Identification Success Research Articles

Identification, assessment and ranking agile software development critical success factors - a factor analysis approach

Agile software development (ASD) methods have emerged as an innovative and diverse way of developing software as compared to the traditional methodologies that are having high project failure, higher cost and more time to complete the project, customer dissatisfaction, etc. The current study is conducted to identify and assess critical success factors along with discovering the perceived level of success factors for ASD. Initially, 39 variables have been identified and finally, 31 variables have been loaded into five factors that lead to success factors and further how these factors are related to perceived level of success factor that is again a cluster of further four identified variables (time, cost and efforts, quality and scope and requirements). The importance index is used to rank the factors along with the variables of the explored factors. Surprisingly, the important factors that came out were project factor followed by organisation, technical, people and process factors respectively.

An Improved Cuckoo Search Algorithm of Boundary Search and Variable Step-Size for Gravitational Reference Sensor Parameters Identification

At this stage, in order to ensure the effective work of the gravitational reference sensor, it’s necessary to ensure the residual velocity of the test mass(mass = 1.9 kg) after being released by the grabbing positioning and release mechanism is less than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5~\mu \text{m}$ </tex-math></inline-formula> /s, so that it can be normally captured by the electrode housing. Therefore, based on mathematical model of the release mechanism electro-mechanical dynamics, this paper conducts related research on the relationship between the residual speed of the test mass and the system parameters of the grabbing positioning and release mechanism. In order to solve the problem of difficulty in identifying model parameters, this paper uses the cuckoo search algorithm to identify model parameters, and improves the search efficiency and success rate by improving the step-length control factor and search strategy. Simulation experiments show that under the same number of iterations, the improved algorithm has achieved an effective improvement in the identification success rate and convergence accuracy of the original algorithm. Through the identification results, the residual speed of the test mass can be derived, verify whether the designed system meets the requirements, and establish an evaluation and guidance system for the system design.

Examining the utility of DNA barcodes for the identification of tallgrass prairie flora.

PremiseThe tallgrass prairies of North America are one of the most threatened ecosystems in the world, making efficient species identification essential for understanding and managing diversity. Here, we assess DNA barcoding with high‐throughput sequencing as a method for rapid plant species identification.MethodsUsing herbarium collections representing the tallgrass prairie flora of Oak Lake Field Station, South Dakota, USA, we amplified and examined four common nuclear and plastid barcode regions (ITS, matK, psbA‐trnH, and rbcL), individually and in combination, to test their success in identifying samples to family, genus, and species levels using BLAST searches of three databases of varying size.ResultsConcatenated barcodes increased performance, although none were significantly different than single‐region barcodes. The plastid region psbA‐trnH performed significantly more poorly than the others, while barcodes containing ITS performed best. Database size significantly affected identification success at all three taxonomic levels. Confident species‐level identification ranged from 8–44% for the global database, 13–56% for the regional database, and 21–80% for the sampled species database, depending on the barcode used.DiscussionBarcoding was generally successful in identifying tallgrass prairie genera and families, but was of limited use in species‐level identifications. Database size was an important factor in successful plant identification. We discuss future directions and considerations for improving the performance of DNA barcoding in tallgrass prairies.

Testing DNA barcoding in Usnea (Parmeliaceae) in Colombia using the internal transcribed spacer (ITS)

