Search Results (7,808)

This study explores the revival of cotton (Gossypium spp. L.) farming in Italy through sustainable practices, addressing economic and water-related challenges by integrating cultivar selection, arbuscular mycorrhizal fungi (AMF) inoculation, and deficit irrigation under organic farming. Field trials evaluated two widely grown Mediterranean cultivars (Armonia and ST-318) under three irrigation levels (I-100: 100% crop water requirement; I-70: 70%; I-30: 30%) across two Sicilian soil types (sandy loam vs. clay-rich). Under I-100, lint yields reached 0.99 t ha⁻¹, while severe deficit (I-30) yielded only 0.40 t ha⁻¹. However, moderate deficit (I-70) maintained 75–79% of full yields, proving a viable strategy. AMF inoculation significantly enhanced plant height (68.52 cm vs. 65.85 cm), boll number (+22.1%), and seed yield (+12.5%) (p < 0.001). Cultivar responses differed: Armonia performed better under water stress, while ST-318 thrived with full irrigation. Site 1, with higher organic matter, required 31–38% less water and achieved superior irrigation water productivity (1.43 kg m⁻³). Water stress also shortened phenological stages, allowing earlier harvests—important for avoiding autumn rains. These results highlight the potential of combining adaptive irrigation, resilient cultivars, and AMF to restore sustainable cotton production in the Mediterranean, emphasizing the importance of soil-specific management. Full article

Foodborne illness caused by bacterial pathogens is a global health concern and results in millions of infections annually. Therefore, food products typically undergo several processing stages, including sanitation steps, before being distributed in an attempt to remove pathogens. However, many sanitation methods have compounding effects on the color, texture, flavor, and nutritional quality of the product or do not effectively reduce the pathogens that food can be exposed to. Some bacterial pathogens particularly possess traits and tactics that make them even more difficult to mitigate such as biofilm formation. Non-thermal plasma sanitation techniques, including plasma-treated water (PTW), have proven to be promising methods that significantly reduce pathogenic bacteria that food is exposed to. Published work reveals that PTW can effectively mitigate both gram-positive and gram-negative bacterial biofilms. This study presents a novel analysis of the differences in antimicrobial effects of PTW treatment between biofilm-forming gram-positive bacteria, commonly associated with foodborne illness, that are sporulating (Bacillus cereus) and non-sporulating (Listeria monocytogenes). After treatment with PTW, the results suggest the following hypotheses: (1) that the non-sporulating species experiences less membrane damage but a greater reduction in metabolic activity, leading to a possible viable but non-culturable (VBNC) state, and (2) that the sporulating species undergoes spore formation, which may subsequently convert into vegetative cells over time. PTW treatment on gram-positive bacterial biofilms that persist in food processing environments proves to be effective in reducing the proliferating abilities of the bacteria. However, the variance in PTW’s effects on metabolic activity and cell vitality between sporulating and non-sporulating species suggest that other survival tactics might be induced. This analysis further informs the application of PTW in food processing as an effective sanitation method. Full article

This study presents a comprehensive design, optimization, and intensification approach for enhancing the energy efficiency of electric grade isopropyl alcohol (IPA) production, a typical energy-intensive chemical process. The process entails preconcentration and dehydration steps, with the intensity of separation formulated from a multicomponent feed that consists of IPA and water, along with other impurities. Modeling and energy optimization were performed for a conventional distillation train as a base case by using the rigorous process simulator Aspen Plus V12.1. To improve energy efficiency, various options for intensifying distillation were examined. The side-stream preconcentration column was subsequently replaced by a dividing wall column (DWC) with two side streams, i.e., a Kaibel column, reducing the total energy consumption of corresponding distillation columns by 9.1% compared to the base case. Further strengthening was achieved by combining two columns in the preconcentration process into a single Kaibel column, resulting in a 22.8% reduction in reboiler duty compared to the base case. Optimization using the response surface methodology identified key operating parameters, such as side-draw positions and stage design, which significantly influence both energy efficiency and separation quality. The intensified Kaibel setup offers significant energy efficiencies and simplified column design, suggesting enormous potential for process intensification in energy-intensive distillation processes at the industrial level, including the IPA purification process. Full article

