Search Results (1,024)

Koji production is a critical process that determines the flavor and quality of the final soy sauce product. However, the complex mechanisms underlying microbial metabolism and the evolution of the physicochemical environment still require further analysis. This study focuses on three parallel koji rooms in an industrialized koji fermentation process. This work tracked the dynamics of physicochemical indices, volatile flavor compounds, and microbial communities over a full 40 h cycle. Data integration and correlation analysis elucidated the close linkage between the microbial community, the fermentation environment, and flavor formation. Koji moisture declined gradually, with faster losses at later fermentation stages. This physiological dehydration arose from microbial metabolic heat, forced aeration and structural loosening of koji, not simple physical evaporation. System pH displayed a typical U-shaped trend across fermentation. Values dropped early, most likely driven by accumulating organic acids, before rising from mid to late fermentation. This pH rebound was tentatively attributed to ammonia release from proteolytic breakdown, which may neutralize acidic compounds. These observations cast doubt on the conventional assumption that organic acid levels may be reliably estimated solely from pH measurements. Physicochemical analysis showed continuous accumulation of amino acid nitrogen (0.6–0.9 g/100 g) and total acidity throughout fermentation. By contrast, reducing sugar concentrations differed across individual koji rooms, presumably owing to divergent microbial adaptation in early fermentation. A total of 77 common compounds were identified, among which 13 key odor-active compounds with OAV ≥ 1, such as 4-vinylguaiacol and 3-methylbutyraldehyde, constitute the characteristic flavor profile of soy sauce starter culture. High-throughput sequencing uncovered a distinct ecological pattern: eukaryotic communities, dominated by Aspergillus oryzae, converged under controlled regulation. While prokaryotic communities differentiated dynamically, driven by spatial heterogeneity in the semi-open fermentation environment. Spearman correlation analysis further indicated potential functional partitioning: high-abundance taxa (e.g., Aspergillus oryzae, Weissella) were predominantly associated with macromolecular substrate degradation, whereas rare low-abundance taxa (e.g., Alternaria) displayed significant correlations with the biosynthesis of key characteristic flavor compounds. This study clarifies the synergistic regulatory mechanisms linking physicochemical conditions, microbial metabolism, and flavor precursor formation during industrial koji production. The findings establish a scientific foundation for optimizing process parameters and achieving standardized quality control in soy sauce manufacturing. Full article

Expanded snack extrusion is governed by tightly coupled interactions among raw material composition, moisture, barrel temperature, screw speed, feed rate, screw configuration, die geometry, and energy input. These variables affect not only final responses such as expansion ratio, bulk density, hardness, crispness, and water absorption or solubility indices, but also intermediate state variables including specific mechanical energy (SME), melt temperature, die pressure, melt viscosity, and bubble growth dynamics. As a result, modelling has become essential for product design, process optimisation, and scale-up. This review critically evaluates the major classes of models used to describe process–structure–quality relationships in the extrusion of expanded snacks. The literature shows that empirical regression and response surface methodology (RSM) remain the most widely applied tools because they are experimentally efficient and easy to interpret. However, mixture-process designs are more appropriate when formulation and operating variables are changed simultaneously, while phenomenological and mechanistic approaches provide better physical insight into expansion and structure development. More recently, machine-learning and interpretable artificial intelligence approaches have demonstrated strong predictive capability when large, well-curated datasets are available. Across model families, a consistent theme is that operating variables act on final product quality through intermediate process state variables rather than independently. On that basis, this review proposes a practical hybrid framework for expanded snack extrusion: a mixture-process quadratic model augmented with SME, die pressure, melt temperature and shear-related state variables, and structured in three levels linking (i) controllable inputs to state variables, (ii) state variables to measurable quality attributes, and (iii) quality attributes to a gold-standard product target or sensory-control criterion. Such a model offers a realistic balance between predictive performance, physical interpretability, experimental burden, and industrial usefulness, while also providing a clear pathway toward future digital twin and machine-learning-enabled optimisation. Full article

