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In the last few years, automatic extraction and classification of animal vocalisations has been facilitated by machine learning (ML) and deep learning (DL) methods. Different frameworks allowed researchers to automatically extract features and perform classification tasks, aiding in call identification and species recognition. However, the success of these applications relies on the amount of available data to train these algorithms. The lack of sufficient data can also lead to overfitting and affect generalisation (i.e. poor performance on out-of-sample data). Further, acquiring large data sets is costly and annotating them is time consuming. Thus, how small can a dataset be to still provide useful information by means of ML or DL? Here, we show how convolutional neural network architectures can handle small datasets in a bioacoustic classification task of affective mammalian vocalisations. We explain how these techniques can be used (e.g. pre-training and data augmentation), and emphasise how to implement them in concordance with features of bioacoustic signals. We further discuss whether these networks can generalise the affective quality of vocalisations across different taxa. [ABSTRACT FROM AUTHOR]

The effective identification of reclaimed vegetation species is important for the subsequent management of ecological restoration projects in mining areas. Hyperspectral remote sensing has been used for identifying vegetation species. However, few studies have focused on mine-reclaimed vegetation. Even if there are studies in this field, the methods used by the researches are mainly traditional discriminant analyses. The environmental conditions of reclaimed mining areas lead to significant intraclass spectral differences in reclaimed vegetation, and there is uncertainty in the identification of reclaimed vegetation species using traditional classification models. In this study, in situ hyperspectral data were used to analyze the spectral variation in the reclaimed vegetation canopy in mine restoration areas and evaluate their potential in the identification of reclaimed vegetation species. We measured the canopy spectral reflectance of five vegetation species in the study area using the ASD FieldSpec 4. The spectral characteristics of vegetation canopy were analyzed by mathematically transforming the original spectra, including Savitzky–Golay smoothing, first derivative, reciprocal logarithm, and continuum removal. In addition, we calculated indicators for identifying vegetation species using mathematically transformed hyperspectral data. The metrics were submitted to a feature selection procedure (recursive feature elimination) to optimize model performance and reduce its complexity. Different classification algorithms (regularized logistic regression, back propagation neural network, support vector machines with radial basis function kernel, and random forest) were constructed to explore optimal procedures for identifying reclaimed vegetation species based on the best feature metrics. The results showed that the separability between the spectra of reclaimed vegetation can be improved by applying different mathematical transformations to the spectra. The most important spectral metrics extracted by the recursive feature elimination (RFE) algorithm were related to the visible and near-infrared spectral regions, mainly in the vegetation pigments and water absorption bands. Among the four identification models, the random forest had the best recognition ability for reclaimed vegetation species, with an overall accuracy of 0.871. Our results provide a quantitative reference for the future exploration of reclaimed vegetation mapping using hyperspectral data. [ABSTRACT FROM AUTHOR]

Eleotrids, also known as gudgeons or sleeper gobies, are found mostly in freshwater and mangrove habitats of tropical and subtropical regions. Some eleotrids exhibit minimal morphological variation at the species level. In this study, DNA barcoding was used to assess the molecular diversity of common freshwater eleotrids in the Philippines in relation to other eleotrid species from other countries with available DNA sequences in public databases. A total of 422 mitochondrial DNA cytochrome c oxidase I (COI) gene sequences were analyzed: 107 of which were generated from this study, while the remaining 315 sequences were mined from Barcode of Life Data System and GenBank. Both the neighbor-joining and maximum likelihood trees constructed based on the COI sequences clustered most of the species in concordance with their taxonomic classification. The mean Kimura 2-parameter genetic distances within species and genera were 1.31% and 11.60%, respectively. As expected, the mean interspecific distance was higher than the mean intraspecific distance except in some species. This study revealed the presence of nine distinct eleotrid species belonging to five genera in the Philippines. These species include Giuris laglaizei, G. tolsoni, Eleotris acanthopomus, E. fusca, E. melanosoma, Belobranchus sp., Belobranchus belobranchus, Butis butis, and Ophiocara ophicephalus. This study also revealed the presence of possibly undescribed Belobranchus species in the Philippines. This undescribed Belobranchus species differs by a high percentage of genetic divergence from the other species of Belobranchus (3.00% from B. segura and 13.40% from B. belobranchus). Furthermore, high genetic distance (2.62%) was also observed between G. laglaizei species of Laguna de Bay and Mindanao. This study strongly recommends a taxonomic review of the Laguna de Bay G. laglaizei and the Philippine Belobranchus spp., as these species may harbor species complexes that require closer examination so that proper conservation and management measures can be implemented for each species.

Identifying freshwater mussel species within the Unionidae family can be challenging due to systematic confusion. This study investigates shell shapes to identify four sympatric species of freshwater mussels (Potamida littoralis, Unio durieui, U. gibbus, and U. ravoisieri) in the Maâden river (northern Tunisia) using two morphological approaches: global shape descriptors and geometric morphometrics of shell contours. The results revealed significant differences in global shape descriptors among the species. More in-depth analyses showed distinct shape variations, with P. littoralis and U. gibbus significantly differing from U. durieui and U. ravoisieri across most descriptors. Notably, U. durieui and U. ravoisieri exhibited similar shape traits, differing primarily in roundness, characterized by low circularity and high ellipticity. Principal Component Analyses depicted substantial morphological variance, with Procrustes data requiring the first two components to fully elucidate dispersion. Linear Discriminant Analysis revealed effective discrimination among species, with an accuracy rate of over 74 % in classifying individuals into their respective populations across both approaches. Geospatial analyses indicated varying influences of latitude, longitude, and altitude on shell morphology among species. Latitude had noteworthy impacts on P. littoralis, approaching significance for shape descriptors and Procrustes data. Conversely, U. durieui and U. gibbus displayed minimal geographic influence on shell morphology, while U. ravoisieri showed significant variations across these parameters. This study highlights the distinct morphological differences among sympatric mussel species in northern Tunisia, providing valuable insights for conservation efforts, especially for species vulnerable to climate change.

Numerous Cymbidium species have significant commercial value globally due to their exotic ornamental flowers. Identifying Cymbidium species is challenging due to their similar shapes, which hinders their rational use and the conservation of germplasm resources. In the present study, firstly, four plastid loci (matK, rbcL, psbA-trnH, and atpF-atpH) and a nuclear locus (internal transcribed spacer, ITS) were initially examined to identify Cymbidium species. Secondly, we inferred the interspecific phylogeny of Cymbidium species using ITS sequences. All of these DNA regions, with the exception of atpF-atpH, could be readily amplified from Cymbidium, and the corresponding DNA sequences can be successfully obtained by sequencing. Our research demonstrated that ITS exhibited the highest intra- and interspecific divergences, the greatest barcoding gap, and the highest proportion of species identification. The phylogenetic analysis of Cymbidium species based on the ITS regions primarily corroborated the results obtained using traditional morphological methods. A comparative analysis of candidate DNA barcodes has shown that the ITS can be used not only for barcoding Cymbidium species but also for the phylogenetic analysis of Cymbidium. [ABSTRACT FROM AUTHOR]

Obtaining reliable species identification of the legume genus Caragana has been challenging. Until now, species identification was mostly carried out utilizing diagnostic morphological characteristics, in addition to some successful applications of secondary chemical compounds. This study was designed to establish a DNA barcoding protocol enabling unambiguous identification of 238 accessions belonging to 67 species of Caragana. The performance of four DNA barcoding regions nrITS, trnH‐psbA, matK, and rbcL was explored using three analytical approaches, Pairwise Genetic Distance, Sequence Similarity and Phylogenetic Tree method. The chloroplast regions rbcL and matK showed lower discriminatory power compared with the nuclear region internal transcribed spacer (ITS) and the chloroplast region trnH‐psbA. The nrITS outperformed the other regions in the resolution rate. The present study brings forth an efficient barcode locus for Caragana. A barcode based either on a single‐locus nrITS or the combination of nrITS and trnH‐psbA was found to be most suitable for species discrimination with distinctive barcoding gaps. An attempt has also been made to resolve taxonomic issues in the Caragana opulens complex. DNA barcoding tools when complemented with alpha taxonomic evidence can aid in solving complex systematic problems, especially when taxa are characterized by overlapping traits, such as species belonging to the Fabaceae family. [ABSTRACT FROM AUTHOR]

