Identification Of Animal Species Research Articles

Comparison of Universal mtDNA Primers in Species Identification of Animals in a Sample with Severely Degraded DNA

Analysis of mitochondrial DNA, specifically the cytochrome b gene (cyt b), has become an essential tool for species identification. In the case of degraded samples, in which DNA is fractionated, universal primers, which are highly effective at amplifying the target region, are necessary. The material analysed in this study was a keychain made of bone, which was secured at a border crossing due to the suspicion that it was made of ivory. Due to processing of the bone and the likelihood of DNA degradation, five pairs of universal primers with different product lengths (from 148 to 990 base pairs) were used for species identification. Fragments of mtDNA from the cyt b and the 12S rRNA and 16S rRNA subunits were analysed. The analysis showed that only one pair of primers (L15601/H15748) enabled identification of the species, which is very common in samples with highly degraded DNA. The material was bone tissue belonging to the species Bos taurus (cattle). Species identification by molecular methods is extremely important in analysis of material when the species cannot be identified on the basis of morphological characteristics.

Animal species identification in historical parchments by CWT-CNN classifier applied to UV-Visible-NIR spectroscopic data

Animal species identification in historical parchments by CWT-CNN classifier applied to UV-Visible-NIR spectroscopic data

A study on the intertidal animal diversity of Xia-Sanheng Island by using morphological and DNA barcoding identification

Intertidal animals are an essential part of the ecosystem, and species diversity can reflect the state of the local ecological environment. However, traditional morphological identification is prone to corresponding classification errors or research limitations. With the development of molecular biology, many techniques and bioinformatics classification methods have been applied to identify species efficiently in recent years. This research aimed to examine the feasibility of DNA barcoding within the identification of intertidal animal species collected from the Xia-Sanheng Island. A total of 41 cox1 gene sequences were obtained by experimentalization or downloaded from the National Center for Biotechnology Information (NCBI) database. Then morphological classification, molecular identification, phylogenetic tree analysis, and Automatic Barcode Gap Discovery (ABGD) method were used to analyze the animal samples. We found that although the molecular classification of molluscs was not accurate enough, the collected specimens could be divided into 15 species, 12 families, and 4 phyla. Tetraclita japonica, Thais luteostoma, and Mytilus coruscus were the dominant species on the Xia-Sanheng Island. Additionally, there may be a new species, Platynereis sp., which needs further confirmation. We suggest that further identification of marine biodiversity should be carried out by combining morphological and molecular biological methods.

Markers for meat provenance and authenticity with an account of its defining factors and quality characteristics - a review.

Provenance is becoming increasingly important in meat supply chains as it lends products higher perceived quality. However, its precise definition and interpretation along with its associated characteristics factors have remained somewhat elusive. This review meticulously defines meat provenance while dissecting the essential factors and associated quality attributes that constitute its essence and are subsequently employed to establish pertinent markers for provenance. Meat provenance emerges as a multi-dimensional construct stemming from the adept management of a constellation of factors relating to geographical origin, farm production system, traceability, and authenticity. Through intricate interactions, these factors unveil innate originality that not only forges a distinct reputation but also imparts a unique typicity to the meat product. Gaining insights into a meat product's provenance becomes attainable by scrutinizing its pertinent composition and organoleptic quality traits. Trace elements and stable isotopes stand out as provenance markers, forging a direct connection to both geographical origin and dietary sources. While somewhat less direct in linkage, other markers such as plant biomarkers, fatty acid composition, pH levels, flavour and aromatic compounds along with organoleptic characteristics contribute to the overall understanding of provenance. Additionally, the identification of animal species and breeds serves as key markers, particularly in the context of protected geographical indications. The study findings are useful for the various stakeholders of how the information for meat provenance can be linked with intrinsic and extrinsic factors for meat quality and protecting the integrity of the supply chain with special reference to traceability and authenticity. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Analysis of Whole-Genome as a Novel Strategy for Animal Species Identification.

