Search Results (235)

Barley (Hordeum vulgare L.) is a major cereal in Kazakhstan, where diverse breeding material supports crop improvement. We characterized 86 two-row spring barley accessions from six breeding organizations using the Illumina Infinium 50K Barley SNP Array. Analysis of 29,920 high-quality SNPs revealed moderate diversity (H_e = 0.346, PIC = 0.278, Shannon = 0.752), with 80.84% of molecular variation occurring within and 19.16% among breeding organizations. A minor allele frequency-free (MAF-free) analysis showed that 95.61% of marker–allele combinations at polymorphic loci were shared by at least two organizations. Although PCA, kinship, and neighbor-joining analyses indicated extensive overlap, discriminant analysis of principal components (DAPC) cluster membership was significantly associated with breeding origin (χ² = 106.38, Monte Carlo p = 1 × 10^–5; bias-corrected Cramér’s V = 0.513), demonstrating substantial but incomplete differentiation among breeding programs. Phenotypic differentiation was evaluated using environment-adjusted genotype BLUPs. All seven traits differed significantly among five DAPC clusters. In a reduced six-trait linear discriminant analysis (LDA) excluding vegetation period, LD1 was associated most strongly with number of kernels per spike, followed by heading time, spike length, and heading-to-maturity time. Leave-one-out cross-validation (LOOCV) accuracy was 36.47%, exceeding the permutation mean of 19.83% but indicating considerable phenotypic overlap. The examined materials therefore constitute a diverse, interconnected breeding panel that may support germplasm management and parent selection and provide a genomic and phenotypic framework for future GWAS, genomic selection, and targeted validation of molecular markers within the represented collections. Full article

Smart chemical sensors have emerged as promising tools for real-time monitoring of food spoilage in both fermented and non-fermented products. By detecting key spoilage indicators—including biogenic amines, ammonia, hydrogen sulfide, methane, pH variations, and microbial volatile organic compounds (MVOCs)—these systems enable rapid, on-site assessment of food quality, offering a viable alternative to conventional, time-consuming laboratory analyses. Recent advances encompass diverse sensing mechanisms, including chemiresistive platforms based on conducting polymers and MEMS (Microelectromechanical Systems); optical/colorimetric systems using dyes, metal–organic frameworks, and porphyrins; and electrochemical and biosensing approaches employing enzymes, antibodies, aptamers, and whole-cell recognition elements. These sensors demonstrate high sensitivity (ppb–ppm range), enabling early detection of spoilage before sensory perception or microbiological threshold exceedance. Their applicability has been validated across a wide range of food matrices, including meat, fish, dairy products, vegetables, beverages, and fermented foods. Despite significant progress, key challenges persist, including signal drift, limited specificity, susceptibility to environmental factors such as humidity and temperature, and interference from complex food matrices. Furthermore, integration into intelligent packaging requires the development of flexible, food-safe, and regulatory-compliant materials. Emerging approaches that combine sensor arrays with machine learning and MVOC pattern recognition are enhancing predictive accuracy and enabling food classification across commodity types. Overall, smart chemical sensing technologies are rapidly transitioning from laboratory prototypes to practical applications in intelligent packaging and wireless monitoring systems, with ongoing research focused on improving robustness, standardization, and scalability for commercial deployment. This article provides an overview of the topic, drawing on the available bibliography from the last five years and the most-cited scientific databases. Full article

Background: In the coming decades, the agricultural system will increasingly rely on organic amendments to sustain crop production, maintain soil health and ensure long-term food security. While inorganic fertilizers remain widely used for vegetable production due to their rapid nutrient availability, their prolonged application has been shown to degrade soil quality, disrupt microbial communities and limit the nutritional quality of harvested produce. Consequently, there is a growing need to explore organic alternatives such as biochar and poultry manure that can enhance both crop productivity and functional quality. Objective: This study aimed to determine the influence of different application rates of biochar (5/T₁, 10/T₂, and 20/T₃ t/ha), poultry manure (10/T₁, 20/T₂, 30/T₃ t/ha), and NPK (2:3:4) as control on the metabolomic profile of tomato fruit. Methods: The metabolomic profile was determined using 1H-nuclear magnetic resonance (NMR). Results: Common metabolites across biochar rates included allantoin, asparagine and betaine, while rate-specific released metabolites such as inosine (T₁), epicatechin (T₂) and kynurenine (T₃) were also identified. Similarly, poultry manure showed an array of metabolites at the highest application rate, with metabolites such as cellobiose, creatinine and maltose, while histamine (T₁) and ADP (T₃) were also detected as distinct metabolites. Full article