Temperature is a key physiological indicator of plant health, influenced by factors including water status, disease and developmental stage. Monitoring changes in multiple factors is helpful for early diagnosis of plant growth. However, there are a variety of complex light interference phenomena in the greenhouse, so traditional detection methods cannot meet effective online monitoring of strawberry health status without manual intervention. Therefore, this paper proposes a leaf soft-sensing method based on a thermal infrared imaging sensor and adaptive image screening Internet of Things system, with additional sensors to realize indirect and rapid monitoring of the health status of a large range of strawberries. Firstly, a fuzzy comprehensive evaluation model is established by analyzing the environmental interference terms from the other sensors. Secondly, through the relationship between plant physiological metabolism and canopy temperature, a growth model is established to predict the growth period of strawberries based on canopy temperature. Finally, by deploying environmental sensors and solar height sensors, the image acquisition node is activated when the environmental interference is less than the specified value and the acquisition is completed. The results showed that the accuracy of this multiple sensors system was 86.9%, which is 30% higher than the traditional model and 4.28% higher than the latest advanced model. It makes it possible to quickly and accurately assess the health status of plants by a single factor without in-person manual intervention, and provides an important indication of the early, undetectable state of strawberry disease, based on remote operation. Full article

Studying the impact of different tillage practices on crop water consumption can help us identify optimal tillage practice choices. The traditional tillage (TT) and conservation tillage (CT) methods are the dominant practices in Jilin Province, China. Few studies have explored the differences in crop water consumption between TT and CT. To address this knowledge gap, this study utilized maize as its research object and employed the water footprint (WF) as the indicator to assess crop water consumption under TT and CT. This study aimed to investigate when differences in water consumption between TT and CT appear and whether the differences are significant. The results of this study demonstrated that the total WF under CT (339.65 m³ t⁻¹) was less than that under TT (378.19 m³ t⁻¹), and the spatial difference was distinct. The total WF exhibited a clear change under different CT durations. At the initial stage of CT implementation, the total WF decreased slightly compared to that under TT. With an increase in CT duration, the total WF was significantly reduced. The findings of this study demonstrate that CT is an effective measure to ensure sustainable crop production and that it could lead policymakers to choose CT to reduce water consumption. Full article

Shandong Province is rich in geothermal resources, mainly stored in sandstone reservoirs. The setting of reasonable well spacing in the early stage of large-scale recharge has not attracted enough attention. The problem of small well spacing in geothermal engineering is particularly prominent in the sandstone thermal reservoir production area represented by Dezhou. Based on the measured data of temperature, flow, and water level, this paper constructs a typical engineering numerical model by using TOUGH2 software. It is found that when the distance between production and recharge wells is 180 m, the amount of production and recharge is 60 m³/h, and the temperature of reinjection is 30 °C, the temperature of the production well will decrease rapidly after 10 years of production and recharge. In order to solve the problem of thermal breakthrough, three optimization schemes are assumed: reducing the reinjection temperature to reduce the amount of re-injection when the amount of heat is the same, reducing the amount of production and injection when the temperature of production and injection is constant, and stopping production after the temperature of the production well decreases. However, the results show that the three schemes cannot solve the problem of thermal breakthrough or meet production demand. Therefore, it is necessary to set reasonable well spacing. Therefore, based on the strata near the Hydrological Homeland in Decheng District, the reasonable spacing of production and recharge wells is achieved by numerical simulation. Under a volumetric flux scenario ranging from 60 to 80 m³/h, the well spacing should exceed 400 m. For a volumetric flux between 80 and 140 m³/h, it is recommended that the well spacing be greater than 600 m. Full article

As a typical porous medium, unsaturated loess demonstrates critical hydro-mechanical coupling properties that fundamentally influence geohazard mitigation, groundwater resource evaluation, and foundation stability in geotechnical engineering. This investigation develops a novel theoretical framework to overcome the limitations of existing models in converting electrical resistivity tomography (ERT) profiles into water content distributions for unsaturated loess through quantitative inversion modeling. Systematic laboratory investigations on remolded loess specimens with controlled density and water content conditions revealed distinct resistivity–water interaction mechanisms. A characteristic two-stage decay pattern was identified: resistivity exhibited an exponential decrease from 420 Ω·m (water saturation (S_w = 10%)) to 90 Ω·m (S_w = 40%), followed by asymptotic stabilization at S_w ≥ 40%. The derived quantitative correlation provides a robust mathematical basis for water content profile inversion. Field validation through integrated ERT and borehole data demonstrated exceptional predictive accuracy in shallow strata (<20 m depth), achieving mean absolute errors of <5%. However, inversion reliability decreased with depth (>20 m), primarily attributed to density-dependent charge transport mechanisms. This underscores the necessity of incorporating coupled thermo-hydro-mechanical processes for deep-layer characterization. This study provides a robust framework for engineering applications of ERT in loess terrains, offering significant advancements in geotechnical monitoring and geohazard prevention. Full article

