Search Results (300)

Xylitol is a five-carbon sugar alcohol of industrial interest due to its applications as a food sweetener and sugar substitute. In this study, artificial neural networks combined with a genetic algorithm were evaluated as a data-driven approach for modeling and exploring xylitol production by Spathaspora boniae and Spathaspora brasiliensis during fermentation of sugarcane bagasse hemicellulosic hydrolysate. The dataset comprised 20 experimental points obtained from a face-centered central composite design, using urea, yeast extract, peptone, and ammonium sulfate as input variables. The neural network models showed high goodness-of-fit, with R² values of 0.9952 for S. boniae and 0.9930 for S. brasiliensis. Experimental validation of the optimized conditions resulted in xylitol production of 11.54 ± 0.52 g L⁻¹ for S. boniae and 9.29 ± 0.24 g L⁻¹ for S. brasiliensis. Comparison with response surface methodology showed that both approaches provided strong predictive performance, although the statistical model predicted the optimum conditions more accurately. For S. boniae, however, the ANN-GA approach identified an alternative condition associated with lower nitrogen supplementation and higher experimental xylitol production. Given the limited dataset, this study should be regarded as a proof-of-concept for the application of data-driven optimization tools to xylitol fermentation. The results indicate that ANN-GA can complement classical statistical methods by helping to identify alternative operating conditions in bioprocess optimization. Full article

Electrostatic protein–polysaccharide hydrogels are attractive materials formed without thermal denaturation or chemical crosslinkers and at low biopolymer contents. Their broader application in foods, however, has been limited by slow gelation, with network development often requiring many hours (~18 h). In this study, millimeter-scale hydrogel beads were fabricated from amaranth proteins and xanthan gum by extrusion into glucono-δ-lactone (GDL) solutions (1–5 mg/mL) using hardening times of 10 or 30 min. Beads were successfully formed under all conditions (3.07–3.95 mm diameter), and their physicochemical properties, intermolecular interactions, microstructure, and gel strength were evaluated. Electrostatic attraction remained the dominant force driving gelation. Furthermore, 10 min hardening favored interpolymeric electrostatic interactions, whereas longer exposure reduced them and promoted hydrogen bonding and hydrophobic interactions. These molecular rearrangements were accompanied by a decreased size, lower water retention capacity (WRC), and higher mechanical strength. The mildest treatment (1 mg/mL GDL, 10 min) was post-loaded with a coffee pulp phenolic extract and showed reduced gel strength and electrostatic interactions, suggesting competition for binding sites within the macromolecular network. The extrusion of amaranth protein–xanthan gum mixtures into a GDL bath markedly shortens electrostatic gelation time, supporting this approach as a potential alternative to ionic gelation for the production of millimeter-scale hydrogel beads for food applications. Full article

Amid the ongoing transformation of global climate governance, climate policy uncertainty has emerged as an increasingly important factor influencing both energy and agricultural commodity markets, with direct implications for energy and food security. Using monthly data from 2008 to 2025, this study applies the TVP-VAR-DY and TVP-VAR-BK frameworks, together with complex network analysis, to investigate spillover dynamics among climate policy uncertainty, energy, and agricultural markets from both time-varying and frequency-based perspectives. The results show that spillover effects evolve substantially over time and become more pronounced during periods of major external shocks, particularly under the influence of short-run factors. Notably, the transmission effect of climate policy uncertainty is stronger for bioenergy-related agricultural commodities, especially soybeans and corn. While the agricultural market exhibits strong internal connectedness, cross-market risk transmission is heterogeneous across commodities, with corn remaining a relatively stable net transmitter of risk. By contrast, crude oil generally acts as a net receiver, whereas climate policy uncertainty behaves as a net receiver in the short run but gradually shifts into a net transmitter over the medium and long term, suggesting a lagged transmission pattern. Robustness checks based on alternative lag lengths, forecast horizons, and CPU proxies confirm that the main connectedness structure is stable and not driven by specific parameter choices. These findings provide useful evidence for policymakers seeking to improve the stability and transparency of climate policy and mitigate cross-market risk, while also offering practical guidance for investors in portfolio allocation and hedging against policy-induced volatility. Full article

