Search Results (832)

This study systematically investigates the mechanistic effects of multifactor interactions (including soil properties, climatic conditions, and cultivation practices) on the productivity parameters (grain yield, stover yield, dry biomass, harvest index) of maize cultivars of different maturity groups in the arid region of Xinjiang, China. Twelve representative maize-growing counties were selected as study sites, where we collected maize samples to measure HI, grain yield, stover yield, and soil physicochemical properties (e.g., organic matter content, total nitrogen, and available phosphorus). Additionally, climate data (effective accumulated temperature) and agronomic parameters (planting density) were integrated to comprehensively analyze the interactive effects of multiple environmental factors on HI using structural equation modeling (SEM). The results demonstrated significant varietal differences in HI across maturity periods. Specifically, early-maturing cultivars showed the highest average HI (0.58), significantly exceeding those of medium-maturing (0.55) and late-maturing varieties (0.54). Environmental analysis further revealed that soil phosphorus content (both available and total phosphorus), elevation, and organic matter content significantly positively affected HI, whereas soil bulk density and electrical conductivity exhibited negative impacts. Notably, HI exhibited a strong negative correlation with stover yield (R² = 0.49), but remained relatively stable across different dry matter (DM) and grain yield levels. Despite the strong positive correlation between DM and grain yield (R² = 0.81), the relative stability of HI suggests that yield improvement requires balanced optimization of both DM and partitioning efficiency. This study provides crucial theoretical foundations for optimizing high-yield maize cultivation systems, regulating fertilizer application rates and their ratios, and improving the configuration of planting density in arid regions. These findings offer practical guidance for sustainable agricultural development in similar environments. Full article

Water scarcity in arid regions poses a severe threat to agricultural sustainability, necessitating optimized irrigation strategies. This study investigates the cumulative impacts of long-term irrigation deficits on soil quality, microbial diversity, and maize yield in the arid maize fields of Xinjiang, China, where consistent irrigation patterns have been maintained over multiple years. Seven sites were monitored from April 2023 to March 2024, with a single end-of-cycle sampling in March 2024. Using the Irrigation Water Deficit Index (IWDI), the sites were classified into low (LD, 16.37–22.30%), moderate (MD, 30.54–38.10%), and high drought (HD, 47.49–50.00%) categories. The findings reveal that long-term consistent irrigation deficits exacerbate soil salinization, compaction, and nutrient loss, with organic matter declining significantly under HD conditions. Bacterial richness increased by ~6% under HD, driven by stress-tolerant taxa, while fungal diversity decreased by 14–50%, impairing nutrient cycling functions critical for soil health. The Soil Quality Index (SQI) and maize yield declined with drought severity (LD > MD by 26.18% and 21.05%; LD > HD by 45.02% and 13.13%), highlighting the pivotal role of sustained irrigation patterns in maintaining productivity. These results underscore the need for tailored irrigation management in arid regions, such as precision drip irrigation, to mitigate soil degradation and sustain maize yields, providing a scientific foundation for optimizing water use efficiency in water-scarce agroecosystems under long-term irrigation regimes. Full article

Background/Objectives: Propranolol HCl (PPH), a nonselective beta-adrenergic receptor blocker, is employed as an anti-hypertensive, anti-anginal, anti-arrhythmic, and anti-migraine agent. Given its utility in chronic conditions, developing a sustained-release dosage form becomes imperative to optimize therapeutic outcomes while enhancing patient adherence and minimizing side effects. In this study, we employed a widely adopted matrix-based system to develop PPH sustained-release (PPH-SR) matrix tablets, ensuring the uniform dispersion of the drug within the polymeric matrix to regulate its release rate. Methods: Utilizing cellulose-based polymers, specifically HPMC K100M and ethyl cellulose (EC), as matrix formers, nine different formulations were prepared at varying drug-to-polymer ratios. We employed a wet granulation method, followed by compression of the dried granules, to fabricate round-shaped biconvex PPH-SR tablets. Results: Among these different formulations, formulation 2 (F2), comprising 40 mg PPH and 50 mg HPMC K100M (along with other excipients), showed excellent flowability, as evidenced by Carr’s index and angle of repose values of 12.50 and 28.50, respectively. Additionally, the mechanical properties of F2 tablets showed a hardness of 12.34 ± 0.91 KP, an average weight of 200.45 ± 1.87 mg, with a friability of 0.20%, and a content uniformity of 98.36%. Moreover, in vitro release characteristics of F2 tablets demonstrated a sustained-release behavior, with 94.3 ± 10.2% drug release over 24 h. A comparative analysis with marketed tablets yielded similarity and dissimilarity factors of 64 and 8, respectively. Furthermore, the release profile of F2 exhibited a high degree of linearity with the Korsmeyer–Peppas model (R² of 0.977), showcasing its reliability and predictability. Conclusions: In essence, this in-house developed PPH sustained-release formulation can improve patient adherence, reduce side effects, and improve therapeutic outcomes. These results align with our objective of enhancing the therapeutic efficacy of PPH and affirm the broader relevance of innovative formulation strategies in addressing the challenges of chronic disease management. Full article