With the increasing awareness of energy consumption issues, there has been a growing emphasis on energy-saving retrofits for central air-conditioning systems that constitute a significant proportion of energy consumption in buildings. Efficient energy utilization can be achieved by optimizing the modeling of the equipment within the chiller plants of central air-conditioning systems. Traditional modeling approaches have been static and have focused on modeling within narrow time frames when a certain amount of equipment operating data has accumulated, thus prioritizing the precision of the model itself while overlooking the fact that energy-saving retrofits are a long-term process. This study proposes a modeling scheme for the equipment within chiller plants throughout the energy-saving retrofit process. Based on the differences in the amount of available operating data for the equipment and the progress of retrofit implementation, the retrofit process was divided into three stages, each employing different modeling techniques and ensuring smooth transitions between the stages. The equipment within the chiller plants is categorized into two types based on the clarity of their operating characteristics, and two modeling schemes are proposed accordingly. Based on the proposed modeling scheme, chillers and chilled-water pumps were selected to represent the two types of equipment. Real operating data from actual retrofit projects was used to model the equipment and evaluate the accuracy of the model predictions. The results indicate that the models established by the proposed modeling scheme exhibit good accuracy at each stage of the retrofit, with the coefficients of variation (CV) remaining below 6.88%. Furthermore, the prediction accuracy improved as the retrofitting process progressed. The modeling scheme performs better on equipment with simpler and clearer operating characteristics, with a CV as low as 0.67% during normal operation stages. This underscores the potential application of the proposed modeling scheme throughout the energy-saving retrofit process and provides a model foundation for the subsequent optimization of the refrigeration system. Full article

This study develops an integrated environmental–economic assessment framework to evaluate the life cycle environmental impacts and economic costs of CO₂ geological storage and produced water treatment in saline formations in China. Using a case study of a saline aquifer carbon storage project in the Ordos Basin, eight full-chain carbon capture, utilization, and storage (CCUS) scenarios were analyzed. The results indicate that environmental and cost performance are primarily influenced by technology choices across carbon capture, transport, and storage stages. The scenario employing potassium carbonate-based capture, pipeline transport, and brine reinjection after a reverse osmosis treatment (S5) achieved the most balanced outcome. Breakeven analyses under three carbon price projection models revealed that carbon price trajectories critically affect project viability, with a steadily rising carbon price enabling earlier profitability. By decoupling CCUS from power systems and focusing on unit CO₂ removal, this study provides a transparent and transferable framework to support cross-sectoral deployment. The findings offer valuable insights for policymakers aiming to design effective CCUS support mechanisms under future carbon neutrality targets. Full article

Acacia mearnsii De Wild. has been introduced to over 150 countries for its economic value. However, it easily escapes from plantations and establishes monospecific stands across plains, hills, valleys, and riparian habitats, including protected areas such as national parks and forest reserves. Due to its negative ecological impact, A. mearnsii has been listed among the world’s 100 worst invasive alien species. This species exhibits rapid stem growth in its sapling stage and reaches reproductive maturity early. It produces a large quantity of long-lived seeds, establishing a substantial seed bank. A. mearnsii can grow in different environmental conditions and tolerates various adverse conditions, such as low temperatures and drought. Its invasive populations are unlikely to be seriously damaged by herbivores and pathogens. Additionally, A. mearnsii exhibits allelopathic activity, though its ecological significance remains unclear. These characteristics of A. mearnsii may contribute to its expansion in introduced ranges. The presence of A. mearnsii affects abiotic processes in ecosystems by reducing water availability, increasing the risk of soil erosion and flooding, altering soil chemical composition, and obstructing solar light irradiation. The invasion negatively affects biotic processes as well, reducing the diversity and abundance of native plants and arthropods, including protective species. Eradicating invasive populations of A. mearnsii requires an integrated, long-term management approach based on an understanding of its invasive mechanisms. Early detection of invasive populations and the promotion of public awareness about their impact are also important. More attention must be given to its invasive traits because it easily escapes from cultivation. Full article