Rising population pressures and growing resource consumption underscore the urgent need for sustainable strategies in resource management and waste valorization. Agriculture and the agri-food industry generate substantial biomass residues that, when effectively reused, can be transformed into high-value materials aligned with circular economy and bioeconomy principles. This study presents a Systematic Literature Review (SLR) on the valorization of agro-industrial by-products, focusing on their potential to drive sustainable material innovation strategies. Using the Scopus database, 1063 publications (2015–2025) were analyzed through bibliometric, network and content analysis methods combined with a quantitative meta-analytical approach. The bibliometric analysis outlines research trends and identifies leading journals and disciplines, while network mapping reveals five thematic clusters and a transition toward integrated frameworks linking sustainability and industrial applications. The content analysis is performed through a quantitative meta-analytical approach that highlights that studies integrating multiple waste origins tend to achieve higher scientific visibility. Overall, results highlight a 27.5% annual growth in publication output and five dominant thematic areas: waste recovery, chemical recovery, systemic valorization, energy recovery and alternative fuels. Studies involving multiple waste sources display higher citation averages, highlighting the relevance of integrated valorization strategies. This review provides a solid foundation for future research on agro-industrial by-product management by contributing to the definition of sustainable supply-chain strategies. Full article

Hypertension is a severe global public health issue. Food-derived angiotensin-converting enzyme (ACE)-inhibitory peptides have shown great potential as safe and effective alternatives to synthetic antihypertensive drugs. Camel milk is rich in bioactive peptides. This study aimed to screen for ACE-inhibitory peptides from hydrolyzed camel casein, explore their inhibitory mechanisms and endothelial protective effects in vitro, and reveal their potential antihypertensive pathways using network pharmacology. This study screened three peptides with angiotensin-converting enzyme (ACE) inhibitory activity from enzymatically hydrolyzed camel casein components: MVPFLQPK, VPFLQPKVM, and QKWKFL, with IC₅₀ values of 277.1, 396.9, and 486.9 μmol/L, respectively. Enzyme inhibition kinetics analysis indicated that MVPFLQPK exhibited a non-competitive inhibition pattern, VPFLQPKVM exhibited a mixed inhibition pattern, and QKWKFL exhibited a competitive inhibition pattern. Molecular docking revealed that all three peptides formed hydrogen bond interactions with ACE, and QKWKFL and VPFLQPKVM directly bound to the enzyme’s active site to inhibit substrate catalysis. Molecular dynamics simulation further confirmed the high stability of the three peptide–ACE complexes, with binding free energies from −34.24 to −51.19 kcal/mol. The primary contributing forces include hydrogen bonds, van der Waals interactions, electrostatic forces, and nonpolar solvation effects. Network pharmacology analysis suggested that these peptides may exert synergistic antihypertensive effects by regulating multiple blood pressure-related pathways, including the renin–angiotensin system, renin secretion, and calcium signaling pathways, by acting on key targets such as ACE, REN, SRC, and MMP9. Cell experiments demonstrated that all three peptides exhibited no cytotoxicity in the Ang II-induced HUVEC injury model, significantly promoted NO release, inhibited ET-1 secretion, and possessed endothelial protective potential. This study investigated the in vitro ACE-inhibitory mechanism of peptides derived from camel milk and their potential role in blood pressure regulation, providing experimental evidence for subsequent in vivo activity validation and the development of functional camel milk protein products. Full article

As global demand grows for natural health-promoting food ingredients, the agri-food industry’s organic wastes are emerging as promising alternatives thanks to attributes such as biocompatibility, nutritional value and nutraceutical effect. During saffron (Crocus sativus L.) production, approximately 53 kg of petals are obtained as a by-product for every 1 kg of saffron spice. The use of saffron petals and petal extracts in bakery products improves products’ shelf life due to the petals’ high content of nutraceuticals and minerals acting as natural preservatives. Petal-enriched bakery products contain high levels of fiber, minerals and antioxidants. Addition of saffron petals into bread dough reduces gluten network strength, increases crumb hardness, enhances acidity, improves water retention, alters color profiles and increases the duration of the shelf life. The formulation for incorporating saffron petals or petal extracts into food products must address three primary criteria: the maximum concentration of bioactive compounds per 100 g of the finished matrix, the thermal stability of these compounds during the baking process, and their bioavailability (in the food matrix) within the human gastrointestinal tract. Nutraceuticals with pharmacological potential are also influenced by the compositional profile: the proximate composition, minerals, phenolic content, flavonols, and antioxidant capacity of saffron petals and bakery products containing saffron petals. Saffron petals exhibit diverse therapeutic potentials, acting as antidepressants, anxiolytics, anticonvulsants, and neuroprotective agents. They also offer metabolic, cardiovascular, hepatoprotective, and renoprotective benefits, along with anti-inflammatory, antimicrobial, and antitumor activities. This article proposes a roadmap for developing bakery products enriched with saffron petals or petal extracts, targeting both pharmacological applications and consumer goods focused on disease prevention and general wellness. This study investigates the biochemical composition of saffron petals and their integration into bakery products. It evaluates the influence of petal-derived additives on rheological properties, shelf stability, and organoleptic characteristics, alongside an assessment of their bioactivity and toxicological profiles. Furthermore, the analytical methodologies employed for ingredient and biological sample characterization are discussed, emphasizing their role in verifying the authenticity, safety, and nutritional functionality of both raw materials and finished formulations. Full article

