Search Results (522)

The advancement of Artificial Intelligence (AI) has significantly accelerated progress across various research domains, with growing interest in plant science due to its substantial economic potential. However, the integration of AI with digital vegetation analysis remains underexplored, largely due to the absence of large-scale, real-world plant datasets, which are crucial for advancing this field. To address this gap, we introduce the PP3D dataset—a meticulously labeled collection of about 500 potted plants represented as 3D point clouds, featuring fine-grained annotations for approximately 20 species. The PP3D dataset provides 3D phenotypic data for about 20 plant species spanning model organisms (e.g., Arabidopsis thaliana), potted plants (e.g., Foliage plants, Flowering plants), and horticultural plants (e.g., Solanum lycopersicum), covering most of the common important plant species. Leveraging this dataset, we propose the panoptic plant recognition task, which combines semantic segmentation (stems and leaves) with leaf instance segmentation. To tackle this challenge, we present SCNet, a novel dual-representation learning network designed specifically for plant point cloud segmentation. SCNet integrates two key branches: a cylindrical feature extraction branch for robust spatial encoding and a sequential slice feature extraction branch for detailed structural analysis. By efficiently propagating features between these representations, SCNet achieves superior flexibility and computational efficiency, establishing a new baseline for panoptic plant recognition and paving the way for future AI-driven research in plant science. Full article

DNA methylation, mediated by DNA methyltransferases (DMTs) and demethylases (DMLs), is an important epigenetic modification that maintains genomic stability and regulates gene expression in plant growth, development, and stress responses. However, a comprehensive characterization of these gene families in Populus sect. Turanga remains lacking. In this study, eight PeDMT and two PeDML genes were identified in Populus euphratica, and six PpDMT and three PpDML genes in Populus pruinosa. Phylogenetic analysis revealed that DMTs and DMLs could be classified into four and three subfamilies, respectively. The analysis of cis-acting elements indicated that the promoter regions of both DMTs and DMLs were enriched with elements responsive to growth and development, light, phytohormones, and stress. Collinearity analysis detected three segmentally duplicated gene pairs (PeDMT5/8, PeDML1/2, and PpDML2/3), suggesting potential functional diversification. Transcriptome profiling showed that several PeDMTs and PeDMLs exhibited leaf shape- and developmental stage-specific expression patterns, with PeDML1 highly expressed during early stages and in broad-ovate leaves. Whole-genome bisulfite sequencing revealed corresponding decreases in DNA methylation levels, suggesting that active demethylation may contribute to heteromorphic leaf formation. Overall, this study provides significant insights for exploring the functions and expression regulation of plant DMTs and DMLs and will contribute to future research unraveling the molecular mechanisms of epigenetic regulation in P. euphratica. Full article

Bird-dropping fouling and hotspot anomalies remain the most prevalent and detrimental defects in utility-scale photovoltaic (PV) plants; their co-occurrence on a single module markedly curbs energy yield and accelerates irreversible cell degradation. However, markedly disparate visual–thermal signatures of the two phenomena impede high-fidelity concurrent detection in existing robotic inspection systems, while stringent onboard compute budgets also preclude the adoption of bulky detectors. To resolve this accuracy–efficiency trade-off for dual-defect detection, we present YOLOv8-SG, a lightweight yet powerful framework engineered for mobile PV inspectors. First, a rigorously curated multi-modal dataset—RGB for stains and long-wave infrared for hotspots—is assembled to enforce robust cross-domain representation learning. Second, the HSV color space is leveraged to disentangle chromatic and luminance cues, thereby stabilizing appearance variations across sensors. Third, a single-head self-attention (SHSA) block is embedded in the backbone to harvest long-range dependencies at negligible parameter cost, while a global context (GC) module is grafted onto the detection head to amplify fine-grained semantic cues. Finally, an auxiliary bounding box refinement term is appended to the loss to hasten convergence and tighten localization. Extensive field experiments demonstrate that YOLOv8-SG attains 86.8% mAP@0.5, surpassing the vanilla YOLOv8 by 2.7 pp while trimming 12.6% of parameters (18.8 MB). Grad-CAM saliency maps corroborate that the model’s attention consistently coincides with defect regions, underscoring its interpretability. The proposed method, therefore, furnishes PV operators with a practical low-latency solution for concurrent bird-dropping and hotspot surveillance. Full article