We tested the functionality of ITS-based DNA barcoding in lichen fungi using Colombian samples of the genus Usnea as an example. New ITS sequences were generated for 15 samples from five localities in two different ecoregions, representing varying morphologies and medullary chemistries. We employed five strategies to identify the samples: (1) BLASTn on the NCBI BLAST site with the original identifications of the best matching reference sequences; (2) as previous, but with revised identifications of the reference sequences based on a separately published revision of ITS sequences published for the genus; (3) local BLASTn in BioEdit using a separately published, revised and curated set of ITS reference sequences for the genus; (4) multiple alignment based phylogenetic analysis within the framework of all available ITS sequences for Usnea s.str.; and (5) integrative taxonomy, combining molecular phylogeny and comparative analysis of phenotype and chemical data. Using the latter approach as reference, we found that NCBI BLASTn with original identifications performed poorly, resulting in an identification success rate of only 7% (a single sample). NCBI BLASTn with revised identifications more than tripled identification success (23%), but was still unsatisfactory. Local BLASTn in BioEdit using the revised, curated reference data further doubled identification success (47%), but remained inadequate. Multiple alignment-based phylogenetic analysis achieved an identification success rate of 80% compared to the result from integrative taxonomy. Based on these results, we conclude that ITS-based DNA barcoding of the genus Usnea under the current circumstances performs poorly, but can be substantially improved using three strategies: (1) update identifications of reference sequences in primary repositories such as GenBank or alternatively use a curated reference data set; (2) perform local BLAST with a curated reference data set focusing on the target genus only, combined with multiple alignment-based phylogenetic analysis as a verification step; and (3) close substantial geographic and taxonomic gaps in the existing reference data. Our analyses suggest that if a near-complete reference data set with correct identifications existed for the genus, then standard BLAST approaches could achieve high levels of identification success close to 100%. As part of our DNA barcoding exercise, which generated the first 15 ITS sequences for Colombian samples of the genus Usnea, we confirm the presence of U. aranea and U. wasmuthii in Colombia and we report for the first time U. tenuicorticata for the country.

Estimating Population Abundance of Burying Beetles Using Photo-Identification and Mark-Recapture Methods.

Successful conservation and management of protected wildlife populations require reliable population abundance data. Traditional capture-mark-recapture methods can be costly, time-consuming, and invasive. Photographic mark-recapture (PMR) is a cost-effective, minimally invasive way to study population dynamics in species with distinct markings or color patterns. We tested the feasibility and the application of PMR using the software Hotspotter to identify Nicrophorus spp. from digital images of naturally occurring spot patterns on their elytra. We conducted a laboratory study evaluating the identification success of Hotspotter on Nicrophorus americanus (Olivier, 1790) and Nicrophorus orbicollis (Say, 1825) before implementation of a mark-recapture study in situ. We compared the performance of Hotspotter using both 'high-quality' and 'low-quality' photographs. For high-quality photographs, Hotspotter had a false rejection rate of 2.7-3.0% for laboratory-reared individuals and 3.9% for wild-caught individuals. For low-quality photographs, the false rejection rate was much higher, 48.8-53.3% for laboratory-reared individuals and 28.3% for wild-caught individuals. We subsequently analyzed encounter histories of wild-caught individuals with closed population models in Program MARK to estimate population abundance. In our study, we demonstrated the utility of using PMR in estimating population abundance for Nicrophorus spp. based on elytral spot patterns.

Eisenia fetida and Eisenia andrei delimitation by Automated Barcode Gap Discovery and neighbor-joining analyses: A review

Identification and differentiation of morphologically similar species have been a significant challenge to taxonomists due to a higher degree of similarity in their physical appearances leading to make the taxonomic investigation more complex. Such a problem is more common in invertebrate soil animals such as earthworms (Eisenia fetida and Eisenia andrei) since their identification requires observation of morphological characters that are very difficult and complex to visualize, especially in the case of sibling or subspecies. In this review, we assessed the utility of mitochondrial cytochrome c oxidase subunit I (COI) gene as a molecular marker for identification and differentiation among these species. We achieved this by analyzing their phylogeny using the neighbor-joining method and Automated Barcode Gap Discovery (ABGD) by retrieving 84 COI sequences from NCBI. As a result, we found that the identification and differentiation success of Eisenia fetida was 96.42%, whereas, for Eisenia andrei, it was 100%. Besides, ABGD analysis suggested that the species failed to give a distinct barcode gap, and the partition pattern may be due to probable misidentification leading to generate discordance among results of ABGD and NJ tree. Finally, we suggest that the multiloci approach of the mitochondrial genome can be used to solve this taxonomic ambiguity making the molecular identification system more reliable and comprehensive fulfilling need of growing biodiversity conservation programs on a global scale.