This study evaluated the chemical properties of phosphocompost extracts and their effectiveness in inducing tomato seedlings resistance to Meloidogyne javanica. Phosphocomposts: Sugar beet phosphocompost (PC-SB: CP2), green waste phosphocompost (PC-GW: CP3), and olive mill waste phosphocompost (PC-OMW: CP4), were utilized to produce compost water extracts at concentrations of 1:5, 1:10, 1:20, and 1:100 g:mL and then applied as soil drenches for tomato seedlings one-week post-inoculation. The CP2 extract applied at a 1:5 dilution led to marked improvements in growth parameters, with plant height increasing by over 52.2%, shoot fresh biomass rising by approximately 52.44%, and shoot dry biomass showing a gain of 62.21%. Root biomass also rose by 33%. Chlorophyll a increased with CP4 at 1:5 and 1:100 (41.05% and 37.32%), chlorophyll b increased with CP3 at 1:5 and 1:10 (22.34% and 7.59%), while carotenes showed no variation. Polyphenols rose by 86.45–91.01% with CP2 from 1:5 to 1:20, and flavonoids increased by 64.90% with CP4 at 1:10. CP2 diminished the ultimate M. javanica population and reproduction factor by 171.43%, while CP4 at 1:20 decreased egg masses by 151.94%. The root gall index showed no variation. The chemical composition of phosphocomposts revealed that the strategic incorporation of diverse organic improvers (10%) in phosphocomposts yielded distinct nutrient signatures, with sugar beet waste enhancing PO₄³⁻ (12.91 mg/L) and secondary macronutrients, green waste optimizing NO₃⁻ (69.91 mg/L) and SO₄²⁻ (62.70 mg/L) availability, and olive mill waste producing superior micronutrient concentrations alongside dominant Ca (24.21 mg/L), K (392.50 mg/L), and P (9.17 mg/L) levels. Overall, the results underscore the potential of phosphocompost extracts as a viable, low-cost, and eco-friendly alternative to synthetic nematicides, offering a sustainable and resilient approach to M. javanica control while enhancing tomato plant growth. Full article

This study investigates the impact of climate variability on wheat production in Algeria’s semi-arid interior plains from 2014 to 2024, aiming to curb the challenges of rainfed wheat cultivation, optimize irrigation, and improve water productivity. The Soil–Water–Atmosphere–Plant (SWAP) model-driven approach refined irrigation scheduling to mitigate climate-induced losses and improve resource efficiency. Using historical climate data, soil properties, and wheat growth observations from the experimental farm of the Technical Institute for Field Crops, the SWAP model was calibrated and validated using one-factor-at-a-time sensitivity analysis, achieving a coefficient of determination (R²) of 0.93 and a Normalized Root Mean Squared Error (NRMSE) of 17.75. Two drought-based irrigation indices, Soil Moisture Drought Index (SMDI) and Crop Water Stress Index (CWSI), guided adaptive irrigation strategies, showing a significant reduction in crop failure during drought periods. Results revealed a strong link between rainfall variability and wheat yield. Adopting a 9-day irrigation interval could increase water productivity to 18.91 kg ha⁻¹ mm⁻¹, enhancing yield stability under varying climatic conditions. The SMDI approach maintained soil moisture during extreme drought, while CWSI optimized water use in normal and wet years. This study integrates SMDI and CWSI into a validated irrigation framework, offering data-driven strategies to enhance wheat production resilience. Findings support sustainable water management and provide practical insights for policymakers and farmers to refine irrigation planning and climate adaptation, contributing to long-term agricultural sustainability. Full article

