Search Results (16,967)

Soil water content (SWC) critically governs the physical and mechanical behavior of soils. However, conventional methods such as oven drying are laborious, time-consuming, and difficult to replicate in the field. To overcome these limitations, we developed an image-based interpolation framework that leverages histogram statistics from 12 soil surface photographs spanning 3.83% to 19.75% SWC under controlled lighting. For each image, pixel-level values of red, green, blue (RGB) channels and hue, saturation, value (HSV) channels were extracted to compute per-channel histograms, whose empirical means and standard deviations were used to parameterize Gaussian probability density functions. Linear interpolation of these parameters yielded synthetic histograms and corresponding images at 1% SWC increments across the 4–19% range. Validation against the original dataset, using dice score (DS), Bhattacharyya distance (BD), and Earth Mover’s Distance (EMD) metrics, demonstrated that the interpolated images closely matched observed color distributions. Average BD was below 0.014, DS above 0.885, and EMD below 0.015 for RGB channels. For HSV channels, average BD was below 0.074, DS above 0.746, and EMD below 0.022. These results indicate that the proposed method reliably generates intermediate SWC data without additional direct measurements, especially with RGB. By reducing reliance on exhaustive sampling and offering a cost-effective dataset augmentation, this approach facilitates large-scale, noninvasive soil moisture estimation and supports machine learning applications where field data are scarce. Full article

A smart irrigation system based on soil moisture sensors supported by photovoltaic energy is an innovation to address water use efficiency in the agricultural sector, especially in remote areas. This technology utilizes photovoltaic panels as a renewable energy source to operate water pumps, while soil moisture sensors provide real-time data that is used to automatically manage irrigation according to plant needs. This technology not only increases the efficiency of water and energy use but also supports environmental conservation by reducing dependence on fossil fuels. This research was conducted using a Systematic Literature Review (SLR) approach guided by the PRISMA framework to analyze trends, benefits, and challenges in implementing this technology. The analysis results show that this system offers various advantages, including energy efficiency, reduced carbon emissions, and ease of management through the integration of Internet of Things (IoT) technology. Several challenges remain, such as high initial investment costs, limited network access, and obstacles. Technical matters related to installation and maintenance. Various solutions have been proposed, including providing subsidies for small farmers, implementing radiofrequency modules, and using modular designs to simplify implementation. This study contributes to the development of a conceptual framework that can be adapted to various geographic and socio-economic conditions. Potential further developments include the integration of artificial intelligence and additional sensors to increase efficiency and support the sustainability of the agricultural sector globally. Full article

Soybean (Glycine max L.) is one of the world’s most important sources of plant-based protein, with a protein content exceeding 35–40% (dry basis), along with other essential nutritional benefits. Ideally, soybeans are field-dried to approximately 13% moisture content (wet basis, wb); however, adverse weather conditions can necessitate harvesting at elevated moisture levels sometimes exceeding 20% (wb). In such cases, mechanized drying systems, particularly in northern U.S. regions, become essential for safe storage and quality preservation. This study investigated the effects of drying temperature, airflow rate, and initial moisture content on drying kinetics and kernel integrity using mathematical modeling. Drying behavior was modeled using fractional calculus and compared to the empirical Page model, while kernel cracking and breakage were analyzed using logistic regression. Both fractional and Page models exhibited strong agreement with experimental data (R² = 0.903–0.993). The fractional model achieved superior predictive accuracy, improving RMSE and MAE by 83.7% and 81.2%, respectively, compared to the Page model. Cracking and breakage were more strongly influenced by drying temperature than by initial moisture content, with the greatest quality degradation occurring at high temperatures. Optimal drying conditions were identified as temperatures below 27 °C and initial moisture contents between 19 and 20% (wb), which best preserved kernel quality. Logistic models more accurately predicted breakage than cracking, confirming their effectiveness in assessing mechanical damage during drying. The results affirm the suitability of fractional order models for accurately capturing drying kinetics, while logistic models offer robust performance for evaluating physical quality degradation. These modeling approaches provide a framework for efficient and quality-preserving soybean drying strategies in regions reliant on off-field drying systems. Full article