Estimating Coyote Densities with Local, Discrete Bayesian Capture‐Recapture Models

ABSTRACTRecent advances in noninvasive genetic sampling and spatial capture‐recapture (SCR) techniques are particularly useful for monitoring cryptic wildlife species such as carnivores. In southern Arizona, USA, coyotes (Canis latrans) are thought to negatively affect endangered Sonoran pronghorn (Antilocapra americana sonoriensis), although no estimates of coyote abundance or monitoring programs exist. Sonoran pronghorn are provided supplemental feed and water in this region, resulting in areas where pronghorn and other species are congregated. Because of the higher density of artificial water sources for Sonoran pronghorn on the Cabeza Prieta National Wildlife Refuge (CPNWR), we predicted that coyote density would be higher relative to the Barry M. Goldwater Range (BMGR), where artificial water sources are less dense. We used discrete Bayesian SCR models in a local evaluation approach to provide baseline estimates of coyote abundance and understand how coyote density varied between 2 contrasting areas of land use. We identified 106 individuals from scat samples across 3 sessions in 2013 and 2014 and achieved high genotyping and individual identification success rates (~78%). Encounter rates at water catchments were nearly 11 times higher compared to road and trail transects. As predicted, we found that coyote density was on average 2 times higher on the CPNWR (11.2 coyotes/100 km2) compared to the BMGR (5.3 coyotes/100 km2). The local evaluation approach significantly reduced computational time, making the discrete Bayesian approach more practical to implement across a large study area. Our study represents an important contribution towards developing a robust monitoring program for coyotes. We hope that our novel implementation of the local evaluation approach increases the ability of wildlife managers to understand the effects of land use and other ecological influences on large carnivore populations. © 2020 The Wildlife Society.

Rapid species level identification of fish eggs by proteome fingerprinting using MALDI-TOF MS

Quantifying spawning biomass of commercially relevant fish species is important to generate fishing quotas. This will mostly rely on the annual or daily production of fish eggs. However, these have to be identified precisely to species level to obtain a reliable estimate of offspring production of the different species. Because morphological identification can be very difficult, recent developments are heading towards application of molecular tools. Methods such as COI barcoding have long handling times and cause high costs for single specimen identifications. In order to test MALDI-TOF MS, a rapid and cost-effective alternative for species identification, we identified fish eggs using COI barcoding and used the same specimens to set up a MALDI-TOF MS reference library. This library, constructed from two different MALDI-TOF MS instruments, was then used to identify unknown eggs from a different sampling occasion. By using a line of evidence from hierarchical clustering and different supervised identification approaches we obtained concordant species identifications for 97.5% of the unknown fish eggs, proving MALDI-TOF MS a good tool for rapid species level identification of fish eggs. At the same time we point out the necessity of adjusting identification scores of supervised methods for identification to optimize identification success. SignificanceFish products are commercially highly important and many societies rely on them as a major food resource. Over many decades stocks of various relevant fish species have been reduced due to unregulated overfishing. Nowadays, to avoid overfishing and threatening of important fish species, fish stocks are regularly monitored. One component of this monitoring is the monitoring of spawning stock sizes. Whereas this is highly dependent on correct species identification of fish eggs, morphological identification is difficult because of lack of morphological features.

Raman spectroscopy study of manganese oxides: Layer structures

Abstract Raman spectra were collected for an extensive set of well-characterized layer-structure Mn oxide mineral species (phyllomanganates) employing a range of data collection conditions. We show that the application of various laser wavelengths, such as 785, 633, and 532 nm, at low power levels (30–500 μW) in conjunction with the comprehensive database of standard spectra presented here, makes it possible to distinguish and identify the various phyllomanganate minerals. The Raman mode relative intensities can vary significantly as a function of crystal orientation relative to the incident laser light polarization direction as well as incident laser light wavelength. Consequently, phase identification success is enhanced when using a standards database that includes multiple spectra collected for different crystal orientations and with different laser light wavelengths. The position of the highest frequency Raman mode near 630–665 cm–1 shows a strong linear correlation with the fraction of Mn3+ in the octahedral Mn sites. With the comprehensive Raman database of well-characterized Mn oxide standards provided here (and available online as Online Material1), and use of appropriate data collection conditions, micro-Raman is a powerful tool for identification and characterization of biotic and abiotic Mn oxide phases from diverse natural settings, including on other planets, as well as for laboratory and industrial materials.

