Search Results (3,078)

Wildfire and drought are key drivers of shrubland expansion in southwestern US landscapes. Stand-replacing fires in conifer forests induce shrub-dominated stages, and changing climatic patterns may cause a long-term shift to deciduous shrubland. We assessed change in deciduous fractional shrub cover (DFSC) in the eastern Jemez Mountains from 2019 to 2023 using topographic and Sentinel-2 satellite data and evaluated the impact of spatial scale on model performance. First, we built a 10 m and a 20 m random forest model. The 20 m model outperformed the 10 m model, achieving an R-squared value of 0.82 and an RMSE of 7.85, compared to the 10 m model (0.76 and 9.99, respectively). We projected the 20 m model to the other years of the study using imagery from the respective years, yielding yearly DFSC predictions. DFSC decreased from 2019 to 2022, coinciding with severe drought and a 2022 fire, followed by an increase in 2023, particularly within the 2022 fire footprint. Overall, DFSC trends showed an increase, with elevation being a key variable influencing these trends. This framework revealed vegetation dynamics in a semi-arid system and provided a close look at post-fire regeneration in deciduous resprouting shrubs and could be applied to similar systems. Full article

Amidst global climate change, carbon emissions across the edible vegetable oil supply chain are critical for sustainable development. This paper systematically reviews the existing literature, employing life cycle assessment (LCA) to analyze key factors influencing carbon footprints at stages including cultivation, processing, and transportation. It reveals the differential impacts of fertilizer application, energy structures, and regional policies. Unlike previous reviews that focus on single crops or regions, this study uniquely integrates global data across major edible oils, identifying three critical gaps: methodological inconsistency (60% of studies deviate from the requirements and guidelines for LCA); data imbalance (80% concentrated on soybean/rapeseed); weak policy-technical linkage. Key findings: fertilizer emissions dominate cultivation (40–60% of total footprint), while renewable energy substitution in processing reduces emissions by 35%. Future efforts should prioritize multidisciplinary integration, enhanced data infrastructure, and policy scenario analysis to provide scientific insights for the low-carbon transformation of the global edible oil industry. Full article

Accurate and non-destructive monitoring of leaf chlorophyll content (LCC) is essential for assessing crop photosynthetic activity and nitrogen status in precision agriculture. This study introduces a phenology-aware machine learning framework that combines hyperspectral reflectance data with various regression models to estimate leaf chlorophyll content (LCC) in cotton at six key reproductive stages. Field experiments utilized synchronized spectral and SPAD measurements, incorporating spectral transformations—such as vegetation indices (VIs), first-order derivatives, and trilateration edge parameters (TEPs, a new set of geometric metrics for red-edge characterization)—for evaluation. Five regression approaches were evaluated, including univariate and multivariate linear models, along with three machine learning algorithms: Random Forest, K-Nearest Neighbor, and Support Vector Regression. Random Forest consistently outperformed the other models, achieving the highest R² (0.85) and the lowest RMSE (4.1) during the bud stage. Notably, the optimal prediction accuracy was achieved with fewer than five spectral features. The proposed framework demonstrates the potential for scalable, stage-specific monitoring of chlorophyll dynamics and offers valuable insights for large-scale crop management applications. Full article

