Search Results (30,605)

This study focuses on the optimization of modern extraction techniques for selected by-product materials, including apple, lemon, and tangerine peels, and onion skins, using artificial neural network (ANN) models. The extraction methods included ultrasound-assisted extraction (UAE) and microwave-assisted extraction (MAE) with water as the extractant, as well as maceration (MAC) with natural deep eutectic solvents (NADES). Key parameters, such as total phenolic content (TPC), total flavonoid content (TFC), and antioxidant activities, including reducing power (EC₅₀) and free radical scavenging capacity (IC₅₀), were evaluated to compare the efficiency of each method. Among the techniques, UAE outperformed both MAE and MAC in extracting bioactive compounds, especially from onion skins and tangerine peels, as reflected in the highest TPC, TFC, and antioxidant activity. UAE of onion skins showed the best performance, yielding the highest TPC (5.735 ± 0.558 mg CAE/g) and TFC (1.973 ± 0.112 mg RE/g), along with the strongest antioxidant activity (EC₅₀ = 0.549 ± 0.076 mg/mL; IC₅₀ = 0.108 ± 0.049 mg/mL). Tangerine peel extracts obtained by UAE also exhibited high phenolic content (TPC up to 5.399 ± 0.325 mg CAE/g) and strong radical scavenging activity (IC₅₀ 0.118 ± 0.099 mg/mL). ANN models using multilayer perceptron architectures with high coefficients of determination (r² > 0.96) were developed to predict and optimize the extraction results. Sensitivity and error analyses confirmed the robustness of the models and emphasized the influence of the extraction technique and by-product type on the antioxidant parameters. Principal component and cluster analyses showed clear grouping patterns by extraction method, with UAE and MAE showing similar performance profiles. Overall, these results underline the potential of UAE- and ANN-based modeling for the optimal utilization of agricultural by-products. Full article

Firstly, based on one-dimensional Terzaghi consolidation theory, we derived and established the analytical solution of excess pore water pressure and average consolidation degree of double-layered foundation, which can reflect the effect of fiber reinforcement. Meanwhile, the one-dimensional consolidation test of a double-layered foundation was carried out by means of a modified WG-type (product series code) consolidation instrument. The accuracy of the theoretical solution was verified by designing different consolidation parameters of the basalt fiber-reinforced solidified lightweight soil (BF-SLS) layer. Secondly, our findings suggest that the settlement rate of the double-layered foundation decreased with the increase in thickness, compression modulus and fiber mixing ratio of the BF-SLS layer. Nevertheless, the average pore pressure dissipation rate changed in the opposite trend. Both increased with increasing permeability coefficient of the BF-SLS layer. Within the thickness ratio range of 0 to 1/2 between the upper and lower layers, the thickness of the BF-SLS layer significantly influenced the consolidation process of the double-layer foundation. At equivalent T_v levels, the difference in consolidation degree exceeded 60%. Finally, a comparison of various simplified methods for calculating the average consolidation degree of double-layer foundations reveals that neither the weighted consolidation coefficient method nor the average index method yields results that are in good agreement with theoretical solutions. The difference between U_s (defined by sedimentation) and U_p (defined by pore pressure) cannot be distinguished. This research can further refine the consolidation theory of “upper hard and lower soft” double-layer foundations. Full article

The current work focuses on the study of the long-term evaluation of wind potential and energy production for a specific wind farm siting position over a mountainous region in Hellas. It aims to calculate the probability of exceedance of the twenty-year normalized average annual net production of the wind farm based on ground wind measurements coupled with Copernicus ERA5 data via a measure–correlate–predict (MCP) method. The study proposes an integrated long-term wind resource assessment workflow that couples short-term mast data with a twenty-year ERA5 record via a refined MCP procedure including temporal shifting for complex terrain. It introduces a practical uncertainty framework that jointly treats measurement, MCP, and terrain effects through dRIX and propagates these to energy yield using a bin-wise power curve and Weibull weighting. The proposed methodology is both fast and readily available to end-users and provides a realistic estimate of the energy production and long-term wind distribution in the investigated area. The data and assumptions employed in the calculations are given in detail. The uncertainty of the parameters in the estimation of the wind potential of the broader area and the energy calculation is analyzed. The results of the calculations and the probability of exceedance curve of the normalized twenty-year average annual net production of the wind farm summarize all uncertainty sources, delivering bankable long-term energy projections for the specific case study. Full article