Robust defect classification is critical for intelligent process inspection and quality control in steel manufacturing, but it remains challenging when industrial tabular data are small, imbalanced, statistically skewed, and characterized by nonlinear inter-feature dependencies. This study proposes a robust steel plate defect classification framework based on a feature-embedded Transformer. A quantile-based transformation is first introduced to regularize heterogeneous and heavy-tailed process descriptors. Each numerical variable is then represented as a learnable feature token and processed by a Transformer encoder to model contextual interactions among positional, geometric, luminosity-related, and morphological attributes. Experiments were conducted on the Steel Plates Faults dataset, containing 1941 samples, 27 input features, and 7 defect categories. On the held-out test set, the model achieved an accuracy of 0.735, remaining competitive with XGBoost (0.794) and Random Forest (0.783). SHAP and self-attention analyses further indicate that the model captures distributed and interaction-aware defect representations, providing an interpretable solution for robust industrial defect classification. Full article

To address the “3R” issues (resistance, resurgence, and residue) associated with chemical control of the sea buckthorn fruit fly (R. batava obscuriosa), this study proposes a novel physical barrier technology aimed at reducing pesticide application intensity, mitigating environmental pollution, and enhancing fruit quality. Yellow sticky traps were deployed to monitor adult occurrence dynamics and delineate the critical control window, while black polyethylene (PE) ground cover was installed on the orchard floor around the base of sea buckthorn trunks to prevent adult emergence from the soil. Control efficacy was evaluated by comparing adult trap catches and fruit infestation rates between the black PE ground cover treatment and the untreated control. Monitoring results revealed that adult emergence commenced on 29 June, entered the peak period on 9 July, attained maximum trap catch on 24 July, and persisted into the late emergence phase through mid-to-late August. Control data demonstrated that mean trap catches in the black PE ground cover treatment were lower than those in the control. From 2024 to 2025, fruit infestation rates declined from 74.5% and 62.3% in the control plot to 19.0~22.0% and 16.2~19.3% in the treatment plots, respectively, with control efficacy consistently exceeding 65%. This study demonstrates that black PE ground cover reduces adult abundance and fruit infestation rates of R. batava obscuriosa, with control efficacy consistently exceeding 65%. The observed effects are consistent with a soil-surface barrier effect and likely attributed to dual physical mechanisms: it may reduce adult emergence from the soil into the canopy and may obstruct mature larvae from entering the soil to pupate. This technology represents an environmentally sound, sustainable green control option suitable for integration into IPM programs for the sea buckthorn industry. Full article

Efficient grazing management is critical for optimising animal growth and carcass quality in dairy beef systems; however, the combined effects of turnout date to spring pasture and post-grazing sward height have not been well quantified. This study evaluated the effects of spring turnout date (early vs. late) and post-grazing sward height (3.5 vs. 5.5 cm) on steer performance, intake, and carcass attributes, over three production cycles in a dairy calf-to-beef system. A total of 188 dairy and dairy × beef steers (initial body weight approximately 250–285 kg) were used across three experiments, conducted in a pasture-based calf-to-beef system. Animals grazed for ~200 days followed by ~100 days of indoor finishing. Early turnout improved average daily gain during early- and mid-season (p < 0.05 to p < 0.001), but differences had disappeared by housing, with no effect on carcass traits (p > 0.05). Grazing swards to 5.5 cm increased average daily gain at pasture (p < 0.01) and housing weight in the three experiments (p < 0.01). Animals grazed to 3.5 cm at pasture subsequently had a higher indoor finishing average daily gain (p < 0.05). Grazing to a stubble height of 5.5 cm improved (p < 0.001) daily gain at pasture but reduced finishing daily gain (p < 0.001). Carcass weight per day of age and were unaffected by either factor (p > 0.05), and no significant turnout × post-grazing sward height interactions were detected for any measured variables (p > 0.05). These findings indicate that maintaining a higher post-grazing sward height provides improved animal performance, while early turnout offers short-term gains, supporting grazing strategies that prioritise sward height management for sustained performance. Full article

