Search Results (3,317)

In populations with limited genotyping, single-step genomic best linear unbiased predictions (ssGBLUP) can produce biased or less accurate genomic predictions due to incompatibilities between genomic and pedigree relationship matrices. The study evaluated the impact of five alternative ssGBLUP models for genomic predictions of milk, fat, and protein yield production traits in South African Holstein cattle. The dataset included 696,413 milk production records and pedigrees of 541,325 animals. Production traits were 305-day lactation yields for milk, protein, and fat. Genotype data were based on the Illumina 50K chip v3, with 53,218 SNPs. A total of 1221 animals with genotypes and 41,407 SNP markers were in the final dataset. The five models used to estimate genomic estimated breeding values (GEBVs) were the single-step method (ssGBLUP), ssGBLUP accounting for inbreeding (ssGBLUP_Fx), ssGBLUP with unknown parent groups (ssGBLUP_upg), and two ssGBLUP models with blending, tuning, and scaling parameters set to optimum values in constructing the inverse of the unified relationship matrix (ssGBLUP_adjusted). Realized prediction accuracies were highest for ssGBLUP_adjusted models (6–7% improvements compared to ssGBLUP). Accuracy of GEBVs for milk, protein, and fat yields ranged from 0.23, 0.29, and 0.30 for both ssGBLUP and ssGBLUP_Fx, 0.26, 0.32, and 0.34 for ssGBLUP_upg, and 0.29, 0.35, and 0.37 for ssGBLUP_adjusted models, respectively. Corresponding bias, expressed as regression coefficients, ranged from 0.30, 0.31, and 0.36 for ssGBLUP; 0.31, 0.32, and 0.37 for ssGBLUP_Fx; 0.41, 0.44, and 0.49 for ssGBLUP_upg; and 0.44, 0.47, and 0.53 for ssGBLUP_adjusted models, respectively. The improved accuracy and reduced bias observed with the ssGBLUP_adjusted underscores the importance of optimizing the blending of pedigree- and genome-based relationships to achieve more reliable GEBVs, thereby improving selection decisions in Holstein dairy cattle. Full article

The non-thermal plasma-driven cascade process for CO₂-to-methanol conversion shows significant potential in the field of green methanol synthesis. This process innovatively couples a plasma activation module with a catalytic synthesis module via a multi-stage pressurization device, establishing an efficient two-step pathway that converts CO₂ into methanol via a CO intermediate. Such an arrangement establishes an energy conversion system characterized by both low carbon emissions and high efficiency. This work involved an initial technical evaluation employing a custom-built, lab-scale apparatus. The optimum parameters determined through this assessment were a plasma input voltage of 40 V combined with a subsequent reaction temperature of 240 °C. Operation at these specified parameters yielded a CO₂ conversion of 48%, with the methanol selectivity and production rate reaching 40% and 502 g_MeOH${·\mathrm{kg}}_{\mathrm{cat}}^{-1}$·h⁻¹, respectively. Furthermore, industrial-scale process design and scale-up were performed, accompanied by process simulation using Aspen Plus and a subsequent techno-economic evaluation. The results indicate that, compared to the conventional direct CO₂ hydrogenation process, the proposed cascade route can reduce the capital investment by approximately 17%. Full article

In the current climate change context and the potential to extend exotic crops in Romania, sweet potato could become an option for extensive areas with optimum ecophysiological conditions to provide economic and ecological benefits and assure food security. This study aimed to validate the suitability, photosynthetic performance, yield productivity, and sugar content of three sweet potato cultivars, KSC, Koretta, and Hayanmi, in Central Romania. Three key phenophases were selected: the beginning of flowering (P1), 50% tuber formation/full flowering (P2), and total tuber formation/leaves and stems bleached and dry (P3), respectively. At the beginning of flowering, extreme heat and moisture stress showed a reduced effect on the sweet potato development and photosynthetic parameters. The only exception was the assimilation rate for Hayanmi, which was markedly lower, with the highest relative chlorophyll content and leaf dry biomass. Koretta registered increased values for stomatal features. A higher tuber weight was registered for Hayanmi in P2 due to slightly increased rainfall and elevated evapotranspiration. In P3, the temperatures dropped sharply, rainfall exceeded evapotranspiration, and KSC accumulated a seven times higher value for tuber weight. The total biomass was 2–3 times higher for KSC in P3. Sugar content was negatively correlated with tuber weight, and Hayanmi had 1% higher values compared with KSC and Koretta. Sweet potato showed a variety-specific response to ecophysiological conditions, and for each variety, these physiological features suggest potential advantages for different cropping scenarios. Full article