Global interest in nematode communities and their ecological relationships as unique and complex soil ecosystems has remarkably increased in recent years. As they have a representative role in the soil biota, nematodes present great potential to help understand soil health through analyzing their food chains in different environments. The objective of this study was to analyze the spatial and dynamic distributions of nematode communities and soil properties in two riparian areas of the Caatinga biome: one with native vegetation and the other with a history of agricultural use (modified). The study was carried out in a semi-arid region of Brazil in Parnamirim, PE. In both areas, sampling grids of 60 m × 40 m were established to obtain data on soil moisture, organic matter, particle size, electrical conductivity, and pH, as well as metabolic activity and ecological indices of nematode communities. There was a greater abundance and diversity of nematodes in riparian soils with native vegetation compared to in the modified area due to agricultural use and the dominance of exotic and invasive species. In both areas, bacterivores and plant-parasitic nematodes were dominant, with the genus Acrobeles and Tylenchorhynchus as the main contributors to the community. In the modified area, soil variables (fine sand, clay, and pH) positively influenced Fu4 and PP4 guilds, while in the area with native vegetation, moisture and organic matter exerted a greater influence on Om4, PP5, and Ba3 guilds. Kriging maps showed the soil variables were more concentrated in the center in the areas with native vegetation, in contrast to the area with modified vegetation, where they concentrated more on the margins. The functional guilds in the native vegetation did not exhibit a gradual increase towards the regions close to the riverbank, unlike in the modified area. The presence of plant-parasitic nematodes, especially of the genus Tylenchorhynchus, indicates the need for greater attention in the management of these ecosystems. The study contributes to understanding the interactions between nematode communities and soil in riparian areas of the Caatinga biome, emphasizing the importance of preserving native vegetation to maintain the diversity and balance of this ecosystem, in addition to highlighting the need for appropriate management practices in areas with a history of agricultural use, aiming to conserve soil biodiversity. Full article

The phosphofructokinase (PFK) gene family plays a pivotal role in glycolysis and energy metabolism in plants. This study aimed to systematically characterize the PFK gene family in Arabidopsis thaliana at the genome-wide level and to investigate the function of AtPFK2 (ATP-dependent phosphofructokinase 2) in response to salt and drought stress. Through bioinformatics analysis, 11 AtPFK genes were identified. Phylogenetic analysis revealed that these PFK genes can be classified into two subfamilies: PFK and PFP. Notably, AtPFK2 possesses a unique structure, containing only a single intron, and its promoter is enriched with stress- and hormone-responsive elements, such as ABRE and MBS. T-DNA insertion mutants (pfk2) exhibited slightly shorter roots but slightly higher fresh weight under stress conditions, whereas Arabidopsis lines AtPFK2-overexpressing (OE-PFK2) showed increased stress sensitivity, with inhibited root and leaf growth, leaf wilting, reduced malondialdehyde and chlorophyll content, and enhanced accumulation of proline and soluble sugars. Weighted gene co-expression network analysis (WGCNA) identified 14 stress-related modules, from which six core genes—LBD41, TRP3, PP2-A3, SAUR10, IAA6, and JAZ1—were selected. These genes are involved in glycine metabolism and plant hormone signaling. The results of this study indicate that AtPFK2 mediates stress responses by regulating osmoregulatory substances and hormone signaling pathways, offering new insights into the mechanisms of stress resistance in crops. Full article

Since airborne microplastics (AMPs) are a recent and unexplored field of study, there are several unresolved issues regarding their effects on plants. The accumulating potential of AMPs and their effect on the biochemical parameters of ten different plant species in an Indian city environment were assessed. The four types of AMPs deposited in the phyllosphere—fragment (30.76%), film (28.95%), fiber (22.61%), and pellet (17.68%)—were examined using stereomicroscopy and fluorescence microscopy. The air pollution tolerance index (APTI) was determined, and other biochemical parameters such as proline, phenol, malondialdehyde, carotenoids, superoxide dismutase, catalase, and peroxidase were also measured. The findings showed that in the case of polymers type, PE (30%) was more abundant than others, followed by PET (17%), PP (15%), PVC (13%), PVA (10%), PS (7%), ABS (5%), and PMMA (3%). Clerodendrum infortunatum L., Calotropis procera (Aiton) W.T. Aiton, and Mangifera indica L. all showed a strong APTI and also exhibited significantly higher amounts of AMP accumulation. Principal component analysis showed a stronger association between phyllospheric AMPs and biochemical parameters. Additionally, the correlation analysis revealed that the presence of accumulated AMPs may significantly influence the biochemical parameters of the plants. Thus, it can be concluded that the different plant species are uniquely specialized in AMP accumulation, which is significantly impacted by the plants’ APTI as well as other biochemical parameters. Full article