Cascade hydropower alters river hydrological regimes and threatens aquatic ecosystems, calling for robust ecological risk assessment (ERA). Conventional assessments often rigidly apply the full five-layer Driving Force–Pressure–State–Impact–Response framework, leading to indicator redundancy and unbalanced weighting. Single weighting methods also fail to reconcile expert judgment with data variability. To address these issues, we developed a three-layer (target–element–indicator) evaluation system embedding DPSIR logic without its full structure, focusing on hydrological regime, water environmental quality, and aquatic ecology with ten indicators. We used an improved group AHP-CRITIC coupling method for weighting: AHP aggregates expert judgments via geometric mean, and CRITIC integrates data variability and inter-indicator conflict. Multi-attribute utility theory normalized indicators into a unified security index, applied to four cascade stations in the middle Jinsha River using 66-year (1953–2018) hydrological and seven-year (2013–2019) in situ monitoring data. The evaluation obtained a comprehensive index of 0.71 to 0.74, which is generally safe. River connectivity loss was the primary limiting factor. Hydrological alteration was mild overall with a value of 0.139, while extreme flow decline rate variation reached a high level of 0.83. Weekly regulated stations achieved over 97% ecological flow guarantee, which is much higher than daily regulated stations. This streamlined framework improves interpretability for cascade basins and supports sustainable watershed management. Full article

Phase-inversion in situ implants (PIISIs) represent a versatile polymer platform in which the rational choice of matrix former and solvent system directly governs the macroscopic properties of the resulting depot. This study applied a Quality by Design (QbD) approach to rationalize a bleached shellac–based PIISI, with particular focus on the physicochemical interactions between the polymer and the injection vehicle. Bleached shellac—a natural, low-cost, biodegradable oligomeric resin bearing –COOH, –OH, and ester functional groups—was selected as the matrix former and screened in seven neat solvents and five 1:1 binary combinations at 25% (m/m). Twelve formulations were evaluated against a predefined set of critical quality attributes, including injectability, phase-inversion kinetics, solvent diffusion volume, and implant structure (n = 5 per formulation; mean ± standard deviation (SD); one-way analysis of variance (ANOVA) with Tukey’s post hoc test, p < 0.05). Three lead solvent systems—propylene glycol/N-methylpyrrolidone (PG+NMP), PG/dimethyl sulfoxide (PG+DMSO), and DMSO/benzyl alcohol (DMSO+BA)—were identified as those providing an optimal balance between hydrogen-bond donor/acceptor solvation and controlled solvent extraction. In the second stage, shellac concentration (20–35%) was optimized, with 30% shellac in PG+NMP yielding the fastest phase inversion (~50 s), a structurally uniform matrix, and the lowest swelling (22%). A working mechanistic framework consistent with all observed critical quality attribute (CQA) trends in which solvent hydrogen-bond donor/acceptor balance and water miscibility govern implant architecture is proposed, and it is intended as a hypothesis-generating basis for the rational design of PIISI formulations; direct validation by spectroscopic, thermal-analytical, and biological methods is identified as the next step. The developed formulations are presented as a preliminary physicochemical platform; biological validation (in vitro cytocompatibility and inflammatory response assessment) is required before the system can be considered a validated formulation for dental drug delivery. Full article

Background: The transition from linear to circular supply chains (CSC) is critical for advancing sustainability, resilience, and resource efficiency, while supporting the UN Sustainable Development Goals (SDGs). However, existing studies rarely integrate internal operational performance with external PESTEL factors under the Benefits, Opportunities, Costs, and Risks (BOCR) perspective, limiting the ability to prioritize circular strategies holistically. Methods: This study develops a decision-making framework that combines the Best-Worst Method (BWM) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS), enabling reliable prioritization of interdependent sustainability criteria. Results: A case analysis in the chemical industry demonstrates the applicability of the framework, enhancing transparency and reducing subjectivity in CSC evaluation. Findings highlight quality as the key operational attribute and social as the dominant PESTEL dimension, reinforcing the integration of internal and external factors toward SDG-oriented strategies. Conclusions: The study contributes theoretically by bridging operational and contextual dimensions in CSC evaluation under the BOCR perspective, and methodologically by advancing hybrid MCDM applications to address uncertainty. Managerially, the framework provides a structured tool for aligning circular supply chain strategies with organizational objectives and SDGs, supporting decision-making that strengthens environmental sustainability, stakeholder legitimacy, and resilience. Full article