Foodborne illness caused by bacterial pathogens is a global health concern and results in millions of infections annually. Therefore, food products typically undergo several processing stages, including sanitation steps, before being distributed in an attempt to remove pathogens. However, many sanitation methods have compounding effects on the color, texture, flavor, and nutritional quality of the product or do not effectively reduce the pathogens that food can be exposed to. Some bacterial pathogens particularly possess traits and tactics that make them even more difficult to mitigate such as biofilm formation. Non-thermal plasma sanitation techniques, including plasma-treated water (PTW), have proven to be promising methods that significantly reduce pathogenic bacteria that food is exposed to. Published work reveals that PTW can effectively mitigate both gram-positive and gram-negative bacterial biofilms. This study presents a novel analysis of the differences in antimicrobial effects of PTW treatment between biofilm-forming gram-positive bacteria, commonly associated with foodborne illness, that are sporulating (Bacillus cereus) and non-sporulating (Listeria monocytogenes). After treatment with PTW, the results suggest the following hypotheses: (1) that the non-sporulating species experiences less membrane damage but a greater reduction in metabolic activity, leading to a possible viable but non-culturable (VBNC) state, and (2) that the sporulating species undergoes spore formation, which may subsequently convert into vegetative cells over time. PTW treatment on gram-positive bacterial biofilms that persist in food processing environments proves to be effective in reducing the proliferating abilities of the bacteria. However, the variance in PTW’s effects on metabolic activity and cell vitality between sporulating and non-sporulating species suggest that other survival tactics might be induced. This analysis further informs the application of PTW in food processing as an effective sanitation method. Full article

Bare land exposed by glacier retreat provides new opportunities for ecosystem development. Investigating primary vegetation succession in deglaciated regions can provide significant insights for ecological restoration, particularly for future climate change scenarios. Nonetheless, research on this topic in the Qinghai–Tibet Plateau has been exceedingly limited. This study aimed to investigate vegetation succession in the deglaciated area of the Zepu glacier during the Little Ice Age in southeastern Tibet. Quadrat surveys were performed on arboreal communities, and trends in vegetation change were assessed utilizing multi-year (1986–2024) remote sensing data. The findings indicate that vegetation succession in the Zepu glacier deglaciated area typically adheres to a sequence of bare land–shrub–tree, divided into four stages: (1) shrub (species include Larix griffithii Mast., Hippophae rhamnoides subsp. yunnanensis Rousi, Betula utilis D. Don, and Populus pseudoglauca C. Wang & P. Y. Fu); (2) broadleaf forest primarily dominated by Hippophae rhamnoides subsp. yunnanensis Rousi; (3) mixed coniferous–broadleaf forest with Hippophae rhamnoides subsp. yunnanensis Rousi and Populus pseudoglauca C. Wang & P. Y. Fu as the dominant species; and (4) mixed coniferous–broadleaf forest dominated by Picea likiangensis (Franch.) E. Pritz. Soil depth and NDVI both increase with succession. Species diversity is significantly higher in the third stage compared to other successional stages. In addition, soil moisture content is significantly greater in the broadleaf-dominated communities than in the conifer-dominated communities. An analysis of NDVI from 1986 to 2024 reveals an overall positive trend in vegetation recovery in the area, with 93% of the area showing significant vegetation increase. Temperature is the primary controlling factor for this recovery, showing a positive correlation with vegetation cover. The results indicate that Key ecological indicators—including species composition, diversity, NDVI, soil depth, and soil moisture content—exhibit stage-specific patterns, reflecting distinct phases of primary succession. These findings enhance our comprehension of vegetation succession in deglaciated areas and their influencing factors in deglaciated areas, providing theoretical support for vegetation restoration in climate change. Full article

This study compares the nutritional and metabolic properties of unconventional cold-pressed vegetable oils available on the Polish market. Twelve oils—milk thistle, evening primrose, flaxseed, camelina sativa, black cumin, pumpkin seed, sesame, mustard seed, sea buckthorn, blue poppy seed, borage, and safflower—were examined. The chosen oils were investigated based on their fatty acids profiles, total phenolic compounds (TPC), tocopherols, and pigment contents. Despite the high polyunsaturated fatty acids (PUFAs) content raising concerns about oxidative stability, the significant tocopherol levels and polyphenols content contribute to antioxidative protection. These oils’ favorable hypocholesterolemic, antiatherogenic, and antithrombogenic properties were highlighted by key nutritional indices, showing potential benefits for cardiovascular health. These results suggest that these oils are a promising dietary supplement for promoting both cardiovascular health and sustainability, owing to their rich content of essential fatty acids and bioactive compounds. Moreover, high correlations were found between theoretical and experimental established oxidative stability of the tested oils at the ending stage of the thermostat test. Full article

