Search Results (710)

Expanding the capacity of Matrix-Assisted Laser Desorption Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS) beyond species identification to strain typing becomes a new challenge in clinical microbiology. This study demonstrated a specific identification of Streptococcus agalactiae sequence type 1 (ST1) by a manual decision tree and automatically ranking from the newly added MTPPs library, which has not been previously reported. The mass spectra of 25 STs (277 isolates) were generated. The presence and absence of specific peaks were combined to create a decision tree for manual identification. Three peaks at 3127, 5914, and 6252 in combination with m/z 3368 and 6281 were used for primary identification of ST1. However, to differentiate ST1 and ST314, five additional peaks were required. For the automatic system, the MTPP of all isolates was divided into three training–testing ratios of 40:60, 50:50, and 60:40. All categories revealed excellent accuracy rates of above 90% for ST1 identification. The 60:40 group showed the highest overall performance, in which sensitivity was observed at 83.9 to 96.8%, and specificity reached up to 100.0% for both the top two and the top three matches. In conclusion, we propose that the MTPP from MALDI-TOF is a potential model for speedy bacterial typing, crucial in epidemiology, prevention, and patient management. Full article

Agarwood, valued for its resin, has long been used in perfumery, incense, and traditional medicine. Its resin is primarily derived from species of Aquilaria and is produced through a still-unknown process in response to biotic or abiotic stress. Concerns regarding agarwood’s sustainability and conservation have emerged because of the substantial loss of natural resources due to overharvesting and illegal trade. To address these concerns, artificial techniques are being used to produce agarwood. The mechanism underlying agarwood production must be elucidated to enhance yield. The authentication of agarwood species is challenging because of morphological similarities between pure and hybrid Aquilaria species. Techniques such as DNA barcoding, molecular marker assessment, and metabolomics can ensure accurate identification, facilitating conservation. Artificial intelligence and machine learning can support this process by enabling rapid, automated identification on the basis of genetic and phytochemical data. Advances in resin induction methods (e.g., fungal inoculation) and chemical induction treatments are improving yield and quality. Endophytic fungi and bacteria promote resin production at minimal harm to the tree. Agarwood’s pharmacological potential—antimicrobial, anti-inflammatory, and anticancer effects—has driven research into bioactive compounds such as sesquiterpenes and flavonoids for the development of novel drugs. This systematic review synthesized current evidence on species authentication, induction techniques, and pharmacological properties. The findings may guide future research aimed at ensuring sustainable use and enhancing the medicinal value of agarwood. Full article

The population size of black poplar (Populus nigra L.), once an important part of floodplain forests in the Czech Republic, has greatly declined due to human activity. In this study, we applied microsatellite (SSR) markers to identify species and assess genetic diversity, with the aim of supporting conservation of this endangered species. A total of 378 poplar trees were analyzed following field surveys. Five diagnostic SSR markers with species-specific alleles for P. deltoides Bartr. ex Marsh. enabled the identification of 39 interspecific hybrids, which were distinguished from native P. nigra. Thirteen SSR loci were used to evaluate genetic diversity among confirmed P. nigra individuals. The results revealed high genetic variation, with 66% of pairwise genotype comparisons differing at all loci. After excluding 45 genetically similar individuals, 292 genetically verified and polymorphic P. nigra trees were selected as potential sources of reproductive material. Genetic differentiation (Fst) was highest between P. nigra and P. deltoides (0.27), and lowest between reference Populus ×euroamericana clones and detected hybrid poplars (0.05) from natural localities. Distinct genetic structures were identified among P. nigra, P. deltoides, and hybrid individuals. These findings provide essential data for the protection, reproduction, and planting of black poplar. Full article

The application of artificial intelligence (AI) techniques has improved the accuracy of forest species identification, particularly in timber inventories conducted under Sustainable Forest Management (SFM). This study developed and evaluated machine learning models to recognize 16 Amazonian timber species using digital images of tree bark. Data were collected from three SFM units located in Nova Maringá, Feliz Natal, and Cotriguaçu, in the state of Mato Grosso, Brazil. High-resolution images were processed into sub-images (256 × 256 pixels), and two feature extraction methods were tested: Local Binary Patterns (LBP) and pre-trained Convolutional Neural Networks (ResNet50, VGG16, InceptionV3, MobileNetV2). Four classifiers—Support Vector Machine (SVM), Artificial Neural Networks (ANN), Random Forest (RF), and Linear Discriminant Analysis (LDA)—were used. The best result (95% accuracy) was achieved using ResNet50 with SVM, confirming the effectiveness of transfer learning for species recognition based on bark texture. These findings highlight the potential of AI-based tools to enhance accuracy in forest inventories and support decision-making in tropical forest management. Full article

