Search Results (6,511)

Efficient crop health monitoring is crucial for global food security. Supervised deep learning approaches are often impractical due to the scarcity of large, labeled datasets. To address this limitation, this study adapts EfficientAD, an unsupervised, label-free anomaly detection framework originally designed for industrial inspection, for agricultural imagery on small datasets. The method utilizes a Patch Description Network (PDN) for localized feature extraction, a student network for local anomalies, and an autoencoder for global structural constraints. Benchmarked against AnoGAN, Pix2Pix, InTra, and Teacher–Student models, the framework demonstrated superior performance on the MVTec AD, PlantVillage, Coffee Leaf, and a custom real-world Sweet Potato dataset. The model achieved perfect area under the receiver operating characteristic curve (AUROC) scores of up to 100% in categories like “Pongamia”, “Potato”, and “Coffee Leaf”. While image-level classification was exceptionally robust, pixel-level localization (AUPRO) proved sensitive to complex agricultural backgrounds. To overcome this, a background interference analysis was conducted using Background Removed (BGRM) and out-of-distribution Background Replaced-Green (BGRP-G) strategies on the custom dataset. Notably, the BGRP-G strategy remarkably improved the image-level AUROC from 88.9% to 99.5% and substantially boosted the pixel-level AUPRO from 47.1% to 61.9%, successfully preserving the boundary integrity of severe structural defects. Achieving millisecond-level latency without complex data augmentation, this adapted label-free framework offers a versatile, highly efficient solution for real-time crop health diagnostics on resource-constrained Edge AI devices. Full article

The herbal tea industry has experienced substantial growth, particularly regarding green tea (Camellia sinensis). In the manufacturing of filter tea, fine herbal dust is generated as a residual by-product during grinding and sieving and is typically discarded as waste. This study aims to explore the application of ultrasound-assisted extraction (UAE) for secondary valorisation of green tea herbal dust by investigating the effects of various parameters on extraction efficiency. Antiradical activity of UAE extracts was determined using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, and the total phenolic content (TPC) was measured using Folin–Ciocalteu’s assay. Furthermore, selected phenolics were quantified by HPLC and qualitatively characterised by liquid chromatography coupled with electrospray ionisation and quadrupole time-of-flight tandem mass spectrometry (LC-ESI-QToF-MS/MS). The results demonstrate that UAE parameters have a pronounced influence on the antioxidant activity, TPC, and individual polyphenolic profile of green tea herbal dust extracts. Ethanol–water mixtures at a ratio of around 40–60%, as well as moderate impulse regimes (around 60%) and extraction times (around 10 min), were the most suitable for extracting green tea polyphenols. Epigallocatechin gallate was the predominant phenolic component in most extracts, alongside epicatechin, epigallocatechin, catechin, and gallic acid. The findings highlight the UAE technique as a robust, green, and scalable method for valorising green tea by-products, thereby facilitating the development of high-value natural extracts for applications in the food, pharmaceutical, and cosmetic industries. Full article

In recent years, the green extraction of natural active ingredients has generated widespread attention. And deep eutectic solvents have widely replaced traditional organic solvents. In this study, choline chloride/glycolic acid (1:2) was chosen as the optimal extractant to extract flavonoids from Tartary buckwheat. The optimal extraction conditions were as follows: water content of 30%, liquid–solid ratio of 40 mL/g, extraction temperature of 60 °C and extraction time of 40 min. And the extraction efficiency reached 27.22 ± 0.31 mg/g. Then kinetic and thermodynamic mechanisms were investigated comprehensively, and the results showed that the extraction process could be well fitted by Fick’s second law. In addition, macroporous resins were used to recover flavonoids from extracts. The adsorption efficiency of flavonoids on HP20 resins under the optimal conditions (time of 2 h, liquid–resin ratio of 2.5 mL/g, temperature of 25 °C) could reach 80.14 ± 0.33%. Full article