To elucidate the molecular mechanisms underlying anther abortion in celery male sterile lines, this study investigates the morphological differences of floral organs and differential gene expression patterns between two lines at the flowering stage. Using the male sterile line of celery ‘QCBU-001’ and the fertile line ‘Jinnan Shiqin’ as materials, anther structure was analyzed by paraffin sections, and related genes were detected using transcriptome sequencing and qRT-PCR. The results indicated that the anther locules were severely shrunken at maturity in the sterile lines. The callose deficiency led to abnormal development of microspores, preventing the formation of mature pollen grains and ultimately leading to complete anther abortion. The transcriptome results revealed that 3246 genes were differentially expressed in sterile and fertile lines, which were significantly enriched in pathways such as starch and sucrose metabolism and phenylpropanoid biosynthesis. Additionally, differential expression patterns of transcription factor families (MYB, bHLH, AP2, GRAS, and others) suggested their potential involvement in regulating anther abortion. Notably, the expression level of callose synthase gene AgGSL2 was significantly downregulated in sterile anthers, which might be an important cause of callose deficiency and pollen sterility. This study not only provides a theoretical basis for elucidating the molecular mechanism underlying male sterility in celery but also lays a foundation for the utilization and improvement of male sterile lines in vegetable hybrid breeding. Full article

The ongoing decade of UN restoration matches with the European goal of bringing nature back into our lives, including in urban systems, and Nature Restoration Regulation. Within such a framework, this work is aimed at highlighting the ecological rationale and strategic value of an NRRP measure devoted to forest restoration in Italian Metropolitan Cities, and at assessing respective preliminary results. Therefore, the measure’s overarching goal (not to create urban parks or gardens, but activate forest recovery), geographic extent and scope (over 4000 ha and more than 4 million planted trees and shrubs across the country), plantation model (mandatory use of native species consistent with local potential vegetation, density of 1000 seedlings per ha, use of at least four tree and four shrub species in each project, with a minimum proportion of 70% for trees, certified provenance for reproductive material), and compulsory management activities (maintenance and replacement of any dead plants for at least five years), are herein shown and explained under an ecological perspective. Current implementation outcomes were thus assessed in terms of coherence and expected biodiversity benefits, especially with respect to ecological and biogeographic consistency of planted forests, representativity in relation to national and European plant diversity, biogeographic interest and conservation concern of adopted plants, and potential contribution to the EU Habitats Directive. Compliance with international strategic goals and normative rules, along with recognizable advantages of the measure and limitations to be solved, are finally discussed. In conclusion, the forestation model proposed for the Italian Metropolitan Cities proved to be fully applicable in its ecological rationale, with expected benefits in terms of biodiversity support plainly met, and even exceeded, at the current stage of implementation, especially in terms of the contribution to protected habitats. These promising preliminary results allow the model to be recognized at the international level as a good practice that may help achieve protection targets and sustainable development goals within and beyond urban systems. Full article

Understanding the alterations to the shoot and root traits of rapeseed (Brassica napus) in response to salt stress is vital for improving its ability to thrive in saline-prone regions. This research aims to evaluate the responses of shoot and root traits of rapeseed at the vegetative stage under salt- and salicylic acid-induced stress in hydroponic culture. Five parents and ten F₃ segregants of rapeseed were subjected to three treatments: T1: control, T2: 8 dSm⁻¹ salt, and T3: 8 dSm⁻¹ salt + 0.1 mM salicylic acid at 21 days of age. Salinity stress significantly reduced the estimated root surface area by 54% compared to control, highlighting the plasticity of roots under stress. The simultaneous application of salt and SA did not alleviate the salinity stress, but rather reinforced the degree of stress and decreased the number of leaves, diameter of the main axis, chlorophyll content, and estimated root surface area by 18.5%, 15.4%, 38.8%, and 23%, respectively, compared to T2. The parental genotype M-245 followed by F₃ genotype M-232×M-223 accounted for the higher overall estimated root surface area. These results provide novel insights into the responses of root traits in rapeseed breeding lines under dual treatment, which hold promising implications for future rapeseed breeding efforts focused on sustainable rapeseed production. Full article