Considering the complexity and difficulty of identifying forest species, wooden disks were collected to verify the potential of colorimetry to distinguish native species from Araucaria Forest stands of the Lauraceae family. The following species were used: Nectandra megapotamica, Ocotea indecora, Ocotea diospyrifolia and Ocotea puberula. Nees, to provide data on these species that grow naturally in Santa Catarina state, southern Brazil, enriching a robust database that can be practically applied in the commercialization of native woods. Visible spectra and colorimetric parameters were obtained from each anatomical surface and the results were evaluated by comparing the mean of each species regarding radial trunk position and anatomical surface. The data were also submitted to principal component analysis and performance of discriminant models (k-NN, SVM and ANN) for species discrimination with raw and second-derivative data. In general, colorimetric data presented different behavior, and chromatic coordinates a* and b* had higher potential for distinguishing the species. According to the mean spectra, Ocotea indecora had reflectance values different from the other species. By principal component analysis, raw data indicated the separation only of Ocotea indecora, while second-derivative data allowed better distinction of species. In all discrimination models, second-derivative data produced the best results. Thus, the use of colorimetry has potential for wood distinction of the Lauraceae species evaluated, improving the oversight of illegally traded timber.

Our goal was to resolve phylogenetic relationships among Apis laboriosa, and the Apis dorsata subspecies A. d. dorsata, A. d. binghami, and A. d. breviligula, the last two of which have been proposed as full species by several authors. We carried out a phylogenetic analysis of the giant honey bees using mitochondrial cox1 and cox2 gene sequences analyzed with maximum likelihood methods. We obtained strong support for four clades within A. dorsata in the broad sense: the three subspecies or species mentioned above, and a fourth lineage from south India. However, our analysis did not resolve the phylogenetic relationships among the four lineages. The presence of two genetically distinguishable groups of “A. dorsata” in India parallels the presence there of two cavity-nesting honey bees, A. cerana cerana and A. c. indica (the black hill bees and yellow plains bees, respectively). This suggests that past climatic or geological events may have temporarily isolated Indian populations from populations of the Asian mainland, leading to divergence and possibly speciation of Indian giant and cavity-nesting bees, followed by recolonization of India by eastern Asian forms. Recognition of these distinct lineages is important for conservation planning, so that their individual distributions, ecologies, and migration patterns can be considered, and so that the genetic diversity they represent can be maintained.

Background: Aconitum species, belonging to Ranunculaceae, have high medicinal importance but due to their overexploitation come under IUCN (International Union for Conservation of Nature) red list. The precise identification of the Aconitum species is equally important because they are used in herbal formulations. The present study aimed to develop an efficient DNA barcode system for the authentic identification of Aconitum species. Methods and results: A set of 92 barcode gene sequences (including 12 developed during the present study and 80 retrieved from NCBI) of 5 Aconitum species (A. heterophyllum, A. vialoceum, A. japonicum, A. napellus, and A. stapfianum) were analyzed using three methods (tree-based, distance-based, and similarity-based) for species discrimination. The PWG-distance method was found most effective for species discrimination. The discrimination rate of PWG- distance ranged from 33.3% (rbcL + trnH-psbA) to 100% (ITS, rbcL + ITS, ITS + trnH-psbA and rbcL + ITS + trnH-psbA). Among DNA barcodes and their combinations, the ITS marker had the highest degree of species discrimination (NJ-40%, PWG-100% and BLAST-40%), followed by trnH-psbA (NJ-20%, PWG-60% and BLAST-20%). ITS also had higher barcoding gap as compared to other individual barcodes and their combinations. Further, we also analyzed six Aconitum species (A. balfourii, A. ferox, A. heterophyllum, A. rotundifolium, A. soongaricum and A. violaceum) existing in Western Himalaya. These species were distinguished clearly through tree-based method using the ITS barcode gene with 100% species resolution. Conclusion: ITS showed the best species discrimination power and was used to develop species-specific barcodes for Aconitum species. DNA barcodes developed during the present study can be used to identify Aconitum species. [ABSTRACT FROM AUTHOR]

The effective monitoring and identification of existing subterranean termite populations within coarse woody debris and infested wood in service depend on accurate detection. These insects are often concealed within logs, wooden support structures, walls, and floorboards of buildings. In the absence of external mud tubes, termite infestations normally must be discovered through the destructive exploration of wooden structures to reveal the physical presence of these insect pests. Subterranean termite species are difficult to identify due to similarities in morphological features, but they may be readily distinguished by differences in volatile emissions from which they are divided into chemotaxonomic groups. Consequently, a more effective and nondestructive approach for detection and identification is to take advantage of unique species-specific emissions of volatile organic compounds (VOCs) from termite bodies which easily pass through wooden structures, allowing for detection without physical damage to wood and avoiding expensive DNA analysis. Electronic aroma detection analyses were conducted with an Aromascan A32S electronic-nose (e-nose) instrument, fitted with a 32-sensor conducting polymer (CP) sensor array, for discrimination between four common subterranean termite species based on differences in volatile emissions. Principal component analysis (PCA) of whole-body volatiles effectively distinguished between four termite species with the first two principal components accounting for more than 98% of sample variance (p < 0.01). Unique electronic aroma signature patterns (smellprints) were produced from e-nose sensor array outputs that allowed for the effective identification of termite species based on distinct differences in volatile metabolites released from their bodies. The e-nose methods were determined to be an improved means for rapidly detecting and monitoring termite species in wood. The method is cheaper than conventional detection methods and allows for the timelier discovery of species-specific termite infestations necessary for better management. The e-nose capability of detecting the Formosan termite in indoor living spaces was particularly significant due to the production of naphthalene, a volatile hazardous gas causing many adverse human health effects in enclosed environments. [ABSTRACT FROM AUTHOR]

Plants of the genus Physalis are of economic interest because of their fleshy edible fruits with high nutritional value. Some species have high medicinal value with a long history of ethno-medicinal use to treat diverse diseases. There is therefore a need to correctly discriminate the different species of Physalis for proper utilization. Although most Physalis species have unique morphologies, their vegetative stages are identical, making it difficult to accurately identify them based on morphological characteristics. DNA barcoding has the potential to discriminate species accurately. In this study, ribulose bisphosphate carboxylase large (rbcL) and internal transcribed spacer 2 (ITS2) regions were used to discriminate Physalis species and to reveal their phylogenetic relationships and genetic diversity. Physalis plant samples were collected from seven counties in Kenya based on the availability of the germplasm. The voucher specimens were identified using the botanical taxonomy method and were deposited in the University of Nairobi herbarium. Genomic DNA was isolated from leaf samples of 64 Physalis accessions and used for PCR amplification and the sequencing of rbcL and ITS2 barcode regions. The discriminatory ability of the barcodes was based on BLASTn comparison, phylogenetic reconstruction and cluster analysis, and the determination of inter- and intra-specific distances. The nucleotide polymorphism, genetic diversity and distance of the identified Physalis species were determined using DnaSP and MEGA 11.0 software. Species discrimination was more robust using ITS2 sequences. The species identified and discriminated by ITS2 sequences were Physalis purpurea, Physalis peruviana and Physalis cordata. The rbcL sequences were only able to identify Physalis to the genus level. There was high interspecific and low intraspecific divergence within the identified Physalis species based on ITS2 sequences. The ITS2 barcode is an ideal DNA barcode for use in the discrimination of species, as well as in genetic diversity studies of Physalis accessions in Kenya. [ABSTRACT FROM AUTHOR]