The drying kinetics and quality attributes of Polygonatum cyrtonema Hua (PCH), including color, rehydration efficiency, microstructure, and oxidation resistance, were systematically evaluated under various drying methods: hot-air drying (H-D), infrared drying (IR-D), microwave drying (M-D), freeze-drying (F-D), and vacuum drying (V-D). The results indicate that the Midilli model provides the best fit for the experimental data. Among the five drying methods, hot air drying (H-D) is extensively utilized due to its well-established technology; however, its drying performance is relatively average. M-D and IR-D exhibit high drying rates attributed to their strong thermal permeability. Notably, M-D achieves the highest drying rate, with a drying time of only 1/83 that of F-D, yet it demonstrates a relatively low retention rate of total polysaccharides. Furthermore, while IR-D offers fast drying rates, low energy consumption, and favorable color preservation, it performs poorly in preserving the microstructure, active component content, and oxidation resistance of PCH. By contrast, F-D and V-D exhibit significant advantages in maintaining antioxidant activity, active ingredients, and flavor. Nevertheless, F-D requires an extended duration (1080 min), leading to high energy consumption, which restricts its large-scale industrial application. This comprehensive analysis revealed that V-D achieves an optimal balance between energy consumption and product quality, demonstrating substantial advantages and providing a critical reference for the industrial drying production of PCH. Full article

Shrimp are among the most valuable seafood commodities worldwide, but are also highly perishable, making their quality preservation a critical issue for both food safety and supply chain sustainability. The rapid deterioration of fresh shrimp contributes to significant post-harvest losses, highlighting the need for reliable freshness indicators capable of supporting shelf-life assessment under commercial conditions. This study evaluated the evolution of microbiological, physicochemical, and sensory parameters in two commercially important Mediterranean shrimp species, Parapenaeus longirostris and Melicertus kerathurus, stored on ice for up to 15 days under retail-like conditions. Microbial load, pH, total volatile basic nitrogen (TVB-N), thiobarbituric acid reactive substances (TBARS), formaldehyde, formic acid, and sensory attributes were monitored during storage. Microbial populations increased progressively over time but remained below commonly accepted spoilage thresholds, while physicochemical indicators showed significant changes associated with post-mortem biochemical processes. In particular, TVB-N, pH, and formic acid increased during storage, whereas formaldehyde levels decreased, suggesting the progressive transformation of trimethylamine-N-oxide degradation products. Sensory analysis indicated that shrimp maintained high quality up to approximately 12 days of iced storage, whereas samples stored for 15 days approached the limit of consumer acceptability. The combined behaviour of microbial, chemical, and sensory indicators highlights the importance of a multidimensional approach for evaluating shrimp freshness under commercial storage conditions. Based on the experimental dataset, practical reference ranges for key quality parameters are proposed (pH < 7.4; TVB-N ≤ 30 mg N/100 g; formaldehyde < 10 mg/kg; formic acid < 18 mg/kg). These results may support improved freshness evaluation, contribute to more accurate shelf-life estimation, and help reduce unnecessary seafood waste within the supply chain. Full article

N-glycosylation, particularly terminal mannose exposure, is a critical quality attribute affecting macrophage targeting and the clinical efficacy of enzyme replacement therapy for Gaucher disease. This study developed a universal, sensitive, and quantitative method to compare the N-glycan profiles of three recombinant human glucocerebrosidase products from different expression systems: imiglucerase, velaglucerase alfa, and velaglucerase beta. Using 2-aminobenzamide labeling combined with HILIC-UPLC-FLD and high-resolution mass spectrometry, an N-glycan profiling platform was established. A multidimensional calibration system integrating retention time, glucose unit values, and mass-to-charge ratios was constructed, and collision-induced dissociation tandem MS was used to identify isomers and phosphorylated glycans. The method showed good specificity, linearity, precision, and accuracy. Glycan profiling revealed clear product-dependent differences: imiglucerase was enriched in core-fucosylated Man3 structures, velaglucerase alfa was dominated by Man9 and contained more phosphorylated and sialylated glycans, whereas velaglucerase beta showed a highly homogeneous Man5 profile. These findings demonstrate how distinct manufacturing strategies shape glycosylation patterns and provide a basis for biosimilar development and comparability assessment. Full article