The increasing demand for environmentally sustainable and efficient laundry detergents has prompted the exploration of innovative biotechnological solutions. This study aims to integrate solid fermentation and by-product valorization for high-quality proteases suitable for laundry detergents. Of 486 strains isolated from fruit by-products, 9 were selected for their proteolytic activity, but only 3 showed proteolytic activity in the presence of detergent components. Strain M17, identified as Yarrowia lipolytica (Yl), proved to be the most effective in producing proteolytic extracts with activity similar to that found in commercial detergents. The produced proteases were incorporated into laundry detergent formulations, and their enzyme activity was compared with that of commercial laundry detergents. The results showed that the proteolytic extracts have enzyme activity similar to that of commercial laundry detergents. Culture media were developed to enhance protease production using fruit by-products. The highest activity (43.71 U (g dm)⁻¹) was achieved at C/N = 20.04, while the best productivity (1.37 U (g dm·h)⁻¹) at pH 7.0 and 30 °C was observed. The results demonstrate that culture media based on fruits and vegetable by-products enhance protease yield and activity. This approach not only reduces waste but also adds value to natural resources through an environmentally friendly process. This study underscores the potential of combining solid-state fermentation with by-products. Using Yl in combination with fruit and vegetable by-products is a practical, eco-friendly method for producing high-quality proteases for laundry detergents. This green enzyme innovation offers significant promise for advancing the detergent proteolytic enzymes and promoting sustainable practices in by-product management. Full article

The present study provides an exhaustive exploration of twelve macroalgal species from the Adriatic Sea, including seven brown algae (Ericaria amentacea, Fucus virsoides, Cutleria multifida, Cystoseira compressa, Cystoseira corniculata, Gongolaria barbata and Padina pavonica), three green algae (Codium adhaerens, Codium vermilara and Ulva lactuca), and two red algae (Scinaia furcellata and Asparagopsis taxiformis). Matrix solid-phase dispersion (MSPD) was applied as the extraction technique, using generally recognized as safe (GRAS) solvents. The bioactive profile of the extracts was assessed through the quantification of total phenolic content (TPC) and antioxidant activity. Among the three phyla, U. lactuca, F. virsoides and S. furcellata exhibited the highest TPC (0.8, 26 and 3.0 mgGAE·g⁻¹) and antioxidant activity (1.9, 38 and 7.5 mgTE·g⁻¹), respectively. Targeted HPLC-MS/MS analysis enabled the identification of nineteen phenolic compounds across all taxa. Chlorophyta showed a characteristic profile enriched in coumarins, benzaldehydes and flavanones, including the selective detection of 7-hydroxycoumarin in species with higher antioxidant potential. Additionally, compounds such as chlorogenic, rosmarinic and caffeic acids exhibited taxon-specific distributions that may explain differences in antioxidant activity. Complementary untargeted ultra-high performance liquid chromatography quadrupole time-of-flight (UHPLC-QToF) metabolomics analysis provided broader coverage, revealing eighty metabolites spanning phenolics, sugars, organic acids, lipids, amino acids and their derivatives. Notably, the proposed detection of fatty acid esters of hydroxy fatty acids (FAHFAs) represents the first report of these compounds in macroalgae, alongside a pronounced presence of sulphated phenolics. Overall, these findings provide a robust baseline on the bioactivity and chemical composition of Adriatic macroalgae, highlighting their value as a natural source of functional compounds. Full article