Plants of the genus Physalis are of economic interest because of their fleshy edible fruits with high nutritional value. Some species have high medicinal value with a long history of ethno-medicinal use to treat diverse diseases. There is therefore a need to correctly discriminate the different species of Physalis for proper utilization. Although most Physalis species have unique morphologies, their vegetative stages are identical, making it difficult to accurately identify them based on morphological characteristics. DNA barcoding has the potential to discriminate species accurately. In this study, ribulose bisphosphate carboxylase large (rbcL) and internal transcribed spacer 2 (ITS2) regions were used to discriminate Physalis species and to reveal their phylogenetic relationships and genetic diversity. Physalis plant samples were collected from seven counties in Kenya based on the availability of the germplasm. The voucher specimens were identified using the botanical taxonomy method and were deposited in the University of Nairobi herbarium. Genomic DNA was isolated from leaf samples of 64 Physalis accessions and used for PCR amplification and the sequencing of rbcL and ITS2 barcode regions. The discriminatory ability of the barcodes was based on BLASTn comparison, phylogenetic reconstruction and cluster analysis, and the determination of inter- and intra-specific distances. The nucleotide polymorphism, genetic diversity and distance of the identified Physalis species were determined using DnaSP and MEGA 11.0 software. Species discrimination was more robust using ITS2 sequences. The species identified and discriminated by ITS2 sequences were Physalis purpurea, Physalis peruviana and Physalis cordata. The rbcL sequences were only able to identify Physalis to the genus level. There was high interspecific and low intraspecific divergence within the identified Physalis species based on ITS2 sequences. The ITS2 barcode is an ideal DNA barcode for use in the discrimination of species, as well as in genetic diversity studies of Physalis accessions in Kenya.

Abstract Insect pests cause tremendous impact to agriculture worldwide. Species identification is crucial for implementing appropriate measures of pest control but can be challenging in closely related species. True fruit flies of the genus Anastrepha Schiner (Diptera: Tephritidae) include some of the most serious agricultural pests in the Americas, with the Anastrepha fraterculus (Wiedemann) complex being one of the most important due to its extreme polyphagy and wide distribution across most of the New World tropics and subtropics. The eight morphotypes described for this complex as well as other closely related species are classified in the fraterculus species group, whose evolutionary relationships are unresolved due to incomplete lineage sorting and introgression. We performed multifaceted phylogenomic approaches using thousands of genes to unravel the evolutionary relationships within the A. fraterculus complex to provide a baseline for molecular diagnosis of these pests. We used a methodology that accommodates variable sources of data (transcriptome, genome, and whole‐genome shotgun sequencing) and developed a tool to align and filter orthologs, generating reliable datasets for phylogenetic studies. We inferred 3031 gene trees that displayed high levels of discordance. Nevertheless, the topologies of the inferred coalescent species trees were consistent across methods and datasets, except for one lineage in the A. fraterculus complex. Furthermore, network analysis indicated introgression across lineages in the fraterculus group. We present a robust phylogeny of the group that provides insights into the intricate patterns of evolution of the A. fraterculus complex supporting the hypothesis that this complex is an assemblage of closely related cryptic lineages that have evolved under interspecific gene flow. Despite this complex evolutionary scenario, our subsampling analysis revealed that a set of as few as 80 loci has a similar phylogenetic resolution as the genome‐scale dataset, offering a foundation to develop more efficient diagnostic tools in this species group.

The effective identification of reclaimed vegetation species is important for the subsequent management of ecological restoration projects in mining areas. Hyperspectral remote sensing has been used for identifying vegetation species. However, few studies have focused on mine-reclaimed vegetation. Even if there are studies in this field, the methods used by the researches are mainly traditional discriminant analyses. The environmental conditions of reclaimed mining areas lead to significant intraclass spectral differences in reclaimed vegetation, and there is uncertainty in the identification of reclaimed vegetation species using traditional classification models. In this study, in situ hyperspectral data were used to analyze the spectral variation in the reclaimed vegetation canopy in mine restoration areas and evaluate their potential in the identification of reclaimed vegetation species. We measured the canopy spectral reflectance of five vegetation species in the study area using the ASD FieldSpec 4. The spectral characteristics of vegetation canopy were analyzed by mathematically transforming the original spectra, including Savitzky–Golay smoothing, first derivative, reciprocal logarithm, and continuum removal. In addition, we calculated indicators for identifying vegetation species using mathematically transformed hyperspectral data. The metrics were submitted to a feature selection procedure (recursive feature elimination) to optimize model performance and reduce its complexity. Different classification algorithms (regularized logistic regression, back propagation neural network, support vector machines with radial basis function kernel, and random forest) were constructed to explore optimal procedures for identifying reclaimed vegetation species based on the best feature metrics. The results showed that the separability between the spectra of reclaimed vegetation can be improved by applying different mathematical transformations to the spectra. The most important spectral metrics extracted by the recursive feature elimination (RFE) algorithm were related to the visible and near-infrared spectral regions, mainly in the vegetation pigments and water absorption bands. Among the four identification models, the random forest had the best recognition ability for reclaimed vegetation species, with an overall accuracy of 0.871. Our results provide a quantitative reference for the future exploration of reclaimed vegetation mapping using hyperspectral data.

Insect pests cause tremendous impact to agriculture worldwide. Species identification is crucial for implementing appropriate measures of pest control but can be challenging in closely related species. True fruit flies of the genus Anastrepha Schiner (Diptera: Tephritidae) include some of the most serious agricultural pests in the Americas, with the Anastrepha fraterculus (Wiedemann) complex being one of the most important due to its extreme polyphagy and wide distribution across most of the New World tropics and subtropics. The eight morphotypes described for this complex as well as other closely related species are classified in the fraterculus species group, whose evolutionary relationships are unresolved due to incomplete lineage sorting and introgression. We performed multifaceted phylogenomic approaches using thousands of genes to unravel the evolutionary relationships within the A. fraterculus complex to provide a baseline for molecular diagnosis of these pests. We used a methodology that accommodates variable sources of data (transcriptome, genome, and whole‐genome shotgun sequencing) and developed a tool to align and filter orthologs, generating reliable datasets for phylogenetic studies. We inferred 3031 gene trees that displayed high levels of discordance. Nevertheless, the topologies of the inferred coalescent species trees were consistent across methods and datasets, except for one lineage in the A. fraterculus complex. Furthermore, network analysis indicated introgression across lineages in the fraterculus group. We present a robust phylogeny of the group that provides insights into the intricate patterns of evolution of the A. fraterculus complex supporting the hypothesis that this complex is an assemblage of closely related cryptic lineages that have evolved under interspecific gene flow. Despite this complex evolutionary scenario, our subsampling analysis revealed that a set of as few as 80 loci has a similar phylogenetic resolution as the genome‐scale dataset, offering a foundation to develop more efficient diagnostic tools in this species group. [ABSTRACT FROM AUTHOR]

Numerous Cymbidium species have significant commercial value globally due to their exotic ornamental flowers. Identifying Cymbidium species is challenging due to their similar shapes, which hinders their rational use and the conservation of germplasm resources. In the present study, firstly, four plastid loci (matK, rbcL, psbA-trnH, and atpF-atpH) and a nuclear locus (internal transcribed spacer, ITS) were initially examined to identify Cymbidium species. Secondly, we inferred the interspecific phylogeny of Cymbidium species using ITS sequences. All of these DNA regions, with the exception of atpF-atpH, could be readily amplified from Cymbidium, and the corresponding DNA sequences can be successfully obtained by sequencing. Our research demonstrated that ITS exhibited the highest intra- and interspecific divergences, the greatest barcoding gap, and the highest proportion of species identification. The phylogenetic analysis of Cymbidium species based on the ITS regions primarily corroborated the results obtained using traditional morphological methods. A comparative analysis of candidate DNA barcodes has shown that the ITS can be used not only for barcoding Cymbidium species but also for the phylogenetic analysis of Cymbidium.

