Search Results (9,560)

Yeast culture (YC) is a microbial product that enhances ruminal fiber breakdown and improves nutrient digestion and utilization. Our previous research showed that oxalic acid (OA) is a crucial metabolite in YC that enhances rumen function. This study aimed to investigate the effects of YC, OA, and their combination (YO) on rumen function, growth, and fattening in sheep. Twenty lambs were divided into 4 groups (ctrl, YC, OA, and YO; n = 5 each) and fed a diet supplemented with 2 levels of YC and 2 doses of OA for 60 days in a 2 × 2 factorial design. Growth and fattening performance, rumen microbiome analysis, serum indices and anti-oxidant levels, and metabolomic profiling were performed. Individual supplementation with YC and OA significantly increased the digestibility of dry matter (DM), organic matter (OM), and crude protein (CP) (p < 0.001); neutral detergent fiber (NDF) (p < 0.05); and acid detergent fiber (ADF) (p < 0.001) and their interaction significantly increased dry matter intake (DMI) (p = 0.05). Serum IgA and IgM levels were higher in the supplemented groups (p < 0.05). Serum calcium levels were higher in the OA and YO groups (p < 0.001). The supplemented groups showed significantly higher growth hormone and superoxide dismutase levels (p < 0.05). The longissimus dorsi muscle had higher levels of iron in the OA and YO groups; zinc in the OA, YO, and YC groups (p < 0.01); and selenium in the YC group (p < 0.05). The OA group had a higher total antioxidant capacity. All supplemented groups showed higher bacterial richness and diversity. Ruminococcus, Succinivibrio, and Fibrobacter were positively correlated with the fermentation and digestibility parameters. The supplementation also altered metabolite levels and types in key physiological pathways. In conclusion, this supplementation improved bacterial composition, nutrient digestibility, weight gain, carcass weight and quality, serum indices, antioxidant levels and metabolomic profiles. This suggests potential for the development of dietary supplements for ruminants. Full article

Strawberries and blueberries are globally recognized for their dense nutritional profile, bioactive compounds, and health-promoting properties. Yet, their perishability and seasonality limit their availability, stability, and functionality in food and nutraceutical formulations. Drying technologies, particularly spray drying and freeze drying, are effective preservation strategies that convert fresh berries into stable, shelf-ready powders. However, the high sugar content, low glass transition temperature (Tg), and hygroscopic nature of berry matrices pose significant challenges in maintaining powder flowability, preventing caking, and ensuring structural integrity during processing, storage, and transportation. This review examines the physicochemical and surface properties of strawberry and blueberry powders as influenced by the drying method, environmental conditions, and carrier selection (e.g., maltodextrin, gum arabic, and whey proteins). Emphasis is placed on glass transition phenomena, moisture sorption behavior, and surface composition as determinants of physical stability and shelf life. The roles of water activity (aw), particle morphology, and interparticle interactions are analyzed in the context of formulation design and powder performance. Analytical techniques in characterizing bulk properties for the amorphous structure and sorption kinetics and probing surface properties of powders are crucial for understanding interactions with water, assessing flow, caking, sintering, and dissolution. By integrating insights from food physical chemistry and materials surface properties, this review provides a framework for the rational design of berry-based powders with improved handling, stability, and bio-functionality. The findings have direct implications for scalable production, global distribution, and the development of functional ingredients aligned with health and wellness priorities worldwide. Full article