This study presents an integrated approach for producing antioxidant-rich polar fractions from Inula salicina L. via pressurised ethanol/water extraction (PLE-EtOH/H₂O), optimised by coupling a central composite design and response surface methodology (CCD-RSM) with Aspen Plus^® simulation. The effects of PLE temperature, extraction time, and EtOH/H₂O ratio for yield, total phenolic (TPC) and flavonoid (TFC) content, and Trolox equivalent antioxidant capacity (TEAC) measured in ABTS^•+-scavenging, cupric ion reducing antioxidant (CUPRAC) and oxygen radical absorbance (ORAC) assays were assessed via a multi-response optimisation approach. Optimal conditions were set at 82 °C, 27 min, and 60% EtOH (v/v), yielding ~29 g extract per 100 g plant material, characterised by high TPC (227 mg GAE/g), TFC (34 mg QE/g), and TEAC values in the CUPRAC (1473 mg TE/g), ABTS (869 mg TE/g), and ORAC assays (1165 mg TE/g). The TPC and TEAC values of the post-extraction residue were >92% lower than those of unextracted I. salicina, confirming efficient recovery of the major portion of antioxidant-active constituents by PLE-EtOH/H₂O. The high in vitro radical scavenging capacity, reducing power, and photoprotective potential (sun protection factor ~50 at 0.5 mg/mL) of the I. salicina extract are consistent with its phenolic-rich composition, with chlorogenic acid (~97 mg/g extract) and its derivatives being the major constituents. The validated Aspen Plus^® model closely aligned with the CCD-RSM predictions, supporting process scale-up and energy feasibility and demonstrating an industry-relevant, green-solvent PLE process for producing higher value-added I. salicina fractions with potential applications in the food, pharmaceutical, nutraceutical, and cosmetic sectors. Full article

Propolis is a resin collected by bees from several plant sources and used by humans for centuries. Its commercial use is usually based on alcoholic extracts, which is a drawback for some applications. Conversely, oil extracts are non-toxic and capable of extracting and dissolving a wide range of less polar compounds. As previous studies showed that oil extracts presented bioactivity similar to ethanolic extracts, a reproducible method for the extraction of green Brazilian propolis was developed and patented. The antimicrobial and cytotoxic activities of the ethanolic and oil extracts of green propolis were compared as well as their ultra-high-performance liquid chromatography with high-resolution mass spectrometry (UHPLC-HRMS) profiles, with similar results. A method was developed to recover propolis bioactive compounds from the oily matrix in order to allow its qualitative and quantitative quality control, according to parameters determined by the Brazilian Ministry of Agriculture, and is presented herein for the first time. The total flavonoid and phenolic contents, antioxidant activity and dry mass are comparable to the ethanolic extract. Therefore, OEP can be recommended for the diverse food supplements and cosmetic products that currently use the ethanolic extract of propolis, without the drawbacks of the presence of alcohol in these formulations. Full article

Globally, the combined pollution of fine particulate matter (PM_2.5) and ground-level ozone (O₃) poses severe challenges to public health and sustainable urban development. Recent data indicate that the annual average PM_2.5 concentration in the vast majority of cities worldwide fails to meet World Health Organization safety standards, with air pollution causing millions of premature deaths annually. As a nature-based solution, the purification efficacy of vegetation remains poorly quantified due to unclear coupling mechanisms with local meteorological conditions. This study systematically reviewed and synthesized 229 empirical studies published between 2000 and 2025 from Web of Science and China National Knowledge Infrastructure (CNKI), aiming to clarify the quantitative relationships and regulatory mechanisms of plant–meteorological synergistic purification of PM_2.5–O₃. Following double-blind independent screening (κ = 0.85) and data extraction, a quantitative minimal feasible synthesis approach was adopted due to high data heterogeneity. The results indicated the following. (1) The median canopy purification efficiency of urban vegetation for PM_2.5 was 18.2% (IQR: 12.5–30.1%, n = 17), with a median dry deposition velocity (Vd–PM) of 0.05 cm s⁻¹ (0.02–30 cm s⁻¹, n = 15). The median dry deposition velocity (Vd–O₃) for O₃ was 0.55 cm s⁻¹ (0.12–1.82 cm s⁻¹, n = 8), with non-stomatal deposition contributing approximately 35%. (2) Meteorological factors exhibit nonlinear regulation: relative humidity (RH) > 70% significantly enhances PM_2.5 adsorption, wind speeds of 1.5–3.0 m s⁻¹ are optimal for PM_2.5 deposition, and temperatures > 30 °C generally inhibit plant uptake of both pollutants (n = 7). (3) Functional traits strongly correlate with purification efficacy: species with high leaf roughness (R² = 0.8), high stomatal conductance, and low BVOC emissions (e.g., Ginkgo biloba, Platycladus orientalis) exhibit optimal synergistic purification potential. Species with high BVOC emissions (Populus przewalskii, Eucalyptus robusta) can increase daily net O₃ pollution equivalents by up to 86 g and must be strictly avoided. Based on quantitative evidence, a green space planning decision matrix indexed by climate zone and pollution type was developed, specifying vegetation configuration patterns, functional group selection, and key design parameters (canopy closure, green belt width, etc.) for different scenarios. This study provides an actionable scientific basis for precision planning and climate-adaptive management of urban green infrastructure. Full article