This paper assesses the effect of DNA barcoding—the use of informative genetic markers to identify and discriminate between species—on taxonomy. Throughout, we interpret this in terms of varipraxis, a concept we introduce to make sense of the treatment of biological variation by scientists and other practitioners. From its inception, DNA barcoding was criticised for being reductive, in attempting to replace multiple forms of taxonomic evidence with just one: DNA sequence variation in one or a few indicative genes. We show, though, how DNA barcoding has not narrowed or reduced taxonomy in the way it was projected to. We examine the development and implementation of DNA barcoding across three kingdoms of life: animals, plants, and protists. Through this, we demonstrate that for DNA barcoding to work, the range of acceptable intra-specific variation needs to be demarcated from variation deemed to be characteristic of inter-specific differences. Consequently, biological processes responsible for particular patterns of variation need to be investigated and understood. This encourages an integrative disposition towards understanding and explaining the evolutionary processes affecting the rate and nature of change at the nucleotide level. We detail how the impact of DNA barcoding has manifested differently across the three kingdoms we examine, assessing this in terms of the ontological commitments that are held and instantiated in practice. Based on this evaluation, we consider the problem of studying multi-kingdom communities, and assess the consequences of our analysis for understanding classification and taxonomy. [ABSTRACT FROM AUTHOR]

DNA barcode databases are increasingly available for a range of organisms, facilitating the wide application of DNA barcode‐based studies. Here we announce the development of a comprehensive DNA barcode reference library of Japanese native woody seed plants representing 43 orders, 99 families, 303 genera and 834 species, and comprising 77.3% of the genera and 72.2% of the species of native woody seed plants in Japan. A total of 6216 plant specimens were collected from 223 sites across the subtropical, temperate, boreal and alpine biomes in Japan with most species represented by multiple accessions. This reference library utilized three chloroplast DNA regions (rbcL, trnH‐psbA and matK) and consists of 14,403 barcode sequences. Individual regions varied in their identification rates, with species‐level and genus‐level rates for rbcL, trnH‐psbA and matK based on blast being 57.4%/96.2%, 78.5%/99.1% and 67.8%/98.1%, respectively. Identification rates were higher using region combinations, with total species‐level rates for two region combinations (rbcL & trnH‐psbA, rbcL & matK and trnH‐psbA & matK) ranging between 90.6% and 95.8%, and for all three regions being equal to 98.6%. Genus‐level identification rates were even higher, ranging between 99.7% and 100% for two region combinations and being 100% for the three regions. These results indicate that this DNA barcode reference library is an effective resource for investigations of native woody seed plants in Japan using DNA barcodes and provides a useful template for the development of libraries for other components of the Japanese flora. [ABSTRACT FROM AUTHOR]

Lantana Camara L. (LC) invasive species has not been successfully mapped due to inadequate spectral information. This study aimed at assessing the performance of leaf-level in-situ hyperspectral data and derived indices in discriminating LC among co-occurring species during the dry and wet seasons. In addition, the performance of simulated Sentinel-2 bands, Sentinel-2 derived indices and machine learning algorithms in discriminating it was explored. Spectrally distinct features for species discrimination were selected using the guided regularized random forest (GRRF) and their separability quantified with Jeffries–Matusita distance method. We found that ratio-based and difference indices constructed with first and second-order derivative hyperspectral reflectance wavelengths perfectly separated LC from co-occurring species in the dry and wet seasons with ≥ 97% of separability accuracy. Similarly, a set of derived ratio-based and difference Sentinel-2 indices yielded > 95% and

Melioidosis is a bacterial infection caused by Burkholderia pseudomallei (B. pseudomallei), posing a significant threat to public health. Rapid and accurate detection of B. pseudomallei is crucial for preventing and controlling melioidosis. However, identifying B. pseudomallei is challenging due to its high similarity to other species in the same genus. To address this issue, this study proposed a dual-target method that can specifically identify B. pseudomallei in less than 40 min. We analyzed 1722 B. pseudomallei genomes to construct large-scale pan-genomes and selected specific sequence tags in their core genomes that effectively distinguish B. pseudomallei from its closely related species. Specifically, we selected two specific tags, LC1 and LC2, which we combined with the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-CRISPR associated proteins (Cas12a) system and recombinase polymerase amplification (RPA) pre-amplification. Our analysis showed that the dual-target RPA-CRISPR/Cas12a assay has a sensitivity of approximately 0.2 copies/reaction and 10 fg genomic DNA for LC1, and 2 copies/reaction and 20 fg genomic DNA for LC2. Additionally, our method can accurately and rapidly detect B. pseudomallei in human blood and moist soil samples using the specific sequence tags mentioned above. In conclusion, the dual-target RPA-CRISPR/Cas12a method is a valuable tool for the rapid and accurate identification of B. pseudomallei in clinical and environmental samples, aiding in the prevention and control of melioidosis.

Commercial forest species discrimination is valuable for optimal management of commercial forests. Therefore, second-order image texture combinations computed from a 0.5 m WorldView-2 pan-sharpened image integrated with sparse partial least squares discriminant analysis (SPLS-DA) and partial least squares discriminant analysis (PLS-DA) were used to discriminate commercial forest species. The findings show that the SPLS-DA model, which is characterised by concurrent variable selection and reduction of data dimensionality, produced an overall classification accuracy of 86%, with an allocation disagreement of 9 and a quantity disagreement of 5. Conversely, the PLS-DA model with variable importance in projection (VIP) produced an overall classification accuracy of 81%, with an allocation disagreement of 12 and a quantity disagreement of 7. Overall, this study demonstrates the value of second-order image texture combinations in discriminating commercial forest species and presents an opportunity for improved commercial forest species delineation. [ABSTRACT FROM AUTHOR]

Quality control of traditional Chinese medicine (TCM) should be linked with the authentication and efficacy of TCM. Selaginella tamariscina is a frequently used traditional Chinese herbal medicine. However, its quality control is still difficult due to its multiple adulterants. We established quality markers (Q-markers) of S. tamariscina by using metabolomics, molecular networking and network pharmacology to improve the authenticity study and quality control of S. tamariscina. In this study, ultra high performance liquid chromatography-mass spectrum (UHPLC-MS) coupled with multivariate statistical analyses was applied to distinguish between S. tamariscina samples and their confusing adulterants. Principal component analysis, hierarchical clustering analysis (PCA), hierarchical clustering analysis (HCA) and partial least squares discriminant analysis (PLS-DA) were employed to screen the distinguishing markers from S. tamariscina samples and their adulterants. The top-2 distinguishing markers were isolated from S. tamariscina and identified by molecular networking together with nuclear magnetic resonance spectroscopy (NMR). Network pharmacology predicted the bioactivity and cytotoxicity of the top-2 distinguishing markers. The top-2 distinguishing markers were adopted as Q-markers of S. tamariscina for content determination. Based on the results of ultra performance liquid chromatography-quardrupole-time of flight mass spectrometry (UHPLC-QTOF-MS) metabolomics, we revealed that selaginellins could only be detected in S. tamariscina samples and contributed greatly to discriminating S. tamariscina samples from their confused species. The top-2 distinguishing markers were isolated and purified from S. tamariscina extract. Then, they were further identified as selaginellin and selaginellin A by molecular networking and NMR. Network pharmacology predicted the antitumor activity of selaginellin and selaginellin A, while the cytotoxicity assay verified their bioactivity. In conclusion, selaginellin and selaginellin A were selected as Q-markers for the determination and quality evaluation of S. tamariscina based on ultra performance liquid chromatography-triple quadrupole tandem mass spectrometry (UHPLC-QQQ-MS). The ranges of the concentrations of selaginellin and selaginellin A were 41.57–44.89 μg/g and 15.09–16.75 μg/g, respectively. This study provides a novel strategy combining Ultra performance liquid chromatography mass spectrometry based (UHPLC-MS-based) metabolomics with molecular networking for rapid species identification of S. tamariscina and discovery of the Q-markers of TCM.