Droughts are becoming more frequent, severe, and impactful across the globe. Agroecosystems, which are human-made ecosystems with high water demand that provide essential ecosystem services, are vulnerable to extreme droughts. Although water use efficiency in agriculture has increased in rec ent decades, drought management should be based on long-term, proactive strategies rather than crisis management. The AgrHyS network of sites in French Brittany collects high-resolution soil moisture data from agronomic stations and catchments to improve understanding of temporal soil moisture dynamics and enhance water use efficiency. Frequent mapping of soil moisture and plant water stress is crucial for assessing water stress risk in the context of global warming. Although satellite remote sensing provides reliable, periodic global data on surface soil moisture, it does so at a very coarse spatial resolution. The intrinsic spatial heterogeneity of surface soil moisture requires a higher spatial resolution in order to address upcoming challenges on a local scale. Drones are an excellent tool for upscaling point measurements to catchment level using different onboard cameras. In this study, we evaluated the potential of multispectral images, thermal images and LiDAR data captured in several concurrent drone flights for high-resolution mapping of soil moisture spatial variability, using in situ point measurements of soil water content and plant water stress in both agricultural areas and natural ecosystems. Statistical models were fitted to map soil water content in two areas: a natural marshland and a grassland-covered agricultural field. Our results demonstrate the statistical significance of topography, land surface temperature and red band reflectance in the natural area for retrieving soil water content. In contrast, the grasslands were best predicted by the transformed normalised difference vegetation index (TNDVI). Full article

A comprehensive overview is provided on factors and processes influencing the final quality of a cup of coffee, with an emphasis on the brewing method’s central role. Coffee quality assessment, both at the bean and cup level, combines objective parameters (color, moisture, bean defects, density) with a notable degree of subjectivity, as consumer sensory perception is ultimately decisive. The brewing technique is described as a critical determinant of the final chemical, physical, and sensory attributes. Key parameters such as aroma profile, pH, titratable acidity, total and filtered solids, lipid and fatty acid content, viscosity, foam (crema), and colorimetric indices are detailed as essential metrics in coffee quality evaluation. Roasting creates most of coffee’s key aroma compounds. The brewing method further shapes the extraction of both volatile and other bioactive compounds like caffeine, chlorogenic acids, and lipids. Brewing methods significantly affect acidity, “body,” and crema stability, while water quality, temperature, and pressure are shown to impact extraction results and sensory properties. Attention is paid to how methods such as Espresso, filter, French press, and cold brew yield distinct physicochemical and sensory profiles in the cup. Overall, the review highlights the multifaceted nature of coffee cup quality and the interplay between raw material, processing, and preparation, ultimately shaping the coffee sensory experience and market value. Full article

Given the complexity of near-surface soil moisture retrieval, a single machine learning algorithm often struggles to capture the intricate relationships among multiple features, resulting in limited generalization and robustness. To address this issue, this study proposes a multi-satellite fusion GNSS-IR soil moisture retrieval method based on heterogeneous ensemble machine learning models. Specifically, two heterogeneous ensemble learning strategies (Bagging and Stacking) are combined with three base learners, Back Propagation Neural Network (BPNN), Random Forest (RF), and Support Vector Machine (SVM), to construct eight ensemble GNSS-IR soil moisture retrieval models. The models are validated using data from GNSS stations P039, P041, and P043 within the Plate Boundary Observatory (PBO) network. Their retrieval performance is compared against that of individual machine learning models and a deep learning model (Multilayer Perceptron, MLP), enabling an optimized selection of algorithms and model architectures. Results show that the Stacking-based models significantly outperform those based on Bagging in terms of retrieval accuracy. Among them, the Stacking (BPNN-RF-SVM) model achieves the highest performance across all three stations, with R of 0.903, 0.904, and 0.917, respectively. These represent improvements of at least 2.2%, 2.8%, and 2.1% over the best-performing base models. Therefore, the Stacking (BPNN-RF-SVM) model is identified as the optimal retrieval model. This work aims to contribute to the development of high-accuracy, real-time monitoring methods for near-surface soil moisture. Full article