Survival crises stalk many animals, especially endangered and rare animals. Accurate species identification plays a pivotal role in animal resource conservation. In this study, we developed an animal species identification method called Analysis of whole-GEnome (AGE), which identifies species by finding species-specific sequences through bioinformatics analysis of the whole genome and subsequently recognizing these sequences using experimental technologies. To clearly demonstrate the AGE method, Cervus nippon, a well-known endangered species, and a closely related species, Cervus elaphus, were set as model species, without and with published genomes, respectively. By analyzing the whole genomes of C. nippon and C. elaphus, which were obtained through next-generation sequencing and online databases, we built specific sequence databases containing 7,670,140 and 570,981 sequences, respectively. Then, the species specificities of the sequences were confirmed experimentally using Sanger sequencing and the CRISPR-Cas12a system. Moreover, for 11 fresh animal samples and 35 commercially available products, our results were in complete agreement with those of other authoritative identification methods, demonstrating AGE's precision and potential application. Notably, AGE found a mixture in the 35 commercially available products and successfully identified it. This study broadens the horizons of species identification using the whole genome and sheds light on the potential of AGE for conserving animal resources.

Animal Species and Blood Identification with Peptide Mass Fingerprinting.

As more families are acquiring pets and the opportunities for wild animals to appear in human neighborhoods are increasing, the number of cases and accidents involving animals is increasing. Hence, the need to identify animal species from blood left over at accident sites is increasing. Human hemoglobin is used as a marker for human blood. Although tandem mass spectrometry is the dominant methodology used in proteomics research, peptide mass fingerprinting, given its instant applicability, may be useful for screening animal species, as the amino acid sequences of hemoglobin from various animals differ. In this study, solutions that were easily purified─using hemoglobin reagents from humans, Japanese macaques, bears, cattle, goats, sheep, sika deer, pigs, wild boars, dogs, cats, and nutrias─were digested by trypsin, and subjected to database searched using Mascot. No candidate proteins were found in the blood of goats, sheep, sika deer, wild boars, pigs, or nutrias. However, bloodstains from all animal species except nutria (which is not registered in the database) yielded candidates, which were identified as the hemoglobin of origin or its relatives. This difference may be attributed to more contaminants being included in blood. Further narrowing was possible using the average mass obtained via infusion electrospray ionization mass spectrometry measurement of the undigested solution in Mascot results. Saliva, urine, semen, and sweat collected from humans were also examined and searched for mascots, but no hits were obtained. In conclusion, this method may be useful for estimating animal species and identifying blood in forensic science.

A universal tool for marine metazoan species identification: towards best practices in proteomic fingerprinting

Proteomic fingerprinting using MALDI-TOF mass spectrometry is a well-established tool for identifying microorganisms and has shown promising results for identification of animal species, particularly disease vectors and marine organisms. And thus can be a vital tool for biodiversity assessments in ecological studies. However, few studies have tested species identification across different orders and classes. In this study, we collected data from 1246 specimens and 198 species to test species identification in a diverse dataset. We also evaluated different specimen preparation and data processing approaches for machine learning and developed a workflow to optimize classification using random forest. Our results showed high success rates of over 90%, but we also found that the size of the reference library affects classification error. Additionally, we demonstrated the ability of the method to differentiate marine cryptic-species complexes and to distinguish sexes within species.

Animal Identity Recognition using Object Detection Techniques

Object detection is a method for recognizing and detecting various objects present in an image or video by using the combination of learning approaches such as classification, recognition, and object localization. The identification of animal species in the wild through camera traps continues to pose an unsolved challenge, primarily attributed to various difficulties arising from shooting conditions such as fluctuating illumination, diverse weather patterns, seasonal changes, and complex backgrounds. Additionally, the unpredictable movements, diverse shapes and poses, and occlusions caused by natural objects contribute to the complexity, making accurate recognition a persistent issue. This paper utilizes the frameworks of YOLOv5 and Detectron2 for classifying animal images into predefined classes along with annotated regions. These automated frameworks for recognition and subsequent identity detection are applied to the gorillas and monkeys using the Bristol and Monkey Species dataset respectively. The experiments conducted resulted in good results on both the datasets achieving the highest mAP of 95.07 for YOLOv5.