Sol–gel-based optical functional sensor coatings were developed for real-time monitoring of multiphase saponification reactions in microreactors. Various pH-sensitive indicator mixtures, including bromocresol green and bromocresol purple (BCG and BCP) and methyl red–methyl orange, were incorporated into sol–gel coatings and evaluated on test plates across pH range of 2–12. Coatings with BCG and BCP 1:3 demonstrated the most pronounced color change at high pH (11–12), with distinct hue (H) transitions providing a reliable measure of local pH. These optimized coatings were integrated into microreactor channels to track the passage of oil and NaOH slugs under varying flow rates. Hue analysis produced reproducible plateaus corresponding to NaOH-rich (H = 50°) and oil-rich (H = 41°) phases, enabling droplet-level resolution of slug flow and detection of flow-regime transitions. The sensor response was fully reversible, highlighting the robustness and reusability of the coatings. Unlike previous high-resolution fluorescence-based systems, this approach relies on simple visible-light imaging and low-cost data extraction, leaving the reaction chemistry unaltered. The results demonstrate that sol–gel coatings coupled with hue-based analysis provide a practical, noninvasive, and real-time monitoring strategy for multiphase reactions in microreactors, with potential for implementation in industrial or IoT-enabled process control systems. Full article

The expansion of the global agri-food industry has led to the generation of large volumes of processing by-products that, although traditionally treated as waste, represent valuable sources of bioactive phytochemicals with potential for sustainable valorisation. This review critically examines the integration of fruit, vegetable, cereal, and dairy processing side streams into functional dairy products. Particular attention is given to recent advances in green and emerging extraction technologies, including ultrasound-assisted extraction, microwave-assisted extraction, and supercritical fluid extraction, with emphasis on their efficiency, environmental performance, and effects on the stability and recovery of phytochemicals. The review also discusses the health-related properties of these bioactive compounds, including antioxidant, anti-inflammatory, and metabolic regulatory effects, in relation to their incorporation into milk, yogurt, cheese, and ice cream matrices. In addition, key barriers to industrial implementation are assessed, including compound stability, sensory constraints, bioavailability, and current regulatory limitations. Beyond direct fortification, the review also considers broader valorisation pathways, such as the biotechnological production of microbial enzymes from agro-industrial biomass, as relevant strategies for supporting circularity. Overall, this review highlights how sustainable extraction approaches and functional dairy innovation can contribute to improving the nutritional value, resource efficiency, and circularity of the dairy sector. Full article

This study presents a statistically optimized protocol for the green synthesis of gold nanoparticles (Au NPs) using aqueous Kalanchoe pinnata leaf extract (AKPLE). An integrated experimental strategy, transitioning from preliminary one-factor-at-a-time (OFAT) screening to a five-factor Box–Behnken Design, was employed to model and simultaneously optimize two critical optical responses derived from surface plasmon resonance: the peak position (λ_max) and its absorbance intensity. Highly predictive quadratic models (R² > 0.97) revealed that synthesis outcomes are governed by significant nonlinear curvature, with minimal interaction effects. Multi-response optimization via a desirability function identified a harmonized set of conditions (HAuCl₄: 0.44 mM, AKPLE: 3.50% v/v, temperature: 80.6 °C, pH: 7.2, time: 66.7 min) predicted to minimize λ_max at 540 nm while maximizing absorbance to 0.61. Synthesis under these optimized conditions successfully produced spherical, crystalline Au NPs, as confirmed by characterization (average TEM size: 26.3 ± 4.1 nm; zeta potential: –30.45 mV). This work demonstrates that a hybrid OFAT-RSM approach is superior for the precise, multivariate optimization of plant-mediated Au NP synthesis, providing a validated and scalable framework to balance nanoparticle size and plasmonic intensity—an outcome unattainable through conventional OFAT methods. Full article

