Search Results (8,585)

Land use and land cover (LULC) dynamics are critical indicators of environmental transformation and anthropogenic pressure on regional landscapes. Mirzapur, located in the transitional zone between the Indo-Gangetic Plain and the Vindhyan uplands in Northern India, represents a region characterized by ecological sensitivity, mineral-based industries, agricultural dependency, and rapid infrastructural growth. In recent decades, Northern India has experienced accelerated urbanization, population pressure, land fragmentation, and environmental stress, thus making systematic LULC monitoring crucial for sustainable resource management and policy planning. The present study examines the spatio-temporal changes in land use and land cover in Mirzapur for the years 2004, 2014, and 2024. The study employed a cloud-based platform and the Random Forest algorithm for supervised classification of multi-temporal satellite imagery. LULC maps were generated and post classification comparison was used to assess changes across the selected years. Accuracy assessment was conducted using standard validation metrics, including the Kappa coefficient, to evaluate classification. From 2004 to 2024, urban areas expanded by a relative increase of 169.36%, largely through the conversion of cropland, although the overall cropland area showed a slight increase due to agricultural expansion in other parts of the study area. A slight increase in forest cover was also observed during this period. Water bodies and barren lands declined, indicating ecological stress in the region. These changes reflect rapid urbanization, demographic pressure, and evolving socio-economic activities within the district. The LULC classification achieved overall accuracies of 96.50% (2004), 97.52% (2014), and 96.08% (2024), showing the reliability of the generated maps. The study demonstrates the effectiveness of cloud-based geospatial analysis combined with a machine learning algorithms for long-term LULC monitoring and provides valuable insights for sustainable land management and regional planning. Full article

One of the most common dynamic phenomena occurring in surface waters is the transport of soluble and insoluble contaminants from various sources, such as industry and agriculture. A key concern associated with this transport is the rate at which contaminants migrate downstream to a point of interest, as well as their overall impact. In order to characterize the transport of contaminants in a body of surface water (in this case, a river), this study applied a one-dimensional advection–dispersion model that incorporated transient storage effects. This enabled the characterization of nutrient transport considering varying flow velocities along the river’s course. Adopting a more comprehensive, systemic approach enables a more holistic environmental application and facilitates parameterization of a considerably larger river than in previous case studies. The model’s innovation lies in using routinely monitored water quality constituents to evaluate their ability to inform the characterization of mixing conditions and solute transport in surface water streams. Its dynamic nature provides a reasonable approximation of the real system’s behavior over time. Finally, for management purposes, the proposed model can be replicated without extensive changes to its fundamental structure. Full article

This study investigates the automatic classification of crop phenological stages from low-altitude UAV RGB imagery. The dataset included 11,489 images of five crops: sunflower, rapeseed, soybean, wheat, and barley. The images were annotated using the Biologische Bundesanstalt, Bundessortenamt und Chemische Industrie (BBCH) scale, with labels corresponding to either single stages or stage ranges to reflect heterogeneous field conditions and transitional crop states. A pretrained ResNet18 model was adapted to the task using transfer learning. Training was conducted in two stages: first, the classification head was optimized while the backbone remained frozen; second, the entire network was fine-tuned. The model achieved strong internal test accuracy across all crops, with 100% test accuracy for rapeseed and barley, more than 99% for the remaining crops, and a mean accuracy of 99.73% under the studied survey conditions. The results also compare favorably with previously reported studies on UAV-based phenological classification. Overall, the findings support the potential of low-altitude UAV imagery and deep learning for localized phenological assessment of selected field zones in precision agriculture, while broader deployment requires validation across independent fields, seasons, regions, and survey conditions. Full article

Agri-food by-products and residues are increasingly being studied as raw materials for three-dimensional (3D) printing, especially to convert secondary streams into useful, more sustainable products. This review discusses recent advances in the use of these materials, focusing on how their origins, compositions, pretreatments, processing behaviors, and final applications are interconnected. Plant-, animal-, industrial-, and post-consumer-derived residues are considered, particularly when they provide fibers, proteins, polysaccharides, lipids, bioactive compounds, or biopolymers with technological value. The review also examines the main printing approaches used in this field, including extrusion-based printing, inkjet printing, sintering, and direct ink writing. Particular attention is given to factors that determine successful printing, including rheological behavior, viscosity, particle size, moisture content, structural stability after deposition, interlayer adhesion, and shape fidelity. Current applications range from functional foods and biodegradable or active packaging to biomaterials, controlled-release systems, biocomposites, construction materials, energy-related devices, textiles, and agricultural products. Although the reviewed studies show clear potential, most developments still face important barriers, including raw material variability, safety requirements, sensory acceptance, mechanical performance, scale-up, and regulatory uncertainty. Future progress will depend on moving beyond printable prototypes toward reproducible formulations, real-use validation, and clearer comparison criteria, in line with Sustainable Development Goal 12 and the transition toward higher-value circular production chains. Full article