Securing food for an expanding population in the face of climate change necessitates a transformation of global food systems towards sustainability, emphasizing nutritional quality and environmental consequences. This research assessed eight cytoplasmic male sterility-based cabbage hybrids and two controls across nine environments from 2020 to 2022 to improve cabbage output and sustainability. Essential characteristics, including head weight, compactness, and yield, were examined, revealing considerable heterogeneity and elevated heritability for features such as ascorbic acid content (98.41%) and net head weight (86.12%). Yield had a favorable correlation with characteristics such as net head weight and harvest index. Path coefficient research revealed that gross and net head weight have the most significant direct effects on yield. Heterosis research indicated UHF-CAB-HYB-1 had the highest significant positive heterosis in yield compared to the standard checks, Pusa Hybrid-81 and Pusa Cabbage-1, across all nine conditions. The results underscore the need to identify essential characteristics for the creation of high-yield, hardy cabbage hybrids, in accordance with sustainable agriculture and food security objectives. Full article

Cotton root systems sustain photosynthesis by nutrient uptake and coordinate with above-ground growth to influence yield. This study explored the effects of fulvic acid (FA) and phosphorus (P) fertilizers on the relationships between cotton photosynthetic capacity (CAP) and root carbohydrate metabolism. A field experiment was conducted including five treatments: no P fertilizer (CK), 105 kg P₂O₅ ha⁻¹ (P1), 150 kg P₂O₅ ha⁻¹ (P2), 105 kg P₂O₅ ha⁻¹ + FA (FP1), and 150 kg P₂O₅ ha⁻¹ + FA (FP2). Results found that FP2 showed the most significant advantage, ensuring a suitable leaf area index (LAI) and cotton fractional interception of photosynthetically active radiation (IPAR) and consequently maintaining a high CAP. Compared with FP2, FP1 resulted in an increase in the boll loading of the root system (BLR) by 8.1% and the boll capacity of the root system (BCR) by 9.3%. From the peak flowering stage to the peak boll setting stage, sucrose and starch contents in FP1 were 6.2–19.2% and 26.5–27.9% lower than those in FP2, respectively. Conversely, fructose and glucose contents in FP1 were 6.4–10.8% and 7.2–8.8% higher than in FP2. The cotton reproductive organ biomass was increased by 11.1% and 14.7% relative to FP2. Moreover, FP1 achieved the highest yield, with an increase of 8.5% and 11.0% compared with P2 and FP2, respectively. Taken together, our study suggests that application of FP1 (105 kg P₂O₅ ha⁻¹ + FA) could be a proper P fertilization method in cotton production of saline-alkali and arid regions. Full article

Today, open-source Cloud Computing platforms are valuable for geospatial image analysis while the combination of the Google Earth Engine (GEE) platform and new satellite launches greatly facilitate the monitoring of national-scale lake Water Quality (WQ). The main aim of this research is to assess the transferability and performance of published general, natural-only and artificial-only lake WQ models (Chl-a, Secchi Disk Depth-SDD- and Total Phosphorus-TP) across Greece’s WFD (Water Framework Directive) lake sampling network. We utilized Landsat (7 ETM +/8 OLI) and Sentinel 2 surface reflectance (SR) data embedded in GEE, while subjected to different atmospheric correction (AC) methods. Subsequently, Carlson’s Trophic State Index (TSI) was calculated based on both in situ and modelled WQ values. Initially, WQ models employed both DOS1-corrected (Dark Object Subtraction 1; manually applied) and GEE-retrieved respective SR data from the year 2018. Double WQ values per lake station were inserted in a linear regression analysis to harmonize the AC differences, separately for Landsat and Sentinel 2 data. Yielded linear equations were accompanied by strong associations (R² ranging from 0.68 to 0.98) while modelled and GEE-modelled TSI values were further validated based on reference in situ WQ datasets from the years 2019 and 2020. The values of the basic statistical error metrics indicated firstly the increased assessment’s accuracy of GEE-modelled over modelled TSIs and then the superiority of Landsat over Sentinel 2 data. In this way, the hereby adopted methodology was evolved into an efficient lake management tool by providing managers the means for integrated sustainable water resources management while contributing to saving valuable image pre-processing time. Full article