Estimating biomass burning emissions remains challenging due to both the substantial spatiotemporal variability of fires and the inherent uncertainties associated with the limited overpass frequency of polar-orbiting satellites. Integrating geostationary (5–10 min, 2 km) and polar-orbiting (twice daily, 375 m) satellite observations provides a detailed characterization of active fire diurnal cycles. However, the conventional unimodal Gaussian approximation (Pol/Geo-Uni), commonly used in fire emission models, fails to accurately reproduce the diurnal patterns. This study systematically analyzed the seasonal and diurnal variation in different types of active fires (AFs) and fire radiative power (FRP) across North America (GOES-16, ABI) and East Asia (Himawari-8, AHI). In North America, forest and savanna fires exhibited high FRP and a pronounced bimodal diurnal cycle lasting 4–8 h, whereas the corresponding fire types in East Asia exhibited a shorter, unimodal pattern of 2–4 h. Agricultural fires in East Asia were predominantly small in scale with low FRP, and frequently occurred at night. We used a modified Gaussian function to estimate dry matter burned (DMB), quantitating regional emission impacts for different fire types. The fused product (VIIRS/ABI-Bi) yielded amounts of DMB in North America that was 1.22 and 1.24 times higher than that from VIIRS/ABI-Uni and GFASv1.2, respectively. In East Asia, VIIRS/AHI-Bi DMB exceeded those from VIIRS/AHI-Uni and GFASv1.2 by 1.08 and 0.94 times, with agricultural fire estimates during the fire season being 1.18–1.62 times higher. This increase was notably pronounced in eastern China, where VIIRS/AHI-Bi DMB reached 1.76 to 9.77 times higher than estimates from VIIRS/AHI-Uni, GFED5, GFED4.1s, and GFASv1.2. Overall, integrating high spatiotemporal resolution satellite fire products with regionally diurnal models can substantially improve emission estimates, particularly for frequent, small-scale fire events. Full article

The growing global demand for food and energy requires land-use strategies that support agricultural production and renewable energy generation. Agrivoltaic (APV) systems allow farmland to be used for both agriculture and solar power generation. The aim of this study is to critically synthesize the interactions between the key dimensions of APV implementation—technical, agronomic, legal, and economic—in order to create a multidimensional framework for designing an APV optimization model. The analysis covers APV system topologies, appropriate types of photovoltaic modules, installation geometry, shading conditions, and micro-environmental impacts. The paper categorizes quantitative indicators and critical thresholds that define trade-offs between energy production and crop yields, including a discussion of shade-tolerant crops (such as lettuce, clover, grapevines, and hops) that are most compatible with APV. Quantitative aspects were integrated in detail through a review of mathematical approaches used to predict yields (including exponential-linear, logistic, Gompertz, and GENECROP models). These models are key to quantitatively assessing the impact of photovoltaic modules on the light balance, thus enabling the simultaneous estimation of energy efficiency and yields. Technical solutions that enhance synthesis, such as dynamic tracking systems, which can increase energy production by up to 25–30% while optimizing light availability for crops, are also discussed. Additionally, the study examines regional legal frameworks and the economic factors influencing APV deployment, highlighting key challenges such as land use classification, grid connection limitations, investment costs and the absence of harmonised APV policies in many countries. It has been shown that APV systems can increase water retention, mitigate wind erosion, strengthen crop resilience to extreme weather conditions, and reduce the levelized cost of electricity (LCOE) compared to small rooftop PV systems. A key contribution of the work is the creation of a coherent analytical design framework that integrates technical, agronomic, legal and economic requirements as the most important input parameters for the APV system optimization model. This indicates that wider implementation of APV requires clear regulatory definitions, standardized design criteria, and dedicated support mechanisms. Full article

