Search Results (201)

Understanding how pollinators adjust their behavior to maximize reproductive success in resource-limited desert ecosystems is a fundamental ecological question. In this study, we investigated X. mongolicus using a combination of field behavioral observations, pollen identification, nutritional analysis, and morphometric measurements to systematically examine interannual variations in its flower visitation spectrum, foraging behavior, bee bread composition, and offspring body size. Our findings reveal a striking contrast: although this species exhibits polyphagy in flower visitation, it shows dietary specialization in larval nutrition—over 92% of the pollen in its bee bread originates from just two leguminous species, A. mongolicus and O. bicolor. Foraging duration increased with rising temperature and humidity, and bees adapted to strong winds by flying close to the ground. Compared with 2024, the bee bread in 2025 had lower fresh weight but higher crude protein content, and offspring body size was larger—likely due to more abundant spring rainfall in 2025, which improved the flowering performance of A. mongolicus. Collectively, these results indicate that this bee species copes with resource uncertainty in desert habitats through flexible foraging range and highly specialized food storage, with its reproductive success closely tied to the nutritional supply of key plants and precipitation patterns. This study highlights the role of precipitation timing in shaping the nutritional foundation of plant–pollinator interactions, providing a scientific basis for the conservation and management of desert pollinators. Full article

Aeropalynology, the monitoring and interpretation of airborne pollen, has become increasingly relevant in Latin America as allergic rhinitis and asthma rise alongside rapid urbanization, land-use change, and climate variability. Yet the region’s capacity remains heterogeneous: long-standing traditions in the Southern Cone coexist with emerging programs in tropical and Andean settings, and many series are not translated into standardized products useful for clinical care or public health. We conducted a structured literature review guided by PRISMA 2020 to synthesize the historical evolution, current monitoring infrastructure, dominant pollen taxa, and translational outputs reported across Latin American countries. Evidence indicates that Mexico currently represents the most mature aeropalynological ecosystem in the region, supported by multi-site monitoring, open weekly reporting (REMA), multiple city-level pollen calendars, and emerging computational approaches for pollen identification. Across countries, recurrent high-impact taxa include Cupressaceae, Fraxinus, Platanus, Olea, Poaceae, Urticaceae, Amaranthaceae, Rumex, Ambrosia, and Parietaria, with local dominance shaped by biogeography and urban vegetation. Key gaps include limited long-term continuity outside a few cities, variable methodology (sampler type, taxonomic resolution, units, thresholds), and scarce linkage of pollen exposure metrics with clinical outcomes. Future priorities include harmonized volumetric monitoring, interoperable data standards, routine publication of pollen calendars and thresholds, integration with meteorology for forecasting, and expansion of digital decision-support tools to improve prevention and management of allergic respiratory diseases in Latin America. Full article

With the continuous renewal of urban greening, pollen released by allergenic tree species has become a prominent environmental issue affecting residents’ health. However, existing research still lacks city-wide, rapidly replicable methods for identifying allergenic tree species and assessing exposure risks. Taking Beijing’s central urban districts as a case study, this research establishes a method for the automated identification of allergenic tree species and the assessment of pollen exposure risks based on high-resolution satellite imagery. This study coupled tree species distribution results derived from model inference with population density per unit area to delineate three tiers of exposure risk zones. Subsequently, these risk zones were overlaid with the road network within the study area to determine the distribution of roads with low, medium, and high exposure risk. Public transport stop locations were then introduced as a proxy variable for areas of high population mobility. Lorenz curves and Gini coefficients were calculated to quantify the spatial equity of pollen exposure risk. The results indicate that the model reliably identifies target tree species, with approximately 117,000 valid targets. Exposure risks exhibit significant clustering characteristics and can form continuous expansions along road networks. Incorporating population factors shows minimal change in risk concentration, suggesting pollen exposure risk is primarily driven by the spatial clustering of allergenic tree species and their accessibility within road networks. This risk is highly correlated with the spatial distribution patterns and accessibility characteristics of allergenic tree species, rather than being solely determined by population size. This study provides foundational data and methodological support for urban tree species identification, pollen exposure risk management, and optimised greening configurations. Full article

