Search Results (4,864)

Radish (Raphanus sativus), a commonly grown root vegetable prized for its nutrition and culinary use, is particularly vulnerable to lead (Pb) stress, which mainly results in Pb accumulation in the roots. However, the molecular mechanisms underlying Pb accumulation in radish remain largely unknown. In this study, we investigated the role of BASIC PENTACYSTEINE (BPC) genes in radish’s response to Pb stress. Phylogenetic analysis revealed that radish contains 10 BPC genes, which are distinctly clustered in Cluster III. Expression analysis revealed that, except for RsBPC2, RsBPC4, and RsBPC7, the expression of most RsBPC genes was significantly altered under Pb stress. Notably, the expression of RsBPC5 gradually decreased with prolonged Pb exposure. Subcellular localization analysis confirmed that RsBPC5 is localized in the nucleus and acts as a transcriptional repressor. Functional assays demonstrated that transient overexpression of RsBPC5 enhanced the tolerance of radish plants to Pb stress via reducing Pb accumulation and activating the antioxidant defense system. Collectively, our findings suggest that RsBPC5 plays a key role in radish’s response to Pb stress, potentially improving Pb tolerance by modulating Pb uptake and strengthening antioxidant defense mechanisms. Full article

Plant functional traits serve as vital tools for understanding vegetation adaptation mechanisms in changing environments. As the primary organs for nutrient acquisition from soil, fine roots are highly sensitive to environmental variations. However, current research on fine-root adaptation strategies predominantly focuses on tropical, subtropical, and temperate forests, leaving a significant gap in comprehensive knowledge regarding fine-root responses in rocky-desertification habitats. This study investigates the fine roots of Pseudotsuga sinensis across varying degrees of rocky desertification (mild, moderate, severe, and extremely severe). By analyzing fine-root morphological and nutrient traits, we aim to elucidate the trait differences and correlations under different desertification intensities. The results indicate that root dry matter content increases significantly with escalating desertification severity. Fine roots in mild and extremely severe desertification exhibit notably higher root C, K, and Mg concentrations compared to those in moderate and severe desertification, while root Ca concentration shows an inverse trend. Our correlation analyses reveal a highly significant positive relationship between specific root length and specific root area, whereas root dry matter content demonstrates a significant negative correlation with elemental concentrations. The principal component analysis (PCA) further indicates that the trait associations adopted by the forest in mild- and extremely severe-desertification environments are different from those in moderate- and severe-desertification environments. This study did not account for soil nutrient dynamics, microbial diversity, or enzymatic activity—key factors influencing fine-root adaptation. Future research should integrate root traits with soil properties to holistically assess resource strategies in rocky-desertification ecosystems. This study can serve as a theoretical reference for research on root characteristics and adaptation strategies of plants in rocky-desertification habitats. Full article

Grazing affects soil organic carbon (SOC) through plant removal, livestock trampling, and manure deposition. However, the impact of grazing on SOC is also influenced by multiple factors such as climate, soil properties, and management approaches. Despite extensive research, the mechanisms by which grazing intensity influences SOC density in grasslands remain incompletely understood. This study examines the effects of varying grazing intensities on SOC density (0–30 cm) dynamics in temperate grasslands of northern China using field surveys and experimental analyses in a typical steppe ecosystem of Inner Mongolia. Results show that moderate grazing (3.8 sheep units/ha/yr) led to substantial consumption of aboveground plant biomass. Relative to the ungrazed control (0 sheep units/ha/yr), aboveground plant biomass was reduced by 40.5%, 36.2%, and 50.6% in the years 2016, 2019, and 2020, respectively. Compensatory growth failed to fully offset biomass loss, and there were significant reductions in vegetation carbon storage and cover (p < 0.05). Reduced vegetation cover increased bare soil exposure and accelerated topsoil drying and erosion. This degradation promoted the downward migration of SOC from surface layers. Quantitative analysis revealed that moderate grazing significantly reduced surface soil (0–10 cm) organic carbon density by 13.4% compared to the ungrazed control while significantly increasing SOC density in the subsurface layer (10–30 cm). Increased precipitation could mitigate the SOC transfer and enhance overall SOC accumulation. However, it might negatively affect certain labile SOC fractions. Elucidating the mechanisms of SOC variation under different grazing intensities and precipitation regimes in semi-arid grasslands could improve our understanding of carbon dynamics in response to environmental stressors. These insights will aid in predicting how grazing systems influence grassland carbon cycling under global climate change. Full article