The growing demand for more sustainable construction materials has driven the development of composites incorporating industrial and agricultural residues, contributing to the reduction in virgin raw material consumption and the valorisation of by-products. In this context, the present study investigated the influence of incorporating rice husk subjected to different chemical treatments and the partial replacement of commercial gypsum with recycled gypsum on the flexural strength, compressive strength and microstructural characteristics of gypsum-based composites. Initially, formulations containing 5 wt.% and 10 wt.% rice husk in three different conditions, untreated, treated with calcium hydroxide, and treated with acetic acid, were produced and evaluated in terms of compressive strength and flexural strength. The formulation containing 5 wt.% rice husk treated with acetic acid exhibited the best overall performance and was therefore selected for the subsequent stage of the study. In the second phase, mixtures incorporating 20 wt.%, 30 wt.% and 40 wt.% recycled gypsum, with and without the addition of 5 wt.% treated rice husk, were investigated. Furthermore, particle size distribution, X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDS) analyses were performed. The results demonstrated that the acetic acid treatment resulted in higher flexural and compressive strength compared with the other treatment conditions evaluated. Partial replacement with recycled gypsum also yielded promising results, with the formulation containing 70 wt.% commercial gypsum and 30 wt.% recycled gypsum exhibiting the highest mechanical strength among the composites without lignocellulosic reinforcement. Microstructural characterisation revealed the preservation of the principal mineralogical phases following the recycling process, and SEM micrographs showed the incorporation of rice husk within the gypsum matrix. Overall, the combination of 30 wt.% recycled gypsum and 5 wt.% rice husk treated with acetic acid represents a technically viable alternative for the development of gypsum composites intended for non-structural applications in the construction industry, while promoting the beneficial utilisation of waste materials. Full article

Interest in sustainable protein sources is increasing because of environmental concerns related to animal agriculture and the growing burden of chronic non-communicable diseases. Plant-derived bioactive peptides (PDBAPs), amino acid sequences released from dietary proteins, are gaining attention because experimental studies have reported activities relevant to hypertension, type 2 diabetes, and cancer-associated processes. Although animal proteins have long been major sources of bioactive peptides, plant materials may offer advantages such as abundance, potentially lower production costs, and broad cultural acceptability; however, these benefits depend on the source, processing requirements, safety, and scale-up conditions. This review integrates plant sources, processing technologies, proposed mechanisms of action, and translational barriers. Current research covers traditional sources, including legumes and cereals, as well as agro-industrial by-products such as potato peels, spent coffee grounds, and broccoli stems. Modern processing strategies increasingly combine enzymatic hydrolysis or microbial fermentation with process-assisting technologies, including ultrasound treatment and subcritical water processing, to improve protein recovery or peptide release. Recent studies also examine proposed mechanisms of PDBAP activity, including Keap1/Nrf2-associated responses and inhibition of enzymes involved in metabolic disorders. Evidence is interpreted according to the stage of experimental validation, from computational prediction and cell-free assays to cellular, animal, and human studies. Key challenges remain, particularly digestive instability, uncertain systemic bioavailability, bitterness, safety standardization, and limited human clinical evidence. Future work should prioritize standardized extraction and analytical methods, optimized delivery systems, and robust clinical trials. Full article

Existing reviews on AI in tea production are either agriculture-generic or limited to isolated tasks. This review thoroughly compares vision technologies (RGB, hyperspectral, near-infrared, thermal, Light Detection and Ranging (LiDAR), Unmanned Aerial Vehicle (UAV)) and establishes a task-oriented algorithm selection framework for the tea industry. For small-sample or near-linear problems, traditional machine learning (ML) (support vector machine (SVM); partial least squares regression (PLSR)) remains effective. For unstructured field tasks, deep learning achieves superior performance: pest detection accuracy exceeds 97%, tea bud detection reaches 96.8% with RGB images, and hyperspectral imaging predicts nitrogen content with R² > 0.90 and tea polyphenols with R² up to 0.925. Algorithm choice further differentiates by task granularity: lightweight convolutional neural networks (CNNs) balance speed and accuracy for edge deployment at 16 fps; You Only Look Once (YOLO) series detectors enable real-time localization on mobile platforms at 93.1% accuracy, 24 ms per target. No single algorithm dominates all tea tasks; selection is a trade-off among accuracy, speed, data availability, and computational constraints. These findings outline a structured analysis of the challenges and pathways for transitioning computer vision (CV) from laboratory research toward field-deployable tools. Full article