Extra virgin olive oil (EVOO) is prone to oxidative degradation during storage, especially after opening, when exposure to oxygen and light accelerates the depletion of antioxidants and promotes the formation of oxidation products, including hydroperoxides and C₇–C₉ aldehydes associated with rancidity. Packaging materials play a critical role in preserving EVOO quality in real-use conditions. This study comparatively evaluated the effectiveness of three widely used packaging materials: green polyethylene terephthalate (PET), bag-in-box (BB), and chrome-plated tin (CPT) in preserving regulatory, sensory, and health-related qualities of EVOO under simulated household use and storage conditions. Methods: PET, BB, and CPT containers (3 L) were totally filled with the same EVOO and stored at 25 °C under a 12 h light/dark cycle, with 75 mL withdrawn daily for 40 days to mimic consumer use. Every 10 days, regulatory quality indices (free acidity (FA), peroxide value (PV), K₂₃₂, and K₂₇₀), antioxidants, volatile compounds, and sensory attributes were evaluated. Results: Free acidity, K₂₃₂, and K₂₇₀ increased slightly in EVOOs across all containers, while EVOO stored in PET showed a sharp rise in PV, exceeding the legal limit after 30 days. Antioxidant depletion was significantly (p ≤ 0.05) more pronounced in the EVOO stored in PET (44% α-tocopherol and 26% total phenols, respectively) than in BB (1% and 11%) and CPT (5% and 12%). The EVOO stored in PET also showed a reduction in C₅–C₆ aldehydes (−26% and −24% compared to BB and CPT, respectively), alongside an accumulation in C7–C9 aldehydes (+8% and +5%), exhibiting higher loss of C₅–C₆ aldehydes and of C₇–C₉ aldehydes, which is responsible for fruity–green notes and rancid defect, respectively, compared to BB and CPT. Conclusions: Overall, the EVOOs stored in BB, followed by CPT, showed higher oxidative stability than those stored in PET, resulting in prolonged “extra virgin” classification and improved preservation of antioxidant content, volatility profile, and sensory quality during consumer-level storage. Full article

Trimethyl chitosan (TMC)-coated alginate/dextran sulfate (ADS) nanoparticles were developed as mucoadhesive nanocarriers for oral insulin delivery using a Quality-by-Design strategy. In a first screening step, a two-level factorial design was applied to evaluate the influence of ADS concentration, TMC concentration, insulin concentration, and poloxamer^® concentration on particle size and encapsulation efficiency. The screening design identified the ADS-TMC pair as the main formulation parameter for particle size, while TMC and poloxamer^® were the most influential factors for encapsulation efficiency. In a second step, formulation optimization was performed using a three-factor, three-level Box–Behnken design in which ADS concentration, TMC concentration, and the degree of quaternization (DQ) of TMC were investigated as critical material attributes. Particle size, zeta potential, and in vitro mucoadhesion were selected as critical quality attributes. Across the Box–Behnken design, the experimental formulations showed particle sizes ranging from 316 to 1340 nm, zeta potentials between +17 and +39 mV, and mucin-binding values from 7 to 87%. Numerical optimization by Design-Expert^® desirability analysis identified an optimal formulation composed of 0.096% (w/v) ADS and 0.700% (w/v) TMC with 60% DQ. The model predicted a particle size of 316.24 nm, a zeta potential of +38.43 mV, and an in vitro mucoadhesion of 87.14%. Experimental confirmation yielded values of 330.79 nm, +37.09 mV, and 84.61%, respectively, with prediction errors below 5% for all responses. In simulated gastric medium, partial insulin leakage was observed during the first 120 min, whereas cumulative insulin release reached 54% after 5 h in simulated intestinal medium. These results demonstrate the usefulness of a QbD framework combined with desirability-based optimization for defining robust formulation conditions for mucoadhesive TMC-coated ADS nanoparticles intended for oral insulin delivery. Full article