On 20 April 2024, an extreme rainfall event occurred in Jiangwan Town Shaoguan City, Guangdong Province, China, where a historic 24 h precipitation of 206 mm was recorded. This triggered extensive landslides that destroyed residential buildings, severed roads, and drew significant societal attention. Rapid acquisition of landslide inventories, distribution patterns, and key controlling factors is critical for post-disaster emergency response and reconstruction. Based on high-resolution Planet satellite imagery, landslide areas in Jiangwan Town were automatically extracted using the Normalized Difference Vegetation Index (NDVI) differential method, and a detailed landslide inventory was compiled. Combined with terrain, rainfall, and geological environmental factors, the spatial distribution and causes of landslides were analyzed. Results indicate that the extreme rainfall induced 1426 landslides with a total area of 4.56 km², predominantly small-to-medium scale. Landslides exhibited pronounced clustering and linear distribution along river valleys in a NE–SW orientation. Spatial analysis revealed concentrations on slopes between 200–300 m elevation with gradients of 20–30°. Four machine learning models—Logistic Regression, Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost)—were employed to assess landslide susceptibility mapping (LSM) accuracy. RF and XGBoost demonstrated superior performance, identifying high-susceptibility zones primarily on valley-side slopes in Jiangwan Town. Shapley Additive Explanations (SHAP) value analysis quantified key drivers, highlighting elevation, rainfall intensity, profile curvature, and topographic wetness index as dominant controlling factors. This study provides an effective methodology and data support for rapid rainfall-induced landslide identification and deep learning-based susceptibility assessment. Full article

The Inner Mongolia Plateau (IMP), situated in the arid and semi-arid ecological transition zone of northern China, is particularly vulnerable to both climate change and human activities. Understanding the spatiotemporal vegetation dynamics and their driving forces is essential for regional ecological management. This study employs Sen’s slope estimation, BFAST analysis, residual trend method and Geodetector to analyze the spatial patterns of Normalized Difference Vegetation Index (NDVI) variability and distinguish between climatic and anthropogenic influences. Key findings include the following: (1) From 1982 to 2022, vegetation cover across the IMP exhibited a significant greening trend. Zonal analysis showed that this spatial heterogeneity was strongly regulated by regional hydrothermal conditions, with varied responses across land cover types and pronounced recovery observed in high-altitude areas. (2) In the western arid regions, vegetation trends were unstable, often marked by interruptions and reversals, contrasting with the sustained greening observed in the eastern zones. (3) Vegetation growth was primarily temperature-driven in the eastern forested areas, precipitation-driven in the central grasslands, and severely limited in the western deserts due to warming-induced drought. (4) Human activities exerted dual effects: significant positive residual trends were observed in the Hetao Plain and southern Horqin Sandy Land, while widespread negative residuals emerged across the southern deserts and central grasslands. (5) Vegetation change was driven by climate and human factors, with recovery mainly due to climate improvement and degradation linked to their combined impact. These findings highlight the interactive mechanisms of climate change and human disturbance in regulating terrestrial vegetation dynamics, offering insights for sustainable development and ecosystem education in climate-sensitive systems. Full article

Mung bean (Vigna radiate) sprouts are a popular choice among sprouted vegetables in Asia. Currently, the impact of nitrogen sources on the growth of mung bean sprouts remains poorly understood, and the underlying biological mechanisms responsible for the observed nonlinear growth patterns at different nitrogen levels have yet to be elucidated. In this research, in addition to conventional growth monitoring and quality evaluation, a comparative proteomics method was applied to investigate the molecular mechanisms of mung bean in response to 0, 0.025, 0.05, 0.075, and 0.1% urea concentrations. Our results indicated that mung bean sprout height and yield increased with rising urea concentrations but were suppressed beyond the L3 level (0.075% urea). Nitrate nitrogen and free amino acid content rose steadily with urea levels, whereas protein content, nitrate reductase activity, and nitrite levels followed a peak-then-decline trend, peaking at intermediate concentrations. Differential expression protein analysis was conducted on mung bean sprouts treated with different concentrations of urea, and more differentially expressed proteins participated in the L3 urea concentration. Analysis of common differential proteins among comparison groups showed that the mung bean sprouts enhanced their adaptability to urea stress environments by upregulating chlorophyll a-b binding protein and cationic amino acid transporter and downregulating the levels of glycosyltransferase, L-ascorbic acid, and cytochrome P450. The proteomic analysis uncovered the regulatory mechanisms governing these metabolic pathways, identifying 47 differentially expressed proteins (DEPs) involved in the biosynthesis of proteins, free amino acids, and nitrogen-related metabolites. Full article