The increasing demand for different value-added products from natural seaweeds requires a sustainable cultivation method for the regular supply of biomass and to safeguard the natural ecosystem from overexploitation. This study evaluated laboratory acclimatization of the green seaweed Acrosiphonia orientalis (DGR: 2.71 ± 0.21%; GPP: 12.55 ± 0.1 mg O₂ L⁻¹ day⁻¹), followed by a comparative evaluation of its physicochemical and biochemical characteristics, metabolite profile, and antiproliferative activity compared with naturally harvested seaweed. Metabolite profiling identified 47 compounds exhibiting differential accumulation patterns, with the natural specimens enriched in omega-3 polyunsaturated fatty acids, including docosahexaenoic acid, and the laboratory-acclimatized specimens exhibited elevated arachidonic acid levels. Amino acid profiling revealed higher concentrations of essential and non-essential amino acids in the natural specimens, with prominent levels of phenylalanine and aspartic acid, while the lab-acclimatized specimens were enriched in isoleucine, methionine, proline, and cysteine. The lab-acclimatized specimens exhibited significantly enhanced water absorption (WSC: 6 ± 0.25 mL/g DW; WHC: 2.68 ± 0.11 g/g DW) and higher total sugar (47.11 ± 0.52% Glc eq. DW) and phenolic contents (51.28 ± 0.54 mg GAE g⁻¹ extract), while the natural specimens had a superior oil-holding capacity (OHC: 1.8 ± 0.12 g/g DW); higher total flavonoid (123.62 ± 2.97 mg Q g⁻¹ extract), protein (5.11 ± 0.36 µg BSA eq/mg DW), and chlorophyll contents (8.82 ± 0.58 mg/L); and higher antioxidant activities (ABTS-EC₅₀: 67.33 ± 0.97 μg/mL extract). The mineral analysis revealed distinct elemental profiles, with enrichment of sodium, magnesium, and calcium in the lab-acclimatized specimens and a more favorable Na/K ratio (0.14 vs. 0.78) in the natural specimens. Of note, extracts from both seaweeds exhibited significant dose-dependent antiproliferative activity against HeLa cervical cancer cells (Wild EC₅₀: 118.63 ± 14.14 µg/mL extract; lab EC₅₀: 153.35 ± 10.18 µg/mL extract), suppressed colony formation in soft agar assays, induced nuclear condensation (based on Hoechst staining), and modulated the expression of key oncogenes (upregulating NDRG1, TP53, and CASP3 and downregulating BCL2, MYC, and CCND1). Collectively, this study provides an approach to acclimatize A. orientalis that may be utilized for developing a cultivation method. Moreover, this green seaweed has a great potential to be used for nutraceutical and functional food applications. Full article

With accelerating global urbanization and increasingly diverse demands for public spaces, promoting urban low-carbon transitions and enhancing residents’ quality of life have become central missions of modern urban development. As one of the city’s primary arteries, streets—through their green landscapes, slow-moving transportation systems, and public facilities—play an indispensable role in reducing carbon emissions, promoting healthy living, and improving residents’ well-being. In this study, the Yubei District of Chongqing was selected as the research area, and an automated evaluation framework was proposed for street visual quality, based on multi-source street view data and ensemble learning. PSP-Net semantic segmentation model was employed to extract eight key visual indicators from street view images, including green view index, Visual Entropy (Entropy), sky view factor (SVF), drivable space, sidewalk, safety facilities, buildings, and enclosure. Based on these features, a Stacking-based ensemble learning model was constructed, integrating multiple base models such as Random Forest, XGBoost, and LightGBM, with Linear Regression as the meta-learner, to predict street visual quality. The results demonstrate that the ensemble model significantly outperforms any single model, achieving a correlation coefficient (r) of 0.77 and effectively capturing the complex perceptual features of street environments. This study provides a reliable, intelligent, and quantitative method for large-scale evaluation of urban street visual quality, while supplying data support and decision-making references for street renewal and spatial optimization. Full article