While livestock production is a significant source of greenhouse gas emissions, it remains vital for fulfilling the growing global demand for animal protein. Including by-products in ruminant diets can enhance food circularity and reduce competition for human food, while also increasing the likelihood of reducing methane (CH₄) emissions. This study aimed to evaluate the impact of fully replacing corn grain and urea in the control diet with local by-products, specifically corn distillers’ grains combined with either barley brewed grains or with wheat middlings, on enteric CH₄ emissions and performance of sheep. Diets were balanced to be isoproteic and isoenergetic with 2.6 Mcal ME/kg of dry matter (DM) and 160 g crude protein/kg DM, respectively. Corn silage is the only source of forage in the diet, and the forage-to-concentrate ratio was maintained to 60:40 on a DM basis. Twelve Highlander female sheep of 35.9 ± 3.12 kg initial body weight (BW, mean ± standard deviation), were used in a Completely Randomized Block design, with four sheep per treatment and two measurement periods under the same treatment. Experiment lasted 60 d, 30 d acclimatization and 30 d measurements. Dry matter intake (DMI) was restricted to 2.5% of BW. Enteric CH₄ emissions of individual sheep were quantified in respiration chambers over a 48 h period. Dietary treatments did not have a significant effect either on DMI or BW gain. The diet containing barley brewed grains significantly reduced total daily CH₄ production by 22.3%, CH₄ emissions per kg of DMI by 34% and energy loss as CH₄ by 38% compared to the control diet. In conclusion, the agro-industrial by-products combinations evaluated in this study effectively replaced corn grain and urea without compromising feed intake or animal performance. Additionally, the diet containing barley brewed grains significantly reduced CH₄ yield, and energy loss compared to the control diet. Full article

Humidity monitoring is essential in industrial and scientific scenarios, yet remains challenging for compact EMI (electromagnetic interference)-immune sensors with high sensitivity and robust stability. A novel fiber Bragg grating (FBG) humidity sensor was developed, which incorporated LiCl@UIO-66 microfillers within a poly(N-isopropylacrylamide) (PNIPAM) hydrogel matrix. Structural characterization using X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and Fourier-transform infrared (FTIR) spectroscopy confirms that LiCl is confined or nanodispersed within intact UIO-66, and that interfacial ion–dipole/hydrogen-bonding exists between the composite and water. Systematic variation in coating time (30–720 min) reveals monotonic growth of the total wavelength shift with diminishing returns. A coating time of 4 h was found to yield a wavelength shift of approximately 0.38–0.40 nm, representing about 82% of the maximum shift observed at 12 h, while maintaining good quasi-linearity and favorable kinetics. Calibration demonstrates sensitivities of 6.7 pm/%RH for LiCl@UIO-66_33 and 10.6 pm/%RH for LiCl@UIO-66_51 over ~0–95%RH. Stepwise tests show response times t90 of ≈14 min for both composites, versus ≈30 min for UIO-66 and ≈55 min for neat PNIPAM. Long-term measurements on the 51 wt.% device are stable over the first ~20 days, with only slow drift thereafter, and repeated humidity cycling is reversible. The wavelength decreases monotonically during drying while settling time increases toward low RH. The synergy of hydrogel–MOF–salt underpins high sensitivity, accelerated transport, and practical stability, offering a scalable route to high-performance optical humidity sensing. Full article

Soybeans are widely used in agro-industrial sectors, and global demand for this crop continues to rise. After harvest, however, soybean seeds often lack the appropriate moisture content for storage, making drying a common practice under changing climate conditions. Because temperature is a critical factor during drying, this study aimed to evaluate the effect of air-drying temperature on physiological responses and cytogenetic conformation of soybean seeds. The experiment was conducted under a completely randomized design with four replications for each temperature. Seeds with 23 percent moisture content were dried in a convective dryer equipped with airflow and temperature control at 40 °C, 50 °C, 60 °C, and 70 °C until reaching 13 percent. Samples for physiological and cytological analyses were collected before and after drying. The results indicated that drying temperature influenced seed performance and vigor. Moreover, nuclear alterations were identified as an important component of the genotoxicity caused by high drying temperatures. Overall, air temperatures above 50 °C induced physiological and cytogenotoxic effects, underscoring the need for careful monitoring during seed drying. Full article