Melissopalynological analysis is essential for determining the botanical origin of honey, corbicular pollen and bee bread, as well as detecting adulteration. However, it traditionally relies on labor-intensive and subjective manual pollen identification. As a proof-of-concept preceding full honey analysis, this study evaluates artificial intelligence methods for automated pollen grain recognition under controlled conditions. Hazel (Corylus avellana L.) and dandelion (Taraxacum officinale F.H. Wigg.) were used as model taxa to validate the proposed approach before its application to real varietal honey samples. This study introduces a novel three-stage pipeline that decouples object detection from feature extraction, utilizing YOLOv12m for region-of-interest generation and, for the first time in melissopalynology, DINOv3 ConvNeXt-B for deep feature representation. Microscopic images acquired at 400× magnification yielded 2498 dandelion and 1941 hazel pollen grains. The detector achieved an mAP@0.5 of 0.936 with an F1 score of 0.88, while the classifier reached 98.1% accuracy with good class separability (Silhouette coefficient: 0.407). The primary technical contribution is the systematic optimization of the detection-to-classification interface. Context-aware bounding box expansion (12%) and an optimized IoU-NMS threshold (0.65) significantly improve the stability of morphological feature extraction, as confirmed by ablation studies. Computational cost reporting further supports reproducible, deployment-oriented comparison. The results confirm the feasibility of this AI-based framework as an intermediate step toward automated melissopalynological analysis, with future work focusing on standardized microscopy protocols and expanded pollen databases for varietal honey authentication. Full article

Goji, a plant unique to China, is recognized for its dual use as both a food and a medicine and is rich in various nutrients. However, long-term asexual propagation often leads to cultivar degeneration and viral accumulation, which severely impact its yield, quality, and disease resistance. Homozygous seeds can stably produce offspring with uniform traits. Haploid breeding technology, which involves doubling the chromosomes of haploid plants to obtain homozygous diploids, can significantly accelerate the breeding process. The DMP (Domain of Unknown Function 679 Membrane Protein) family is a plant-specific family of membrane proteins involved in various biological functions, including physiological processes, reproductive development, and senescence. Concurrently, loss-of-function of the DMP gene impedes the proper integration of the paternal genome following fertilization. Consequently, the embryo develops with exclusively maternal chromosomes, a mechanism that underlies the induction of haploids. In this study, we conducted a genome-wide identification of the DMP gene family in goji, analyzing the physicochemical properties, chromosomal locations, cis-acting elements, phylogenetic relationships, sequence characteristics, expression patterns, and subcellular localization of its members. The objective was to identify DMP genes capable of inducing haploid production in goji berry for future breeding applications. The results revealed a total of 11 DMP family members in the goji berry genome, distributed across seven chromosomes. The proteins encoded by these members contain 136 to 237 amino acids, with molecular weights ranging from 15,267.96 to 26,141.01 Da and isoelectric points (pI) ranging from 5.14 to 9.32. The LbDMPs were found to contain numerous cis-acting elements that play roles in plant responses to abiotic stresses and various phytohormones. Notably, LbDMP1 and LbDMP11, which contain the typical DUF679 domain, are predominantly expressed in pollen, suggesting their involvement in the reproductive process of goji berry. They were therefore identified as candidate genes for haploid induction. Subcellular localization analysis demonstrated that LbDMP1 is localized to the plasma membrane, while LbDMP11 is localized to membrane systems such as the endoplasmic reticulum. This research provides a fundamental basis for further exploration of the functional roles of the DMP gene family in goji berry and offers valuable genetic resources for haploid induction in its breeding programs. Full article