Albi-boric argosols, mainly distributed in the Sanjiang Plain of Heilongjiang Province, China, accounting for over 80% of the total cultivated land area, is characterized by a nutrient-deficient layer beneath black soil. This study addresses the challenges of modern agriculture by investigating the impact of straw incorporation on soil dissolved organic carbon (DOC) and its structures in albi-boric argosols, profiles, using fluorescence excitation–emission spectroscopy and parallel factor analysis (PARAFAC). Three treatments were applied: undisturbed albi-boric argosols (C), mixed albic and illuvium layers (M), and mixed albic and illuvium layers with straw (MS). Results showed that the yield of M and MS increased by 9.9% and 13.0%, respectively. There was a significant increase in DOC content, particularly in the MS treatment. Fluorescence index (FI) values ranged from 1.65 to 1.86, biological index (BIX) values were less than 1, and humification index (HIX) values were below 0.75, indicating a mix of plant and microbial sources for DOC, autochthonous characteristics, and weaker humification degree. PARAFAC identified two/three individual fluorophore moieties that were attributed to fulvic acid substances, soluble microbial products, and tyrosine-like substances, with microbial products as the dominant component. This study demonstrates the effect of improving barrier soil and maintaining sustainable agriculture by enhancing soil quality. Full article

The Yangtze River Delta (YRD) region, located inside the Yangtze River Basin, functions as a vital ecological and economic area in China, with its natural environment directly impacting human existence. This study seeks to elucidate the spatial and temporal evolution of rural resilience in the Yangtze River Delta region and its underlying mechanisms by establishing a comprehensive assessment framework for rural resilience, thereby offering a scientific foundation and policy guidance for the region’s sustainable development. The research first established the DPSIR (driving force–pressure–state–impact–response) assessment index system. Subsequently, the entropy weighting method and TOPSIS were utilized to assess and rank the rural resilience levels in the Yangtze River Delta region (Shanghai, Jiangsu, Zhejiang, and Anhui) from 2012 to 2022. Ultimately, partial least squares structural equation modeling (PLS-SEM) was employed to examine the intrinsic logical relationships among the five dimensions of the DPSIR framework and to extract conclusions. The study effectively met the goals of SDG 7 (clean water and sanitation), SDG 8 (decent work and economic growth), and SDG 11 (sustainable cities and communities). The research indicated that (1) the resilience level in the Yangtze River Delta region initially declined, then increased, and eventually attained a condition of stabilization. Changes in the “driving force”, influenced by the “response level” and environmental “pressure”, have affected the resilience level of rural areas. There is heterogeneity in the assessment values and ranges of change among provinces, with the “impact” component exhibiting the most substantial evaluation value. The findings yield policy recommendations for the implementation of diverse regional governance, the establishment of connectivity mechanisms, the customization of strategies to address the specific deficiencies of each province, and the systematic enhancement of rural resilience. Full article