The global shift to digital terrestrial television broadcasting (DTTB) from the conventional analogue has significantly transformed television culture, necessitating comprehensive technical and infrastructural evaluations. This study addresses the limitations of existing path-loss models for accurately predicting path loss in digital terrestrial television broadcasting in the UHF bands, motivated by the need for reliable, location-specific models that account for seasonal, meteorological, and topographical variations in Abeokuta, Nigeria. The study focuses on path-loss prediction in the UHF band using Ogun State Television (OGTV), Abeokuta, Nigeria, as the transmission source. Eight receiving sites, spaced 2 kilometers apart, were selected along a 16.7 km transmission contour. Daily measurements of received signal strength (RSS) and weather conditions were collected over one year. Seasonal path-loss models ${PL}_{wet}$ for the wet season and ${PL}_{dry}$. For the dry season, models were developed using multiple regression analysis and further optimized using least squares (LS) and gradient descent (GD) techniques, resulting in six refined models: ${PL}_{wet}$, ${PL}_{dry}$, ${PL}_{wet-LS}$, ${PL}_{dry-LS}$, ${PL}_{wet-GD}$, and ${PL}_{dry-GD}$. Model performance was evaluated using Mean Absolute Error, Root Mean Square Error, Coefficient of Correlation, and Coefficient of Multiple Determination. Results indicate that the Okumura model provided the closest approximation to measured RSS for all the receiving sites, while the Hata and COST-231 models were unsuitable. Among the developed models, ${PL}_{wet}$ ($RMSE- 1.2633$, $MAE - 0.9968$, $MSE - 1.5959$, $R - 0.9935$, $R^2 - 0.9871$) and ${PL}_{dry-LS}$($RMSE- 1.1884$, $MAE - 0.7692$, $MSE - 1.4124$, $R - 0.9942$, $R^2 - 0.9883$) were found to be the most suitable models for the wet and dry seasons, respectively. The major influence of location-based elevation and meteorological data on path-loss prediction over digital terrestrial television broadcasting communication lines in Ultra-High-Frequency bands was evident. Full article

Waste generated from agricultural activities is anticipated to increase in the future, especially in less developed countries, and this could cause environmental health risks if these wastes are not well managed. The anaerobic digestion (AD) by co-digesting organic waste is a technology used to produce biogas while utilizing biodigestate as a biofertilizer; however, AD requires a lot of water to be efficient, which could pose water challenges to arid areas. This study evaluated biogas production under semi-dry conditions by augmenting the process with a high-water content wild melon and determined the nutrient composition of the resultant biodigestate. Batch studies of AD were performed to evaluate methane potential of the different animal waste using an online and standardized Automatic Methane Potential Test System (AMPTS) II light for approximately 506 h (21 days) at 38 °C. The highest biomethane potential (BMP) determined for mono and co-substrate digestion was 29.5 NmL CH₄/g VS (CD) and 63.3 NmL CH₄/g VS (CMWM), respectively, which was calculated from AMPTS biomethane yield of 3166.2 NmL (CD) and 1480.6 NmL (CMWM). Water-displacement method was also used to compare biogas yield in wet and semi-dry AD. The results showed high biogas yield of 8480 mL for CM (mono-substrate) and 10,975 mL for CMCC in wet AD. Semi-dry AD was investigated by replacing water with a wild melon (WM), and the highest biogas production was 8000 mL from the CMCC combination augmented with WM. Generally, in wet AD, co-digestion was more effective in biogas production than mono-substrate AD. The biodigestate from different substrate combinations were also evaluated for nutrient composition using X-ray Fluorescence (XRF) analysis, and all the samples contained fair amount of essential nutrients such as calcium (Ca), phosphorus (P), potassium (K) and microelements such as chloride (Cl), magnesium (Mn), iron (Fe), zinc (Zn). This study successfully implemented semi-dry AD from co-digested animal wastes to produce biogas as an energy solution and biofertilizer for crop production, thereby creating a closed-loop system that supports a circular bioeconomy. In addition, the study confirmed that lowering the water content in the AD process is feasible without compromising substantial biogas production. This technology, when optimized and well implemented, could provide sustainable biogas production in areas with water scarcity, therefore making the biogas production process accessible to rural communities. Full article

CuZn39Pb3 leaded brass is one of the most widely used alloys in machining, with a 100% machinability index. However, there has been a lack of research on the effects of coldworking on surface integrity (SI) and operating behaviour of CuZn39Pb3 components. This study addresses this knowledge gap by examining the effects of three optimised combined processes on surface roughness, a key SI characteristic. Specifically, samples were subjected to a turning process followed by diamond burnishing (DB); this combined process was performed under three conditions: conventional flood lubrication (F), dry (D), and dry and cool-assisted (D+C) conditions. Cool-assisted conditions were achieved using a special device with a cold air nozzle operating on the vortex tube principle. The D and D+C conditions represent environmentally sustainable alternatives because they eliminate the use of cutting fluids, thereby reducing their adverse effects on both the environment and human health. The resulting surfaces obtained after each of the three optimised combined processes (F, D, and D+C) exhibited mirror-like finishes with minimum average roughness Ra values of 0.054, 0.079, and 0.082 μm, respectively. In addition, the F- and D+C-processes resulted in surface profiles with negative skewness and kurtosis values greater than three. Since roughness shape parameters are known to influence the operating behaviour of machined components, these processes are suitable for improving wear resistance in boundary lubrication regimes. Full article