Clarifying how vegetation restoration regulates wind erosion, sediment redistribution, and soil improvement is essential for ecological management in desert photovoltaic power stations. This study was conducted in a high-clearance flexible-support photovoltaic power station at the edge of the Kubuqi Desert. Three restoration measures were compared: reed mulch combined with Atriplex canescens planting along the panel front edge (M1), A. canescens planting along the panel front edge alone (M2), and reed mulch combined with grass seeding (M3). The panel front-edge zone (QY), under-panel zone (BX), and pedestal zone (JZ) were used as functional units to analyze surface sediment grain-size characteristics, soil moisture, soil nutrients, windbreak efficiency, aerodynamic roughness length, and cumulative sand-fixing efficiency. All restoration measures altered the surface sediment structure, with Mz ranging from 2.005 to 2.364 and D₀ from 1.459 to 1.935. Soil moisture ranged from 0.58% to 4.34%, with the highest value occurring in the 20–30 cm layer of QY under M1. M1 also showed higher soil organic matter in QY and JZ, reaching 1.87 and 1.16 g·kg⁻¹, respectively. Windbreak efficiency decreased with height under all measures. M1 maintained the highest and most stable values, decreasing only from 61.16% at 10 cm to 55.52% at 100 cm. The total cumulative sand-fixing efficiency was also highest under M1 (233.66%), while M2 (215.05%) and M3 (214.58%) showed comparable total effects but different zonal responses. Wind-eroded materials shifted from fine-sand dominance toward a higher relative contribution of medium sand, reflecting the reduction in finer transported fractions rather than true grain coarsening. The novelty of this study lies in linking wind-erodible sediment redistribution, soil water and nutrient responses, and windbreak–sand-fixing performance across internal functional zones of a flexible-support photovoltaic array. These results indicate that vegetation restoration in desert photovoltaic power stations should be configured by functional zone, with composite interception at the panel front edge, structural maintenance in the under-panel zone, and cover-based sand trapping in deposition-prone areas. Full article

Fermentation is a foundational process that has historically underpinned the development of global civilizations. By extending the shelf life of perishable ingredients while enhancing flavor, nutrition, and bioactive properties, fermentation has provided the food security necessary for societies to flourish. Traditionally, these processes utilized locally available raw materials—such as milk, cereals, fruits, and vegetables—to produce a diverse array of non-alcoholic, alcoholic, and functional foods. This review explores the evolution of prominent ancient fermentation products and the contemporary movement to revive their authentic sensory profiles, including unique aromas and textures. Furthermore, it examines the transition from traditional artisanal methods to modern industrial production, where the use of standardized starter cultures and precise process parameters ensures product uniformity for the global market while employing precision fermentation to improve traditional fermentation products. By bridging ancestral wisdom with modern food science, this review highlights the enduring relevance of fermentation in the current food landscape. Full article

Emotional design is increasingly recognised within landscape architecture, particularly in the context of sustainable and user-centred environments; however, systematic and data-driven approaches that translate users’ emotional responses into concrete design parameters remain limited. To address this gap, the aim of this study is to systematically integrate users’ emotional expectations into landscape design by applying Kansei Engineering, using ornamental pools as a case study. A semantic differential survey was conducted with 91 participants, including landscape design students and experts. The experimental stimuli were developed based on a Taguchi L8 orthogonal array, enabling the systematic evaluation of five design factors (depth, interior surface colour, surface planting, form, and motion) across eight configurations. The collected data were analysed using the Taguchi method and Analysis of Variance (ANOVA) to identify optimal design combinations and quantify the relative influence of each factor. The results reveal that surface planting is the dominant factor influencing perceptions such as captivating and legible, while motion plays a key role in shaping mental restoration. The optimal configuration, characterised by shallow depth, light colour, vegetation, natural form, and dynamic water, evoked strong positive responses including captivating, aesthetically pleasing, and satisfying. This study proposes a data-driven framework for linking emotional perception with landscape design variables, contributing to the development of more socially and psychologically sustainable, user-centred, and emotionally responsive landscape environments. Full article