In response to the global ecological and agricultural challenges posed by coastal saline-alkali areas, this study focuses on Dongying City as a representative region, aiming to develop a high-precision soil salinity prediction mapping method that integrates multi-source remote sensing data with machine learning techniques. Utilizing the SCORPAN model framework, we systematically combined diverse remote sensing datasets and innovatively established nine distinct strategies for soil salinity prediction. We employed four machine learning models—Support Vector Regression (SVR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Geographical Gaussian Process Regression (GGPR) for modeling, prediction, and accuracy comparison, with the objective of achieving high-precision salinity mapping under complex vegetation cover conditions. The results reveal that among the models evaluated across the nine strategies, the SVR model demonstrated the highest accuracy, followed by RF. Notably, under Strategy IX, the SVR model achieved the best predictive performance, with a coefficient of determination (R²) of 0.62 and a root mean square error (RMSE) of 0.38 g/kg. Analysis based on SHapley Additive exPlanations (SHAP) values and feature importance indicated that Vegetation Type Factors contributed significantly and consistently to the model’s performance, maintaining higher importance than traditional salinity indices and playing a dominant role. In summary, this research successfully developed a comprehensive, high-resolution soil salinity mapping framework for the Dongying region by integrating multi-source remote sensing data and employing diverse predictive strategies alongside machine learning models. The findings highlight the potential of Vegetation Type Factors to enhance large-scale soil salinity monitoring, providing robust scientific evidence and technical support for sustainable land resource management, agricultural optimization, ecological protection, efficient water resource utilization, and policy formulation. Full article

Currently, in the context of the emphasis on introducing a reduction in mineral fertilization and the increase in pressure on sustainable agriculture, magnesium fertilization and the use of biostimulants are becoming an alternative tool to increase the quality of potato tuber yield. This study aimed to assess the impact of potato genotype, cultivation technology, and long-term storage on the susceptibility of tubers to enzymatic browning. Two edible potato varieties were examined: the early ‘Wega’ and the mid-early ‘Soraya’. It was demonstrated that the varieties maintained their characteristic browning susceptibility consistent with their breeding descriptions. The ‘Wega’ variety exhibited decreasing browning susceptibility immediately after harvest; however, after 6 months of storage, its susceptibility significantly increased, exceeding that of the ‘Soraya’ variety. Additionally, the application of magnesium fertilization (90 kg ha⁻¹) and biostimulant treatment (3 L ha⁻¹) most effectively reduced the oxidative potential of the tubers, thereby decreasing browning susceptibility. This is due to a significant change in the concentration of organic acids responsible for enzymatic browning processes. A decrease in the content of chlorogenic acid by 9.4% and 8.4% and an increase in the content of citric and ascorbic acid by 11.1%, 5.3%, and 13.6% were achieved. Storage significantly affected the chemical composition of the tubers. An increase in chlorogenic (7.3%) and citric (5.8%) acids and a decrease in ascorbic (34%) acid content were observed. These changes correlated with the intensification of browning, with the increase in chlorogenic acid and the decrease in ascorbic acid having the greatest influence. The results indicate that the technology based on supplementary fertilization and biostimulation improves the quality of potato raw material without a significant increase in production costs. Further research on varieties with different vegetation lengths and those intended for food processing and starch production is advised. Full article

Protein degradation plays a fundamental role in maintaining protein homeostasis and ensures proper cellular function by regulating protein quality and quantity. Heat shock protein 100 (Hsp100), found in bacteria, plants, and fungi, is a unique chaperone family responsible for rescuing misfolded proteins from aggregated states in an ATP-dependent manner. To date, they are primarily known to mediate heat stress adaptation and enhance cellular survival under extreme conditions in higher plants and algae. Resting cyst formation in dinoflagellates is widely recognized as a response to adverse conditions, which offers an adaptive advantage to endure harsh environmental extremes that are unsuitable for vegetative cell growth and survival. In this study, based on a full-length cDNA sequence, we characterized an Hsp100 gene (SaHsp100) from the cosmopolitan bloom-forming dinoflagellate Scrippsiella acuminata, aiming to examine its life stage-specific expression patterns and preliminarily explore its potential functions. The qPCR results revealed that Hsp100 transcript levels were significantly elevated in newly formed resting cysts compared to vegetative cells and continued to increase during storage under simulated marine sediment conditions (darkness, low temperature, and anoxia). Parallel reaction monitoring (PRM)-based quantification further confirmed that Hsp100 protein levels were significantly higher in resting cysts than in vegetative cells and increased after three months of storage. These findings collectively highlighted the fundamental role of Hsp100 in the alteration of the life cycle and dormancy maintenance of S. acuminata, likely by enhancing stress adaptation and promoting cell survival through participation in proteostasis maintenance, particularly under natural sediment-like conditions that trigger severe abiotic stress. Our work deepens the current understanding of Hsp family members in dinoflagellates, paving the way for future investigations into their ecological relevance within this ecologically significant group. Full article