The increasing environmental impact of the textile industry has led to the development of sustainable production methods. One of the effective approaches is the use of recycled fibers, which helps to save resources, reduce carbon emissions, and support the circular economy. This study investigates the feasibility of producing durable upholstery fabrics incorporating recycled polypropylene (r-PP) and virgin polypropylene (v-PP). Filament yarns with varying r-PP/v-PP blend ratios, produced by the melt spinning process, were used as weft yarns, while commercially available virgin polyester filament yarns were employed in the warp direction for all fabric samples. Performance tests in accordance with the standards were applied to the fabrics and the results were also evaluated statistically. The results show that acceptable performance is achieved in some mechanical properties if similar blend ratios and production parameters are used. In the study, an optimization model was developed to maximize the weft breaking strength using the equations obtained from the regression analyses. With the help of the mathematical model created, the values of other physical and performance properties of the fabric depending on the maximum breaking strength value could be estimated without the need for trial production. The model was solved using Lingo 18.0 optimization software. The solution of the model revealed that the optimum weft yarn blend ratio is 10/90 r-PP/v-PP, and the maximum weft breaking strength value is 562.45 N. Full article

Addressing the challenges of low resource-use efficiency and supply–demand mismatch in Hami melon production, this study investigated the interactive effects of irrigation and fertilization to identify an optimal regime that balances yield, water conservation, and resource-use efficiency (i.e., water use efficiency and fertilizer partial factor productivity). A greenhouse experiment was conducted in Hami, Xinjiang, employing a two-factor design with five irrigation levels (W1–W5: 60–100% of full irrigation) and three fertilization levels (F1–F3: 80–100% of standard rate), replicated three times. Growth parameters, yield, water use efficiency (WUE), and partial factor productivity of fertilizer (PFP) were evaluated and comprehensively analyzed using the entropy-weighted TOPSIS method, regression analysis, and the NSGA-II multi-objective genetic algorithm. Results demonstrated that irrigation volume was the dominant factor influencing growth and yield. The W4F3 treatment (90% irrigation with 100% fertilization) achieved the optimal outcome, yielding 75.74 t ha⁻¹—a 9.71% increase over the control—while simultaneously enhancing WUE and PFP. Both the entropy-weighted TOPSIS evaluation (C = 0.998) and regression analysis (optimal irrigation level at w = 0.79, ~90% of full irrigation) identified W4F3 as superior. NSGA-II optimization further validated this, generating Pareto-optimal solutions highly consistent with the experimental optimum. The model-predicted optimal regime for greenhouse Hami melon in Xinjiang is an irrigation amount of 3276 m³ ha⁻¹ and a fertilizer application rate of 814.8 kg ha⁻¹. This regime facilitates a 10% reduction in irrigation water and a 5% reduction in fertilizer input without compromising yield, alongside significantly improved resource-use efficiencies. Full article

This study investigated the optimisation of roselle (Hibiscus sabdariffa L.) leaf tisane formulation using response surface methodology (RSM), targeting total phenolic content (TPC), ferric reducing antioxidant power (FRAP), and DPPH radical scavenging activity as quality indicators. A face-centred central composite design was employed to evaluate dose effects (0.5–2.5 g) and infusion time (5–15 min). Multi-response optimisation using the desirability function identified 1.81 g dose and 5 min infusion as the optimum condition, yielding predicted values of 24.46 mg GAE/100 mL (TPC), 61.07 µmol Fe²⁺/100 mL (FRAP), and 80.47% (DPPH), with a composite desirability score of 0.64. Validation experiments confirmed strong predictive accuracy, with deviations of 0.80% (FRAP) and 3.92% (DPPH), and a modest deviation of 13.2% (TPC), acceptable within complex food matrices. The findings demonstrate that short infusion times are sufficient to extract key bioactives, ensuring consumer convenience and energy efficiency, while valorising roselle leaves as an underutilised by-product into a sustainable functional beverage. Future studies should address sensory acceptance, stability, and bioavailability to support industrial applications further. Full article