Urban Park vegetation plays a crucial role in mitigating air pollution by serving as a natural sink for gaseous and particulate pollutants, thereby enhancing the ecological sustainability of cities. Identifying tree species with high tolerance to air pollution is therefore essential for effective urban park planning and management in highly polluted urban environments. This study evaluated the air pollution tolerance of selected tree species commonly found in urban parks of Kandy City, Sri Lanka, using the Air Pollution Tolerance Index (APTI). Five tree species—Terminalia catappa (Indian almond), Cassia fistula (golden shower tree), Pongamia pinnata (Indian beech), Madhuca longifolia (butter tree), and Tabebuia rosea (pink poui)—were assessed at two urban park locations representing contrasting pollution levels, identified based on ambient SO₂, NO₂, and PM_2.5 concentrations. APTI was calculated using four leaf biochemical parameters: pH, ascorbic acid content, relative water content, and total chlorophyll content. Leaf samples were collected from ten replicates of each species at both sites. Madhuca longifolia exhibited the highest APTI values (17.06 at the HP site and 25.17 at the LP site), followed by Cassia fistula, Terminalia catappa, Tabebuia rosea, and Pongamia pinnata. These findings suggest that the identified species, particularly Madhuca longifolia and Cassia fistula, are well-suited for urban greening and can contribute to mitigating air pollution impacts. However, these findings are constrained by a single cross-sectional sampling term, limited species screening, sequential data collection variances, and fixed mathematical equations. Consequently, future research should implement continuous multi-station monitoring arrays, expand species diversity, establish localized biochemical weightings, and initiate long-term multi-seasonal tracking to resolve temporal dynamics in tropical urban ecosystems. Full article

Ground-based scatterometers are widely used for quantitative microwave backscattering measurements in soil moisture retrieval, vegetation monitoring, and satellite scatterometer validation. However, low-cost software-defined radio (SDR) transceivers provide limited instantaneous bandwidth, making it difficult to transmit and process signals with bandwidths on the order of hundreds of MHz for fine range resolution, especially for systems requiring real-time onboard processing. To address this problem, this paper presents a vehicular, fully polarimetric, SDR-based scatterometer that achieves an equivalent wideband response by sequentially transmitting adjacent narrow subbands and coherently synthesizing them onboard. To enable real-time operation on a resource-limited field-programmable gate array/system-on-chip (FPGA/SoC) platform, we adopt a frequency-domain synthesis-pulse-compression pipeline that avoids interpolation and eliminates repeated matched filtering across subbands. A slot-based online phase calibration is performed within the settling window after each fast lock to estimate and compensate random local oscillator (LO) phase offsets, preserving coherent stitching. In addition, pulse repetition within each subband and coherent accumulation are integrated to improve the signal-to-noise ratio (SNR) under real-time throughput constraints. A Zynq-based implementation demonstrates deterministic onboard range-profile output, with a minimum processing latency of about 1.57 ms per frame. Loopback and outdoor experiments validate the equivalent 200 MHz bandwidth (five 40 MHz subbands), achieving approximately 0.75 m resolution and yielding sidelobe metrics consistent with the designed windowing, including a peak sidelobe ratio (PSLR) of −27.43 dB and an integrated sidelobe ratio (ISLR) of −12.38 dB. Field scans over farmland further show consistent ${\mathsf{\sigma }}_0$ trends across incidence angle and azimuth, indicating reliable onboard quantitative backscattering measurement. These results demonstrate that the proposed method provides a feasible solution for deterministic real-time equivalent wideband scatterometry on a low-cost SDR platform. Full article

Vegetatively propagated crops, including cassava, sweet potato, banana, and potato, are susceptible to mixed-pathogen infections resulting from the continuous use of clonal planting material and infrequent seed replacement. A diverse array of viruses, bacteria, and fungi can accumulate within these materials over successive cultivation cycles, precipitating seed degeneration and complex disease syndromes that complicate diagnosis and management. Mixed infections frequently trigger synergistic interactions that exacerbate disease severity and yield losses. This review synthesizes data on mixed-pathogen complexes in vegetatively propagated crops, with particular focus on vascular and systemically colonizing pathogens and analyzing starch crops to highlight the epidemiological, biological, and ecological drivers of synergism and antagonism. Furthermore, the review examines host defense responses during coinfection, including the modulation of plant immune pathways, and evaluates how interpathogen dynamics influence pathological outcomes. Although advancements in molecular diagnostics—notably next-generation sequencing and metagenomics—have revolutionized the detection of mixed infections, they have also introduced challenges in differentiating causal agents from commensal microorganisms. Finally, we discuss the implications for integrated disease management, emphasizing clean seed systems, resistance breeding, and phenotyping strategies tailored to multipathogen environments. The dynamics of mixed infections is critical for resilient and sustainable management strategies amidst increasingly complex agricultural and climatic shifts. Full article