Rapid changes in agricultural environments caused by global warming pose a major challenge to food production and safety. Common wheat (Triticum aestivum) is a hexaploid plant (AABBDD) that shares large numbers of quantitative traits and resistance genes with B and D genomes of Aegilops species, which are responsible for several metabolic functions and biosynthetic processes, particularly in plant adaptation to biotic as well as abiotic stresses. Comparatively, the abundance of the Aegilops gene pool is much higher than that of Triticum. Therefore, we used four universal DNA barcodes for plants (ITS2, matK, rbcL, and psbM-petN) to construct a phylogenetic tree to classify the genus Aegilops. Fourteen species were distinguished among a total of 17 representative species. Aegilops biuncialis, Aegilops juvenalis, and Aegilops umbellulata could not be grouped into any of the clusters in the phylogenetic tree, indicating that these three species could not be distinguished by four DNA barcodes. Therefore, from 2408 SNPs obtained using genotyping by sequencing (GBS), we manually screened 30 SNPs that could be potentially used to classify these three species. The results of gene flow and genetic differentiation index (Fst) showed that the genetic differentiation among the three species was small, and there was bidirectional horizontal gene transfer between the three species, which was consistent with our results that the three species were difficult to classify by DNA barcode. [ABSTRACT FROM AUTHOR]

The ability to discriminate species and recognize individuals is crucial for reproductive success and/or survival in most animals. However, the temporal order and neural localization of these decision-making processes has remained unclear. In this study, event-related potentials (ERPs) were measured in the telencephalon, diencephalon, and mesencephalon of the music frog Nidirana daunchina. These ERPs were elicited by calls from 1 group of heterospecifics (recorded from a sympatric anuran species) and 2 groups of conspecifics that differed in their fundamental frequencies. In terms of the polarity and position within the ERP waveform, auditory ERPs generally consist of 4 main components that link to selective attention (N1), stimulus evaluation (P2), identification (N2), and classification (P3). These occur around 100, 200, 250, and 300 ms after stimulus onset, respectively. Our results show that the N1 amplitudes differed significantly between the heterospecific and conspecific calls, but not between the 2 groups of conspecific calls that differed in fundamental frequency. On the other hand, the N2 amplitudes were significantly different between the 2 groups of conspecific calls, suggesting that the music frogs discriminated the species first, followed by individual identification, since N1 and N2 relate to selective attention and stimuli identification, respectively. Moreover, the P2 amplitudes evoked in females were significantly greater than those in males, indicating the existence of sexual dimorphism in auditory discrimination. In addition, both the N1 amplitudes in the left diencephalon and the P2 amplitudes in the left telencephalon were greater than in other brain areas, suggesting left hemispheric dominance in auditory perception. Taken together, our results support the hypothesis that species discrimination and identification of individual characteristics are accomplished sequentially, and that auditory perception exhibits differences between sexes and in spatial dominance. [ABSTRACT FROM AUTHOR]

Bupleuri Radix (BR) is a traditional Chinese medicine and widely used for cold and fever, influenza, inflammation, hepatitis and menstrual diseases. Two authentic medicinal plants of Bupleuri chinense DC. (Beichaihu, BCH) and B. scorzonerifolium Willd. (Nanchiahu, NCH) are recommended by the current Chinese Pharmacopoeia for BR. In the present study, the comparative investigations on the anti-inflammatory effects and gas chromatographymass spectrometry (GC-MS)-based metabolomics for the species discrimination of BCH and NCH were conducted and reported. The in vitro evaluations indicated that the supercritical fluid extracts (SFEs) (IC50 of 6.39 ± 0.52 and 1.32 ± 0.05 mg (herb)/mL for BCH and NCH) were determined to be more potent than those of the hydro-distillation extracts (HDEs) (IC50 of 203.90 ± 8.08 and 32.32 ± 2.27 mg (herb)/mL for BCH and NCH) against LPS-induced inflammation in RAW264.7 macrophages. The higher antiinflammatory effects of NCH were associated to its different chemical compositions to the BCH as characterized by the GC-MS analysis. Furthermore, based on the metabolomics and deep chemometric approaches, a minimum combination containing 15 chemical markers was optimized from the identified components and successfully applied for the species discrimination of BCH and NCH. This study not only helps to comparative understand BCH and NCH both in phytochemistry and pharmacology, but also provides the potential chemical markers for improvement of methods for the quality control of BCH and NCH. [ABSTRACT FROM AUTHOR]

Commercial interest in the culinary herb, Eryngium foetidum L., has increased worldwide due to its typical pungency, similar to coriander or cilantro, with immense pharmaceutical components. The molecular delimitation and taxonomic classification of this lesser-known medicinal plant are restricted to conventional phenotyping and DNA-based marker evaluation, which hinders accurate identification, genetic conservation, and safe utilization. This study focused on species discrimination using DNA sequencing with chloroplast–plastid genes (matK, Kim matK, and rbcL) and the nuclear ITS2 gene in two Eryngium genotypes collected from the east coast region of India. The results revealed that matK discriminated between two genotypes, however, Kim matK, rbcL, and ITS2 identified these genotypes as E. foetidum. The ribosomal nuclear ITS2 region exhibited significant inter- and intra-specific divergence, depicted in the DNA barcodes and the secondary structures derived based on the minimum free energy. Although the efficiency of matK genes is better in species discrimination, ITS2 demonstrated polyphyletic phylogeny, and could be used as a reliable marker for genetic divergence studies understanding the mechanisms of RNA molecules. The results of this study provide insights into the scientific basis of species identification, genetic conservation, and safe utilization of this important medicinal plant species. [ABSTRACT FROM AUTHOR]

Species of Cephalotaxus have great economic and ecological values. However, the taxonomy and interspecific phylogenetic relationships within the genus have been controversial and remained not fully resolved until now. To date, no study examined the efficiency of the complete plastome as super-barcode across Cephalotaxus species with multiple samples per taxon. In this study, we have evaluated the complete plastome in species discrimination and phylogenetic resolution in Cephalotaxus by including 32 individuals of all eight recognized species and five varieties following Farjon's classification (2010) with multiple samples per taxon. Our results indicated that not all species recognized in recent taxonomic revisions of Cephalotaxus could be distinguished and not all were monophyletic. Based on the plastome phylogeny, a new taxonomic classification for the genus comprising nine species and two varieties, including a cryptic species, was proposed. The phylogeny also resolved all interspecific relationships. Compared to the plastome based classification, standard DNA barcodes, alone or in combination, only recognized a maximum of seven out of the nine species. Moreover, two highly variable single loci, ycf 1 and rps 16, each alone achieved full species discrimination. With the moderate length of 1079 bp, rps 16 is proposed as a specific barcode to discriminate Cephalotaxus species. The super-barcodes and specific barcode candidates will aid in the identification of endangered Cephalotaxus species, and to help focus conservation measures. [ABSTRACT FROM AUTHOR]