Microplastic pollution threatens coastal wetland ecosystems, yet its impacts on the dominant plant species and soil properties remain poorly understood. We investigated the effects of four microplastic types (PP, PE, PS, PET) at three concentrations (0.1%, 0.5%, 1% w/w) on Scirpus mariqueter, a keystone species in the coastal wetlands of China, and the associated soil physicochemical properties. In a controlled pot experiment, microplastics significantly altered the plant biomass, vegetative traits, and reproductive strategies, with type-specific and concentration-dependent responses. PET and PE strongly suppressed the belowground and total biomass (p < 0.05), with reductions in the belowground biomass of 42.87% and 44.13%, respectively, at a 0.1% concentration. PP promoted seed production, particularly increasing the seed number by 25.23% at a 0.1% concentration (p < 0.05). The soil NH₄⁺-N, moisture, and EC were key mediators, with NH₄⁺-N declines linked to biomass reductions via nitrogen limitation. The Spearman correlations confirmed strong associations between the plant traits and soil properties, particularly nitrogen forms. These findings reveal that microplastics disrupt wetland plant performance and soil environments, potentially impairing carbon sequestration and ecosystem stability. Our study underscores the urgent need for microplastic risk assessments in coastal wetlands and highlights soil–microbe–plant interactions as critical mechanisms for future investigation. Full article

Plant protein phosphatase 2C (PP2C) represents the largest and most functionally diverse group of protein phosphatases in plants, playing pivotal roles in regulating metabolic processes, hormone signaling, stress responses, and growth regulation. Despite its significance, a comprehensive genome-wide analysis of the PP2C gene family in oat (Avena sativa L.) has remained unexplored. Leveraging the recently published oat genome, we identified 194 AsaPP2C genes, which were unevenly distributed across all 21 chromosomes. A phylogenetic analysis of PP2C classified these genes into 13 distinct subfamilies (A-L), with conserved motif compositions and exon-intron structures within each subfamily, suggesting evolutionary functional specialization. Notably, a promoter analysis revealed an abundance of stress-responsive cis-regulatory elements (e.g., MYB, MYC, ARE, and MBS), implicating AsaPP2Cs in hormones and biotic stress adaptation. To elucidate their stress-responsive roles, we analyzed transcriptomic data and identified seven differentially expressed AsaPP2C (Asa_chr6Dg00217, Asa_chr6Ag01950, Asa_chr3Ag01998, Asa_chr5Ag00079, Asa_chr4Cg03270, Asa_chr6Cg02197, and Asa_chr7Dg02992) genes, which were validated via qRT-PCR. Intriguingly, these genes exhibited dynamic expression patterns under varying stress conditions, with their transcriptional responses being both time-dependent and stress-dependent, highlighting their regulatory roles in oat stress adaptation. Collectively, this study provides the first comprehensive genomic and functional characterization of the PP2C family in oat, offering valuable insights into their evolutionary diversification and functional specialization. Full article

Viticulture is vital to Italy’s agricultural sector, since it significantly contributes to the global wine industry. Microflora and microfauna are considered important factors for soil quality, improving grapevine growth, and promoting resistance to biotic and abiotic stresses. This study examined the impact of selected Trichoderma strains (T. harzianum M10 and T. afroharzianum T22) and their secondary metabolite 6-pentyl-α-pyrone (6PP) on the soil microbiome, the metabolome, and physiological changes of grapevines. Before treatment application, low levels of plant-parasitic nematodes (Rotylenchulus spp., Xiphinema pachtaicum) were found in the soil, together with pathogens (Fusarium spp., Neonectria spp.) and beneficial microbes (Clonostachys rosea, Pseudomonas spp.). Metagenomic analysis revealed significant treatment impacts in the soil microbiome, with T22 and 6PP treatments increasing Proteobacteria abundance, while slight variations of fungal communities and no significant differences in nematofauna were found. Metabolomic analysis showed that treatments induced grapevines to produce antioxidant secondary metabolites able to boost plant defense against abiotic and biotic stresses and increase nutraceutical grapes’ value. Finally, T22 treatment increased the grapes’ winemaking value, raising their Brix grade. Our results demonstrate that microbial or metabolite-based treatments could affect the soil microbiome composition, grapevine health and resilience, and grapes’ oenological and nutraceutical properties. Full article