Mineral composition modulates plant health, agro-morphological attributes, and functional quality in coffee, yet large-scale evaluations remain limited. In 150 Coffea arabica L. accessions, we quantified grain minerals (Ca, K, Mg, Na, P, Zn, Cu, Fe, Mn); resistance to coffee leaf miner (CLM), coffee berry borer (CBB), and coffee leaf rust (CLR); agro-morphological traits; bioactive compounds (phenolics, flavonoids, chlorogenic acid, trigonelline, caffeine); and antioxidant capacity (ABTS, DPPH, FRAP). Mn and Zn were associated with greater resistance to CBB and CLM, whereas P and Ca related with lower susceptibility to CLR; a P–Zn antagonism emerged as a critical nutritional axis. Phosphorus was linked to larger size and higher 100-bean mass; Ca and Mg to greater fruit number and fruit mass per plant; and Fe to improved filling and higher 100-bean mass in parchment coffee. For bioactive compounds, P and K were positively associated with total phenolics, total flavonoids, caffeine, and ABTS/FRAP antioxidant activity, while trigonelline and chlorogenic acid correlated positively with the micronutrients Zn, Cu, and Fe. Cluster analysis resolved groups associated with resistance, Zn/Fe biofortification, productivity, and functional quality. PER1002287, PER1002216, PER1002207, and PER1002197 emerged as promising accessions balancing plant health, yield, and phytochemical quality. Overall, grain mineral composition is linked to plant health, productivity, and functional quality in coffee, providing a foundation for precision nutrient management and breeding programs aimed at resilient and high–value-added coffee. Full article

In this study, we aimed to investigate the potential of utilizing red grape pomace as a source of polyphenolic compounds in the growing, fragmented winemaking sector in Poland. For polyphenol extraction, we compared two methods: conventional extraction using water and alcohol solutions, and the supercritical CO₂ technique with ethanol as a cosolvent. The conventional method yielded at least 30% more polyphenols compared to the advanced SC-CO₂ technique. Experimentally chosen conditions, including a solvent composition of ethanol–water (1:1; v/v) containing 3% HCl, a liquid-to-solid ratio of 25:1 mL/g, and 2 min of ultrasound pretreatment and conventional extraction at a temperature of 30 °C over 4.5 h, enabled an extraction efficiency of 101 mg of total polyphenols per 1 g of raw material used, with an antioxidant capacity equivalent to 600 µmol of Trolox. According to HPLC analyses, the main components of the investigated biomass were epicatechin, anthocyanins and p-coumaric acid. The extract was encapsulated in liposomes, revealing no negative effect on their stability or aggregation under the conditions tested (21 days). The study suggests that conventional water–ethanol extraction can be a relatively safe and effective method for managing winemaking residuals, increasing the competitiveness of small producers through the production of high-value antioxidant additives. Full article

(1) Background: Oat (Avena sativa L.) is a crop that is widely used in human nutrition, while it also plays an important role in animal husbandry as a high-quality forage crop. However, this crop is particularly susceptible to combined biotic stressors, including insect pests (Agriotes lineatus) and fungal infections (Fusarium spp.). These stresses act synergistically: root damage caused by wireworms increases the plant’s susceptibility to fungal infection, while pathogens further limit nutrient uptake and root system development. In recent years, the reduced efficacy of chemical pesticides against both insect pests and fungal pathogens has highlighted the need for alternative strategies in oat protection, leading to an increased focus on developing bacterial bio-inoculants as sustainable and effective biocontrol agents. (2) Methods: This study aimed to identify bacterial strains capable of suppressing wireworms (Agriotes lineatus) and Fusarium spp. in oats, while simultaneously promoting plant growth. Bacterial isolates were screened for key Plant Growth Promoting (PGP) and biocontrol traits, including IAA and siderophore production, phosphate solubilization, and the presence of toxin- and antibiotic-coding genes. (3) Results: The highest insecticidal effect against wireworms was recorded for Bacillus velezensis BHC 3.1 (63.33%), while this isolate also suppressed the growth of F. proliferatum for 59%, F. oxysporum for 65%, F. poae for 71%, and F. graminearum for 15%. The most effective Bacillus strains (with insecticidal and antifungal activity) were identified and tested in two pot experiments, where their ability to enhance plant growth in the presence of insects and fungi was evaluated under semi-controlled conditions. An increase in plant biomass, grain yield, and nitrogen content was observed in oat inoculated with B. velezensis BHC 3.1 and B. thuringiensis BHC 2.4. (4) Conclusions: These results demonstrate the strong potential of both strains as multifunctional bio-inoculants for enhancing oat growth and mitigating the adverse effects of wireworm damage and Fusarium infection. Full article