The use of single-layer aerated concrete walls in residential construction has a tradition of over 60 years. Its main advantage is thermal insulation. It is the most advantageous among construction materials used for the construction of external walls. The possibility of modifying the dimensions of the blocks leads to meeting subsequent restrictive values of the heat transfer coefficient U. The high dimensional accuracy of the blocks allows the use of dry vertical joints and thin joints with a thickness of 1–3 mm, the thermal influence of which is omitted. However, the thermal uniformity of such a wall is strictly dependent on the quality of workmanship. The main objective of the analysis is to assess the impact of moisture on the U_wall of walls as a function of vertical joint spacing and horizontal joint thickness. It should be said that the effect of humidity and manufacturing accuracy on the thermal properties of aerated concrete walls has not been sufficiently studied. Further study of these patterns is necessary. Particular attention should be paid to the thin-bed mortar, which depends on the manufacturing accuracy. The separation of AAC masonry elements that occurs during bricklaying significantly affects the thermal insulation of walls. This issue has not yet been analysed. The scientific objective of this article is to develop a procedure for determining the thermal properties of a small, irregular air space created as a result of the separation of masonry elements and the impact of this separation on the thermal insulation of the wall. Based on the analysis of the thermal conductivity of voids and masonry elements, it was determined that this impact is visible at low AAC densities. A detailed analysis taking into account both these joints and horizontal joints, as well as different moisture levels, made it possible to determine the permissible separation of AAC blocks, at which the high thermal insulation requirements applicable in most European countries are met. The analysis showed that it is possible to meet the thermal protection requirements for 42 cm wide blocks intended for single-layer walls with a maximum vertical contact width of 3 mm and a joint thickness of up to 2 mm. AAC moisture content plays a major role in thermal insulation. Insulation requirements can be met for AAC in an air-dry state, as specified by ISO 10456. Full article

The development of biomaterials with tailored properties is indispensable for biomedical applications. In this study, amorphous silica/sodium alginate (SiO₂/SA) hybrids were synthesized via the sol–gel method by incorporating 2, 5, and 8% sodium alginate into the silica matrix. The hybrids were characterized to evaluate their structural, surface, thermal, moisture-responsive, and biological properties. FTIR and XRD analyses confirmed the formation of organic–inorganic networks and amorphous structures. BET measurements revealed a specific surface area of 325 m²/g for SiO₂/SA2%, decreasing with higher SA content to 104.3 m²/g for SiO₂/SA8%; the moisture sorption capacity followed a similar trend. Thermal analysis indicated improved stabilization of the polymer within the silica matrix. Cytotoxicity tests on HaCaT (human keratinocyte) cells line revealed moderate toxicity for the SiO₂/SA2% hybrid (~40% cell viability inhibition (CVI)), while increasing the SA content reduced cytotoxicity, with a CVI of 33% for SiO₂/SA5% and ~15% for SiO₂/SA8%, all within non-toxic ranges according to ISO standards. The SiO₂/SA5% hybrid demonstrated the best balance between functional properties and biocompatibility. These preliminary results suggest that further optimization with intermediate SA concentrations (e.g., 6–7%) could further reduce cytotoxicity while maintaining desirable properties, supporting the potential of silica/sodium alginate hybrids in future biomedical applications. Full article

In recent years, arresters in 10 kV distribution transformer areas of the Guangdong power grid have exhibited a rising trend of premature failures, posing a serious threat to distribution network reliability. This paper studied the failure causes of arresters through performance tests on failed arresters and through deterioration tests on new arresters and their prorated sections under typical operating stresses. The failed arresters and their internal varistors displayed varying degrees of physical damage and pronounced degradation in electrical performance, characterized by a strong polarity effect on the DC reference voltage (U_1mA), elevated DC leakage current (I_L) and resistive current (i_R), and excessive residual voltage (U_5kV). In the lightning impulse test, varistors primarily showed pinhole-type damage and significant polarity effects on ΔU_1mA. In the AC aging test, ΔU_5kV increased markedly. In the water immersion test, varistors exhibited salt deposits and aluminum electrode blackening, with ΔU_1mA decreasing, while I_L and Δi_R increased significantly. Overall, internal moisture superimposed on other operating stresses was identified as a major internal cause of arrester failure, while pollution flashover of the housing was considered the primary external factor. Corresponding improvement measures in material optimization, testing and inspection, and operation and maintenance are proposed to enhance arrester reliability. Full article