Soapstock (SS), a by-product of vegetable oil refining, is a promising source of a mixture of mono-, di-, triglycerides, and free fatty acids (MDTG-FFA), a valuable feedstock for biodiesel production. In this study, the selective extraction of MDTG-FFA from SS using green solvents (ethyl acetate, ethyl formate, methyl acetate, isopropyl acetate, and isobutanol) was investigated. Ethyl acetate showed the highest efficiency, allowing the elimination of the phosphatide (PL) precipitation step with acetone. The process optimization was carried out by response surface methodology with central composite design. Statistical analysis confirmed the significance of the obtained models: F-values were 4.55 (p = 0.013) for MDTG-FFA and 9.62 (p = 0.00074) for PL. Regression analysis revealed a good fit of the experimental data with quadratic models for MDTG-FFA and PL, with coefficients of determination (R²) of 0.804 and 0.897, respectively. The optimum extraction parameters were a solvent-to-dry-matter-of-SS ratio 5:1, time 10.2 min, and initial extraction temperature 21.7 °C. Under these conditions, maximum MDTG-FFA yields of 12.6% and 13.4% were achieved for the two batches of SS, respectively, with minimum PL yields of 0.02% and 0.1%. The obtained MDTG-FFA extracts rich in free fatty acids represent a promising feedstock for biodiesel production. The proposed method provides a rational, resource-efficient, and environmentally preferable extraction of valuable components from SS. Full article

Women of reproductive age, especially those with polycystic ovarian syndrome (PCOS), often use glucagon-like peptide-1 receptor agonists (GLP-1RAs) to improve their metabolic functions. A growing body of evidence suggests that GLP-1R signaling may directly affect ovarian physiology, influencing granulosa cell proliferation, survival pathways, and steroidogenic production, in addition to its systemic metabolic effects. Nonetheless, there is a limited comprehension of the molecular mechanisms that regulate these activities and their correlation with menstrual function, reproductive potential, and assisted reproduction. This comprehensive review focuses on ovarian biology, granulosa cell signaling networks, steroidogenesis, and translational fertility outcomes, integrating clinical, in vivo, and in vitro information to elucidate the effects of GLP-1 receptor agonists on reproductive health. We conducted a thorough search of PubMed, Scopus, and Web of Science for randomized trials, prospective studies, animal models, and cellular experiments evaluating the effects of GLP-1RA on reproductive or ovarian outcomes, in accordance with PRISMA criteria. The retrieved data included metabolic changes, androgen levels, monthly regularity, ovarian structure, granulosa cell growth and death, FOXO1 signaling, FSH-cAMP-BMP pathway activity, and fertility or IVF results. Clinical trials shown that GLP-1 receptor agonists improve menstrual regularity, decrease body weight and central adiposity, increase sex hormone-binding globulin levels, and lower free testosterone in overweight and obese women with PCOS. Liraglutide, when combined with metformin, significantly improved IVF pregnancy rates, whereas exenatide increased natural conception rates. Mechanistic studies demonstrate that GLP-1R activation affects FOXO1 phosphorylation, hence promoting granulosa cell proliferation and anti-apoptotic processes. Incretin signaling altered steroidogenesis by reducing the levels of StAR, P450scc, and 3β-HSD, so inhibiting FSH-induced progesterone synthesis, while simultaneously enhancing BMP-Smad signaling. Animal studies demonstrated both beneficial (enhanced follicular growth, anti-apoptotic effects) and detrimental results (oxidative stress, granulosa cell death, uterine inflammation), indicating a context- and dose-dependent response. GLP-1 receptor agonists influence female reproductive biology by altering overall physiological processes and specifically impacting the ovaries via FOXO1 regulation, steroidogenic enzyme expression, and BMP-mediated FSH signaling. Preliminary clinical data indicate improved reproductive function in PCOS, as seen by increased pregnancy rates in both natural and IVF cycles; nevertheless, animal studies reveal a potential risk of ovarian and endometrial damage. These results highlight the need for controlled human research to clarify reproductive safety, molecular pathways, and optimum therapy timing, particularly in non-PCOS patients and IVF settings. Full article

To reconcile the intensifying trade-off between chronic water scarcity and escalating forage demand in the Yellow River Basin, this study optimized integrated irrigation and fertilization regimes for silage maize. Leveraging the AquaCrop model, validated by 2023–2024 field experiments and a 35-year (1990–2024) meteorological dataset, we systematically quantified the impacts of multi-factorial water–fertilizer–heat stress under drip irrigation with mulch (DIM) and shallow-buried drip irrigation (SBDI). Model performance was robust, yielding high simulation accuracy for soil moisture (RMSE < 3.3%), canopy cover (RMSE < 3.95%), and aboveground biomass (RMSE < 4.5 t·ha⁻¹), with EF > 0.7 and R² ≥ 0.85. Results revealed distinct stress dynamics across hydrological scenarios: mild temperature stress predominated in wet years, whereas severe water and fertilizer stresses emerged as the primary constraints during dry years. To mitigate these stresses, a medium fertilizer rate (555 kg·ha⁻¹) was identified as the stable optimum, while dynamic irrigation requirements were determined as 90, 135, and 180 mm for wet, normal, and dry years, respectively. Comparative evaluation indicated that DIM achieved maximum productivity in wet years (aboveground biomass yield 70.4 t·ha⁻¹), whereas SBDI exhibited superior “stable yield–water saving” performance in normal and dry years. The established “hydrological year–irrigation method–threshold” framework provides a robust decision-making tool for precision management, offering critical scientific support for the sustainable, high-quality development of livestock farming in arid regions. Full article