Proceroplatus (Keroplatidae: Keroplatinae) is a distinct keroplatid group comprising 39 described species. These species are found worldwide, but none had previously been reported in China prior to this study. In this paper, Proceroplatus is recorded for the first time from China, along with two new species: P. dapanshanussp. n. and P. biemarginatussp. n., which were collected from the southern region. Here, a worldwide distribution map of this genus is presented by species, including the new ones. Images and detailed morphological descriptions are provided for each new species, accompanied by molecular identification based on the standard mitochondrial cytochrome oxidase subunit I (COI) gene. To clarify the mitogenomic characteristics of Proceroplatus, the well-assembled and annotated mitogenome of P. dapanshanus was obtained and described in detail. The comparative analyses and phylogenetic tree indicate that the mitogenomic evolution of keroplatids is relatively conserved and influenced not only by mutation pressure but also by natural selection and other factors. Full article

Germplasm resources embody the genetic diversity of plants and form the foundation for breeding and the ongoing improvement of elite cultivars. The establishment of germplasm banks, along with their systematic evaluation, constitutes a critical step toward the conservation, sustainable use, and innovative utilization of these resources. Liriodendron, a rare and endangered tree genus with species distributed in both East Asia and North America, holds considerable ecological, ornamental, and economic significance. However, a standardized evaluation system for Liriodendron germplasm remains unavailable. In this study, 297 Liriodendron germplasm accessions were comprehensively evaluated using 34 phenotypic traits and whole-genome resequencing data. Substantial variation was observed in most phenotypic traits, with significant correlations identified among several characteristics. Cluster analysis based on phenotypic data grouped the accessions into three distinct clusters, each exhibiting unique distribution patterns. This classification was further supported by principal component analysis (PCA), which effectively captured the underlying variation among accessions. These phenotypic groupings demonstrated high consistency with subsequent population structure analysis based on SNP markers (K = 3). Notably, several key traits exhibited significant divergence (p < 0.05) among distinct genetic clusters, thereby validating the coordinated association between phenotypic variation and molecular markers. Genetic diversity and population structure were assessed using 4204 high-quality single-nucleotide polymorphism (SNP) markers obtained through stringent filtering. The results indicated that the Liriodendron sino-americanum displayed the highest genetic diversity, with an expected heterozygosity (He) of 0.18 and a polymorphic information content (PIC) of 0.14. In addition, both hierarchical clustering and PCA revealed clear population differentiation among the accessions. Association analysis between three phenotypic traits (DBH, annual height increment, and branch number) and SNPs identified 25 highly significant SNP loci (p < 0.01). Of particular interest, the branch number-associated locus SNP_17_69375264 (p = 1.03 × 10⁻⁵) demonstrated the strongest association, highlighting distinct genetic regulation patterns among different growth traits. A minimal set of 13 core SNP markers was subsequently used to construct unique DNA fingerprints for all 297 accessions. In conclusion, this study systematically characterized phenotypic traits in Liriodendron, identified high-quality and core SNPs, and established correlations between key phenotypic and molecular markers. These achievements enabled differential analysis and genetic diversity assessment of Liriodendron germplasm, along with the construction of DNA fingerprint profiles. The results provide crucial theoretical basis and technical support for germplasm conservation, accurate identification, and utilization of Liriodendron resources, while offering significant practical value for variety selection, reproduction and commercial applications of this species. Full article

The TIFY gene family participates in crucial processes including plant development, stress adaptation, and hormonal signaling cascades. While the TIFY gene family has been extensively characterized in model plant systems and agricultural crops, its functional role in Eucalyptus grandis, a commercially valuable tree species of significant ecological and economic importance, remains largely unexplored. In the present investigation, systematic identification and characterization of the TIFY gene family were performed in E. grandis using a combination of genome-wide bioinformatics approaches and RNA-seq-based expression profiling. Nineteen EgTIFY genes were identified in total and further grouped into four distinct subfamilies, TIFY, JAZ (subdivided into JAZ I and JAZ II), PPD, and ZML, based on phylogenetic relationships. These genes exhibited considerable variation in gene structure, chromosomal localization, and evolutionary divergence. Promoter analysis identified a multitude of cis-acting motifs involved in mediating hormone responsiveness and regulating abiotic stress responses. Transcriptomic profiling indicated that EgJAZ9 was strongly upregulated under methyl jasmonate (JA) treatment, suggesting its involvement in JA signaling pathways. Taken together, these results offer valuable perspectives on the evolutionary traits and putative functional roles of EgTIFY genes. Full article