Monarch butterflies have declined in both eastern and western populations. Conservation initiatives that support this imperiled species are being implemented in lands managed by the energy and transportation sectors. Vegetation management strategies that encourage the presence of milkweed (Asclepias spp.), the larval host of monarch butterflies (Danaus plexippus), or floral resources to support pollinators are being practiced across North America; however, survey methods to evaluate the success of these strategies vary in accuracy and scalability. In this study, we compared five methods to quantify milkweed stem density and land cover estimates: (1) Site al, (2) Transect plot, (3) Square plot, (4) Large transect (informed by the Monarch CCAA methodology), and (5) Machine learning of images collected by UAVs. These methods encompass full coverage ground counts, partial ground counts, and aerial imagery using object-based image analysis. Sites included distribution, transmission, and gas line ROWs, solar arrays, and transportation easements. We found that Site al and Machine learning most consistently quantified milkweed stem density across sites. Partial ground count methods were likely to over or underestimate milkweed populations. Habitat characteristics (woody, broadleaf, grass, and bare ground) estimates were inconsistent across method and site. The intent of this study was to provide land managers with insight as to the most accurate, efficient, and economical approach to quantify milkweed populations and habitat characteristics. Full article

Dysregulated angiogenesis is involved in cancer and numerous ischemic, autoimmune and inflammatory diseases, prompting extensive research that has yielded a growing array of angiogenesis-modulating molecules used in clinical practice. The dietary phytocomplex of Cruciferous vegetables exhibits multiple biological activities in both in vitro and in vivo models. However, the impact of a myrosinase-activated broccoli extract (MaBE) on angiogenesis, as well as on stromal–endothelial interactions governing endothelial cell behavior, has not yet been explored. We investigated the effects of MaBE on endothelial–stromal crosstalk using endothelial cells (HUVECs) and fibroblasts (HFF1) both individually and in a fibroblast-conditioned medium model. MaBE dose-dependently inhibited endothelial viability, migration and tube formation, key steps of angiogenesis, through interference with the VEGF–VEGFR2 axis. Notably, MaBE also markedly suppressed HFF1-driven HUVEC migration and capillary-like structure formation, likely through the inhibition of fibroblast motility and the downregulation of VEGF and angiogenin signaling in HFF1 cells. Overall, these findings provide new insight into MaBE regulation of pro-angiogenic behaviors in both endothelial cells and fibroblasts while disrupting their functional interplay. By targeting multiple cellular compartments and key mediators involved in angiogenesis, MaBE emerges as a promising bioactive extract with potential relevance for the management of pathological angiogenesis-related disorders. Full article

Publicly accessible spaceborne remote sensing datasets often lack the spatial resolution required to reliably distinguish archeological features from their surrounding geomorphological contexts. In this study, we assess the potential of super-resolution (SR) products derived from multiple public-domain remote sensing datasets for a systematic archeological survey in the Caral–Supe region. We focus on Synthetic Aperture Radar (SAR) and topographic datasets—including Sentinel-1, Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR), and Digital Elevation Models (DEMs)—because of their capacity to detect subtle surface expressions and shallow subsurface structures obscured by vegetation or sediment cover. Using state-of-the-art deep learning algorithms, primarily employing the Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) architecture, we integrated multi-source SAR imagery and DEM data to generate SR products that reveal distinct signatures in areas containing dense archeological remains and clearly delineate shallow, buried anthropogenic features. We further developed deep learning classification models that combine SR SAR and DEM inputs and trained them on known archeological site locations. This approach enabled the detection of previously undocumented structural features distributed along the coastal margin and throughout the Supe Valley. Our findings indicate that enhancing publicly available remote sensing datasets with advanced SR techniques can provide cost-effective and practical high-resolution archeological data, compared to data mining using aerial photography and high-resolution commercial satellite imagery, in terms of both cost and obstacle penetration. Full article