The China Baijiu Golden Triangle (BGT) serves as the core production hub of China’s Baijiu industry, where the ecological environment plays a pivotal role in ensuring the industry’s sustainable development. However, urbanization, industrial expansion, and climate change pose potential threats to the region’s vegetation dynamics. Utilizing Landsat remote sensing data from 2002 to 2022, this study integrates Theil–Sen trend analysis, the Mann–Kendall (MK) test, coefficient of variation (CV) analysis, and the Geodetector model (GD model) to investigate the spatiotemporal evolution of the Normalized Difference Vegetation Index (NDVI) and its underlying driving mechanisms within the BGT. The findings reveal an overall upward trend in vegetation NDVI, with the annual mean NDVI increasing from 0.45 to 0.67, corresponding to a growth rate of 0.49%. Spatially, areas of high vegetation cover are predominantly located in mountainous forest zones with favorable ecological conditions, whereas regions of low vegetation cover are concentrated in zones of urban expansion. Precipitation and topographic factors (elevation and slope) emerge as the primary natural drivers of vegetation change, while land use change and the night-time light index stand out as the most influential human-induced factors. Further analysis uncovers a nonlinear interactive enhancement effect between natural and anthropogenic factors, with the interaction between the night-time light index and precipitation being particularly pronounced. This suggests that urbanization not only directly impacts vegetation but may also exert indirect effects on the ecosystem by altering regional hydrological and climatic processes. The results indicate that ecological protection policies in the BGT have yielded some success; however, vegetation fragmentation and ecological pressures stemming from urban expansion remain significant challenges. Moving forward, optimizing land use policies and promoting eco-friendly development models will be essential to achieving ecosystem stability and sustaining industrial growth. Full article

This study investigates the structural behavior of reinforced concrete slabs and culverts using newly developed tubular rebars as a replacement for conventional deformed rebars. Tubular rebars, which are approximately 50% lighter and exhibit twice the tensile strength of standard deformed rebars, were evaluated through experimental tests and finite element analysis (FEA). Results showed that tubular rebars achieved up to 44.46% higher yield strength and up to 25.31% higher ultimate strength in statically determinate slabs compared to conventional rebars, though with reduced ductility. In statically indeterminate configurations such as fixed slabs and box culverts, the ductility performance improved significantly, with ductility index differences reduced to less than 3%. Hybrid reinforcement combining tubular and deformed rebars also enhanced performance, especially in compression zones. These findings demonstrate that tubular rebars can be a sustainable and structurally efficient alternative to conventional reinforcement when deflection control is ensured. Full article

Climate change is threatening the sustainability of crop yields due to an increasing frequency of extreme weather conditions, requiring timely agricultural monitoring. Remote sensing facilitates consistent and continuous monitoring of field crops. This study aimed to estimate alfalfa crop height through satellite images and machine learning methods within the Google Earth Engine (GEE) Python API. Ground measurements for this study were collected over three years in four Canadian provinces. We utilized Sentinel-2 data to obtain satellite imagery corresponding to the same timeframe and location as the ground measurements. Three machine learning algorithms were employed to estimate plant height from satellite images: random forest (RF), support vector regression (SVR), and extreme gradient boosting (XGB). The efficacy of these algorithms has been assessed and compared. Several widely used vegetation indices, for instance normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and normalized difference red-edge (NDRE), were selected and assessed in this study. RF feature importance was utilized to determine the ranking of features from most to least significant. Several feature selection strategies were utilized and compared with the situation where all features are used. We demonstrated that RF and XGB surpassed SVR when assessing test data performance. Our findings showed that XGB and RF could predict alfalfa crop height with an R² of 0.79 and a mean absolute error (MAE) of around 4 cm Our findings indicated that SVR exhibited the lowest accuracy among the three algorithms tested, with R² of 0.69 and an MAE of 4.63 cm. The analysis of important features showed that normalized difference red edge (NDRE) and normalized difference water index (NDWI) were the most important variables in determining alfalfa crop height. The results of this study also demonstrated that using RF and feature selection strategies, alfalfa crop height can be estimated with comparably high accuracy. Given that the models were fully trained and developed in Python (v. 3.10), they can be readily implemented in a decision support system and deliver near real-time estimations of alfalfa crop height for farmers throughout Canada. Full article