Water infiltration into soil is a key process in regulating the hydrological cycle and sustaining ecosystem services in high-Andean environments. However, limited information is available regarding its dynamics in these ecosystems. This study evaluated the influence of three types of vegetation cover and soil properties on water infiltration in a high-Andean environment. A double-ring infiltrometer, the Water Drop Penetration Time (WDPT, s) method, and laboratory physicochemical characterization were employed. Soils under forest cover exhibited significantly higher quasi-steady infiltration rates (i_s, 0.248 ± 0.028 cm·min⁻¹) compared to grazing areas (0.051 ± 0.016 cm·min⁻¹) and agricultural lands (0.032 ± 0.013 cm·min⁻¹). Soil organic matter content was positively correlated with i_s. The modified Kostiakov infiltration model provided the best overall fit, while the Horton model better described infiltration rates approaching i_s. Sand and clay fractions, along with K⁺, Ca²⁺, and Mg²⁺, were particularly significant during the soil’s wet stages. In drier stages, increased Na⁺ concentrations and decreased silt content were associated with higher water repellency. Based on WDPT, agricultural soils exhibited persistent hydrophilic behavior even after drying (median [IQR] from 0.61 [0.38] s to 1.24 [0.46] s), whereas forest (from 2.84 [3.73] s to 3.53 [24.17] s) and grazing soils (from 4.37 [1.95] s to 19.83 [109.33] s) transitioned to weakly or moderately hydrophobic patterns. These findings demonstrate that native Andean forest soils exhibit a higher infiltration capacity than soils under anthropogenic management (agriculture and grazing), highlighting the need to conserve and restore native vegetation cover to strengthen water resilience and mitigate the impacts of land-use change. Full article

Banana Fusarium wilt (BFW, also known as Panama disease) is a highly infectious and destructive disease that threatens global banana production, requiring early recognition for timely prevention and control. Current monitoring methods primarily rely on continuous variable features—such as band reflectances (BRs) and vegetation indices (VIs)—collectively referred to as basic features (BFs)—which are prone to noise during the early stages of infection and struggle to capture subtle spectral variations, thus limiting the recognition accuracy. To address this limitation, this study proposes a discretized enhanced feature (EF) construction method, the automated kernel density segmentation-based feature construction algorithm (AutoKDFC). By analyzing the differences in the kernel density distributions between healthy and diseased samples, the AutoKDFC automatically determines the optimal segmentation threshold, converting continuous BFs into binary features with higher discriminative power for early-stage recognition. Using UAV-based multi-spectral imagery, BFW recognition models are developed and tested with the random forest (RF), support vector machine (SVM), and Gaussian naïve Bayes (GNB) algorithms. The results show that EFs exhibit significantly stronger correlations with BFW’s presence than original BFs. Feature importance analysis via RF further confirms that EFs contribute more to the model performance, with VI-derived features outperforming BR-based ones. The integration of EFs results in average performance gains of 0.88%, 2.61%, and 3.07% for RF, SVM, and GNB, respectively, with SVM achieving the best performance, averaging over 90%. Additionally, the generated BFW distribution map closely aligns with ground observations and captures spectral changes linked to disease progression, validating the method’s practical utility. Overall, the proposed AutoKDFC method demonstrates high effectiveness and generalizability for BFW recognition. Its core concept of “automatic feature enhancement” has strong potential for broader applications in crop disease monitoring and supports the development of intelligent early warning systems in plant health management. Full article