Rhizomes of the Polygonatum species are well-known in traditional Chinese medicine. The 2020 edition of Chinese Pharmacopoeia includes three different species that possess different pharmacological effects. Due to the lack of standardized discriminant compounds there has often been inadvertently incorrect prescriptions given for these medicines, resulting in serious consequences. Therefore, it is critical to accurately distinguish these herbal Polygonatum species. For this study, UPLC-Q-TOF-MS/MS based metabolomics was employed for the first time to discriminate between three Polygonatum species. Partial least squares discriminant analysis (PLS-DA) models were utilized to select the potential candidate discriminant compounds, after which MS/MS fragmentation patterns were used to identify them. Meanwhile, metabolic correlations were identified using the R language package corrplot, and the distribution of various metabolites was analyzed by box plot and the Z-score graph. As a result, we found that adenosine, sucrose, and pyroglutamic acid were suitable for the identification of different Polygonatum species. In conclusion, this study articulates how various herbal Polygonatum species might be more accurately and efficiently distinguished. [ABSTRACT FROM AUTHOR]

The Korean fir (Abies koreana Wilson) is native to the higher mountains of South Korea, including the upper part of the Mt. Hallasan National Park, which is designated as the Biosphere Reserve of the United Nations Educational, Scientific, and Cultural Organization. This species is considered as endangered and climate-sensitive bioindicator. We collected a species of Anurophorus (Collembola) from withered and rolled leaves of Korean fir, which is distributing at >1,300 m in altitude on Mt. Hallasan. There are 6 species of this genus in the Korean Peninsula, except the collected species (designated as Anurophorus sp.) with clear differences among them. Anurophorus sp. is most similar to A. laricis Nicolet in the general pattern of body chaetotaxy but was characterized by the number of knobbed hairs on tibiotarsi of all legs. Partial DNA sequences of the mitochondrial cytochrome c oxidase subunit I (COI) gene were used as DNA barcodes to distinguish the species and to verify its usefulness. It shows clear difference in genetic distance between studied other Anurophorus spp. The result indicates that the COI barcodes is a useful tool for species discrimination of Anurophorus, and Anurophorus sp. studied here is likely to be new to science.

Species of Cephalotaxus have great economic and ecological values. However, the taxonomy and interspecific phylogenetic relationships within the genus have been controversial and remained not fully resolved until now. To date, no study examined the efficiency of the complete plastome as super-barcode across Cephalotaxus species with multiple samples per taxon. In this study, we have evaluated the complete plastome in species discrimination and phylogenetic resolution in Cephalotaxus by including 32 individuals of all eight recognized species and five varieties following Farjon’s classification (2010) with multiple samples per taxon. Our results indicated that not all species recognized in recent taxonomic revisions of Cephalotaxus could be distinguished and not all were monophyletic. Based on the plastome phylogeny, a new taxonomic classification for the genus comprising nine species and two varieties, including a cryptic species, was proposed. The phylogeny also resolved all interspecific relationships. Compared to the plastome based classification, standard DNA barcodes, alone or in combination, only recognized a maximum of seven out of the nine species. Moreover, two highly variable single loci, ycf1 and rps16, each alone achieved full species discrimination. With the moderate length of 1079 bp, rps16 is proposed as a specific barcode to discriminate Cephalotaxus species. The super-barcodes and specific barcode candidates will aid in the identification of endangered Cephalotaxus species, and to help focus conservation measures.

Rhizomes of the Polygonatum species are well-known in traditional Chinese medicine. The 2020 edition of Chinese Pharmacopoeia includes three different species that possess different pharmacological effects. Due to the lack of standardized discriminant compounds there has often been inadvertently incorrect prescriptions given for these medicines, resulting in serious consequences. Therefore, it is critical to accurately distinguish these herbal Polygonatum species. For this study, UPLC-Q-TOF-MS/MS based metabolomics was employed for the first time to discriminate between three Polygonatum species. Partial least squares discriminant analysis (PLS-DA) models were utilized to select the potential candidate discriminant compounds, after which MS/MS fragmentation patterns were used to identify them. Meanwhile, metabolic correlations were identified using the R language package corrplot, and the distribution of various metabolites was analyzed by box plot and the Z-score graph. As a result, we found that adenosine, sucrose, and pyroglutamic acid were suitable for the identification of different Polygonatum species. In conclusion, this study articulates how various herbal Polygonatum species might be more accurately and efficiently distinguished.

The Fritillaria is an extremely complicated genus in taxonomy and phylogeny, which contains numerous medicinal species in China. Both traditional characteristic-based taxonomy and universal DNA barcodes (ITS, trnH - psbA , and rbcL) are difficult to effectively identify the species. Here, we generated a large dataset of chloroplast genomes from multiple accessions per species of Fritillaria to evaluate their effectiveness in species discrimination. Moreover, phylogeny of species in China was explored based on the complete chloroplast genomes, and then divergence times of each node were estimated. The results showed that all 21 species in Fritillaria here (including two suspicious species) could be correctly discriminated using cpDNA genomes except F. cirrhosa , which suggested that DNA super-barcode could greatly enhance species discriminatory resolution for complicated genera. Furthermore, four regions (ycf1 , matK - trnG-GCC , rpoC1 , and matK) gained remarkably higher resolution than that of other plastid regions, but only matK might be suitable to identify Fritillaria species in consideration of its lengths. Phylogenomic analysis showed that the subgenus Fritillaria in China was divided into four major clades with obvious geographic structure. Among them, Clade I, mainly distributed in southwest China, was a young and complicated group. Moreover, according to the analysis, taxonomic treatments of the two suspicious species, namely " F. omeiensis " and " F. hupehensis " in Flora of China (2000) are questionable and might need further revision. Molecular dating revealed that both origin and divergence of subgenus Fritillaria , as well as its four major clades, were significantly associated with geological and climatic fluctuations during the Middle to Late Miocene. This study would enrich case studies of DNA super-barcode and provide new insights on speciation, lineage diversification, and biogeography of the Fritillaria in China. [ABSTRACT FROM AUTHOR]

Standard plant DNA barcodes based on 2–3 plastid regions, and nrDNA ITS show variable levels of resolution, and fail to discriminate among species in many plant groups. Genome skimming to recover complete plastid genome sequences and nrDNA arrays has been proposed as a solution to address these resolution limitations. However, few studies have empirically tested what gains are achieved in practice. Of particular interest is whether adding substantially more plastid and nrDNA characters will lead to an increase in discriminatory power, or whether the resolution limitations of standard plant barcodes are fundamentally due to plastid genomes and nrDNA not tracking species boundaries. To address this, we used genome skimming to recover near‐complete plastid genomes and nuclear ribosomal DNA from Rhododendron species and compared discrimination success with standard plant barcodes. We sampled 218 individuals representing 145 species of this species‐rich and taxonomically difficult genus, focusing on the global biodiversity hotspots of the Himalaya‐Hengduan Mountains. Only 33% of species were distinguished using ITS+matK+rbcL+trnH‐psbA. In contrast, 55% of species were distinguished using plastid genome and nrDNA sequences. The vast majority of this increase is due to the additional plastid characters. Thus, despite previous studies showing an asymptote in discrimination success beyond 3–4 plastid regions, these results show that a demonstrable increase in discriminatory power is possible with extensive plastid genome data. However, despite these gains, many species remain unresolved, and these results also reinforce the need to access multiple unlinked nuclear loci to obtain transformative gains in species discrimination in plants. [ABSTRACT FROM AUTHOR]

A meta-analysis of previously performed evaluation studies of nucleic acid amplification testing (NAT) approaches for the screening for and differentiation of Plasmodium spp. using identical samples was performed to comparatively assess their suitability for the routine diagnostic setting.