A strategy for constructing trifluoromethylated spiroisoxazolones has been developed. This approach relies on the 1,3-dipolar cycloaddition of CF₃-substituted nitrile imines, generated in situ from trifluoroacetyl hydrazonoyl bromides and K₂CO₃, with the exocyclic double bond of 4-benzylidene-3-methylisoxazol-5(4H)-ones. The reaction provides a series of trifluoromethylated spiro(isoxazolone-pyrazoline) derivatives in moderate to high yields (up to 93%). The protocol exhibits broad substrate compatibility with respect to aromatic substituents on both reaction partners. To the best of our knowledge, the introduction of a trifluoromethyl group at the 3-position of the pyrazoline ring via nitrile imine cycloaddition chemistry has not been previously reported. The resulting products incorporate a valuable CF₃-substituted pyrazoline pharmacophore spiro-fused to an isoxazolone core and may be of interest for medicinal chemistry programs. Full article

Citrus species develop fruits through both sexual reproduction and parthenocarpy, following a growth pattern with an initial exponential phase dominated by cell division in the ovary wall, followed by a linear phase driven by cell expansion in juice vesicles. Sustained carbohydrate supply is essential to support the metabolic energy required for these processes, which are tightly regulated by hormonal signaling pathways involving gibberellins (GAs), auxins (IAA), cytokinins, and abscisic acid (ABA). Recent studies across cultivars have identified genes associated with hormone biosynthesis, carbohydrate metabolism, cell cycle regulation, and abscission in ovule and pericarp tissues. Manipulation of these hormones through targeted treatments and cultural practices has shown potential to enhance fruit set and growth. Notably, exogenous GA₃ application promotes fruit set in parthenocarpic cultivars by upregulating GA20ox2/GA3ox and CYCA1.1, whereas synthetic auxins enhance fruit enlargement by improving assimilate partitioning and water uptake. Optimizing such treatments, however, requires a comprehensive understanding of physiological, environmental, and agronomic factors influencing fruit development. This review summarizes recent advances in hormonal and molecular regulation of citrus fruit set and developments, assesses applied strategies to improve productivity, and identifies current knowledge gaps needed to refine biotechnological and management aimed at enhancing both yield and fruit quality. Full article

Forest fine root litter enters agricultural soils in some cases and its decomposition would change the soil’s properties. However, how this process further influences the ammonia (NH₃) volatilization and nitrous oxide (N₂O) emission from agricultural soil receiving fertilizer nitrogen (N) is unknown. Here, we conducted a soil pot experiment to investigate the responses of the aforementioned gaseous N losses during wheat season to fine root litters derived from Populus deltoides (RP) and Metasequoia glyptostroboides (RM) incorporations. The results showed that two forest fine root litters reduced total NH₃ losses by 30.6−31.9% from 180 kg N ha⁻¹ applied to farmland soil, and this effect was attributed to decreased soil urease activity and ammonium-N during the basal N fertilization period. Whether receiving fertilizer N or not, N₂O emissions from farmland soil were significantly (p < 0.05) mitigated by 62.8–68.2% and 43.0−50.0% following the RP and RM incorporation, respectively. Lower N₂O emission was ascribed to increased soil pH but decreased soil nitrate-N and bulk density. In addition, less AOA and AOB amoA but more nosZ gene abundances explained the fine root litter-induced N₂O mitigation effect. Neither forest fine root litter exerted a negative effect on wheat grain yield and crop N use efficiency in N-added agriculture soil. In conclusion, forest fine root litter incorporation could help to mitigate gaseous N losses via NH₃ volatilization and N₂O emission from fertilizer-N-applied agricultural soils, and without crop production loss. Full article

Climate change induces widespread effects on crop production, influencing multiple developmental stages and associated agronomic outcomes. Using long-term meteorological data from Jilin Province, Northeast China, this study examined temporal and spatial variations in climatic conditions through trend analysis, Mann–Kendall tests, and inverse distance weighting interpolation. A fuzzy comprehensive evaluation model was applied to classify maize cultivation suitability into four levels across major production areas, with Level I representing the most suitable regions, Level II highly suitable regions, Level III moderately suitable regions, and Level IV low suitable regions. Changes in suitable areas were analyzed before and after abrupt climatic shifts. From 1976 to 2020, Jilin Province experienced a significant rise in annual mean temperature, a marked decline in sunshine duration, and a slight increase in precipitation. The area of Level I suitability remained stable, while Level II expanded to approximately 1.3 times its original area. Conversely, Level III and IV areas decreased by 4.59% and 28.77%, respectively, compared with the pre-transition period. Spatially, the most suitable maize cultivation areas shifted from central to northern and eastern Jilin due to climatic warming. Although rising temperatures enhanced thermal conditions for maize production, reduced sunshine and variable precipitation constrained further expansion. These findings provide a scientific basis for optimizing maize variety selection and cropping structure in high-latitude regions, supporting yield improvement and sustainable development of the maize industry under a changing climate. Full article