Wood recognition plays a vital role in the trade and conservation of rare wood species. However, the computer vision-based methods classify the wood species by the features that are not used within the framework of wood anatomy, leading to results that are not interpretable. This study proposes a novel wood recognition method that detects anatomical structures such as vessels, wood rays, and parenchyma in wood microscopic images. These structures are quantified and mapped to the International Association of Wood Anatomists (IAWA) features, which are then used for species classification. Experimental results on 32 wood species demonstrate the effectiveness of the approach, achieving an accuracy of 94.1%, precision of 92.6%, recall of 93.3%, and an F1-score of 92.7%. In addition to its recognition performance, the method may offer interpretable IAWA-based classification criteria in wood science. These findings suggest that the method could serve as an anatomically interpretable framework for wood species identification, contributing to the regulation of the rare timber trade and supporting the conservation of endangered tree species. Full article

Unmanned aerial vehicle (UAV) remote sensing has become an important tool for high-resolution tree species identification in orchards and forests. However, irregular spatial distribution, overlapping canopies, and small crown sizes still limit detection accuracy. To overcome these challenges, we propose YOLOv11-OAM, an enhanced one-stage object detection model based on YOLOv11. The model incorporates three key modules: omni-dimensional dynamic convolution (ODConv), adaptive spatial feature fusion (ASFF), and a multi-point distance IoU (MPDIoU) loss. A class-balanced augmentation strategy is also applied to mitigate category imbalance. We evaluated YOLOv11-OAM on UAV imagery of six fruit tree species—walnut, prune, apricot, pomegranate, saxaul, and cherry. The model achieved a mean Average Precision (mAP@0.5) of 93.1%, an 11.4% improvement over the YOLOv11 baseline. These results demonstrate that YOLOv11-OAM can accurately detect small and overlapping tree crowns in complex orchard environments, offering a reliable solution for precision agriculture and smart forestry applications. Full article

Tree diseases affecting Camellia japonica have emerged as a significant threat to the health and longevity of this ornamental tree, particularly in countries where this tree species is widely distributed and cultivated. Among these, Pestalotiopsis spp. have been frequently reported and are considered one of the most impactful fungal pathogens, causing leaf blight or leaf spot, in multiple countries. Understanding the etiology and distribution of these diseases is essential for effective management and conservation of C. japonica populations. The traditional methods based on pathogen isolation and pure culture cultivation for diagnosis of tree diseases are labor intensive and time-consuming. In addition, the frequent coexistence of the major pathogens with other endophytes within a single C. japonica tree, coupled with inconsistent symptom expression and the occurrence of pathogens in asymptomatic hosts, further complicates disease diagnosis. These challenges highlight the urgent need to develop more rapid, accurate, and efficient diagnostic or monitoring tools to improve disease monitoring and management on trees, including C. japonica. To address these challenges, we applied a metagenomic approach to screen fungal communities within C. japonica trees. This method enabled comprehensive detection and characterization of fungal taxa present in symptomatic and asymptomatic tissues. By analyzing the correlation between fungal dominance and symptom expression, we identified key pathogenic taxa associated with disease manifestation. To validate the metagenomic approach, we employed a combined strategy integrating metagenomic screening and traditional fungal isolation to monitor foliar diseases in C. japonica. The correlation between dominant taxa and symptom expression was confirmed. Simultaneously, traditional isolation enabled the identification of a novel species, Pestalotiopsis, as the causal agent of leaf spot disease on C. japonica. In addition to confirming previously known pathogens, our study led to the discovery and preliminary characterization of a novel fungal taxon with pathogenic potential. Our findings provide critical insights into the fungal community of C. japonica and lay the groundwork for developing improved, rapid diagnostic tools for effective disease monitoring and management of tree diseases. Full article

The integration of unmanned aerial vehicle (UAV) remote sensing and deep learning has emerged as a highly effective strategy for inventorying forest resources. However, the spatiotemporal variability of forest environments and the scarcity of annotated data hinder the performance of conventional supervised deep-learning models. To overcome these challenges, this study has developed efficient tree (ET), a semi-supervised tree detector designed for forest scenes. ET employed an enhanced YOLO model (YOLO-Tree) as a base detector and incorporated a teacher–student semi-supervised learning (SSL) framework based on pseudo-labeling, effectively leveraging abundant unlabeled data to bolster model robustness. The results revealed that SSL significantly improved outcomes in scenarios with sparse labeled data, specifically when the annotation proportion was below 50%. Additionally, employing overlapping cropping as a data augmentation strategy mitigated instability during semi-supervised training under conditions of limited sample size. Notably, introducing unlabeled data from external sites enhances the accuracy and cross-site generalization of models trained on diverse datasets, achieving impressive results with F1, mAP50, and mAP50-95 scores of 0.979, 0.992, and 0.871, respectively. In conclusion, this study highlights the potential of combining UAV-based RGB imagery with SSL to advance tree species identification in heterogeneous forests. Full article