Flavonoids serve as crucial plant antioxidants in drought tolerance, yet their antioxidant regulatory mechanisms within mycorrhizal plants remain unclear. In this study, using a two-factor design, trifoliate orange (Poncirus trifoliata (L.) Raf.) seedlings in the four-to-five-leaf stage were either inoculated with Funneliformis mosseae or not, and subjected to well-watered (70–75% of field maximum water-holding capacity) or drought stress (50–55% field maximum water-holding capacity) conditions for 10 weeks. Plant growth performance, photosynthetic physiology, leaf flavonoid content and their antioxidant capacity, reactive oxygen species levels, and activities and gene expression of key flavonoid biosynthesis enzymes were analyzed. Although drought stress significantly reduced root colonization and soil hyphal length, inoculation with F. mosseae consistently enhanced the biomass of leaves, stems, and roots, as well as root surface area and diameter, irrespective of soil moisture. Despite drought suppressing photosynthesis in mycorrhizal plants, F. mosseae substantially improved photosynthetic capacity (measured via gas exchange) and optimized photochemical efficiency (assessed by chlorophyll fluorescence) while reducing non-photochemical quenching (heat dissipation). Inoculation with F. mosseae elevated the total flavonoid content in leaves by 46.67% (well-watered) and 14.04% (drought), accompanied by significantly enhanced activities of key synthases such as phenylalanine ammonia-lyase (PAL), chalcone synthase (CHS), chalcone isomerase (CHI), 4-coumarate:coA ligase (4CL), and cinnamate 4-hydroxylase (C4H), with increases ranging from 16.90 to 117.42% under drought. Quantitative real-time PCR revealed that both mycorrhization and drought upregulated the expression of PtPAL1, PtCHI, and Pt4CL genes, with soil moisture critically modulating mycorrhizal regulatory effects. In vitro assays showed that flavonoid extracts scavenged radicals at rates of 30.07–41.60% in hydroxyl radical (•OH), 71.89–78.06% in superoxide radical anion (O₂^•−), and 49.97–74.75% in 2,2-diphenyl-1-picrylhydrazyl (DPPH). Mycorrhizal symbiosis enhanced the antioxidant capacity of flavonoids, resulting in higher scavenging rates of •OH (19.07%), O₂^•− (5.00%), and DPPH (31.81%) under drought. Inoculated plants displayed reduced hydrogen peroxide (19.77%), O₂^•− (23.90%), and malondialdehyde (17.36%) levels. This study concludes that mycorrhizae promote the level of total flavonoids in trifoliate orange by accelerating the flavonoid biosynthesis pathway, hence reducing oxidative damage under drought. Full article

Recently, essential rose oils and rose products have gained increasing importance in both the cosmetic and food industries, as well as in the composition of medicinal products. We investigated the in vitro antiviral activity of essential oil and floral water from Rosa damascena Mill against herpes simplex virus type 1 (HSV-1) infection in rabbit retinal cells (RRCs). The composition of the main chemical components in the rose essential oil was determined by means of gas chromatographic analysis. The effect on the viral replication cycle was determined using the cytopathic effect (CPE) inhibition assay. The virucidal activity, the effect on the adsorption stage of the virus to the host cell, and the protective effect on healthy cells were evaluated using the endpoint dilution method. The effects were determined as deviation in the viral titer, Δlg, for the treated cells from the one for the untreated viral control. The identified main active components of rose oil are geraniol (28.73%), citronellol (21.50%), nonadecane (13.13%), nerol (5.51%), heneicosane (4.87%), nonadecene (3.93), heptadecane (2.29), farnesol (2.11%), tricosane (1.29%), eicosane (1.01%), and eugenol (0.85%). The results demonstrated that both rose products do not have a significant effect on the virus replication but directly affect the viral particles and reduce the viral titer by Δlg = 3.25 for floral water and by Δlg = 3.0 for essential oil. Significant inhibition of the viral adsorption stage was also observed, leading to a decrease in the viral titers by Δlg = 2.25 for floral water and by Δlg = 2.0 for essential oil. When pretreating healthy cells with rose products, both samples significantly protected them from subsequent infection with HSV-1. This protective effect was more pronounced for the oil (Δlg = 2.5) compared to the one for the floral water (Δlg = 2.0). We used the in silico molecular docking method to gain insight into the mechanism of hindrance of viral adsorption by the main rose oil compounds (geraniol, citronellol, nerol). These components targeted the HSV-1 gD interaction surface with nectin-1 and HVEM (Herpesvirus Entry Mediator) host cell receptors, at N-, C-ends, and N-end, respectively. These findings could provide a structural framework for further development of anti-HSV-1 therapeutics. Full article