Molecular identification of animal species of Bufonis Venenum from secretions

The animal species is one of the key factors affecting the quality of Bufonis Venenum. The quality of Bufonis Venenum derived from Bufo bufo gargarizans is significantly higher than that from B. melanostictus. Since Bufonis Venenum is from secretions, the conventional identification methods are difficult to identify the animal species due to the lack of the appearance and morphology of the animals. The rapid development of molecular identification technology has provided new methods for the identification of Bufonis Venenum. However, because of the low content and serve degradation of residual DNA in secretions, the research on the molecular identification of Chinese medicinal materials from secretions remains to be carried out. To understand the animal species of Bufonis Venenum, this study collected 83 samples of Bufonis Venenum, including 7 commercially available samples, 5 reference medicinal materials, and 71 animal samples from which Bufonis Venenum was prepared according to the method in the 2020 edition of the Chinese Pharmacopoeia. Different DNA extraction methods were used and compared, and the mitochondrial 16S rRNA gene fragments were amplified, on the basis of which the phylogenetic trees were built. Finally, molecular identification of the animal species of the samples was performed. The results showed that the DNA extracted from Bufonis Venenum by the reagent kit had good quality, and 16S rRNA sequences were successfully amplified from 80 out of the 83 samples. In addition, 71 16S rRNA sequences of the animal species of Bufonis Venenum were downloaded from GenBank. The phylogenetic trees constructed based on the neighbor-joining(NJ) method and the Bayesian inference(BI) method showed that the samples derived from B. bufo gargarizans and B. melanostictus were clustered into separate monophyletic clades, with the support of 100%(NJ) and 1.00(BI), respectively. The animal species of both commercially available samples and reference medicinal materials were B. bufo gargarizans. In conclusion, DNA can be extracted from Bufonis Venenum derived from secretions, and the 16S rRNA gene sequences can be amplified, which can be used for molecular identification of the animal species of Bufonis Venenum. The findings provide a reference for the quality control of Bufonis Venenum and the identification of animal species of medicinal materials derived from secretions.

Fast and on-site animal species identification in processed meat via centrifugal microfluidics and isothermal amplification.

We present a novel centrifugal microfluidic approach to rapidly identify animal species in meat products. The workflow requires a centrifugal cartridge for DNA extraction and for preparation of a recombinant polymerase amplification (RPA) reaction, a programmable centrifuge for processing the cartridge and an isothermal reader to perform the RPA. Liquid reagents are pre-stored on the cartridge and the meat sample can be added directly without any pre-treatment. With this system, we are able to identify six different animal species in a single run within one hour. In pork salami containing horse, turkey, sheep, chicken and beef meat, it was possible to identify species levels as low as 0.01%. In beef salami and cooked pork sausages 0.1% of foreign meat could be detected. This novel workflow enables rapid and sensitive species identification in processed meat at the point of need.

Development of ion torrent-based targeted next-generation sequencing panel for identification of animal species in pet foods

Manufacturers may intentionally or unintentionally incorporate ingredients not specified on the label of canned pet foods. Including any unacknowledged ingredients in a food product is considered food fraud or misbranding. Contamination of pet foods may occur in the processing of the foods, including potential cross-contamination in packaging facilities.Of the methods available to identify meat species in food products, Sanger sequencing and several next-generation sequencing methods are available, but there are limitations including the number of targets analyzed at a time and the method specificity. In this study, we developed a targeted next-generation sequencing panel to detect meat species in canned pet foods using Ion Torrent technology.The panel contains multiple primers targeting mitochondrial genes from as many as 27 animal species, of which 7 major animal species were validated. The meat species targets could be identified from samples spiked with as low as 0.01% w/w of the contaminating meat species in a vegetarian food matrix material. Targeted NGS in the current study enriches species-specific multiple target areas in the mitochondrial genome of the target material, which gives high accuracy in the sequencing results.

Identification of animal species of origin in meat based on glycopeptide analysis by UPLC-QTOF-MS.