Plants in agricultural systems rarely face single stressors; instead, they encounter concurrent biotic (pathogen, pests) and abiotic (drought, salinity, heavy metals) stresses that causes severely reduce crop yields and endanger food security. The traditional methods of breeding, genetic engineering, and agrochemicals tend to target individual stresses and still do not suffice in the complex field conditions. Compared to these approaches, nanotechnology offers distinct advantages: nanoparticles (NPs) can be applied as foliar sprays or seed treatments without lengthy breeding cycles or regulatory hurdles associated with genetically modified organisms. However, nanotechnology is not inherently “better” but rather complementary to crop engineering; each approach has specific strengths. Breeding and genetic engineering provide heritable, long-term solutions, while nanotechnology offers immediate, season-specific, and reversible interventions. Cross-tolerance, the phenomenon whereby exposure to one stress enhances tolerance to another, offers a promising alternative. This review critically examines how NPs act as stress-priming agents that induce cross-tolerance by activating overlapping defense networks, including antioxidant systems (SOD, CAT, APX), phytohormonal crosstalk (ABA, SA, JA), osmolyte homeostasis, and stress-responsive gene expression. We synthesize current evidence on NP uptake, translocation, and cellular interactions, and evaluate their dual role in directly suppressing pathogens while simultaneously enhancing plant immune responses and physiological resilience. However, efficacy is highly dose-dependent: low, subtoxic doses prime defense through hermetic ROS signaling, whereas supraoptimal doses cause phytotoxicity. The current challenges in nano-mediated stress alleviation include: (i) a persistent laboratory-to-field translation gap, with field outcomes averaging only 60–70% of greenhouse efficacy; (ii) dose-dependent phytotoxicity; (iii) poor reproducibility across studies; (iv) scalability and formulation stability issues; and (v) insufficient understanding of long-term environmental fate, including soil accumulation, non-target organism effects, and food chain safety. Future research should consider field-validated formulations (e.g., SiNPs, ZnONPs, Fe₃O₄NPs) across major staple crops); integrating nanotechnology with precision agriculture through nanosensors, remote sensing, and artificial intelligence for site-specific, dose-optimized applications;developing smart, biodegradable nanoparticles with stimuli-responsive release; and establishing harmonized regulatory frameworks for nano-agrochemical approval. When deployed responsibly, nanoparticle-induced cross-tolerance represents a sustainable approach to improve crop resistance against multifactorial stress, with significant implications for climate-resilient agriculture and global food security. Full article

Efficient soil fertility monitoring is essential for sustainable agriculture, food security, and environmental management across Africa, yet conventional laboratory methods remain prohibitively costly and slow for continental-scale applications. Soil spectroscopy is considered as a rapid, non-destructive alternative with transformative potential. This review provides a systematic synthesis of spectroscopic applications across Africa, encompassing laboratory, field, airborne, and satellite-based platforms, while examining major data sources including the Africa Soil Information Service (AfSIS) and GEO-CRADLE spectral libraries. We critically evaluate the evolution of modeling approaches, revealing that Partial Least Squares Regression (PLSR) dominates, but a shift toward advanced frameworks like hybrid physically based models, ensemble learning and deep neural networks is essential. Critically, we identify a pronounced imbalance wherein laboratory spectroscopy prevails while imaging and satellite-based approaches remain comparatively underutilized, despite their unparalleled potential for scaling point measurements to continental extents. The review consolidates findings on key soil properties, demonstrating consistent successes for primary constituents with direct spectral responses (i.e., organic carbon), while revealing relative uncertainty for properties inferred indirectly via covariance (e.g., available phosphorus, potassium). Despite significant local and regional progress, the absence of a standardized pan-African spectral library and the intractable transferability problem remain formidable barriers. Future research must pivot decisively toward imaging spectroscopy and satellite platforms, mitigating PLSR dominance through systematic adoption of ensemble methods, transfer learning, and model harmonization frameworks to fully operationalize these technologies in support of Africa’s sustainable development goals. Full article