In the recognition of fruit leaf diseases, image recognition technology based on deep learning has received increasing attention. However, deep learning models often perform poorly in complex backgrounds, and in some cases, they even outperform traditional algorithms. To address this issue, this paper proposes a Frequency-Adaptive Attention (FA-attention) mechanism that leverages the significance of frequency-domain features in fruit leaf disease regions. By enhancing the processing of frequency domain features, the recognition performance in complex backgrounds is improved. Specifically, FA-attention combines Fourier transform with the attention mechanism to extract frequency domain features as key features. Then, this mechanism is integrated with the Unet model to obtain feature maps strongly related to frequency domain features. These feature maps are fused with multi-scale convolutional feature maps and then used for classification. Experiments were conducted on the Plant Village (PV) dataset and the Plant Pathology (PP) dataset with complex backgrounds. The results indicate that the proposed FA-attention mechanism achieves significant effects in learning frequency domain features. Our model achieves a recognition accuracy of 99.91% on the PV dataset and 89.59% on the PP dataset. At the same time, the convergence speed is significantly improved, reaching 94% accuracy with only 20 epochs, demonstrating the effectiveness of this method. Compared with classical models and state-of-the-art (SOTA) models, our model performs better on complex background datasets, demonstrating strong generalization capabilities. Full article

This study investigates the industrial potential of red gypsum (RG), a major by-product of titanium dioxide (TiO₂) production, for the development of thermoplastic polypropylene (PP)-based composites via melt extrusion, targeting agricultural applications. Prior to compounding, RG was thermally treated at approximately 200 °C to remove residual moisture and chemically bound water, resulting in its anhydrous form (CaSO₄). PP/RG composites were then formulated with RG loadings up to 20 wt.%, employing stearic acid (SA) as a compatibilizer. The resulting materials were thoroughly characterized and successfully processed through industrial-scale injection molding up to 250 °C. Morphological and FTIR analyses confirmed the role of SA in enhancing both filler dispersion and interfacial adhesion between RG and the PP matrix. SEM images revealed finer and more uniformly distributed RG particles, resulting in a reduced loss of ductility and elongation at break typically associated with filler addition. Specifically, the Young’s Modulus increased from 1.62 GPa (neat PP) up to 3.21 GPa with 20 wt.% RG and 0.6 wt.% SA. The addition of 0.6 wt.% SA also helped limit the reduction in stress at break from 46.68 MPa (neat PP) to 34.05 MPa and similarly mitigated the decrease in Charpy impact energy, which declined slightly from 2.66 kJ/m² (neat PP) to 2.24 kJ/m² for composites containing 20 wt.% RG. Preliminary phytotoxicity was assessed using germination tests on Lepidium sativum L. seeds. Eluates from both untreated and SA-treated RG powders resulted in germination indices below 80%, indicating phytotoxicity likely due to high sulfate ion concentrations. In contrast, eluates from composite pellets exhibited germination indices equal to or exceeding 100%, demonstrating the absence of phytotoxic effects. These results highlight the suitability of the developed composites for applications in floriculture and horticulture. The optimized composite pellets were successfully processed via injection molding to manufacture plant pots, which exhibited a dark brown coloration, confirming the effective pigmenting function of RG. These results demonstrate the potential of red gypsum to serve both as a functional filler and pigment in PP composites, providing a sustainable alternative to iron oxide pigments and promoting the valorization of industrial waste through resource recovery. Full article

Yam (Dioscorea spp.) provides various nutritional and medicinal benefits, including a high starch content, dietary fiber, essential micronutrients, and bioactive compounds. The molecular mechanisms underlying tuber expansion have not yet been clarified. Rapid alkalinization factor (RALF) genes, which mediate various processes in plants, are thought to contribute to the regulation of tuber growth; however, their role in yam development, especially in gibberellin (GA)-mediated processes, remains unclear. Here, we characterized seven DrRALF genes in the yam genome. Analysis of gene duplication demonstrated that the expansion of DrRALF genes was primarily driven by whole-genome duplication or segmental duplication. Phylogenetic analysis revealed that DrRALF genes were concentrated in specific clusters, indicating that their functions are relatively conserved. DrRALF5 was specifically expressed in the roots, and DrRALF2, DrRALF3, DrRALF4, and DrRALF6 were highly expressed in flowers. DrRALF1, DrRALF2, DrRALF3, DrRALF4, DrRALF5, and DrRALF6 were shown to play a role in tuber expansion. Subsequent qRT-PCR validation of four selected DrRALF genes confirmed the regulation of DrRALF2, DrRALF4, DrRALF5, and DrRALF6 by GA and PP333 (paclobutrazol, a GA biosynthesis inhibitor). Yeast one-hybrid assays further showed that the DrRALF6 promoter region interacted with the GA-signaling protein, DrDELLA1. Our findings provide novel insights into the regulatory network controlling yam tuber expansion, especially through the interaction between DrRALF6 and GA signaling pathways. Our results clarify the molecular mechanisms involved in tuber growth and propose a promising strategy for improving yam production through genetic manipulation of the GA-RALF signaling pathway. Full article