Snow serves as a crucial water source for vegetation growth on the Mongolian Plateau, and its temporal and spatial variations exert profound influences on terrestrial vegetation phenology. In recent years, global climate change has led to significant changes in snow and vegetation start of growing season (SOS). Therefore, it is necessary to study the mechanism of snow cover on vegetation growth and changes on the Mongolian Plateau. The study found that the spatial snow cover fraction (SCF) of the Mongolian Plateau ranged from 50% to 60%, and the snow melt date (SMD) ranged from day of the year (DOY) 88 to 220, mainly concentrated on the northwest Mongolian Plateau mountainous areas. Using different SOS methods to calculate the vegetation SOS distribution map. Vegetation SOS occurs earlier in the eastern part compared to the western part of the Mongolian Plateau. In this study, we assessed spatiotemporal distribution characteristics of snow on the Mongolian Plateau over the period from 2001 to 2023. The results showed that the SOS of the Mongolian Plateau was mainly concentrated on DOY 71-186. The Cox survival analysis model system established SCF and SMD on vegetation SOS. The SCF standard coefficient is 0.06, and the SMD standard coefficient is 0.02. The SOS_NDVI coefficient is −0.15, and the SOS_NDGI coefficient is −0.096. The results showed that the vegetation SOS process exhibited differential response characteristics to snow driving factors. These research results also highlight the important role of snow in vegetation phenology and emphasize the importance of incorporating the unique effects of vegetation SOS on the Mongolian Plateau. Full article

Objective: To explore the relationship between type of grocery store used (chain vs. independent), transportation access, food insecurity, and fruit and vegetable intake in Detroit, Michigan, USA, during the COVID-19 pandemic. Design: A cross-sectional online survey was conducted from December 2021 to May 2022. Setting: Detroit, Michigan. Participants: 656 Detroit residents aged 18 and older. Results: Bivariate analyses showed that chain grocery store shoppers reported significantly greater fruit and vegetable intake (2.42 vs. 2.14 times/day for independent grocery store shoppers, p < 0.001) and lower rates of food insecurity compared to independent store shoppers (45.9% vs. 65.3% for independent grocery store shoppers, p < 0.001). Fewer independent store shoppers used their own vehicle (52.9% vs. 76.2% for chain store shoppers, p < 0.001). After adjusting for socioeconomic and demographic variables transportation access was strongly associated with increased odds of shopping at chain stores (OR = 1.89, 95% CI [1.21,2.95], p = 0.005) but food insecurity was no longer associated with grocery store type. Shopping at chain grocery stores was associated with higher fruit and vegetable intake after adjusting for covariates (1.18 times more per day, p = 0.042). Qualitative responses highlighted systemic barriers, including poor food quality, high costs, and limited transportation options, exacerbating food access inequities. Conclusions: These disparities underscore the need for targeted interventions to improve transportation options and support food security in vulnerable populations, particularly in urban areas like Detroit. Addressing these structural challenges is essential for reducing food insecurity and promoting equitable access to nutritious foods. Full article