Ultrasound has emerged as a versatile and promising tool to enhance and speed up traditional processing operations used by the food industry or to be used as an alternative food-processing method. This review provides an overview of the fundamental principles of sonication and its diverse applications in food processing. The core concepts of acoustic cavitation and the influence of power on processing outcomes are discussed in detail. The design and operation of different ultrasound systems, including direct-contact probe and indirect-contact bath systems, and their respective advantages were reviewed. Furthermore, a wide array of applications were explored, namely extraction, homogenization, degassing and deodorizing, pasteurization and vegetable blanching, drying and dehydration, freezing and thawing, brining and hydration, and cutting, highlighting how ultrasound waves can enhance process efficiency and improve product quality. The review also provides a critical analysis of the challenges and limitations associated with scaling up the technology for industrial use, including potential impacts on food quality, safety considerations, and economic viability. Finally, future perspectives and potential areas for further research are outlined to encourage the broader adoption of this technology in the food sector. Full article

Soybean is a primary global vegetable oil source, yet modern South American cultivars often exhibit superior oil content compared to those from China, the center of origin. Elucidating the genetic basis of this differentiation is crucial for enhancing production efficiency. In this study, we systematically evaluated 98 representative accessions, comprising Chinese germplasm (CN) and Uruguayan germplasm. The latter included Uruguayan conventional germplasm (UY_N, where ‘N’ indicates ‘Normal’, meaning non-transgenic) and Uruguayan transgenic germplasm (UY_T). Using the “Zhongdouxin No. 1” SNP array and multi-environment phenotypic data. Uruguayan germplasm exhibited significantly higher mean oil content (21.48%) than Chinese germplasm (19.42%, p < 0.001), with high heritability (H² ranging from 0.78 to 0.92). Genetic analysis revealed significant differentiation (mean F_ST = 0.14), with Uruguayan lines showing reduced diversity due to breeding bottlenecks. Genome-wide scans identified differentiation in genomic regions harboring known lipid biosynthesis genes; notably, the high-oil allele frequency of GmDGAT1 was 78.3% in Uruguayan germplasm versus 25.7% in Chinese lines, and the favorable GmbZIP123 haplotype was fixed in the Uruguayan population. Uruguayan accessions also carried significantly more favorable alleles (18.3) than Chinese accessions (14.8). We conclude that high-oil traits in Uruguayan soybean result from the systematic stacking of favorable haplotypes at key loci via directional selection. Consequently, we propose incorporating South American high-oil allelic modules into the broadly adapted genetic backgrounds of Chinese cultivars to bridge the oil content gap. Full article

The momentum transport and scale-dependent motion characteristics within vegetation canopies play a crucial role in shaping near-surface turbulent structures and exchange processes, yet the interactions among different turbulent scales and their statistical representations remain insufficiently understood. Based on a series of controlled wind tunnel experiments, this study identifies coherent turbulent structures using a phase-space algorithm constructed from streamwise velocity fluctuation u′, acceleration a, and jerk j, and compares transport efficiency (exuberance η). This study uses scale-wise (cut-off frequency) momentum flux contribution analysis, natural visibility graph (NVG), and large–small-scale amplitude modulation to examine transport and multiscale behaviors across different canopy densities, array layouts, and inflow conditions. Results show that canopy density (different C_d drag coefficient) is a primary factor governing transport efficiency. Under low-wind staggered configurations, increasing canopy density strengthens the contribution of low-frequency large-scale motions to total momentum flux. In contrast, high-wind aligned configurations intensify canopy-top shear, enhancing small-scale motions and thereby reducing the relative contribution of large-scale motions. NVG analysis further reveals that in high-density canopies, large-scale acceleration and deceleration events tend toward equilibrium, whereas deceleration events dominate consistently in low- and medium-density cases. Amplitude modulation results indicate that high-density cases exhibit highly consistent modulation behavior, followed by low-density cases, while medium-density cases display a pronounced height-dependent variation, characterized by a distinct modulation critical point. This study proposes a unified analytical framework integrating coherent structure detection, graph-theoretic analysis, multiscale transport characterization, and large–small-scale modulation, providing a comprehensive description of momentum transport and scale motions within canopy flows, and it offers new insight into the mechanisms governing complex vegetation canopy turbulence. Full article