With its millennia-long agricultural history, Olive (Olea europaea L.) is one of the most strategic crops of the Mediterranean basin and a key component of the Turkish economy. This study assessed the effects of climate change on the potential distribution of olive in Türkiye using machine learning-based species distribution models (SDMs). Analyses were conducted using the 1970–2000 reference period and future projections for 2041–2060 and 2081–2100 under the SSP2-–4.5 and SSP5–8.5 scenarios, incorporating bioclimatic variables as well as topographic factors such as elevation, slope, and aspect. The model showed strong predictive performance (AUC = 0.93; TSS = 0.77) and identified elevation, winter precipitation (Bio19), and mean temperature of driest quarter (Bio9) as the primary variables influencing the distribution of olive trees. Model results predict a significant shift in suitable areas for olive cultivation, both northward—from the traditional Aegean and Mediterranean coastal belt toward the Marmara and Black Sea regions—and upward in elevation into higher-altitude inland areas. High-suitability areas, which accounted for 4.4% of Türkiye’s land area during the reference period, are projected to decline to 0.2% by the end of the century under the SSP5–8.5 scenario. UNEP Aridity Index analyses indicate increasing aridity pressure on olive habitats. While 87.2% of suitable habitats were classified as sub-humid in the reference period, projections for 2081–2100 under SSP5–8.5 suggest that 40.1% of these areas will shift to dry sub-humid and 26.4% to semi-arid conditions. Full article

According to climate projections, the Pannonian region is expected to experience an increasing frequency of drought events. This trend affects not only agricultural areas but also natural grasslands. The Festuca wagneri species, selected for this study, is a dominant and well-adapted grass in dry natural habitats. A total of 54 Festuca wagneri individuals were examined across three soil types: sand, loam, and clay. In each soil type, 18 plants were assessed for drought tolerance. Water was applied at three dosage levels: 200, 300, and 400 mL. The experiment was conducted between 4 April and 18 July 2024, during which the total weight of the pots and the amount of drained water were measured regularly. All data processing and statistical analyses were performed in R version 4.3.2. A three-way factorial ANOVA was used to evaluate main and interaction effects. Model residuals were tested for normality (Shapiro–Wilk test) and homoscedasticity using diagnostic plots. The results showed that Festuca wagneri individuals tolerated even the lowest soil moisture levels induced by low water-holding capacity of the soil and low water input. This indicates that the species can be effectively used in grassland management and restoration under future climate change scenarios. The main differences were observed among soil types, highlighting the crucial importance of soil structure when establishing this species. Loam soils, already near optimal, respond best to moderate. Full article

Salvia dumetorum Andrz. ex Besser is a promising non-pharmacopoeial plant species with traditional medicinal potential. This study aimed to determine the optimal microwave-assisted extraction (MAE) conditions for obtaining a polyphenol-rich ethanolic extract from the S. dumetorum leaves. Dried and powdered leaves were extracted using 40% ethanol with different power of microwaves varying from 200 to 800 W and time of extraction 2–8 min. The extract was filtered, concentrated, and evaluated for yield, identification of phenolic compounds using high-performance liquid chromatography (HPLC), total phenolic content (TPC), and total flavonoid content (TFC). Extraction yields ranged from 2.20% to 25.80% based on dry weight. TPC and TFC were determined using Folin–Ciocalteu and aluminum chloride colorimetric assays, respectively, and are expressed as mg GAE/g and mg RUE/g of dry extract. The antioxidant activity of the extracts was evaluated using the DPPH (2,2-diphenyl-1-picrylhydrazyl radical) assay. According to HPLC analysis, the main phenolic components of the extracts were rosmarinic acid (1.78–2.95 mg/mL), chlorogenic acid (0.31–0.54 mg/mL), caffeic acid (0.11–0.20 mg/mL), rutin (up to 0.47 mg/mL) and ferulic acid (0.13–0.33 mg/mL); traces of myricetin were found only in isolated samples. The optimum extraction conditions were found to be 400 W microwave power, 8 min extraction time, one MAE cycle, and a 1:30 g/mL solvent-to-material loading ratio; TPC and TFC were evaluated as 35.23 ± 0.50 mg GAE/g DW and 19.94 ± 0.14 mg RuE/g DW, respectively, indicating the highest yield of polyphenolic compounds, antioxidant potential inhibiting 96.68% ± 0.27 of DPPH radicals, and IC₅₀ = 10.24 µg/mL. These findings highlight the efficiency of MAE in producing a bioactive ethanolic extract of S. dumetorum, which can be further explored for potential applications as a natural antioxidant in pharmaceutical or cosmetic formulations. Full article