Screening of suitable yeast strains is essential for high-quality fruit wine production. In this study, twelve Saccharomyces and non-Saccharomyces yeasts were evaluated for their performance in fermenting peach wines. Results showed that all strains completed alcoholic fermentation and produced ethanol levels within the typical range for fruit wines. Saccharomyces strains had higher ethanol production ability. Non-Saccharomyces yeast-fermented peach wines showed higher sugar-free extract and acidity. Fermentation by different yeast strains resulted in diverse characteristics of phenolic and volatile profiles in peach wines. The peach wine fermented by S. cerevisiae strain EC1118 was characterized by improved color parameters and higher antioxidant capacity. The non-Saccharomyces yeasts tended to produce more esters than alcohols. The Saccharomyces strains favored the production of alcohols more than esters. P. fermentans 33372 yielded a higher level of ethyl esters. I. orientalis 31-129 produced higher levels of isoeugenol, linalool, and β-damascenone. Overall, non-Saccharomyces yeast strains appeared more promising for use on their own or in co-fermentation with S. cerevisiae strains to produce peach wines with a higher level of volatile organic compounds. Full article

Isabella grape pomace (IGP) the primary by-product of Colombia’s winemaking industry, represents a promising source of nutraceuticals with potential uses in the food industry. This study developed a sequential green extraction process to recover nutraceutical from IGP. The approach integrated supercritical fluid extraction with CO₂ (SFE-CO₂) to obtain lipophilic compounds, followed by SFE with ethanol/water as co-solvent (SFE-CO₂/EtOH:H₂O) for medium-polarity phenolics, and pressurized liquid extraction (PLE) with EtOH:H₂O to recover the polar phenolic-rich fraction. The extraction parameters were optimized using response surface methodology, and optimal conditions were identified: SFE-CO₂ at 31.7 MPa/58.9 °C yielded 6.95% extract rich in linoleic acid (65.5%) and α-tocopherol (107.2 mg/kg); SFE-CO₂/EtOH:H₂O with 15% of co-solvent produced extracts with high phenolic content (105.35 mg GAE/g) and antioxidant activity (0.18 mmol TE/g); while PLE at 58.91% of EtOH/107.98 °C achieved notable recovery of flavonoids (757.18 mg QE/g), anthocyanins(1508 μg MAE/g) and condensed tannins (258.39 mg ECE/g), with potent antioxidant capacity (130.40 mmol TE/g). The sequential process demonstrated synergistic effects, with a total cumulative yield of 41.08% and phenolic recovery of 349.89 mg GAE/g extract. This approach offers a sustainable biorefinery approach for transforming IGP into high-value nutraceutical ingredients. Full article

The efficiencies of additive manufacturing (AM) over conventional processes have enabled the rapid production of aluminum (Al) alloys with AM. Because laser beam powder bed fusion (LB-PBF) parts do not offer the surface quality and geometrical accuracy for direct use, the functional surfaces of LB-PBF parts are usually machined by subtractive machining. The machinability of LB-PBF AlSi10Mg was studied in dry, MQL (used corn oil), and cryo-LN₂ cutting environments across distinct speed–feed combinations using CVD-AlTiN-coated carbide inserts, and surface integrity and tool life were quantified in terms of surface roughness (Ra) and flank wear (Vb), respectively. The lowest Ra (0.98–1.107 μm) was obtained with cryo-LN₂, followed by MQL and dry cutting environments, because the trends observed were consistent with the surface mechanisms observed in 3D topography and bearing curves. Similarly, the tool wear results mirrored the Ra results, lowest with LN₂ (0.087–0.110 mm), due to improved thermal management, reduced adhesion and abrasion, and shorter contact length. Cryo-LN₂ provided the best surface finish and tool life among all tested environments. To enable data-driven prediction, the limited dataset was augmented using SMOTE, and machine learning (ML) models were trained to predict Ra and Vb. CatBoost was found to yield the best Ra predictions (R² = 0.9090), while Random Forest and XGBoost yielded the best Vb predictions (R² ≈ 0.878). Full article