Morphological characteristics of pollen grains, including shape, size, pore number, and exine thickness, vary significantly among species and enable the reliable use of palynological data in taxonomic studies. In this context, the present study investigates the pollen morphology of seven Betulaceae taxa (Alnus glutinosa, Betula pendula, Carpinus betulus, Carpinus orientalis, Corylus avellana, Corylus colurna, and Ostrya carpinifolia). Detailed morphometric measurements were carried out using Light Microscopy (LM), and high-resolution images were obtained using Scanning Electron Microscopy (SEM). For each taxon, thirty measurements were taken for the main pollen characters, including polar axis length (P), equatorial diameter (E), pore length (plg), pore width (plt), and exine thickness (Ex). Interspecific differences were evaluated using one-way ANOVA, Tukey’s HSD test, and Principal Component Analysis (PCA), and a diagnostic pollen identification key was developed for the investigated species. The results demonstrate statistically significant interspecific variation in pollen size, pore characteristics, and exine thickness. In the PCA ordination, the first principal component (PC1) was mainly associated with pollen size (P and E), clearly separating Carpinus betulus from the remaining taxa. The second principal component (PC2) was primarily related to pore length (plg) and contributed to the separation of Alnus glutinosa from the other small-pollen species. These results show that quantitative pollen morphological characters provide reliable criteria for distinguishing closely related Betulaceae taxa. Full article

Limonium Mill. species present a polymorphic sexual system associated with flower polymorphisms like ancillary pollen and stigma, with sexual and/or apomictic reproduction. The aim of this study was to investigate the reproductive traits, test for autonomous apomixis, and assess seed formation in triploid Limonium algarvense and Limonium daveaui. Pollen-stigma combinations were determined and the number of flowers and seeds counted. Single-seed flow cytometry was performed using seeds in three phenological stages: immature (stage I), early maturing (stage II) and mature seeds (stage III). The findings revealed that all triploid plants were self-sterile and produced seeds in the absence of pollination. Despite L. daveaui having a higher number of flowers than L. algarvense, a significantly higher ratio of seeds/flowers was observed in the latter species. Stage-dependent endosperm developmental patterns were observed, with nucleated cells present in stage II seeds with a light brown or pinkish coat, and an embryo peak and an endosperm peak with the double ploidy level. Stage III seeds, with a dark brown coat, presented only an embryo peak. Additionally, a single hexaploid endosperm peak was detected in stage I seeds, revealing early initiation of the endosperm with nucleated cells prior to embryo development. The single 6C endosperm peak was always associated with shrunken and wrinkled or underdeveloped stage I seeds but was never detected in stage II seeds. Overall, our results support reproduction via asexually formed seeds with pollen-independent endosperm formation and allow the identification of phenological development stages and seed coat morphological markers associated with single-seed flow cytometric screening patterns in apomictic species. Full article

MicroRNAs (miRNAs) are key post-transcriptional regulators of gene expression and play important roles in plant development and reproduction. Liriodendron chinense, a representative woody species of Magnoliaceae, produces a large quantity of pollen but exhibits low natural seed set. Despite numerous studies on factors influencing its low seed production, the molecular mechanisms underlying this reproductive limitation remain poorly understood. Here, we performed small RNA sequencing and transcriptome analyses across five tissues of L. chinense, including leaf, calyx, petal, pistil, and pollen. Genome-wide identification yielded 688 miRNAs, comprising both conserved and species-specific members. Expression-based clustering revealed that miRNAs are organized into distinct, tissue-associated modules rather than being uniformly expressed across organs. Among these, a pollen-enriched miRNA module was clearly separated from those associated with leaves and other floral tissues. By integrating sRNA-seq and RNA-seq data, we identified miRNA–target pairs displaying anticorrelated expression patterns, providing expression-level support for miRNA mediated regulation. In pollen, two complementary regulatory modes were observed: low-abundance miRNAs associated with highly expressed target genes, and highly expressed miRNAs associated with repressed targets. The predicted targets of pollen-associated miRNAs were enriched in biological processes central to pollen development, including signal transduction, polarity establishment, vesicle trafficking, and cell wall biogenesis. Overall, this study provides a comprehensive, tissue-resolved view of miRNA expression and pollen-associated miRNA–target relationships in L. chinense, offering candidate regulatory modules for future functional studies of pollen development. Full article