The storage characteristics of folic acid and NaFeEDTA fortified in a refractance window-dried turmeric powder base and its subsequent application to the formulation of nutritionally functionalized golden milk have not been addressed in previous studies. Golden milk is a staple food and ideal matrix for the fortification of important nutrients such as iron and folic acid. With this motivation, the present study assesses refractance window (RW)-dried turmeric powder fortified with folic acid and NaFeEDTA in terms of its moisture isotherm, permeability of packing material, and storage parameters to calculate its shelf life. Further, a sensory analysis was conducted based on the fuzzy logic method to obtain the best constitution of RW-dried turmeric powder in milk. For the best formulation of golden milk, the characteristics of the product under unrefrigerated and refrigerated conditions were evaluated in addition to the storage study. Additionally, moisture content (MC), total flavonoid content (TFC), total phenolic content (TPC), antioxidant activity (AA), curcumin content (CC), color indices, bulk densities, solubility, swelling power, and water binding capacities were studied with respect to time. The results demonstrated a healthy shelf life of 184, 187, and 183 days for RW-dried, folic acid-fortified, and NaFeEDTA-fortified RW-dried turmeric powder samples, respectively, in the zipper pouch system. The fuzzy scores ranked the sample with 1 g concentration of turmeric powder as the best, considering taste, aroma, mouthfeel, aftertaste, consistency, and overall acceptability. The TPC, TFC, AA, and CC values for RW-dried turmeric powder in milk were 876.21 mg GAE/100 mL, 784.61 mg quercetin/100 mL, 24.50% and 4.20% w/w, respectively. Marginal alterations were found for the RW-dried fortified and unfortified turmeric samples. This fortified golden milk has the potential for use as a health drink. Full article

This study evaluated the effects of different doses of the herbicide fluroxypyr on soil microbial communities under controlled laboratory conditions. Specific enzymatic activities ((dehydrogenase (DA), urease (UA), catalase (CA), phosphatase (PA)) and quantitative variations in bacterial and fungal populations were measured regarding key physico-chemical soil parameters (temperature, pH, electrical conductivity, moisture, organic matter, ammonium, nitrate nitrogen, and available phosphate content). The effects of the herbicide on the targeted parameters were dose- and time-dependent. Fluroxypyr induced a clear decrease in DA, CA, and PA during the first 14 days after administration, while UA showed a decrease in the first 7 days, followed by a slight increase starting on day 14, closely related to the applied dose. Microbial populations decreased in direct relation to the fluroxypyr dose. Organic matter content exhibited a positive correlation with DA, UA, CA, as well as with microbial populations. In addition, three natural compounds structurally similar to fluroxypyr were identified via 3D virtual screening, demonstrating potential herbicidal activity. Fluroxypyr can alter soil metabolic activity and disrupt microbial communities, thereby affecting soil fertility. Used as a reference in 3D screening, fluroxypyr helped identify three natural compounds with potential herbicidal activity as safer alternatives to synthetic herbicides. Full article

Biopolymers have gained significant attention due to their environmental advantages, with insects emerging as a promising but underutilized source of chitin and chitosan. In this study, chitosan was extracted from the larval exuviae of Tenebrio molitor through sequential demineralization, deproteinization, and deacetylation steps. For selected analyses, the extracted chitosan was further purified via reprecipitation from an acid solution using a basic precipitant (1 M NaOH). Chitosan was then characterized using chemical and instrumental methods. The results indicated that the chitosan had a medium degree of deacetylation (72.27%) and viscosity-average molecular weight (612 kDa), along with minimal ash (0.33%) and amino acid (0.14%) content, suggesting high product quality. FTIR analysis identified characteristic functional groups present, and SEM analysis highlighted a fibrous and porous microstructure in the purified chitosan. The prepared films exhibited favorable properties, including low thickness (0.0197 mm), high swelling degree (335.07%), moderate water solubility (46.99%), and moisture content of 32.39%, supporting their practical applicability. T. molitor exuviae thus represents a sustainable and environmentally friendly source of high-quality chitosan, with beneficial structural and functional properties, supporting its use in a wide array of value-added applications. Full article