Italian odonates in the Pandora's box: A comprehensive DNA barcoding inventory shows taxonomic warnings at the Holarctic scale.

The Odonata are considered among the most endangered freshwater faunal taxa. Their DNA-based monitoring relies on validated reference data sets that are often lacking or do not cover important biogeographical centres of diversification. This study presents the results of a DNA barcoding campaign on Odonata, based on the standard 658-bp 5' end region of the mitochondrial COI gene, involving the collection of 812 specimens (409 of which barcoded) from peninsular Italy and its main islands (328 localities), belonging to all the 88 species (31 Zygoptera and 57 Anisoptera) known from the country. Additional BOLD and GenBank data from Holarctic samples expanded the data set to 1,294 DNA barcodes. A multi-approach species delimitation analysis involving two distance (OT and ABGD) and four tree-based (PTP, MPTP, GMYC and bGMYC) methods was used to explore these data. Of the 88 investigated morphospecies, 75 (85%) unequivocally corresponded to distinct molecular operational units, whereas the remaining ones were classified as 'warnings' (i.e. showing a mismatch between morphospecies assignment and DNA-based species delimitation). These results are in contrast with other DNA barcoding studies on Odonata showing up to 95% of identification success. The species causing warnings were grouped into three categories depending on if they showed low, high or mixed genetic divergence patterns. The analysis of haplotype networks revealed unexpected intraspecific complexity at the Italian, Palearctic and Holarctic scale, possibly indicating the occurrence of cryptic species. Overall, this study provides new insights into the taxonomy of odonates and a valuable basis for future DNA and eDNA-based monitoring studies.

Raman spectroscopy study of manganese oxides: Tunnel structures

Abstract Raman spectra were collected for an extensive set of well-characterized tunnel-structure Mn oxide mineral species employing a range of data collection conditions. Using various laser wavelengths, such as 785, 633, and 532 nm at low power levels (30–500 µW), as well as the comprehensive database of standard spectra presented here, it is generally possible to distinguish and identify the various tunnel structure Mn oxide minerals. The Raman mode relative intensities can vary significantly as a function of crystal orientation relative to the incident laser light polarization direction as well as laser light wavelength. Consequently, phase identification success is enhanced when using a standards database that includes multiple spectra collected for different crystal orientations and with different laser light wavelengths. For the hollandite-group minerals, the frequency of the Raman mode near 630 cm–1 shows a strong linear correlation with the fraction of Mn3+ in the octahedral Mn sites. With the comprehensive Raman database of well-characterized Mn oxide standards provided here (and available online as Supplemental Materials1), and use of appropriate data collection conditions, micro-Raman is a powerful tool for identification and characterization of biotic and abiotic Mn oxide phases from diverse natural settings, including on other planets.

Intoxicated person identification using Markov chains and neural networks

In this work, Markov chains are used to model the statistical behavior of the pixels on the image of the forehead of a person in order to detect intoxication. It is the first time that second-order statistics are used for this purpose. The images were obtained in the thermal infrared region. Intoxication affects blood vessels activity and thus the temperature distribution on the face having a significant effect on the corresponding pixels statistics. The pixels of the forehead images are quantized to 32 Gy levels so that Markov chain models are structured using 32 states. The feature vectors used are the eigenvalues obtained from the first-order transition matrices of the Markov chain models. Since for each person a frame sequence of 50 views is acquired, a cluster of 50 vectors is formed in the 32-dimensional feature space. The feature space is firstly analyzed using projections of the clusters in 3D subspaces of the original 32D feature space. After that, the capability of a simple feed forward neural network to separate the clusters belonging to sober persons from those corresponding to intoxicated persons is investigated. A simple three-layer neural structure has a 98% vector separability success and a 100% cluster separability if the majority voting is considered. Furthermore, the classification problem is faced by excluding from the training procedure either one or five persons and using them in the testing phase. Accordingly, a neural network is trained using all except the excluded data. The obtained neural structure tested with the features of the persons in which it was not trained presents high drunk identification success if the majority voting is considered.