Artificial intelligence presents a critical paradox for clean technology: while enabling unprecedented environmental optimization, AI deployment demands massive resource inputs that threaten to offset benefits. As global AI infrastructure investment approaches $500 billion annually, data center electricity consumption is projected to exceed 1000 TWh by 2030. We conducted a systematic literature review of 73 peer-reviewed empirical studies (2021–2025) to develop an Environmental Asset-Cost Framework categorizing AI’s impacts across five asset categories (energy optimization, production enhancement, green innovation, resource conservation, precision applications) and five cost categories (energy consumption, water use, e-waste, infrastructure, supply chain extraction). Our analysis reveals three critical insights: First, AI’s environmental impact follows a synthesized S-curve heuristic—a pattern derived from convergent but methodologically diverse evidence strands—characterized by initial emission reductions (0–2 years), mid-term rebound effects (2–5 years), and conditionally projected long-term optimization (5+ years). Second, geographical context creates 10–60× variation in outcomes; regions with high renewable electricity and water abundance achieve net benefits within 2–3 years, while fossil fuel-heavy, water-stressed regions may never reach net positive outcomes. Third, the rebound effect is predictable and manageable through strategic interventions. Our framework provides actionable deployment guidance, demonstrating that achieving AI’s net environmental benefits requires renewable energy infrastructure development before AI deployment, alternative cooling technologies, and policy frameworks incorporating temporal dynamics. Full article

Small extracellular vesicles (sEVs) derived from mesenchymal stem cells (MSCs) are emerging as potent acellular therapeutics; however, their rapid clearance hinders their clinical translation. To address this issue, 3D-bioprinted genipin-crosslinked gelatin (GECL) was engineered for human health. GECL hydrogels were functionalised with human umbilical cord MSC-derived sEVs (hUCMSC-sEVs) to create a bioactive wound-healing platform. These hydrogels demonstrated favourable physicochemical, mechanical, and biodegradable properties while providing an extracellular matrix (ECM)-mimetic environment conducive to tissue regeneration. MSCs were isolated from the umbilical cords, and their small extracellular vesicles (sEVs) were extracted and incorporated into gelatin-based hydrogels via 3D bioprinting. These sEV-loaded scaffolds were embedded in full-thickness wounds in mice, and healing was evaluated through macroscopic observation, histological analysis, collagen deposition, and angiogenesis assessment. Compared with the untreated controls, both the hydrogel-only (B) and sEV-loaded hydrogel (BE) groups significantly accelerated in vivo wound healing. Notably, the BE group achieved complete wound closure within 14 days, restoring the skin architecture, which closely resembled the native tissue with well-organised epidermal and dermal layers, optimal thickness, and skin appendages. Histological and ultrastructural assessments revealed an increased collagen type I deposition, a reduced α-smooth muscle actin (α-SMA) expression, and a robust neovascularisation. The TEM revealed tight junctions and active cellular infiltration, indicating scaffold integration and functional remodelling. Immunohistochemistry further revealed an upregulated CD31 expression with a balanced α-smooth muscle actin (α-SMA) expression, reflecting coordinated angiogenesis and myofibroblast regulation. These results highlight sEV-functionalised GECL hydrogels as robust and clinically translatable acellular therapeutic green products for accelerated wound closure and functional skin regeneration, advancing the fields of regenerative medicine and life expectancy. Full article