourdough starter, 0.5% of baker's yeast, and 105% of water calculated on flour weight as a base were used as raw materials. Spiked whole wheat dough was fermented for 4 h, 8 h, 12 h, 24 h, and 48 h at 25 °C, and at each point the fermented dough samples were taken, frozen, lyophilized, grounded, and stored until further analysis. To study the effect of sourdough processing on TeA, AOH and AME content, the validated method of high-performance liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) for these mycotoxins was used. Mathematical models of Alternaria toxins reduction were developed in the form of Four Parameter Logistic Regression function. The maximum reduction of TeA, AOH, and AME levels was archived at 48 h of dough fermentation at 25 °C compared with dough after kneading (0 h). Under these conditions, a reduction of the toxin levels of 60.3 %, 41.5%, and 24.1% was observed for TeA, AOH, and AME, respectively.