Adulteration of meat and meat products causes a concerning threat for consumers. It is necessary to develop novel robust and sensitive methods which can authenticate the origin of meat species to compensate forthe drawbacks of existing methods. In the present study, the sarcoplasmic proteins of six meat species, namely, pork, beef, mutton, chicken, duck and turkey, were analyzed by one-dimensional gel electrophoresis. It was found that enolase could be used as a potential biomarker protein to distinguish between livestock and poultry meats. The glycosylation sites and glycans of enolase were analyzed by UPLC-QTOF-MS and a total of 41 glycopeptides were identified, indicating that the enolase N-glycopeptide profiles of different meats were species-specific. The identification models of livestock meat, poultry and mixed animal were established based on the glycopeptide contents, and the explanation degree of the three models was higher than 90%. The model prediction performance and feasibility results showed that the average prediction accuracy of the three models was 75.43%, with the animal-derivedmeat identification model showing superiority in identifying more closely related species. The obtained results indicated that the developed strategy was promising for application in animal-derivedmeat species monitoring and the quality supervision of animal-derived food.

Identification of individual goat animals by means of near infrared spectroscopy and chemometrics analysis of commercial meat cuts.

Although the identification of animal species and muscles have been reported previously, no studies have been found on the use of NIR spectroscopy to identify individual animals from the analysis of commercial meat cuts. The aim of this study was to evaluate the use of a portable near infrared (NIR) instrument combined with classical chemometrics methods [principal component analysis (PCA) and partial least squares discriminant analysis PLS-DA)] to identify the origin of individual goat animals using the spectral signature of their commercial cut. Samples were collected from several carcasses (6 commercial cuts x 24 animals) sourced from a commercial abattoir in Queensland (Australia). The NIR spectra of the samples were collected using a portable NIR instrument in the wavelength range between 950 and 1600nm. Overall, the PLS-DA models correctly classify 82% and 79% of the individual goat samples using either the goat rack or loin cut samples, respectively. The study demonstrated that NIR spectroscopy was able to identify individual goat animals based on the spectra properties of some of the commercial cut samples analysed (e.g. loin and rack). These results showed the potential of this technique to identify individual animals as an alternative to other laboratory methods and techniques commonly used in meat traceability.

Authenticity identification of animal species in characteristic milk by integration of shotgun proteomics and scheduled multiple reaction monitoring (MRM) based on tandem mass spectrometry

Milk is one of the oldest natural dairies with high value, which has different species including cow, camel, donkey, goat, sheep, buffalo, yak and et al. However, economically motivated adulteration of non-cow milk with cheaper cow milk occurs frequently. To develop a high-throughput approach for milk species authentication, integration of shotgun proteomics and scheduled multiple reaction monitoring (MRM) was developed. In total, 37 specific peptides were screened as unique to different species. Specific peptides processing stability was investigated under different treatment (heat, pressure, fermentation). Subsequently, four quantitative ion pairs of peptides from cow milk and six quantitative ion pairs of peptides from six non-cow milks were selected for the adulteration quantitative analysis. The method is capable of detection adulteration in the range of 1%–100%, and the quantitative recoveries ranged from 91.07% to 111.75%. The results suggested that combination of shotgun proteomics and MRM had potential for the milk species authentication.

DNA Barcoding and Its Applications: A Review

The use of DNA sequences has revolutionized biological classification, specifically through the utilization of the DNA barcode technique, which involves amplifying a standardized DNA fragment for the identification of plant and animal species. The methods and techniques involved in DNA barcoding are introduced and visualized in the paper. As incorporated in various applications in diverse fields, a comprehensive discussion on DNA barcoding is presented, highlighting its relevance and use in species identification and discovery. Furthermore, we explore its different roles, ranging from biodiversity assessment and conservation to food safety, forensic science, biosecurity, and public health. We also introduce the current limitations of the technique and its potential use in future applications of genetics-based discoveries.

Identification of animal species by nucleic acid chromatography of hair samples and investigation of its applicability to human biological samples

GeneFields®-Hair is a simple analysis kit that uses nucleic acid chromatography and polymerase chain reaction (PCR) to identify animal species of hair-like food contaminants. In this study, we evaluated GeneFields®-Hair as a simple and rapid method for identifying animal species from hair-like materials collected in forensic science, such as at crime scenes. The use of this kit with other human biological materials (whole blood, head dandruff, nails, saliva, oral mucosa, sebum, and urine) was also investigated. Animal body hair samples were pretreated by grinding in a buffer solution, centrifuged, and the supernatant was used for PCR. Nucleic acid chromatography of the PCR products allowed the identification of the animal species by the presence or absence of coloration on the decision line. For human biological materials, nucleic acid chromatography was performed after the appropriate pretreatment like body hair material. The determination of some animal species was difficult, even if they had a dedicated DNA Strip determination line. Furthermore, animals from the same family but different genera were sometimes detected on the same determination line. All the human biological samples were correctly identified. Smartphone photographs of the coloration of the judgment line were processed using the ImageJ software for quantitative determination.