Plant anthracnose, caused by Colletotrichum spp., is a class of significant diseases that severely threatens global crop production. Traditional management strategies, including chemical control, are hindered by inherent limitations such as the frequent emergence of pathogen resistance, low pesticide utilization efficiency, high environmental residue risks, and inconsistent field efficacy. Moreover, achieving further improvements in control efficacy is constrained by the complex biological characteristics of Colletotrichum species, particularly their hemibiotrophic lifestyle and latent infection strategies. In recent years, nanotechnology has emerged as a potential approach for the management of anthracnose. This review summarizes the research progress of various nanomaterials in the control of plant anthracnose. It analyzes the proposed multi-mechanism modes of action of nanomaterials tailored to the specific infection traits of Colletotrichum. Particular emphasis is placed on analyzing the theoretical mechanisms and preliminary in vitro evidence of nano-enabled controlled-release systems in addressing asymptomatic latent infections and achieving targeted, precise delivery. However, it must be emphasized that most current findings are derived from laboratory or controlled-environment studies, and the actual field-scale effectiveness, long-term environmental behavior, and multi-trophic safety of many nanomaterials remain insufficiently confirmed. Building upon these insights, this review thoroughly evaluates the critical challenges facing the agricultural field application of nanomaterials, such as ecotoxicity, formulation stability, scalable industrial production, and regulatory gaps. This review aims to provide objective theoretical support and technical references for achieving safe, efficient, and sustainable nano-enabled green management of plant anthracnose. Full article

Halotolerant plant growth-promoting bacteria offer a sustainable strategy to improve crop performance under saline conditions. This study evaluated Agave tequilana Weber var. Azul leaf juice was used as an alternative growth medium for Kocuria sediminis AS04, and the bacterium’s ability to alleviate salt stress in chiltepin (Capsicum annuum) was evaluated. The chiltepin seedlings were grown in a specialized chamber and exposed to higher salt levels (200, 400, and 600 mM NaCl) for 10 days. During this time, the protective effect of K. sediminis AS04, which was held in a polymer film, was examined. K. sediminis AS04 grew well in a medium containing 25% agave juice and urea, reaching a density of 1.3 × 10¹⁰ CFU mL⁻¹. Compared with conventional Tryptic Soy Broth, the medium formulated from agave leaf juice and urea could reduce the cost per kilogram of biomass by approximately 4-fold. Under severe salinity stress, plants inoculated with immobilized K. sediminis at 600 mM NaCl exhibited the highest shoot biomass (0.31 g⁻¹ plant), root length (50.7 mm), and proline accumulation (11.25 µmol g⁻¹ fresh weight), whereas uninoculated plants displayed reduced biomass (0.16 g plant⁻¹) and shorter roots (34.5 mm). At 600 mM NaCl, inoculation increased shoot biomass, root length, and plant survival by approximately 94%, 47%, and 200%, respectively, compared with uninoculated seedlings. This method values agro-industrial waste and enhances chiltepin performance under high-salinity conditions. It promotes sustainable production and helps create affordable inoculants for agricultural biotechnology. Full article

Ensuring the sustainability of agriculture-related industries requires not only expanding value added but also maintaining stable value creation and adaptive capacity under changing economic conditions. This study examines the economic and organizational sustainability of China’s agriculture-related industries within global value chains. Using the 2026 release of the OECD Analytical Activities of Multinational Enterprises database and ownership-split inter-country input–output tables for 2011–2023, we construct an ownership-disaggregated value-added accounting framework covering the production, processing, and circulation stages and apply structural decomposition analysis to identify the sources of value-added change and potential weak links. The results show that domestic demand is the principal source of value creation for both domestic-owned and foreign-owned enterprises and became increasingly important over the study period. Final-goods-related value added remains larger than intermediate-goods-related value added, although the latter grows more rapidly, indicating deeper participation in cross-border production networks. Structural exposure varies across stages and periods. Production is strongly supported by domestic demand but exhibits pronounced internal offsetting in some periods; processing becomes a major adjustment node during 2019–2020, while circulation records the clearest contraction in the same period before returning to a more balanced growth structure during 2020–2023. Foreign-owned enterprises, particularly in processing, become increasingly embedded in China’s domestic market and local production structure. Risk exposure is interpreted as structural sensitivity rather than a direct measure of risk probability or expected loss. The findings highlight the importance of domestic demand, diversified input and market linkages, greater stability and adaptability in processing and circulation, and well-governed cross-ownership relationships for sustainable value-chain development. Full article