Salmonella Enteritidis is a major threat to poultry health and food safety, underscoring the need for safe alternatives to conventional antibiotics. In this study, quercetin, a natural flavonoid with antibacterial and immunomodulatory properties, was evaluated using an integrated approach combining network pharmacology, molecular docking, in vitro antibacterial assays, and preliminary in vivo validation. Potential targets of quercetin and Salmonella Enteritidis were identified from the TCMSP and GeneCards databases, followed by protein–protein interaction analysis, topological screening, and GO/KEGG enrichment analyses. Five core targets, namely IL1B, IL6, STAT1, PTGS2, and IFNG, were identified and were mainly enriched in immune- and inflammation-related pathways. Molecular docking suggested favorable interactions between quercetin and these predicted targets. In vitro, quercetin showed moderate antibacterial activity against Salmonella Enteritidis, with a minimum inhibitory concentration of 256 μg/mL and a minimum bactericidal concentration of 512 μg/mL. In vivo, quercetin alleviated intestinal histopathological damage and reduced the transcriptional expression of the five target genes in infected chicks in a dose-dependent manner, with more evident effects at doses of 512 mg/kg or higher. These findings provide preliminary evidence that quercetin may exert both direct antibacterial and host-associated protective effects against Salmonella Enteritidis, although the underlying mechanisms require further validation. Full article

Polyphenols are structurally diverse plant secondary metabolites with broad biological activities and growing applications across the food, health, and materials sectors. Conventional extraction based on organic solvents (e.g., methanol, ethanol) is often energy-intensive, inefficient, and environmentally burdensome. Ionic liquids (ILs) and deep eutectic solvents (DESs) have therefore emerged as greener alternatives for polyphenol extraction. This review evaluates recent advances in solvent design, extraction performance, and process sustainability. Imidazolium-based ILs frequently achieve high yields and selectivity, particularly when coupled with ultrasound or microwave-assisted extraction, but high cost, synthetic complexity, viscosity-related constraints, and potential toxicity hinder scaleup. By contrast, DESs—especially those derived from choline chloride or lactic acid—are easier to prepare, less costly, and more compatible with industrial implementation, with efficiency enhanced by tailoring hydrogen bond networks, water content, and process intensification. Critical downstream challenges persist for both solvent classes, notably in extract purification and solvent recovery due to low volatility; approaches such as resin adsorption, antisolvent precipitation, and direct formulation have been explored. Overall, ILs and DESs represent compelling alternatives to conventional solvents, and future progress will depend on integrated extraction–recovery strategies, systematic solvent selection, and validation under scalable, sustainable processing conditions. Full article

Background: Crosslinker-free, pH-induced hydrogels offer a green alternative for food preservation but often lack mechanical robustness. Objective: In this study, we developed a ternary hydrogel from cod myofibrillar protein (CP), sodium alginate (SA), and Ulva prolifera-derived insoluble dietary fiber (IDF) to enhance structural and preservation properties. Methods: Hydrogels with 0–3% IDF were characterized to assess their texture, water-holding capacity (WHC), and microstructure. Based on the balance between reinforcement and macroscopic processability, the 2% IDF formulation was selected for the shrimp preservation trial, which was conducted over 15 days at 4 °C. Results: Incorporation of 2% IDF significantly increased gel hardness (from 278.0 ± 6.8 g to 393.0 ± 1.8 g; p < 0.01, n² = 0.87) and WHC (from 60% to 84.3 ± 2.1%; p < 0.01). In preservation tests, the CP-SA-IDF coating maintained TVB-N at 41.62 ± 3.7 mg/100 g, significantly lower than the control (78.65 ± 4.5 mg/100 g; p < 0.01) and inhibited microbial growth (TVC: 6.9 ± 0.3 log CFU/g vs. control 9.1 ± 0.4 log CFU/g; p < 0.05). A combined freshness index demonstrated superior overall preservation efficacy (0.82 vs. 0.49 in control; p < 0.05). Conclusions: IDF reinforces the CP-SA network via hydrogen bonding and physical entanglement, creating an effective edible coating for aquatic product preservation. Full article