Saline–alkali stress severely inhibited potato growth, yield, and quality, and exogenous abscisic acid (ABA) played an important role in plant stress resistance. In this study, potato tissue culture seedlings were used as experimental materials, the control group was cultured in the MS medium without adding any substances, and the treatment group was cultured in MS medium supplemented with 50 mmol/L NaHCO₃ or 50 mmol/L NaHCO₃ + 38 µM ABA, respectively. To explore the effect of exogenous ABA on the biological characteristics of potato plants under saline–alkali stress, a genetic improvement strategy was designed based on PP2C (PGSC0003DMT400046381), a key gene of the ABA signaling pathway. The results showed that saline–alkali stress led to leaf greening, wilting, and root development stunting, while exogenous ABA treatment significantly alleviated stress damage. PP2C negatively regulates ABA signaling. SnRK2s are activated when PP2Cs are inactivated during the ABA response. Compared with wild-type CK, it was found that TG lines had increased SOD and POD activities, increased carotenoid and ABA contents, reduced the increase in Na⁺ content and the decrease in K⁺ content, and interfered with PP2C (PGSC0003DMT400046381) to significantly enhance potato salinity–alkali resistance. This study provides a theoretical basis and technical path for the analysis of ABA-mediated plant stress resistance mechanism and the breeding of potato stress resistance varieties. Full article

Phalaenopsis pulcherrima are known for their captivating floral morphology and diverse colors, demonstrate exceptional resilience to adverse environmental conditions, and exhibit significant potential for hybrid breeding. However, current research on flower coloration is still limited. The data from this study indicates that variations in anthocyanin levels are the primary determinants of the difference between white and purple colors. Through RNA-seq, we identified 469 genes that were differentially expressed. Furthermore, our bioinformatics exploration uncovered two potential transcription factors, PpMYB1 and PpbHLH1, which play regulatory roles in anthocyanin accumulation. Y2H assays demonstrated that these two TFs could form heterodimers and interact with each other. Afterwards, transient expression assays were conducted for the first time in P. pulcherrima flowers, revealing that overexpression of PpMYB1 alone or in combination with PpbHLH1 resulted in purple petal pigmentation. Overexpressing PpMYB1 in tobacco resulted in more purple-colored corollas, stamens, pistils, and pods compared to control plants. Y1H and dual-luciferase assays provided further evidence that PpMYB1 and PpbHLH1 interact with the promoters of the structural genes PpF3H, PpDFR, and PpANS in the anthocyanin biosynthesis pathway, thereby driving their robust expression. This study not only enhances our understanding of the molecular mechanisms underlying anthocyanin synthesis but also holds significant practical implications for advancing plant hybrid breeding and genetic engineering applications in flower color regulation. Full article

This study presents the development of the Plant Perception Scale (PPS), a multidimensional tool designed to assess high school students’ awareness of the ecological, utilitarian, and cultural significance of plants. Positioned within the broader goal of Education for Sustainable Development (ESD), the scale aims to identify perception gaps that may hinder students’ engagement with biodiversity and sustainability. Following a rigorous development process—including item generation, expert review, pilot testing, and psychometric validation—the final 21-item scale revealed a three-factor structure: Ecological Awareness and Sustainability Perception (12 items), Utility-Oriented Plant Perception (5 items), and Cultural and Aesthetic Perception (4 items). Exploratory Factor Analysis confirmed data suitability (KMO = 0.920; Bartlett’s χ²(210) = 2245.215, p < 0.001). Confirmatory Factor Analysis supported the structure with strong fit indices (χ²/df = 2.204; CFI = 0.949; RMSEA = 0.055). Internal consistency was high (Cronbach’s α = 0.88 for the total scale; factor α values ranged from 0.823 to 0.939). The PPS contributes to sustainable education by offering a reliable framework to evaluate plant-related awareness among adolescents and can serve as a diagnostic and pedagogical tool to guide curriculum development and educational interventions in support of the SDGs. Full article