A critical challenge in coalbed methane (CBM) extraction is the severe formation damage induced by conventional foam fracturing fluids, primarily through polymer retention and hydrogen bond disruption within the microporous matrix. This study presents a molecularly engineered, low-damage foam fracturing fluid that leverages synergistic nanoparticle–surfactant interactions to construct a robust interfacial pseudo-gel network, thereby decoupling effective fracture stimulation from adverse geochemical damage. The primary novelties of this work are threefold: (i) establishing a direct, quantitative cause-and-effect relationship between molecular interfacial architecture and reservoir protection, (ii) proposing a comprehensive “interfacial control” design paradigm that engineers viscoelasticity at the gas–liquid interface rather than through bulk polymer gelation, and (iii) demonstrating the complete decoupling of foam stability from formation damage in a polymer-free system. A systematic optimization methodology was employed: initial foaming agents were screened via the Waring Blender method, evaluating foam volume, half-life, and a derived comprehensive index; subsequently, synergistic binary surfactant mixtures and foam stabilizers were assessed to formulate the final systems. An optimized formulation, designated Foam System I (0.5 wt.% fluorosurfactant FK + 0.5 wt.% nano-silica RX + 2.0 wt.% KCl), demonstrated exceptional foam quality (Γ = 77.1 ± 1.5%) and kinetic stability (T₁/₂ > 350 s). Rheological characterization confirmed shear-thinning behavior conforming to the Herschel–Bulkley model (n = 0.38–0.42, R² > 0.98) and a structural recovery of 92.5 ± 2.1%—comparable to crosslinked polymer gels but achieved without any bulk viscosifier. Core flood analyses revealed that Foam System I induced a permeability damage of only 12.75 ± 1.8%, representing a 55–75% reduction compared to polyethylene glycol (PEG)-stabilized reference fluids (28.36–51.91%). X-ray photoelectron spectroscopy (XPS) correlated this enhanced reservoir compatibility with an 18.0 ± 2.0% suppression of oxygen-containing functional group adsorption, attributed to the steric hindrance conferred by the fluorinated hydrophobic moieties. This work establishes an “interfacial control” paradigm wherein gel-like stabilization for proppant transport is achieved via interfacial viscoelasticity rather than bulk polymer gelation, thereby directly addressing the critical imperative to harmonize fracture conductivity with reservoir protection in unconventional energy development. The findings are validated for shallow CBM reservoir conditions (25–35 °C), with extension to higher-temperature formations identified as a priority for future investigation. Full article

Multivariate time-series anomaly detection is often evaluated with point-adjusted metrics, which can overstate practical performance when alarms are judged at the event level. Explanation results are also frequently reported as descriptive attributions without directly testing whether selected variables are useful for diagnosis. This study revisits these issues through unified event-level evaluation and repair-based explanation, using DCdetector as the main case study rather than proposing a new detector architecture. Experiments on SMAP, MSL, and HAI 21.03 use full-coverage score export and standard event-level control metrics. The results show that point-adjusted scores can be much higher than stricter event-level measurements. Event-aware refinement changes the detection trade-off by improving event recovery and reducing delay in several settings, but its effect is dataset- and calibration-dependent. For explanation, variables are ranked by exact marginal counterfactual repair effect and evaluated by whether repair reduces anomaly scores more than random or heuristic alternatives. The results provide quantitative evidence that the ranked variables are diagnostically informative, while exact marginal verification is computationally expensive and better suited to offline alarm review and post hoc diagnosis than latency-critical deployment. Auxiliary checks with TranAD, Anomaly-Transformer, and DADA support the plausibility of the main observations, but the evidence remains detector-conditioned rather than a fully backbone-agnostic benchmark. Overall, this work provides a stricter and more verifiable protocol for evaluating anomaly detection, event-aware refinement, and explanation quality in multivariate time-series monitoring. Full article