Environmental sustainability of natural and synthetic fibers used in textiles and composites depends on their impacts throughout production, use, and end-of-life (EoL) stages. Natural fibers are renewable and biodegradable but may require substantial water and agricultural inputs, whereas synthetic fibers contribute to fossil resource depletion, microplastic pollution, and persistent waste generation. Natural fibers are often regarded as more sustainable alternatives to synthetic fiber; however, evidence from a life cycle assessment (LCA) reveals a more nuanced reality. As demand for fiber-based materials increases across textile and composite applications, a deeper understanding of the environmental implications of both natural and synthetic options becomes essential. This review compares these fiber categories from a life cycle perspective, examining carbon footprint, energy demands, resource consumption, and EoL pathways. Natural fibers such as cotton, flax, jute, hemp, sisal, banana, coir, and emerging plant-based alternatives offer advantages including biodegradability and carbon sequestration during cultivation. Nevertheless, agricultural practices and subsequent industrial processing require substantial land, water, and chemical inputs. Synthetic fibers, predominantly derived from fossil resources, provide a long service life and consistent performance but are associated with high greenhouse gas (GHG) emissions, dependence on non-renewable feedstocks, microplastic pollution, and broader environmental impacts. By presenting a comprehensive life cycle-based comparison, this review identifies the conditions under which each fiber type may offer environmental benefits, supporting informed material selection for sustainable development. Full article

Bactrocera dorsalis (Hendel) and Bactrocera correcta (Bezzi) are two globally concerning quarantine pests within the genus Bactrocera (Tephritidae). Both species inflict severe damage on the agricultural industry and international export trade. Their distribution range has expanded due to global warming, posing an increasing threat to fruit production. Heat shock proteins (HSPs), functioning as molecular chaperones, are known to contribute to temperature adaptation in insects. However, the cold adaptation regulatory mechanisms in these two Bactrocera species remain unclear. In this study, eIF4EBP3^−/− mutations were established by the CRISPR-Cas9 system in both species. The survival rate of the mutations was significantly reduced with cold treatments, and qRT-PCR analysis indicated that eIF4EBP3 regulates the expression of several downstream heat shock proteins, suggesting that it may be involved in rapid cold hardening (RCH) adaptability in both fruit fly species. In addition, this work represents the first application of the CRISPR-Cas9 system in B. correcta, which provides methods to further studies on this species. Our results provide insights into the molecular mechanisms underlying rapid cold hardening adaptation in B. dorsalis and B. correcta and a potential molecular marker for monitoring cold tolerance in field populations which could guide the development of novel control strategies that target the RCH adaptation pathways. Full article

The Yellow River Basin is an important ecological security barrier and agricultural production area in China. Using panel data for nine sprovincial-level regions from 2010 to 2022, this study constructs a multidimensional development index of rural industrial integration and examines its association with regional environmental pollution. Regional pollution pressure is measured from total wastewater discharge, sulfur dioxide emissions, and general industrial solid-waste generation; the measure therefore captures broad regional pollution linked to agricultural and related industrial chains rather than agricultural non-point-source pollution alone. Two-way fixed-effects estimates show that higher integration scores are significantly associated with lower pollution levels. This association is statistically evident in the upper reaches, whereas the middle- and lower-reach estimates are not statistically significant and are interpreted as exploratory because each subsample contains only two provinces. Exploratory channel regressions suggest that agricultural technological progress, rural labor mobility, and agricultural industrial scale may help explain the observed association, but the regressions do not establish causal mediation. The findings indicate potential synergies between rural industrial integration and environmental governance, while also requiring caution regarding causal interpretation, composite-index boundaries, and small-sample regional comparisons. Full article

Pyroligneous liquor (PL) is a by-product of charcoal production with potential applications in agriculture, forestry, and industry. This study evaluated the influence of carbonization temperature on the yield, chemical composition, and physicochemical properties of PL obtained from Eucalyptus spp. in a sustainable kiln-furnace system. PL fractions were collected at four temperature intervals: T1 (60–170 °C), T2 (171–270 °C), T3 (271–350 °C), and T4 (351–400 °C). The recovery of condensable gases did not affect the quality of the charcoal and minimized pollutant emissions. Gas chromatography–mass spectrometry (GC-MS) identified 78 organic compounds, mainly carboxylic acids, phenolic compounds, alcohols, carbohydrates, and aromatics. The highest PL yield was obtained in T3 (271–350 °C), accounting for 27% of the recovered liquor and showing high phenolic content, including syringol and catechol. In contrast, T1 (60–170 °C) showed the lowest yield and was dominated by carboxylic acids, particularly acetic acid. Carbonization temperature affected both PL composition and physicochemical properties, resulting in higher electrical conductivity and vegetable tar content at higher temperatures. Hierarchical cluster analysis revealed distinct compound groups according to their concentration patterns across the evaluated temperature intervals. These results reinforce the notion that the evolution of pyrolysis vapors is not a continuous or homogeneous process, but rather occurs through discrete and chemically distinct stages driven by the sequential decomposition of hemicellulose, cellulose, and lignin—a behavior that directly justifies the temperature-based fractionation approach adopted. It was found that temperature-controlled fractionation effectively yields pyrolysis liquid (PL) fractions with distinct chemical profiles, facilitating the selective recovery of value-added compounds for forest biomass biorefineries and specific end-use applications, in addition to offering environmental benefits. Full article