The Fritillaria is an extremely complicated genus in taxonomy and phylogeny, which contains numerous medicinal species in China. Both traditional characteristic-based taxonomy and universal DNA barcodes (ITS, trnH-psbA, and rbcL) are difficult to effectively identify the species. Here, we generated a large dataset of chloroplast genomes from multiple accessions per species of Fritillaria to evaluate their effectiveness in species discrimination. Moreover, phylogeny of species in China was explored based on the complete chloroplast genomes, and then divergence times of each node were estimated. The results showed that all 21 species in Fritillaria here (including two suspicious species) could be correctly discriminated using cpDNA genomes except F. cirrhosa, which suggested that DNA super-barcode could greatly enhance species discriminatory resolution for complicated genera. Furthermore, four regions (ycf1, matK-trnG-GCC, rpoC1, and matK) gained remarkably higher resolution than that of other plastid regions, but only matK might be suitable to identify Fritillaria species in consideration of its lengths. Phylogenomic analysis showed that the subgenus Fritillaria in China was divided into four major clades with obvious geographic structure. Among them, Clade I, mainly distributed in southwest China, was a young and complicated group. Moreover, according to the analysis, taxonomic treatments of the two suspicious species, namely “F. omeiensis” and “F. hupehensis” in Flora of China (2000) are questionable and might need further revision. Molecular dating revealed that both origin and divergence of subgenus Fritillaria, as well as its four major clades, were significantly associated with geological and climatic fluctuations during the Middle to Late Miocene. This study would enrich case studies of DNA super-barcode and provide new insights on speciation, lineage diversification, and biogeography of the Fritillaria in China.

Italian ryegrass [Lolium perenne L. ssp. multiflorum (Lam.) Husnot] is one of the most challenging weeds for winter wheat (Triticum aestivum L.) growers to manage. Italian ryegrass has evolved resistance to the majority of the herbicides labeled for use in wheat and the competitive ability of the species makes it a significant factor driving winter wheat production practices around the world. Previous research has utilized remotely sensed spectral imagery to detect Italian ryegrass in winter wheat to aid weed control decisions. Two studies from 2016 to 2017 were initiated with the intent of identifying the spectral reflectance properties of Italian ryegrass and winter wheat using an unmanned aerial vehicle (UAV) equipped with a 5-band multispectral sensor. Image analysis was conducted to determine the potential for species discrimination throughout the growing season. Supervised classification of the imagery was used to evaluate the ability of the UAV platform for further discrimination between Italian ryegrass and winter wheat. Species differentiation proved to be possible, however the data was not able to be referenced across dates. Due to light variability, the reflectance values changed to such a degree that unsupervised classifications were not possible using a database of values from previous flights. Supervised classification of the multispectral image resulted in >70% classification accuracy between the species. However, near infrared light consistently differed enough for accurate classification between Italian ryegrass and winter wheat across different weed densities, flight altitudes, and imaging dates. On a single field basis, species differentiation was successful and resulted in classified maps of Italian ryegrass and winter wheat. This study also analyzed the exact accuracy of the species differentiation based on the quality and uniformity of light conditions and growth stage of plants.

The diagnostic value of leaf shape for mangrove species Avicennia germinans and A. schaueriana was examined in four areas within the Rio Parnaíba delta, Maranhão, Brazil. Elliptic Fourier analysis of 627 leaves, followed by principal component analysis, provided shape and size data; the first seven principal component shape variables expressed 99.2% total variation. Discrimination between twelve combinations of species, location and disturbance levels was studied using k‐nearest‐neighbour classification. The species differed significantly in leaf shape but determination was reliable only in the tallest undisturbed forest (germinans narrowly elliptic or ovate, base acute, apex acute to acuminate; schaueriana broadly obovate, base attenuate, apex rounded). Symmetric variables (PC1 and PC3, 84.5% total variation) showed strongest differences. Predominant variation between species was in relative width and base shape (PC1), and within species in ovateness (PC3) between conserved and regenerating areas. Leaves were significantly smaller in A. schaueriana. Vernacular taxa siriba branca and siriba preta were inconsistent with taxonomic species but often significantly different in leaf shape. Avicennia germinans varied more under different geographical and ecological conditions. Shape‐size correlation needs further allometric study. Species delimitation needs morphometric study of a broader character range. Vernacular taxa recognition should be studied with ethnobiological techniques. [ABSTRACT FROM AUTHOR]

• Microscopic FT-IR imaging technology was used to MBM species discrimination. • Accuracy of PLS-DA model using the fragment-related fused pixels reached 0.980. • Analytical efficiency was guaranteed with the consuming time around 4.5 min. This study proposes a novel microscopic FT-IR imaging-based analytical strategy for the discrimination of meat and bone meal (MBM) species. The feasibility of correlation coefficient and PLS-DA methods for the screening of bone and meat fragment-related spectral pixels in MBM microscopic FT-IR imaging was validated. Subsequently, PLS-DA models were established for MBM species-specific analysis based on the screened bone and meat fragment-related spectral pixels. Comparative analysis with the PLS-DA model using all FT-IR pixels demonstrated a significant improvement in the performance of the PLS-DA model based on the fused matrix fragment-related spectral pixels, achieving an accuracy of approximately 0.980. Furthermore, the proposed analytical strategy exhibited a time efficiency advantage with a consumption period of approximately 4.5 min, thereby ensuring high spectral technical efficiency. The findings of this study offer a theoretical basis for the spectral discrimination analysis of agricultural materials with complex matrix compositions. [ABSTRACT FROM AUTHOR]

Mangroves are coastal evergreen, salt-tolerant forest ecosystems that play a vital role in biodiversity conservation. Effective mapping and monitoring of mangrove ecosystems are essential for informed management and scientific decision-making. However, the dense and often inaccessible nature of mangrove forests makes traditional field surveys and ground truth collection challenging. Hyperspectral remote sensing offers a valuable solution by enabling species-level discrimination in mangroves through the extraction of vegetation structure and composition from imagery using diverse classification approaches. This study focuses on the discrimination of mangrove species in the mangrove forest areas of Marine National Park (MNP), Jamnagar, Gulf of Kutch, Lothian Island, Sundarbans, West Bengal. The proposed approach utilizes the Modified Spectral Angle Mapper (Modified SAM) algorithm with AVIRIS-NG hyperspectral data. This algorithm addresses the limitations of the traditional Spectral Angle Mapper (SAM) algorithm, which fails to account for the spatial structure and information of mangrove species. Additionally, the proposed algorithm reduces the reliance on a large number of training samples and complex classifiers, which are insufficient for extracting mangrove characteristics due to computational inefficiencies and limited generalization capabilities. By incorporating both spatial and spectral information, the Modified SAM algorithm enhances performance and classification accuracy, even in mixed mangrove pixel regions. This is achieved through the utilization of various distance and similarity measures, including angle change resulting from shape alterations in mangrove spectra, angle change due to the magnitude of mangrove spectra changes, and distance change between two mangrove spectra. These measures facilitate the identification of subtle differences between mangrove spectra. The results demonstrate a significant improvement in classification accuracy compared to the traditional SAM algorithm, particularly in mixed mangrove pixel regions. The achieved overall accuracy (OA) is 93.48% for the Lothian Islands, Sundarbans, West Bengal, and 94.32% for the Marine National Park (MNP), Jamnagar, Gulf of Kutch. The proposed Modified SAM algorithm, in conjunction with AVIRIS-NG hyperspectral data, offers an effective approach for reliable and efficient classification and discrimination of mangrove species. The algorithm's enhanced performance and classification accuracy have significant implications for mapping, monitoring, and managing mangrove ecosystems, supporting conservation efforts, and facilitating informed decision-making for sustainable mangrove ecosystems. [ABSTRACT FROM AUTHOR]