Phytosulfokine (PSK) is a tyrosine-sulfated pentapeptide found throughout the plant kingdom, playing key roles in plant growth, development, and responses to biotic and abiotic stresses. However, there is still a lack of a comprehensive analysis of the BnPSK gene family in Brassica napus. In this study, we conducted a genome-wide identification and characterized 19 BnPSK genes in oil seed plants, which are unevenly distributed across both sub-genomes (A and C). BnPSK proteins ranged from 77 to 99 amino acids (BnPSK3c and BnPSK3d) in length, all belonging to the PSK-α type and containing conserved PSK domains. Synteny analysis revealed that the expansion of the BnPSK gene family is primarily attributed to whole genome duplication, with homology to Arabidopsis thaliana PSK genes. A promoter region analysis identified cis-acting elements related to hormone and stress responses. An expression profile analysis showed that BnPSK genes are highly expressed in roots, leaves, petals, and pollens and are induced by both abiotic stresses and phytohormone application. Furthermore, RT-qPCR assay demonstrated that the expression levels of BnPSK4c, BnPSK5a, and BnPSK5b were significantly enhanced under drought stress (3~5-fold) both in plant roots and leaves following ABA application. Lastly, the application of ABA induced antioxidant activity including SOD, POD, CAT and APX (2~5-fold) and their corresponding genes (3~5-fold), and altered the ROS-signaling in rapeseed plants; also, strong evidence of mitigating drought stress was present. These findings establish a basis for further research into the role of the BnPSK gene family in oilseed plant tolerance against drought stress and underlying molecular mechanisms, offering valuable perspectives for developing novel peptides. Full article

Automated pollen identification has become an increasingly important tool for palaeoecological research; however, its application to fossil pollen assemblages remains challenging due to complex backgrounds, morphological variability, and taxonomic similarity among pollen types. In this study, we propose Pollen-YOLO, a deep learning-based object detection framework designed for automated pollen identification from microscopic images, and evaluate its performance using the TPPOL23 dataset. The model integrates a tailored backbone architecture with attention-based feature enhancement and class-specific data augmentation strategies to address the characteristics of fossil pollen images. Experimental results indicate that Pollen-YOLO achieves stable and competitive detection performance for most pollen taxa under the tested conditions, particularly for dominant taxa with distinctive morphological features. Model behavior is further examined through ablation experiments and Grad-CAM-based interpretability analysis, which provide insights into feature learning and classification mechanisms. The applicability of the framework is explored using a fossil pollen sequence from the Shaqu profile on the Tibetan Plateau. Automated results show a high level of agreement with manual identification in capturing major stratigraphic trends and vegetation succession patterns, while discrepancies persist for morphologically similar or low-abundance taxa. Overall, this study suggests that object detection-based deep learning approaches have the potential to support fossil pollen analysis and palaeoecological reconstruction. Rather than replacing expert identification, Pollen-YOLO is intended as a complementary, high-throughput tool that may assist large-scale pollen analysis under appropriate quality control when combined with expert verification. Full article