Given that the Sunkoshi River watershed (located in the southern foot of the Himalayas) is sensitive to climate change and its mountain ecosystem provides important services, we aim to evaluate its spatial and temporal variation patterns of vegetation, represented by the Normalized Difference Vegetation Index (NDVI), during 2000–2021 and identify the dominant driving factors of vegetation change. Based on the NDVI dataset (MOD13A1), we used the simple linear trend model, seasonal and trend decomposition using loess (STL) method, and Mann–Kendall test to investigate the spatiotemporal variation features of NDVI during 2000–2021 on multiple scales (annual, seasonal, monthly). We used the partial correlation coefficient (PCC) to quantify the response of the NDVI to land surface temperature (LST), precipitation, humidity, and soil moisture. The results indicate that the annual NDVI in 52.6% of the study area (with elevation of 1–3 km) increased significantly, while 0.9% of the study area (due to urbanization) degraded significantly during 2000–2021. Daytime LST dominates NDVI changes on spring, summer, and winter scales, while precipitation, soil moisture, and nighttime LST are the primary impact factors on annual NDVI changes. After removing the influence of soil moisture, the contributions of climate factors to NDVI change are enhanced. Precipitation shows a 3-month lag effect and a 5-month cumulative effect on the NDVI; both daytime LST and soil moisture have a 4-month lag effect on the NDVI; and humidity exhibits a 2-month cumulative effect on the NDVI. Overall, the study area turned green during 2000–2021. The dominant driving factors of NDVI change may vary on different time scales. The findings will be beneficial for climate change impact assessment on the regional eco-environment, and for integrated watershed management. Full article

Brassinosteroids (BRs) are steroid hormones that are essential for plant growth, development, and environmental adaptation. They control the division, elongation, and differentiation of various cell types throughout the entire plant life cycle, affecting growth and the stress response. Therefore, fine-tuning of BR biosynthesis and modulation of signaling pathways offer possibilities for developing cultivars characterized by adjusted plant architecture or improved stress tolerance to benefit crop production. Additionally, precise BR treatments can be employed to increase the productivity of crop plants. This review aims to provide a comprehensive summary of the genetic basis of traits related to BR metabolism and signaling in cucurbits, the second largest vegetable family, which contributes significantly to global vegetable production and nutritional security. We summarize the current knowledge concerning BR biosynthesis mutants, the role of BRs in stress mitigation, and the potential of the exogenous application of BRs to alleviate stress during cucurbit production. We also discuss how genes related to BR metabolism can be used to develop gene editing strategies to advance precision breeding in cucurbits. Full article

Water scarcity challenges floriculture, which depends on quality irrigation for ornamental value. This study assessed short-term salinity tolerance in eight Asteraceae species by measuring physiological (proline levels, antioxidant enzyme activity) and morphological (plant height, flower number, and size) responses. Plants were irrigated with 0, 50, 100, or 300 mM NaCl for 10 days. Salinity significantly enhanced proline content and the activity of key antioxidant enzymes (catalase, peroxidase, and ascorbate peroxidase), reflecting the activation of stress defense mechanisms. However, these defenses failed to fully protect reproductive organs. Flower number and size were consistently more sensitive to salinity than vegetative traits, with significant reductions observed even at 50 mM NaCl. Responses varied between species, with Zinnia elegans and Calendula officinalis exhibiting pronounced sensitivity to salinity, whereas Tagetes patula showed relative tolerance, particularly under moderate stress conditions. The results show that flower structures are more vulnerable to ionic and osmotic disturbances than vegetative tissues, likely due to their higher metabolic demands and developmental sensitivity. Their heightened vulnerability underscores the need to prioritize reproductive performance when evaluating stress tolerance. Incorporating these traits into breeding programs is essential for developing salt-tolerant floriculture species that maintain aesthetic quality under limited water availability. Full article

Unmanned Aerial Vehicle Remote Sensing (UAV-RS) has emerged as a transformative technology in high-resolution Earth observation, with widespread applications in precision agriculture, ecological monitoring, and disaster response. However, a systematic understanding of its scientific evolution and structural bottlenecks remains lacking. This study collected 4985 peer-reviewed articles from the Web of Science Core Collection and conducted a comprehensive scientometric analysis using CiteSpace v.6.2.R4, Origin 2022, and Excel. We examined publication trends, country/institutional collaboration networks, keyword co-occurrence clusters, and emerging research fronts. Results reveal an exponential growth in UAV-RS research since 2015, dominated by application-driven studies. Hotspots include vegetation indices, structure from motion modeling, and deep learning integration. However, foundational challenges—such as platform endurance, sensor coordination, and data standardization—remain underexplored. The global collaboration network exhibits a “strong hubs, weak bridges” pattern, limiting transnational knowledge integration. This review highlights the imbalance between surface-level innovation and deep technological maturity and calls for a paradigm shift from fragmented application responses to integrated systems development. Our findings provide strategic insights for researchers, policymakers, and funding agencies to guide the next stage of UAV-RS evolution. Full article