Plant DNA barcoding necessitates marker-specific efforts to establish more comprehensive reference databases.

The problem of low species-level identification rates in plants by DNA barcoding is exacerbated by the fact that reference databases are far from being comprehensive. We investigate the impact of increased sampling depth on identification success by analyzing the efficacy of established plant barcode marker sequences (rbcL, matK, trnL-trnF, psbA-trnH, ITS). Adding sequences of the same species to the reference database led to an increase in correct species assignment of +10.9% for rbcL and +19.0% for ITS. Simultaneously, erroneous identification dropped from ∼40% to ∼12.5%. Despite its evolutionary constraints, ITS showed the highest identification rate and identification gain by increased sampling effort, which makes it a very suitable marker in the planning phase of a barcode study. The limited sequence availability of trnL-trnF is problematic for an otherwise very promising plastid plant barcoding marker. Future developments in machine learning algorithms have the potential to give new impetus to plant barcoding, but are dependent on extensive reference databases. We expect that our results will be incorporated into future plans for the development of DNA barcoding reference databases and will lead to these being developed with greater depth and taxonomic coverage.

The Essential Role of Taxonomic Expertise in the Creation of DNA Databases for the Identification and Delimitation of Southeast Asian Ambrosia Beetle Species (Curculionidae: Scolytinae: Xyleborini)

DNA holds great potential for species identification and efforts to create a DNA database of all animals and plants currently contains >7.5 million sequences representing ~300,000 species. This promise of a universally applicable identification tool suggests that morphologically based tools and taxonomists will soon not have utility. Here we demonstrate that DNA-based identification is not reliable without the contributions of taxonomic experts. We use ambrosia beetles (Xyleborini), which are known for great diversity as well as global invasions and damage, as a test case. Recent xyleborine introductions have caused major economic and ecological losses, thus timely species identifications of new invaders are necessary. This need is hampered by a paucity of identification tools and a fauna that is only moderately documented. To help alleviate deficiencies in their identification, we created COI and CAD DNA barcode databases (490 and 429 specimens), representing over half of the known fauna of Southeast Asia (165/316 species). Taxonomic experts identified species based on original descriptions and type specimens. Tree, distance, and iterative methods were used to assess the identification and delimitation of species. High intra- and interspecific COI distances were observed for congeneric species and attributed to the beetle’s inbreeding system. Neither of the two markers provided 100% identification success but with the neighbor-joining tree-based method, 80% of species were identified by both genes. As for species delimitation, an obvious barcode gap between intra- and interspecific differences was not observed. Correspondence between distance-based groups and morphology-based species was poor. In a demonstration of iterative taxonomy, we constructed parsimony-based phylogenies using COI and CAD sequences for two genera. Although not all clades were resolved or supported, we provided better explanations for species boundaries in light of morphological and DNA sequence differences. Confident species identifications demonstrated 10–12% COI and/or >2–3% CAD. Involvement of taxonomic experts from the start of this project was essential for the creation of a stable foundation for the DNA identification of xyleborine species. In general, their role in DNA barcoding cannot be underestimated and is further discussed.

Design and implementation of a star-tracker for LEO satellite

An important task of the attitude determination and control subsystem (ADCS) is the determination of attitude of the satellite in reference to the Earth or any other planetary and correct any deviation from the expected attitude. In order to determine the attitude of the satellite, sensors are needed to sense the orientation of the satellite. The star-tracker is able to determine the attitude from the view field of the star set without any prior knowledge of sensor information. In this paper, the design, simulation and implementation of a star-tracker is presented for LEO satellites. For capturing image data, the MT9P031 CMOS image sensor from Aptina Imaging was used. The star tracker uses a Texas Instrument OMAP3530 using an ARM Cortex A8. The processor supports powerful graphic interfaces resulting in reduction of the size and consumption power of the star-tracker. For storage and processing, the star tracker used NAND flash memory. The communication interface to the satellite is done through CAN Bus. One of the key features of this sensor is processing various algorithms for image processing, positioning, and tracking according to mission requirements. Quaternion estimator (QUEST) algorithm was utilized for positioning. The tracking algorithm utilizes information from the previous frame of the star-tracking. This algorithm is a high-speed, low cost, and low memory implementation. In the field tests, the identification success rate of this system was 96.81 %.