Soils act as sources or sinks for three major greenhouse gases (CO₂, CH₄, and N₂O). Approximately 20% of global CO₂ emissions are released from soils through the soil respiration process. Soil respiration (soil CO₂ emission) can account for over 85% of ecosystem respiration. The aim of this study was to compare managed and unmanaged stands of pedunculate oak (Quercus robur L.) in order to investigate the impact of forest management on soil CO₂ emissions. We selected one managed and two unmanaged stands. The first stand (S1) represents a managed middle-aged stand, which is the optimal stage of development. The second stand (S2) belongs to the over-mature stage of development in an old-growth oak forest, while the third stand (S3) belongs to the decay stage of development in an old-growth oak forest. The closed chambers method was used for air sampling and the air samples were analyzed using gas chromatography (GC). Multiple regression models that include soil temperature (ST), soil moisture (SM), and their interaction provide a better explanation for variation in soil CO₂ emission (SCDE) (higher R² values) compared to regression models that only involve two variables (ST and SM). The study showed that SCDE in the decay stage of old-growth forest (S3) was significantly lower (p < 0.001) compared to the other two stands (S1 and S2). S3 is characterized by very low canopy cover and intensive natural regeneration, unlike S1 and S2. However, there were no significant differences in SCDE between the managed middle-aged stand (S1) and the over-mature (old-growth) stand (S2). Over a long-term rotation period in pedunculate oak forests, forest management practices that involve the periodic implementation of moderate silvicultural interventions can be deemed acceptable in terms of maintaining the carbon balance in the soil. Full article

Soil desertification control is a global challenge, and the barrenness of sandy soil limits the growth of plants. To enhance the vegetation growth capacity of sandy soils, the preparation of soil amendments and the experiment of improving desertified soil were conducted. The soil amendment is prepared by mixing polyacrylamide (2.7%), biochar (16.2%), sodium bentonite (16.2%), straw fibers (5.4%), corn straw (2.7%), sheep manure organic fertilizer (54.1%), and composite microbial agents (2.7%). The laboratory experiment was conducted to investigate the effects of varying rates (0, 1.5%, 3%, 4.5%, 6%) of composite soil amendments on the properties of sandy soil and the Lolium perenne L. with a growth period of 30–60 days. The results indicated that the application of composite amendments at different rates maintained the soil pH between 7.0 and 7.5, increased the electrical conductivity, and significantly improved the soil moisture content, soil organic carbon (SOC), total nitrogen (TN), and total phosphorus contents. Under the condition of 3% amendment, the soil TN content increased from 0.74 to 1.83 g·kg⁻¹. The composite amendments remarkably promoted L. perenne growth, as evidenced by increased plant height, dry weight, and nitrogen and phosphorus nutrient content, while the SOC content increased by 1–4 times. The application of composite amendments, prepared by mixing materials such as biochar, organic fertilizer, crop straw, microbial agents, bentonite, and water-retaining agents, enhanced the physicochemical properties of sandy soil and promoted L. perenne growth, and 3% was the most suitable application rate. These findings are expected to advance desertification-controlling technologies and enhance soil carbon sequestration capacity. Full article

The management of groundwater depth (GWD) in alluvial soils under irrigation in arid climates is critical for soil and water conservation, given its influence on salt dynamics and water availability for crops. GWD is influenced by the interaction of irrigation water supply and drainage system design and operation. Controlling GWD is a significant issue in the Hetao Irrigation District due to continuous irrigation, arid climate, and high risks of soil salinization, which concerns farmers and water management authorities. To address this issue, a study was conducted based on open-air laboratory experimentation to rigorously assess the effects of GWD on soil salt dynamics and capillary rise contribution to maize cultivation under level basin irrigation. Data collected served as the basis for parameterizing and calibrating the HYDRUS-1D model, facilitating simulation of soil water and salt dynamics to enhance understanding of GWD effects ranging from 1.25 m to 2.25 m. It was concluded that during calibration and validation, the model demonstrated strong performance; SWC simulations achieved R² > 0.69, RMSE < 0.03 cm³ cm⁻³, and NSE approaching 1; and EC simulations yielded R² ≥ 0.74 with RMSE < 0.22 S cm⁻¹. Additionally, the simulated bottom boundary moisture flux closely matched the measured values. The most favorable GWD range should be between 1.75 m and 2.0 m, minimizing the negative impacts of irrigation-induced soil salinity while maximizing water use efficiency and crop productivity. A higher GWD causes crop water stress, while a lower value results in a greater risk of soil salinity. This study anticipates future field application in Hetao to assess drainage system effectiveness and variability in salinity and productivity effects. Full article