In this study, the association between Neosilba batesi (Diptera: Lonchaeidae) and avocado fruits (Persea americana L.) was investigated. Fruits showing signs of rot and infested with Diptera larvae were collected from commercial orchards in the states of Michoacán and Jalisco, Mexico. N. batesi was identified in association with fruits from both trees and the ground at all sampling sites. Furthermore, a phylogenetic analysis based on the mitochondrial cytochrome c oxidase subunit I (COI) gene supported the morphological identification, showing >99% identity with records from Veracruz, and revealed distinct genetic lineages within the Neosilba genus. In a study within one Michoacán orchard, infested tree-borne fruits averaged 5.40 cm in length and 3.90 cm in width, with a mean of 9.61 larvae emerging per fruit. Females were observed to lay eggs in openings between the pedicel and the fruit, never piercing the exocarp. In contrast, on fallen fruit, they utilized existing wounds with exposed pulp. Infested avocados exhibit characteristic spots indicating the presence of internal larvae and generally detach from the tree. Larvae can feed on avocados in various stages of decomposition and may either emerge through wounds or pupate within the fruit. These findings support the opportunistic and saprophagous behavior associated with this fly species. Full article

Biogenic volatile organic compounds (BVOCs) are low-boiling-point compounds commonly synthesized by secondary metabolic pathways in plants. As key precursors of ozone (O₃) and secondary organic aerosols (SOA), BVOCs play a critical role in ecosystem-atmosphere interactions. However, their emission from both marine and terrestrial ecosystems, as well as their association with climate and the environment, remain poorly characterized. In light of recent advances in BVOC research, including the establishment of emission inventories, identification of driving factors, and evaluation of ecological and environmental impacts, this study reviews the latest advancements in the field. The findings underscore that the carbon losses via BVOC emission should not be overlooked when estimating the terrestrial carbon balance. Additionally, more work needs to be conducted to quantify the emission factors of specific tree species and to establish links between BVOC emission and climate or environment change. This study contributes to a deeper understanding of vegetation ecology and its environmental functions. Full article

Due to the potential role of Auchenorrhyncha in the transmission of the bacterium Xylella fastidiosa in a wide variety of cultivations, during recent years in Europe, many studies have focused on species composition, abundance and seasonal appearance of Auchenorrhyncha. However, females and nymphs are difficult to identify, as species-level identification relies primarily on male genitalia morphology. Sampling was conducted over four years in olive fields in Lesvos Island, in the Northeast Aegean, Greece, using sweep nets and Malaise traps. Both adults and nymphs were collected, with males identified to species level, while females and nymphs were separated on different morphotypes. Representatives from each morphotype and identified adults were sequenced using the mitochondrial cytochrome oxidase subunit I (COI) gene. Using a classical morphological approach, 58 species were identified to species level, and using DNA barcoding, nymph morphotypes and females were successfully identified within the families Cicadellidae, Aphrophoridae, Delphacidae and Issidae. A phylogenetic tree was generated, clustering nymphs together with the corresponding adults. Our results demonstrate the utility of combining morphological and molecular methods for accurate species identification and highlight the importance of enriching online databases with additional species records. Full article

Abies nephrolepis and Picea jezoensis are native Pinaceae trees distributed in high mountainous regions of Northeast Asia (typically above ~1000 m a.s.l. on the Korean peninsula, northeastern China, Sakhalin, and the Russian Far East) and southern boreal forests, vulnerable to climate change and human disturbances, necessitating accurate habitat identification for effective conservation. While protected areas (PAs) are essential, merely expanding existing ones often fail to protect populations under human pressure and climate change. Using species distribution models with current and projected climate data, we mapped potential habitats across Northeast Asia. Spatial clustering analyses integrated with PA and land cover data helped identify optimal sites and priorities for new conservation areas. Ensemble species distribution models indicated extensive suitable habitats, especially in southern Sikhote-Alin, influenced by maritime-continental climates. Specific climate variables strongly affected habitat suitability for both species. The Kamchatka peninsula consistently emerged as an optimal habitat under future climate scenarios. Our study highlights essential environmental characteristics shaping the habitats of these species, reinforcing the importance of strategically enhancing existing PAs, and establishing new ones. These insights inform proactive conservation strategies for current and future challenges, by focusing on climate refugia and future habitat stability. Full article