A detailed characterization of evapotranspiration (ET) patterns is of paramount importance for optimizing irrigation scheduling and enhancing water-use efficiency in the North China Plain. To delve into this, a two-season study was conducted at the National Experimental Station for Precise Agriculture in Beijing. Using 12 weighing lysimeters, the study compared two summer maize varieties with contrasting canopy sizes: Jingke 968 (JK), characterized by a large canopy, and CF 1002 (CF), with a small canopy. The comprehensive analysis yielded the following significant findings: (1) The daily average ET rates exhibited consistent trends across cultivars, yet with notable disparities in magnitude. JK consistently demonstrated higher water consumption throughout the growth seasons. In the first season, at the V13–R1 stage, the peak daily ET of JK and CF reached 5.91 mm/day and 5.52 mm/day, respectively. In the second season, during the R1–R3 stage, these values were 5.21 mm/day for JK and 5.22 mm/day for CF, highlighting the nuanced differences in water use between the varieties under varying growth conditions. (2) Regardless of canopy size, the hourly ET fluctuations across different growth stages followed similar temporal patterns. However, the most striking inter-varietal differences in ET emerged during the R1–R3 reproductive stages, when both cultivars had achieved peak canopy development (leaf area index, LAI > 4.5). Notably, the ET differences between JK and CF adhered to a characteristic diurnal “increase–decrease” pattern. These differences peaked during mid-morning (09:00–11:00) and early afternoon (13:00–15:00), while minimal divergence was observed at solar noon. This pattern suggests complex interactions between canopy structure, microclimate, and plant physiological processes that govern water loss over the course of a day. (3) Analysis of the pooled data pinpointed two critical time periods that significantly contributed to the cumulative ET differences between the varieties. The first period was from 12:00–17:00 during the R1–R3 (anthesis) stage, and the second was from 08:00–16:00 during the R3–R5 (grain filling) stage. JK maintained significantly higher transpiration rates (Tr) compared to CF, especially during the morning hours (09:00–12:00). On average, the Tr of JK exceeded that of CF by 5.3% during the pre-anthesis stage and by 16.0% during the post-anthesis stage. These observed Tr differentials strongly indicate that canopy architecture plays a pivotal role in modulating stomatal regulation patterns. Maize varieties with large canopies, such as JK, demonstrated enhanced morning photosynthetic activity, which likely contributed to increased transpiration. At the same time, both varieties seemed to employ similar midday water conservation strategies, possibly as an adaptive response to environmental stress. In summary, this study has comprehensively elucidated the intricate relationship between the leaf area index and the evapotranspiration of summer maize across multiple timescales, encompassing periodic, daily, and hourly variations. The findings provide invaluable data-driven insights that can underpin the development of precise and quantitative irrigation strategies, ultimately promoting sustainable and efficient maize production in the North China Plain. Full article

Sustainable valorization of lignocellulosic biomass, such as wheat straw (WS), into valuable products is key for efficient resource utilization. This study investigated an integrated strategy combining Irpex lacteus fermentation with subsequent alkali extraction to improve WS valorization. Alkali extraction parameters, including sodium hydroxide concentration, solid-to-liquid (S:L) ratio, temperature, and time, were optimized based on polysaccharide yield and purity. Optimal conditions were identified as 0.8 mol/L sodium hydroxide, a 1:25 S:L ratio, 90 °C, and 1 h, yielding 6.63% polysaccharides with 52.01% purity. Compared to untreated straw, the combined fermentation and alkali extraction treatment significantly altered the WS residue’s composition and structure, substantially reducing hemicellulose and acid detergent lignin while consequently increasing relative cellulose content. This enhanced cellulose accessibility resulted in a markedly improved glucose yield upon enzymatic hydrolysis, reaching 586 g/kg dry matter for the residue after combined treatment. Demonstrating a strong synergistic effect, this yield represents a 5.42-fold increase compared to untreated WS and a 3.30-fold increase compared to solely fermented straw. Analyses of SEM, FTIR, and XRD confirmed that the integrated treatment effectively disrupted the lignocellulosic structure by removing lignin and hemicellulose. This created a more porous morphology and increased cellulose exposure, which was deemed more critical for hydrolysis than the observed 18.58% increase in the cellulose crystallinity index relative to untreated straw. Thermogravimetric analysis further reflected these structural and compositional changes through altered thermal decomposition profiles. Therefore, integrating polysaccharide extraction with fungal fermentation is a highly effective strategy for improving resource efficiency in WS valorization. This approach enables the efficient co-production of valuable polysaccharides alongside significantly boosted platform sugar yields, offering a promising route towards more economically viable and sustainable WS utilization. Full article