Agricultural irrigation accounts for nearly 70% of global freshwater withdrawals, making sustainable water management crucial for food security and ecological stability—particularly in arid and semi-arid regions. However, dynamic water-saving thresholds at both inter-annual and intra-annual scales remain insufficiently quantified in current research. To address this gap, this study developed an integrated SWAT-MODFLOW model for the Hetao Irrigation District and quantified dynamic water-saving thresholds by simulating crop yield responses under a range of irrigation scenarios. The model was calibrated (2008–2014) and validated (2014–2016), demonstrating reliable performance (R² = 0.75, NSE = 0.74) in capturing local hydrological processes. Inter-annual scenarios assessed water-saving levels of 5%, 10%, 20%, and 30% under wet, normal, and dry years, while intra-annual scenarios adjusted seasonal irrigation volumes in spring, summer, and autumn with reduction gradients of 33%, 50%, and 100%. Results show that wet and normal years could achieve a water-saving threshold of up to 20%, whereas dry years were limited to 5%. Intra-annually, autumn irrigation offered the greatest saving potential (33–100%), followed by spring (33–50%). Spatially, crop responses varied substantially: the western part of the region proved particularly sensitive, with even the optimal district-wide strategy reducing local crop yields by 10–20%. This study quantifies dynamic water-saving thresholds and incorporates spatial heterogeneity into scenario assessment. The resulting framework is transferable and provides a basis for sustainable water management in water-limited agricultural regions. Full article

Accurate daily runoff forecasting is essential for flood control and water resource management, yet existing models struggle with the seasonal non-stationarity and inter-basin variability of runoff sequences. This paper proposes a Season-Aware Ensemble Forecasting (SAEF) method that integrates SVM, LSSVM, LSTM, and BiLSTM models to leverage their complementary strengths in capturing nonlinear and non-stationary hydrological dynamics. SAEF employs a seasonal segmentation mechanism to divide annual runoff data into four seasons (spring, summer, autumn, winter), enhancing model responsiveness to seasonal hydrological drivers. An Improved Arctic Puffin Optimization (IAPO) algorithm optimizes the model weights, improving prediction accuracy. Beyond numerical gains, the framework also reflects seasonal runoff generation processes—such as rapid rainfall–runoff in wet seasons and baseflow contributions in dry periods—providing a physically interpretable perspective on runoff dynamics. The effectiveness of SAEF was validated through case studies in the Dongjiang Hydrological Station (China), the Elbe River (Germany), and the Quinebaug River basin (USA), using four performance metrics (MAE, RMSE, NSEC, KGE). Results indicate that SAEF achieves average Nash–Sutcliffe Efficiency Coefficient (NSEC) and Kling–Gupta efficiency (KGE) coefficients of over 0.92, and 0.90, respectively, significantly outperforming individual models (SVM, LSSVM, LSTM, BiLSTM) with RMSE reductions of up to 58.54%, 55.62%, 51.99%, and 48.14%. Overall, SAEF not only strengthens predictive accuracy across diverse climates but also advances hydrological understanding by linking data-driven ensembles with seasonal process mechanisms, thereby contributing a robust and interpretable tool for runoff forecasting. Full article