Pollen identification is critical for melissopalynology (honey authentication), ecological monitoring, and allergen tracking, yet manual microscopic analysis remains labor-intensive, subjective, and error-prone when multiple grains overlap in realistic samples. Existing automated approaches often fail to address multi-grain scenarios or lack systematic comparison across classical and deep learning paradigms, limiting their practical deployment. This study proposes a subinstance-based classification framework combining YOLOv12n object detection for grain isolation, independent classification via classical machine learning (ML), convolutional neural networks (CNNs), or Vision Transformers (ViTs), and majority voting aggregation. Five classical classifiers with systematic feature selection, three CNN architectures (ResNet50, EfficientNet-B0, ConvNeXt-Tiny), and three ViT variants (ViT-B/16, ViT-B/32, ViT-L/16) are evaluated on four datasets (full images vs. isolated grains; raw vs. CLAHE-preprocessed) for four berry pollen species (Ribes nigrum, Ribes uva-crispa, Lonicera caerulea, and Amelanchier alnifolia). Stratified image-level splits ensure no data leakage, and explainable AI techniques (SHAP, Grad-CAM++, and gradient saliency) validate biological interpretability across all paradigms. Results demonstrate that grain isolation substantially improves classical ML performance (F1 from 0.83 to 0.91 on full images to 0.96–0.99 on isolated grains, +8–13 percentage points), while deep learning excels on both levels (CNNs: F1 = 1.000 on full images with CLAHE; ViTs: F1 = 0.99). At the instance level, all paradigms converge to near-perfect discrimination (F1 ≥ 0.96), indicating sufficient capture of morphological information. Majority voting aggregation provides +3–5% gains for classical methods but only +0.3–4.8% for deep models already near saturation. Explainable AI analysis confirms that models rely on biologically meaningful cues: blue channel moments and texture features for classical ML (SHAP), grain boundaries and exine ornamentation for CNNs (Grad-CAM++), and distributed attention across grain structures for ViTs (gradient saliency). Qualitative validation on 211 mixed-pollen images confirms robust generalization to realistic multi-species samples. The proposed framework (YOLOv12n + SVC/ResNet50 + majority voting) is practical for deployment in honey authentication, ecological surveys, and fine-grained biological image analysis. Full article

Allergen sensitization profiles are increasingly affected by environmental and climate changes. This study exemplifies fundamental differences in molecular IgE sensitization profiles in two nearby regions in Argentina with different climatic conditions (La Plata and Bahía Blanca). A cross-sectional study was conducted involving 155 patients with allergic symptoms from La Plata and Bahía Blanca (34.0 ± 11.2 years, female/male: 83/72). Serum samples were analyzed for IgE reactivity using a chip containing 101 micro-arrayed allergen molecules. Statistical analyses were performed to compare allergen-specific IgE levels, sensitization prevalences and reported symptoms. Patients from La Plata—with subtropical weather—showed a higher prevalence of IgE reactivity to house dust mite (HDM) allergens (Der p 23: 74%; Der p 1: 53% and Der p 2: 56%) and more frequently reported asthma (AS) symptoms (40% vs. 24%) than patients from Bahía Blanca. In contrast, patients from Bahía Blanca, with dry and windy weather, exhibited higher sensitization rates to pollen allergens, particularly Phl p 1 (49%) and Ole e 1 (22%) as well as to Alternaria alternata (Alt a 1, 35%) and reported a significantly higher prevalence of skin manifestations (54% vs. 31%) than those from La Plata. Cat allergen Fel d 1 was an equally important sensitizer in both regions (La Plata 30% and Bahía Blanca 37%). Sensitization to class 1 food allergens was rare in both groups (1–8%), including non-specific lipid transfer proteins (peanut Ara h 9 and peach Pru p 3) but IgE sensitizations to genuine peanut allergens were almost absent. Important regional differences in allergen sensitization profiles were observed between two geographically close regions with different climatic conditions. Our findings underscore the relevance of region-specific allergen profiling and highlight the clinical utility of molecular allergy diagnosis for a more precise allergen identification and improved management of allergic diseases. Full article