Identification of animal species housed and herding practices in ancient sediments from the Vallone Inferno rock-shelter (Scillato, Sicily, Italy) using faecal biomarkers, hormones, and their metabolites

The interest in the identification of animal species housed in caves or rock-shelters used as livestock pen and herding management along prehistoric and historic ages, is increasing to understand better the development of pastoral activities. In this manuscript, a method for the quantification of β-sterol/phytosterols, bile acids, hormones and hormones metabolites has been developed to determine the main pastoral activities carried out in Vallone Inferno rock-shelter (Scillato, Sicily, Italy) from Middle Neolithic to Early Middle Age. According to the result obtained, the main animals housed in the rock-shelter went gradually changing from ovicaprids in Middle Neolithic to pigs in Early Middle Age. Additionally, new proxies (progesterone/Ʃbile acids and metabolites of progesterone/Ʃbile acids) were used to detect a high hormonal activity at Early Middle Age samples related with female pig management.

Proteotypic peptides of hairs for the identification of common European domestic and wild animal species revealed by in-sample protein digestion and mass spectrometry analysis.

The aim of this work is to offer an alternative or complementary analytical tool to the time consuming and expensive methods commonly used for the recognition of animal species according to their hairs. The paper introduces a simple and fast way for species differentiation of animal hairs called in-sample digestion. A total of 10 European animal species, including cat, cow, common degu, dog, fallow deer, goat, horse, sika deer, rabbit, roe deer, and 17 different breeds of dogs were examined using specific tryptic cleavage directly in hair followed by matrix-assisted laser desorption/ionization - time of flight mass spectrometry and liquid chromatography electrospray ionization quadrupole time of flight. Principal component analysis was used for the subsequent mass spectrometric data evaluation. This novel approach demonstrates the ability to distinguish among individual animal species, which is supported by finding characteristic m/z values obtained by the mass spectrometry for each animal species. The approach was successfully tested on two "blind" samples. On the other hand, the attempt to distinguish among hairs of different dog breeds has not been successful due to the very similar protein composition and their amino acid sequences. This article is protected by copyright. All rights reserved.

Animal Species Recognition with Deep Convolutional Neural Networks from Ecological Camera Trap Images.

Accurate identification of animal species is necessary to understand biodiversity richness, monitor endangered species, and study the impact of climate change on species distribution within a specific region. Camera traps represent a passive monitoring technique that generates millions of ecological images. The vast numbers of images drive automated ecological analysis as essential, given that manual assessment of large datasets is laborious, time-consuming, and expensive. Deep learning networks have been advanced in the last few years to solve object and species identification tasks in the computer vision domain, providing state-of-the-art results. In our work, we trained and tested machine learning models to classify three animal groups (snakes, lizards, and toads) from camera trap images. We experimented with two pretrained models, VGG16 and ResNet50, and a self-trained convolutional neural network (CNN-1) with varying CNN layers and augmentation parameters. For multiclassification, CNN-1 achieved 72% accuracy, whereas VGG16 reached 87%, and ResNet50 attained 86% accuracy. These results demonstrate that the transfer learning approach outperforms the self-trained model performance. The models showed promising results in identifying species, especially those with challenging body sizes and vegetation.

Animal Species Identification using Deep Learning

Bird identification is a difficult undertaking that frequently results in ambiguous labeling. Even skilled bird watchers dispute the species of a bird when presented with an image of one. It’s a demanding task that tests both people and computers’ visual talents. For example, for different scenarios, animals come with different sizes, forms, colors and from a human viewpoint with different angles. Indeed, the images show different differences that need to be recorded as image recognition of bird & snake species. It is also easier for people to identify animals in the pictures. Identification of animal species is a challenging task often resulting in ambiguous labels. Even professional Wildlife watchers sometimes disagree on the species given an image of animals.