Perancangan Sistem Monitoring Kehadiran Mahasiswa Pada Laboratorium FTKI UNAS Menggunakan Teknologi RFID

The recording of student attendance at the FTKI UNAS laboratory is still done manually which causes UNAS to have to input a large amount of attendance data every day. This often results in recording errors caused by human error, not to mention if there is fraud by manipulating attendance data. This study uses a microcontroller to design a student attendance monitoring system digitally by identifying student code from the RFID Tag. The system is designed using RFID and NodeMCU modules which will be sent to the MySQL database and will be displayed on the website page. The test results from 100 data obtained 100% identification success with an average reading distance of 4cm. of 100 presence test data, the system can store data with 100% accuracy for the corresponding data, and can read the presence of errors with 100% accuracy.

Does Eyewitness Guess or Recognize? Bootstrapping Face and Object Identification Accuracy

The purpose of the study is to determine whether the eyewitness identification can be regarded as a reliable source of information in a police investigation. In light of the many cases of eyewitness misidentifications, it seems reasonable to determine not only what class of objects is more likely to be actually recognized, but also is the level of accuracy sufficient enough to be a solid base for an investigation or a court case. To answer the questions a two-step experiment was designed and performed. At the first stage of the study, 71 participants watched a short video clip, and a week later they were asked to identify persons and the objects that appeared in the film. The participants’ rate of face identification success was 55%, while in the case of objects it was only 28%. Bootstrap estimation was used to determine if those numbers differ from random, and as a result whether they should be considered as a result of an accidental hit. The analysis showed that in the case of objects identification the success rate is within the bounds of randomness, while face identification exceeds it. It can be concluded that unlike faces, objects are more likely guessed than recognized.

ПРОЄКТНА СХЕМА ЦИКЛУ УПРАВЛІННЯ ІНТЕГРОВАНИМИ ЗУСИЛЛЯМИ З РОЗВИТКУ ПІДПРИЄМСТВ КЛАСТЕРУ ТУРИЗМУ ТА РЕКРЕАЦІЇ

Introduction. The authors have proposals outline specification management cycle of integrated effort for the development of business clusters. Tourism and Recreation, based on general features area-specific management.Purpose. The goal of the work was consistent definition management features integrated effort the development of business in clusters Tourism and Recreation.Results. The authors were requested to design, plan the management cycle of integrated effort for the development of business in clusters Tourism and Recreation. That draft contain:1) synthesis, analysis and diagnostic portrait of the cluster, surrounding the geographical, historical, demographic, economic, social characteristic, supported by assessment state of tourist attractions (as a functioning of the environment);2) mission and common vision, which gave operational meaning a promising integrated сluster development, mission each of autonomous members;3) macro-micro analysis, competitive advantage and restrictions future development, integrative environments of cluster;4) identified the strategic direction activities, singled out as population, strategic objectives and provisional action, relatively achieve the goals: a description of the actions, target dates for the implementation, responsible persons, sources of funding; implementation mechanisms strategic plan; the list of participants formulation.Originality. Оn based on the use of comparisons, structural, historical, logical, Systems Analysis; secondary data analysis, integrating, interpretation, project methods being developed іnstrumental time dimension of management process the cascading based on a system of medium-term and ongoing (budget) plans. The provision devoted with what basis for planning cannot be only an optimistic expectation, it is necessary a holistic scientific basis of problem that may arise in implementing the proposed areas development integration of business in clusters Tourism and Recreation.Conclusion. The study is based on a use of comparisons, historical, logical, systems analysis; secondary data analysis, integrating, interpretation, project methods. The scientific approach lies in design of scheme management cycle integrated effort for the development of business in Tourism and Recreation clusters. Following the study conclusions were made about the availability, multi и business environment inside of a Tourism and Recreation clusters. Therefore, strategic analysis is an integrated multi-level conversion of the database, generated by analysis of the external (macro) and internal (micro) cluster environment and internal environments party's autonomous (Microanalysis) and in the future is the basis for strategic map and identification success factor. The further scientific development to define the basic criteria and form the specifics of building an effective governance paradigm the development of Tourism and Recreation clusters.