The vitality of pollen significantly influences the efficiency of pollination and microspore embryogenesis. Mining genes associated with pollen vitality will help accelerate pepper (Capsicum annuum L.) breeding progress via genetic engineering. PEX (pollen extensin-like), a member of the LRX (leucine-rich repeat extensin) family, is predominantly expressed in pollen and participates in regulating pollen vitality. However, its function and regulatory factors in pepper remain elusive. In this study, GUS histochemical staining results revealed that pepper CaPEX3 could be expressed in petals, sepals, anthers, and pollens of transgenic tomato (Solanum lycopersicum L.) lines expressing CaPEX3 promoter::GUS. Moreover, inhibition of the CaPEX3 by virus-induced gene silencing (VIGS) in pepper resulted in reduced pollen germination rate and viability, while overexpression of CaPEX3 in tomato significantly enhanced germination rate and pollen viability. In addition, TRANSPARENT TESTA GLABRA 1 (CaTTG1) and Nuclear transcription factor Y subunit C9 (CaNFYC9) were screened out and identified as the upstream regulatory transcription factors of CaPEX3 through yeast one-hybrid (Y1H) screening and dual-luciferase reporter (Dual-LUC) assays. Taken together, the identification of transcription factors may reveal a more comprehensive mechanism underlying CaPEX3-mediated enhancement of pepper pollen viability. This study not only provides genetic resources for pollen viability research but also establishes a theoretical foundation for pepper breeding. Full article

The pollen morphological characteristics of 16 pummelos and 4 other citrus germplasms from Vietnam, Thailand, and China were observed using scanning electron microscopy (SEM). Observations included equatorial view, polar view, and exine ornamentation. The results showed that the pollen of all tested materials was monads, prolate, or subprolate. The average polar axis length of the pollen ranged from 29.121 to 37.043 µm, and that of the equatorial axis ranged from 19.861 to 25.911 µm. A t-test revealed that the polar axis of pollen from Chinese pummelo germplasms was significantly longer than that of varieties from Southeast Asia, indicating certain geographical differentiation. The apertures were all colporate type, predominantly with four to five colpi (75% of grains); only four colpi were observed in the remainder (25%). The pollen exine ornamentation of pummelo germplasms was perforated, whereas that of other citrus types was reticulate. Pummelos exhibited a smaller pori diameter (0.264–0.673 µm) and wider distance between pori (0.581–1.118 µm), while other citrus species had larger lumina (1.253–1.684 µm) and narrower muri (0.443–0.664 µm). Principal component analysis (PCA) and cluster analysis were performed based on pollen traits, and two principal component factors were extracted. The pummelo germplasms were divided into two subgroups: sweet pummelo and red pummelo, which demonstrated a correlation among their pollen morphology, flesh color, and flesh flavor. The phenotypic diversity of pollen among different pummelo germplasms may provide a valuable auxiliary reference for the identification and systematic classification of pummelos. Full article

Polyploidization is a rapid breeding strategy for producing new varieties with superior agronomic traits. Kenaf (Hibiscus cannabinus L.), an important fiber crop, exhibits high adaptability to diverse stress conditions. However, comprehensive studies on polyploid induction, screening, and genetic identification in kenaf remain unreported. This study first established an optimal tetraploid induction system for diploid kenaf seeds using colchicine. The results showed that a 4-h treatment with 0.3% colchicine yielded the highest tetraploid induction rate of 37.59%. Compared with diploids, tetraploid plants displayed distinct phenotypic and physiological characteristics: dwarfism with shortened internodal distance, increased stem thickness, larger and thicker leaves with deeper green color and serration, as well as enlarged flowers, capsules, and seeds. Physiologically, tetraploid leaves featured increased chloroplast numbers in guard cells, reduced stomatal density, and larger pollen grains, elevated chlorophyll content. Further analyses revealed that tetraploid kenaf had elevated contents of various trace elements, enhanced photosynthetic efficiency, prolonged growth duration, and superior agronomic traits with higher biomass (54.54% higher fresh weight, 79.17% higher dry weight). These findings confirm the effectiveness of colchicine-induced polyploidization in kenaf, and the obtained tetraploid germplasm provides valuable resources for accelerating the breeding of elite kenaf varieties with improved yield and quality. Full article