The final stage of the drinking water treatment process yields two distinct outputs: treated water and the resulting sludge. This sludge is composed of raw water impurities, coagulation and flocculation agents, and various other additives. In any volume of processed drinking water, the continuous production of sludge is not negligible, leading to a significant environmental impact. This is particularly concerning when aluminium-based agents are used, as these compounds are strongly implicated in potential detrimental health risks. This situation is significantly worsened when raw water temperature approaches zero, as the treatment process efficiency is greatly diminished. Drinking water treatment at low temperatures faces a culmination of adverse effects, including a lower rate of hydrolysis and a reduced floc size, both of which negatively impact sedimentation. An effective strategy for suppressing the high dosing of chemicals is the suitable choice of ratio between acidity and the basicity of the treated water. Simply maintaining the pH value that was optimised for higher temperatures is detrimental, leading to, among other issues, increased sludge accumulation. Therefore, attention should instead be concentrated on the pOH value. A simple algebraic relation is proposed for converting the optimised pH value for higher temperatures to an optimum value for more moderate or low-temperature conditions. The application of this method results in a reduction in the amount of chemical agents required and consequently a reduction in the volume of sludge produced. Full article

The oxidation of chlorophenolic compounds is essential for converting these persistent and toxic pollutants into less harmful products, thereby reducing their environmental and health impacts. In this study, a p-coumaric acid ester derivative was employed as the starting material to synthesize the corresponding phthalonitrile precursor (EnCA-CN), followed by the preparation of non-peripherally substituted Co(II) and Cu(II) phthalocyanine complexes (EnCA-Copc and EnCA-CuPc). These complexes were subsequently characterized using a range of spectroscopic techniques and designed to engage in π–π interactions with graphitic carbon nitride to form efficient photocatalytic materials. The structures of the two effective catalysts were characterized by FT-IR, SEM, and XRD analyses, after which their photocatalytic performance and recyclability in the degradation of 2-chlorophenol, 2,3-dichlorophenol, and 2,3,6-trimethylphenol were evaluated. The optimum catalyst loading for the MPc/g-C₃N₄ composites was determined to be 0.5 g/L, yielding the highest photocatalytic efficiency. The EnCA-CoPc/g-C₃N₄ catalyst achieved 90.8% product selectivity and 82.6% conversion in the oxidation of 2-chlorophenol, whereas the EnCA-CuPc/g-C₃N₄ catalyst exhibited approximately 80.0% pollutant removal. The degradation efficiencies followed the order 2-CP > 2,3-DCP > 2,3,6-TCP, with benzoquinone derivatives identified as the major oxidation products. In recyclability tests, both catalysts retained more than 50% of their activity after five cycles; EnCA-CoPc/g-C₃N₄ maintained 68% conversion in the 5th cycle, while EnCA-CuPc/g-C₃N₄ retained 60% conversion in the 4th cycle. Full article

In this study, the advanced oxidation system of peroxymonosulfate (PMS) was activated by molybdenite supported on biochar (Molybdenite@BC), and the degradation efficiency, influencing factors and degradation mechanism of sulfamethoxazole (SMX) were explored through experiments. Molybdenite@BC, a composite material used in the study, was prepared by pyrolysis at high temperature. The optimum pyrolysis temperature was 700 °C, and the mass ratio of molybdenite to biochar (BC) was 1:3. By changing dosage of Molybdenite@BC, pH value, initial concentration of PMS, and the types and concentration of inorganic anions, the effects of various factors on SMX degradation were systematically studied. The optimum reaction conditions of the Molybdenite@BC/PMS process were as follows: Molybdenite@BC dosage was 100 mg/L, PMS concentration was 0.2 mM, pH value was 6.9 ± 0.2, and initial SMX concentration was 6 mg/L. Under these conditions, the degradation rate of SMX was 97.87% after 60 min and 99.06% after 120 min. The material characterization analysis showed that Molybdenite@BC had a porous structure and rich active sites, which was beneficial to the degradation of pollutants. After the composite material was used, the peaks of MoO₂ and MoS₂ became weaker, which indicated that there was some loss of molybdenum from the material structure. Electron paramagnetic resonance (EPR) and radical quenching experiments revealed that Molybdenite@BC effectively catalyzed PMS to generate various reactive oxygen radicals and non-free radicals, including singlet oxygen (¹O₂), hydroxyl radical (^•OH), sulfate radical (SO₄^•−) and superoxide radical (^•O₂⁻). ¹O₂ played a leading role in the degradation of SMX, while ^•OH and SO₄^•− had little influence. The intermediate products of the degradation of SMX in Molybdenite@BC/PMS system were analyzed by liquid chromatography–tandem mass spectrometry (LC–MS). The results showed that there were nine main intermediate products in the process of degradation, and the overall toxicity tended to decrease during the degradation of SMX. The degradation path analysis showed that with the gradual ring opening and bond breaking of SMX, small molecular compounds were generated, which were finally mineralized into H₂O, CO₂, CO₃²⁻, H₂SO₄ and other substances. The research results confirmed that the Molybdenite@BC/PMS process provided a feasible new method for the degradation of SMX in water. Full article