Species identification of zooplankton resting eggs based on DNA barcode technology: A case study of Lake Liuye (Changde), Lake Dongting Basin

以洞庭湖流域的典型城市湖泊常德柳叶湖表层沉积物中浮游动物休眠卵为研究对象，采用DNA条形码技术进行种类鉴定，从191个休眠卵中成功获得101条有效序列，鉴定成功率约为53%.根据NCBI数据库比对成功鉴定休眠卵9科12属11种，另有6个样品鉴定到属或科；3个类群的种间遗传距离平均为种内遗传距离的68倍，表明可以利用线粒体细胞色素c氧化酶第一亚基编码基因（COⅠ）对休眠卵进行有效物种鉴定.通过Neighbor-Joining树进行系统发育分析，发现所鉴定的物种与其参比序列聚类为一支，所有物种分别聚为独立的一个支系，不同物种可有效区分.研究结果均表明，COⅠ基因作为DNA条形码可以实现沉积物中浮游动物休眠卵的物种鉴定.;With the rapid development of modern molecular biology tools, especially DNA barcoding technology, a rapid, accurate and efficient identification method for species of zooplankton resting eggs is possible. In this study, zooplankton resting eggs, including copepods,cladocerans and rotifers in the surface sediments of Lake Liuye (Changde), a typical urban lake in Lake Dongting Basin, were studied. Using DNA barcode technology for species identification, 101 valid DNA sequences were successfully obtained from 191 resting eggs, and the identification success rate was 53%. According to the NCBI database comparison, 9 families, 12 genera and 11 species of resting eggs were successfully identified, and 6 samples were only identified to the genus or family level. The inter-species genetic distance of the three taxa was 68 times that of the intra-species genetic distance, indicating that the cytochrome oxidase Ⅰ (COⅠ) gene could be used for effective species identification of zooplankton resting eggs. Through the phylogenetic analysis by Neighbour-Joining tree, it was found that the identified species and their reference sequences were clustered into one branch, and all different species were clustered into independent branches respective. Therefore, different species could be effectively distinguished. The above results all indicate that the mitochondrial COⅠ gene, as a DNA barcode, can be used to identify the species of zooplankton resting eggs in sediment of lakes.

DNA barcoding augments conventional methods for identification of medicinal plant species traded at Tanzanian markets.

In Africa, traditional medicine is important for local healthcare and plants used for these purposes are commonly traded. Identifying medicinal plants sold on markets is challenging, as leaves, barks and roots are often fragmented or powdered. Vernacular names are often homonymic, and identification of material lacking sufficient morphological characters is time-consuming, season-dependent and might lead to incorrect assessments of commercialised species diversity. In this study, we identified cases of vernacular heterogeneity of medicinal plants using a tiered approach of literature research, morphology and DNA barcoding. A total of 870 single ingredient medicinal plant samples corresponding to 452 local names were purchased from herbal markets in Dar-es-Salaam and Tanga, Tanzania, and identified using conventional methods as well as DNA barcoding using rbcL, matK and nrITS. Using conventional methods, we could identify 70% of samples to at least family level, while 62% yielded a DNA barcode for at least one of the three markers. Combining conventional methods and DNA barcoding, 76% of the samples could be identified to species level, revealing a diversity of at least 175 species in 65 plant families. Analysis of the market samples revealed 80 cases of multilingualism and over- and under-differentiation. Afzelia quanzensis Welw., Zanthoxylum spp., Allophylus spp. and Albizia anthelmintica Brongn. were the most evident cases of multilingualism and over-differentiation, as they were traded under 8-12 vernacular names in up to five local languages. The most obvious case of under-differentiation was mwingajini (Swahili), which matched to eight scientific species in five different plant families. Use of a tiered approach increases the identification success of medicinal plants sold in local market and corroborates findings that DNA barcoding can elucidate the identity of material that is unidentifiable based on morphology and literature as well as verify or disqualify these identifications. Results of this study can be used as a basis for quantitative market surveys of fragmented herbal medicine and to investigate conservation issues associated with this trade.