Recently, within the Fabaceae family, the Vicia genus has been recognized for its vital role in sustainable agriculture. Vicia species are economically important grain and forage crops. However, the presence of complex morphological characteristics makes identification and recognition of native species difficult. In this study, the possibility of using DNA barcoding regions (ITS2, matK, and rbcL) to distinguish among 19 Vicia taxa (59 accessions) found in South Korea was evaluated. The sequence alignment analysis revealed considerable nucleotide diversity (π) between the loci, in which ITS2 showed the highest mean interspecific distance, whereas there was no intraspecific variability among the barcode regions in 12 of the 19 taxa. Phylogenetic analysis of combined barcoding regions revealed well-resolved phylogeny with the highest species level discrimination. Combinations of barcode loci were also used in classification at the subgenera and section levels. The results revealed that the combined barcoding regions can be used effectively to differentiate the following species: Vicia angustifolia var. segetilis, Vicia bungei, Vicia villosa, Vicia cracca, Vicia dasycarpa, Vicia hirsuta, Vicia tetrasperma, Vicia amurensis, Vicia hirticalycina, and Vicia chosenensis. However, it is difficult to differentiate the species of Vicia unijuga, Vicia unijuga var. kaussanensis, Vicia linearifolia, Vicia unijuga f. angustifolia, Vicia nipponica, Vicia amoena, Vicia venosa var. cuspidata, Vicia pseudo-orobus, and Vicia japonica with the tested barcode regions. These species come under sect. Vicilla and are found to be closely related or species that have recently undergone speciation; thus, it has limitation to distinguish with recommended barcodes. Hence, to differentiate the unclassified species, 39 morphological characteristics were investigated, in which 16 useful characteristics were selected for efficient classification. Finally, the 16 selected morphological useful traits efficiently differentiated all the Vicia species. In conclusion, a combination of barcoding loci together with morphological characteristics of this study efficiently discriminated all the Korean Vicia species.

Recently, within the Fabaceae family, the Vicia genus has been recognized for its vital role in sustainable agriculture. Vicia species are economically important grain and forage crops. However, the presence of complex morphological characteristics makes identification and recognition of native species difficult. In this study, the possibility of using DNA barcoding regions (ITS2, matK , and rbcL) to distinguish among 19 Vicia taxa (59 accessions) found in South Korea was evaluated. The sequence alignment analysis revealed considerable nucleotide diversity (π) between the loci, in which ITS2 showed the highest mean interspecific distance, whereas there was no intraspecific variability among the barcode regions in 12 of the 19 taxa. Phylogenetic analysis of combined barcoding regions revealed well-resolved phylogeny with the highest species level discrimination. Combinations of barcode loci were also used in classification at the subgenera and section levels. The results revealed that the combined barcoding regions can be used effectively to differentiate the following species: Vicia angustifolia var. segetilis , Vicia bungei , Vicia villosa , Vicia cracca , Vicia dasycarpa , Vicia hirsuta , Vicia tetrasperma , Vicia amurensis , Vicia hirticalycina , and Vicia chosenensis. However, it is difficult to differentiate the species of Vicia unijuga , Vicia unijuga var. kaussanensis , Vicia linearifolia , Vicia unijuga f. angustifolia , Vicia nipponica , Vicia amoena , Vicia venosa var. cuspidata , Vicia pseudo-orobus , and Vicia japonica with the tested barcode regions. These species come under sect. Vicilla and are found to be closely related or species that have recently undergone speciation; thus, it has limitation to distinguish with recommended barcodes. Hence, to differentiate the unclassified species, 39 morphological characteristics were investigated, in which 16 useful characteristics were selected for efficient classification. Finally, the 16 selected morphological useful traits efficiently differentiated all the Vicia species. In conclusion, a combination of barcoding loci together with morphological characteristics of this study efficiently discriminated all the Korean Vicia species. [ABSTRACT FROM AUTHOR]

To meet the demand of standard spectral information for the subtropical forest, a three-level spectral library including leaf spectra of 67 typical subtropical tree species was built using two spectrometers. Towards the spectra measured by different spectrometers, the spectra consistency was tested using one-way Analysis of Variance (ANOVA) and Jeffries-Matusita distance (J-M distance). The optimal band range and spectral dimension reducing method for subtropical tree species discrimination were assessed using J-M distance based on original spectra and derivative spectra on visible-near infrared band (VNIR, 350–1000 nm), shortwave infrared band (SWIR, 1000–2500 nm) and full band (350–2500 nm). It was found that: (1) the spectra measured by the two spectrometers were significantly different, but the derivative spectra were not; (2) the SWIR spectral band was optimal for separating these subtropical tree species; (3) the selection method outperformed transform method for reducing spectra dimension and separating subtropical tree species [ABSTRACT FROM AUTHOR]

It is a well‐known and geographically widespread problem in archaeozoology that the discrimination between remains of domesticated animals and their wild ancestors is not always possible. Due to an overlap in size as well as other features, substantial parts of bone and teeth assemblages sometimes cannot be assigned either to the wild or the domestic form. In this paper, we apply the logarithmic size index (LSI) method as a tool for discrimination between aurochs (Bos primigenius) and domestic cattle (Bos primigenius f. taurus). By comparing LSI data from definite aurochs with data from Neolithic bovids within a limited geographical area, we show that the overlap of both groups is larger than previously thought. Our analysis also shows that the LSI width values are suited for both differentiating domesticated versus wild animals and sexes within the single groups. For future studies but also for correcting known results, we present division lines between LSI values of aurochs and cattle. The analysed data indicate that female and male aurochs had comparable heights, whereas the latter had a generally more sturdy physique in southern Scandinavia. We consequently expect that the investigated Middle Neolithic assemblages contain a significantly higher number of aurochs bones than previously assumed. [ABSTRACT FROM AUTHOR]

The genus Megastigmus Dalman, 1820 (Hymenoptera: Megastigmidae) contains potential biocontrol agents of the invasive eucalypt galling chalcid Leptocybe spp. (Hymenoptera: Eulophidae), with several species reported in various parts of the world. Species discrimination is challenging due to intraspecific morphological variation, difficulty in measuring sizes of body parts, and the lack of information regarding the global distribution of parasitic Megastigmus. We used two species commonly associated with Leptocybe in its native range to review taxonomic methods and determine the most reliable morphological characters in species delimitation. We examined size variation of body characters, and conducted species discrimination using multivariate ratio analysis, mitochondrial Cytochrome c oxidase subunit 1 (COI) and nuclear 28S rDNA (28S) sequences. Morphological traits were effective in species delimitation yet revealed high variation in several characters employed in current keys. Knowledge generated on morphology and DNA justified the description of a new species, M. manonae, sp. n., the first record of M. pretorianensis in Australia, and revised diagnostic characters for M. zvimendeli. Based on these diagnostic characters and molecular data, we synonymize three species (M. judikingae, syn. n., from Australia, M. sichuanensis, syn. n., from China and M. icipeensis, syn. n., from Kenya) with M. zvimendeli. Our findings highlight the importance of molecular markers in assisting taxonomic decision-making and the need for coordinated work in identifying Megastigmus associated with Leptocybe spp. [ABSTRACT FROM AUTHOR]

In Malaysia, Rhizophora mangroves are represented by three species (R. apiculata, R. mucronata, and R. stylosa) and natural hybrids between any two of the species do occur. While R. apiculata is easily differentiated from R. mucronata and R. stylosa, the lack of easily recognisable morphological keys between the latter two species often causes confusion. The occurrence of morphologically intermediate hybrids between them makes discriminating the taxa even more challenging. In this study, we conducted measurements on four floral characters, namely the peduncle length, diameter at the base of the calyx lobe, length of the calyx lobe, and style length, on the three Rhizophora species and two natural hybrids (R. apiculata x R. stylosa and R. mucronata x R. stylosa). Discriminant analysis indicated that the taxa could be distinguished based mostly on style length and peduncle length, which accounted for 96.7% of the total variation. Also, the floral characters were rather consistent within each taxon, except those of the potential hybrids between R. mucronata and R. stylosa. As more mangrove hybrids are being discovered, such studies are important for the establishment of more effective morphological keys for proper discrimination of the various mangrove taxa. [ABSTRACT FROM AUTHOR]