Quantitative microbial risk assessment (QMRA) has become a central framework for evaluating foodborne microbial hazards by integrating microbiological data, exposure assessment, dose–response modelling, and probabilistic simulation. Over the past three decades, its rapid expansion has created challenges in obtaining a coherent overview of the field’s structure, dominant themes, and research trajectories. This study presents a bibliometric and systematic review of QMRA research in food safety. Bibliographic data were retrieved from the Scopus database (search conducted in January 2026), including peer-reviewed articles published in English between 1995 and 2024, and analysed using performance analysis and science mapping techniques to assess publication trends, influential contributors, collaboration patterns, and thematic evolution. Risk of bias assessment was not applicable due to the bibliometric nature of the study. The results indicate steady long-term growth of QMRA research, based on a final dataset of 186 articles across multiple journals and countries, with a concentrated influence structure dominated by a limited number of specialised journals, institutions, and research groups. International collaboration is particularly strong within European networks. Thematic analysis identifies probabilistic exposure assessment, Monte Carlo simulation, predictive microbiology, and dose–response modelling as the methodological core, with a primary focus on major foodborne pathogens such as Campylobacter, Salmonella, Listeria monocytogenes, and Escherichia coli. Persistent emphasis on uncertainty, cross-contamination, and dose–response relationships highlights key methodological challenges. Limitations include reliance on a single database and potential exclusion of studies using alternative terminology. These findings provide a structured overview of the QMRA landscape and identify priorities for methodological refinement and future application in food safety risk assessment. This study received no external funding and was not prospectively registered. Full article

The aim of this study is to identify the factors that shape the ability of producers in short food supply chains in Slovakia to utilize different types of distribution channels and to penetrate higher-demand markets. The analysis was based on a database compiled from a public SFSC platform, comprising 986 agri-food producers, 1434 points of sale, and 1908 producer–point of sale ties. The data were analyzed as a two-mode network using ERGM models. The results show that most producers remain tied to local direct sales, while access to more demanding channels and distant markets is concentrated among a small group of actors. The study shows that the functioning of SFSCs in Slovakia is strongly shaped by producer size, value added, and the form of production organization. Organic certification emerges as a key tool of product differentiation that enhances ability to access distant and urban markets, although its importance in a post-socialist context is highly dependent on market characteristics. Family farms are selectively able to supply distant markets, while cooperatives, despite their expected association with commodity-oriented production, are able to overcome capacity and logistical barriers within SFSCs, indicating the emergence of new collaborative structures and business models. Full article

The valorization of agro-industrial residues represents a strategic approach to advancing sustainability and circular bioeconomy principles in the food sector. Although bacterial cellulose (BC) production from waste substrates has been widely explored, limited attention has been given to the role of nitrogen source modulation in complex fermentation systems. This study evaluated passion fruit peel hydrolysate (PFPH), a cellulose- and hemicellulose-rich by-product, as an alternative carbon source for BC production using a symbiotic culture of bacteria and yeast (SCOBY) under static conditions. Acid hydrolysis and detoxification were performed to obtain fermentable sugars while minimizing inhibitory compounds. Different nitrogen sources and purification strategies were comparatively assessed. The highest purified BC yield (81 g L⁻¹ of culture medium) was obtained using ammonium sulfate, whereas sodium nitrate promoted greater impurity removal (77.51% mass reduction). Structural and chemical analyses (FTIR, XPS, and XRD) confirmed effective delignification, enhanced surface purity, and increased crystallinity. SEM revealed a homogeneous nanofibrillar network, and thermogravimetric analysis indicated thermal stability up to approximately 300 °C. Soil burial assays showed 26% mass loss after 42 days, demonstrating controlled biodegradation consistent with food packaging requirements. Overall, PFPH proved to be an efficient and sustainable substrate for BC biosynthesis. The modulation of nitrogen source significantly influenced both production yield and structural properties, highlighting the potential of this system for developing environmentally responsible biopolymer materials for food packaging applications. Full article

Net primary production (NPP) in the ocean is fundamental to marine food webs, supporting oxygen production for heterotrophic respiration and contributing to the long-term sequestration of carbon. Rising ocean temperatures associated with climate change are expected to alter NPP dynamics. However, it remains challenging to understand how different abiotic (especially sea temperature) and biotic factors influence marine NPP due to the complex network of interactions between these factors. This study introduces a flexible machine-learning-based framework for evaluating the sensitivity of NPP to variations in key environmental drivers, particularly sea temperature, by testing and comparing alternative machine learning algorithms. In the case study presented here, Support Vector Machines (SVM) achieved the highest predictive performance among the evaluated models. Variable-importance analysis of the best-performing algorithm, within the scope of this comparative framework, revealed that variables intrinsically linked to NPP, such as chlorophyll-a and solar radiation, play a key role in determining the predictive ability of the models. Meanwhile, sea temperature emerged as the key external factor influencing the performance of the models. The NPP exhibits a correlative sensitivity to increase of 1 °C in sea temperature, with relative changes ranging between 3% and 16%. These projections reflect model-based sensitivities derived from historical co-variation. Therefore, the results represent conditional projections under observed relationships. Although SVM performed best for this case study, the proposed framework is adaptable and can incorporate alternative algorithms, predictor sets and preprocessing strategies, enabling robust and transferable assessments of the sensitivity of regional ocean productivity to climate change. Full article