Thirty-six Dorper × Katahdin intact male lambs [44.0 ± 0.27 kg initial body weight (BW)] were used in a randomized complete block design to evaluate the effects of supplementing different organic chromium (OrCr) sources on growth performance, dietary energetics, carcass traits, meat quality, and economic return. Treatments (n = 9 lambs/treatment) were (1) Control (no Cr), (2) chromium-enriched yeast (Cr-Yeast), (3) chromium–methionine (Cr-Met), and (4) chromium–propionate (Cr-Pr). All Cr sources were provided at 1.2 mg elemental Cr/lamb/d for 45 d. Lambs received a high-energy finishing diet (78:22 concentrate/forage; steam-rolled corn-based). Dry matter intake was not affected (p = 0.583; 1.27 ± 0.034 kg/d). Compared with Control, Cr-Pr increased final BW (+5%; p = 0.025) and average daily gain (+66%; p = 0.034), and improved feed efficiency (+59%; p = 0.045) and observed-to-expected net energy ratio (+22%; p = 0.042); Cr-Met and Cr-Yeast showed intermediate responses. No differences were observed (p > 0.05) in longissimus lumborum muscle area, cold carcass weight, dressing percentage, cooling loss, or zoometric traits. Rib and rump fat thickness decreased with Cr-Met (−15 and −12%; p = 0.024 and p = 0.048) and with Cr-Pr (−19 and −13%; p = 0.024 and p = 0.048), and all OrCr sources reduced omental (−6 to −25%; p = 0.034), mesenteric (≈−7%; p = 0.042), visceral (−12 to −16%; p = 0.034), and perirenal fat (−25 to −39%; p = 0.028). Empty body weight and hot carcass weight increased with Cr-Pr (p = 0.029 and p = 0.031, respectively). Cr-Yeast and Cr-Pr increased muscle proportion (+5 to +7%; p = 0.003) and reduced carcass fat (−20 to −27%; p = 0.018), improving the muscle/fat ratio (+42 to +50%; p = 0.045). Cr-Pr improved water-holding capacity (+27%; p = 0.014) without affecting pH_24h, purge loss, cooking loss, or Warner–Bratzler shear force (p > 0.05). Cr-Pr reduced cost per kg of gain (−31%; p < 0.001) and increased income (+188% live; +105% carcass; p < 0.001), whereas Cr-Met and Cr-Yeast provided moderate benefits. In conclusion, OrCr supplementation improved dietary energy utilization, growth, carcass traits, and meat quality, enhancing profitability in lambs finished at heavier weights, with Cr-Pr producing the greatest responses. Full article

Background: The positive identification of a source of tissue as human plays an important role in various contexts. It is particularly important for investigations concerning tissue and organ trafficking, since unequivocal confirmation is required for legal proceedings involving such cases. While deoxyribonucleic (DNA) methods are considered the gold standard for tissue identification, issues such as degraded DNA or the presence of chemical preservatives can hinder performance and positive identification using DNA techniques. Objectives: The aim of this study was to develop a simple method for presumptive identification of human tissue using standard bottom-up proteomics data. Methods: We identified proteins isolated from human kidney, lung and spleen tissues by bottom-up proteomics and database search using Proteome Discoverer and Sequest HT algorithms. The list of identified proteins was sorted based on liquid chromatography (LC)–mass spectrometry (MS) data metrics such as the number of unique peptides used to identify each protein and the % sequence coverage of an identified protein to determine if any parameter would cluster proteins annotated as human in a distinct category. We found that eliminating proteins identified with fewer than two unique peptides and those with less than 5% sequence coverage resulted in a final list where at least half of the remaining proteins are annotated as human. We applied this data filtration process to blinded LC–MS/MS data from 26 previous experiments to assess accuracy. Results: Using bottom-up proteomics data and the filtration rules established, we identified tissue samples (n = 10), including kidney, spleen, lung, formalin-fixed paraffin-embedded uterus, frozen breast tissue, dry blood and dry saliva as human, and tissue (n = 16) from rat, mouse, bovine, and sheep as non-human, resulting in 100% sensitivity and specificity. Conclusions: The results demonstrate that the list of identified proteins following a standard bottom-up proteomics experiment could be filtered and potentially used as a fast and simple method for presumptive human tissue identification. Full article