Prescribed fire is a common habitat management tool for white-tailed deer (Odocoileus virginianus Zimm.) that can influence browse quantity and quality. We tested effects of time since burn and number of burns within a decade on browse forage productivity in forested stands in the Pineywoods ecoregion of Texas. We utilized 46 plots on sites managed by the United States Forest Service National Forests and Grasslands in Texas, The Nature Conservancy, and a private landowner. Preferred browse forage species were sampled and analyzed for nutrient content, and years since last prescribed burn and the number of burns within the last 10 years were compared. Deer had strong preferences for plants with greater crude protein, magnesium, and potassium. Crude protein and net energy for maintenance were generally greater with a more frequent burn regime. Different nutrients peaked at different burn intervals. Frequent fires resulted in higher crude protein ($\overline{\mathrm{x}}$ = 14.0%) than infrequently burned sites. At four burns per decade, net maintenance energy was highest ($\overline{\mathrm{x}}$ = 0.6 Mcal Kg⁻¹). Linear regression models only explained between 28% and 41% of utilization, although some preferences for some nutrients, such as crude protein and magnesium, were detected. To improve the nutritional carrying capacity for white-tailed deer, long-term management regimes should incorporate site-specific burn plans that include fire frequency. Timing and burn frequency are critical to achieving optimum results that improve browse forage availability, quality, and utilization. Full article

Chilli (Capsicum annuum) is a popular spice and vegetable crop of significant economic importance that is cultivated worldwide in warm and humid climatic zones. Although chilli is a thermophilic crop, its quality and yield potential are significantly affected due to various abiotic factors, including extremely fluctuating temperatures beyond the optimum temperatures (18–30 °C). Global warming and anthropogenic activities lead to adverse climatic changes, imposing severe stress on growth, development, and productivity. High temperatures above 43–45 °C adversely affect chilli crops, especially during the reproductive stages, by causing immature fruit dropping, poor seed vigour, reduced number of flowers, flower abscission, aborted reproductive organs, reduced fruit set, and significant yield loss by 50%. Therefore, to reduce quantitative and qualitative losses, heat management is necessary from April to June in Pakistan, when the temperature rises beyond 40 °C. For heat management, the hybridisation of heat-resilient and high-yielding genotypes to develop heat-tolerant high-yielding hybrids appears to be a rational approach. These genetically improved hybrids inherit such characteristics that assist in maintaining vigorous growth, fruit quality, and stable yield without significant yield losses even under heat-stressed conditions. Hence, the thermotolerant chilli hybrids developed through hybridisation help to satisfy the escalating demand for chilli and guarantee the financial stability of farmers. Full article

Cu and Cr are the essential alloying elements for low-Ni stainless steels. An effective and economical method has been developed for the direct production of Cu-Cr-Fe master alloys through the synergistic reduction of chromite and copper smelting slag. The smelting conditions for synergy reduction were systematically investigated by combining thermodynamic calculations and high-temperature experiments. The results indicate that synergistic reduction drives the reactions of Cr₂O₃, FeO, and Cu₂O with carbon in a positive direction, which can increase their recovery and decrease the flux and fuel costs. The optimum slag composition was identified to control the (CaO + MgO)/(SiO₂ + Al₂O₃) ratio between 0.62 and 0.72, where the slag is fully liquid, resulting in an efficient separation of the alloy from the slag. At 1550 °C, with 50 wt% chromite and 50 wt% copper smelting slag as raw materials, a Cu-Cr-Fe alloy containing 5.2 wt% Cu, 28.6 wt% Cr and 57.9 wt% Fe was produced, while the contents of FeO, Cu₂O, and Cr₂O₃ in the final slag were 0.057 wt%, 0.059 wt%, and 0.23 wt%, respectively. Full article