To improve the identification of drought-affected areas in winter wheat, this paper proposes a lightweight network called MF-FusionNet based on multimodal fusion of RGB images and vegetation indices (NDVI and EVI). A multimodal dataset covering various drought levels in winter wheat was constructed. To enable deep fusion of modalities, a Lightweight Multimodal Fusion Block (LMFB) was designed, and a Dual-Coordinate Attention Feature Extraction module (DCAFE) was introduced to enhance semantic feature representation and improve drought region identification. To address differences in scale and semantics across network layers, a Cross-Stage Feature Fusion Strategy (CFFS) was proposed to integrate multi-level features and enhance overall performance. The effectiveness of each module was validated through ablation experiments. Compared to traditional single-modal methods, MF-FusionNet achieved higher accuracy, recall, and F1-score—improved by 1.35%, 1.43%, and 1.29%, respectively—reaching 96.71%, 96.71%, and 96.64%. A basis for real-time monitoring and precise irrigation management under winter wheat drought stress was provided by this study. Full article

Weed infestation contributes significantly to global agricultural yield loss and increases the reliance on herbicides, raising both economic and environmental concerns. Effective weed detection in agriculture requires high accuracy and architectural efficiency. This is particularly important under challenging field conditions, including densely clustered targets, small weed instances, and low visual contrast between vegetation and soil. In this study, we propose GTDR-YOLOv12, an improved object detection framework based on YOLOv12, tailored for real-time weed identification in complex agricultural environments. The model is evaluated on the publicly available Weeds Detection dataset, which contains a wide range of weed species and challenging visual scenarios. To achieve better accuracy and efficiency, GTDR-YOLOv12 introduces several targeted structural enhancements. The backbone incorporates GDR-Conv, which integrates Ghost convolution and Dynamic ReLU (DyReLU) to improve early-stage feature representation while reducing redundancy. The GTDR-C3 module combines GDR-Conv with Task-Dependent Attention Mechanisms (TDAMs), allowing the network to adaptively refine spatial features critical for accurate weed identification and localization. In addition, the Lookahead optimizer is employed during training to improve convergence efficiency and reduce computational overhead, thereby contributing to the model’s lightweight design. GTDR-YOLOv12 outperforms several representative detectors, including YOLOv7, YOLOv9, YOLOv10, YOLOv11, YOLOv12, ATSS, RTMDet and Double-Head. Compared with YOLOv12, GTDR-YOLOv12 achieves notable improvements across multiple evaluation metrics. Precision increases from 85.0% to 88.0%, recall from 79.7% to 83.9%, and F1-score from 82.3% to 85.9%. In terms of detection accuracy, mAP:0.5 improves from 87.0% to 90.0%, while mAP:0.5:0.95 rises from 58.0% to 63.8%. Furthermore, the model reduces computational complexity. GFLOPs drop from 5.8 to 4.8, and the number of parameters is reduced from 2.51 M to 2.23 M. These reductions reflect a more efficient network design that not only lowers model complexity but also enhances detection performance. With a throughput of 58 FPS on the NVIDIA Jetson AGX Xavier, GTDR-YOLOv12 proves both resource-efficient and deployable for practical, real-time weeding tasks in agricultural settings. Full article

Cutting propagation is a commonly employed technology for vegetative reproduction in agricultural, forestry, and horticultural practice. The success of cutting propagation depends on adventitious root (AR) formation—a process whereby roots regenerate from stem cuttings or leaf cuttings. In this review, we summarize the distinct stages of cutting-induced AR formation and highlight the pivotal roles of plant hormones and age in this process. Jasmonic acid (JA) acts as a master trigger for promoting AR formation, while auxin serves as the core regulator, driving AR formation. Furthermore, plant age is a crucial factor determining the regenerative competence of cuttings. Notably, age and JA collaboratively modulate auxin synthesis in cutting-induced AR formation. Overall, this review not only elucidates the molecular mechanisms underlying AR formation but also provides valuable insights for improving efficiency of cutting propagation in various plant species. 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