Concrete mix design plays a pivotal role in ensuring the mechanical performance, durability, and sustainability of construction projects. However, the nonlinear interactions among the mix components challenge traditional approaches in predicting compressive strength and optimizing proportions. This study presents a two-stage hybrid framework that integrates deep learning with reinforcement learning to overcome these limitations. First, a Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) model was developed to capture spatial–temporal patterns from a dataset of 1030 historical concrete samples. The extracted features were enhanced using an eXtreme Gradient Boosting (XGBoost) meta-model to improve generalizability and noise resistance. Then, a Dueling Double Deep Q-Network (Dueling DDQN) agent was used to iteratively identify optimal mix ratios that maximize the predicted compressive strength. The proposed framework outperformed ten benchmark models, achieving an MAE of 2.97, RMSE of 4.08, and R² of 0.94. Feature attribution methods—including SHapley Additive exPlanations (SHAP), Elasticity-Based Feature Importance (EFI), and Permutation Feature Importance (PFI)—highlighted the dominant influence of cement content and curing age, as well as revealing non-intuitive effects such as the compensatory role of superplasticizers in low-water mixtures. These findings demonstrate the potential of the proposed approach to support intelligent concrete mix design and real-time optimization in smart construction environments. Full article

Upon reaching stabilized production in waterflooded reservoirs, waterflood performance curves are conventionally used to predict technically recoverable reserves (TRRs). However, as reservoirs enter high water-cut stages, the relationship between the relative permeability ratio and saturation becomes nonlinear, causing deflection in waterflood performance curves. This leads to systematic overestimation of both predicted TRR and ultimate recovery factors. To overcome these limitations in conventional TRR prediction methods, this study establishes a novel relative permeability ratio-saturation relationship based on characteristic relative permeability curve behaviors. The proposed model is validated for three distinct fluid-rock interaction types. We further develop a permeability-driven forecasting model for oil production rates and water cuts. Comparative analyses with a conventional waterflood curve methodology demonstrate significant accuracy improvements. The results show that while traditional methods predict TRR ranging from 78.40 to 92.29 million tons, our model yields 70.73 million tons—effectively resolving overestimation issues caused by curve deflection during high water-cut phases. This approach establishes a robust framework for determining critical development parameters, including economic field lifespan, strategy adjustments, and ultimate recovery factor. Full article

Floating solar technology has gained significant attention as part of the global expansion of renewable energy due to its potential for installation in underutilized water bodies. Several countries, including the Netherlands, have initiated efforts to extend this technology from inland freshwater applications to open offshore environments, particularly within offshore wind farm areas. This development is motivated by the synergistic benefits of increasing site energy density and leveraging the existing offshore grid infrastructure. The deployment of offshore floating photovoltaic (OFPV) systems involves assembling multiple modular units in a marine environment, introducing operational risks that may give rise to safety concerns. To mitigate these risks, weather windows must be considered prior to the task execution to ensure continuity between weather-sensitive activities, which can also lead to additional time delays and increased costs. Consequently, optimizing marine logistics becomes crucial to achieving the cost reductions necessary for making OFPV technology economically viable. This study employs a simulation-based approach to estimate the installation duration of a 5 MWp OFPV plant at a Dutch offshore wind farm site, started in different months and under three distinct risk management scenarios. Based on 20 years of hindcast wave data, the results reveal the impacts of campaign start months and risk management policies on installation duration. Across all the scenarios, the installation duration during the autumn and winter period is 160% longer than the one in the spring and summer period. The average installation durations, based on results from 12 campaign start months, are 70, 80, and 130 days for the three risk management policies analyzed. The result variation highlights the additional time required to mitigate operational risks arising from potential discontinuity between highly interdependent tasks (e.g., offshore platform assembly and mooring). Additionally, it is found that the weather-induced delays are mainly associated with the campaigns of pre-laying anchors and platform and mooring line installation compared with the other campaigns. In conclusion, this study presents a logistics modeling methodology for OFPV systems, demonstrated through a representative case study based on a state-of-the-art truss-type design. The primary contribution lies in providing a framework to quantify the performance of OFPV installation strategies at an early design stage. The findings of this case study further highlight that marine installation logistics are highly sensitive to local marine conditions and the chosen installation strategy, and should be integrated early in the OFPV design process to help reduce the levelized cost of electricity. Full article