Identify Plant Species Research Articles

Unsupervised leaf segmentation in complex backgrounds using mutual information minimization

Leaf segmentation is crucial for plant recognition, especially for tree species identification. In natural environments, leaf segmentation can be very challenging due to the lack of prior information about leaves and the variability of backgrounds. In typical applications, supervised algorithms often require pixel-level annotation of regions, which can be labour-intensive and limited to identifying plant species using pre-labelled samples. On the other hand, traditional unsupervised image segmentation algorithms require specialised parameter tuning for leaf images to achieve optimal results. Therefore, this paper proposes an unsupervised leaf segmentation method that combines mutual information with neural networks to better generalise to unknown samples and adapt to variations in leaf shape and appearance to distinguish and identify different tree species. First, a model combining a Variational Autoencoder (VAE) and a segmentation network is used as a pre-segmenter to obtain dynamic masks. Secondly, the dynamic masks are combined with the segmentation masks generated by the mask generator module to construct the initial mask. Then, the patcher module uses the Mutual Information Minimum (MIM) loss as an optimisation objective to reconstruct independent regions based on this initial mask. The process of obtaining dynamic masks through pre-segmentation is unsupervised, and the entire experimental process does not involve any label information. The experimental method was performed on tree leaf images with a naturally complex background using the publicly available Pl@ntLeaves dataset. The results of the experiment showed that compared to existing excellent methods on this dataset, the IoU (Intersection over Union) index increased by 3.9%.

The first ITS2 sequence data set of eDNA from honey of Malaysian giant honeybees (Apis dorsata) and stingless bees (Heterotrigona itama) reveals plant species diversity

ObjectivesPollen is a useful tool for identifying the provenance and complex ecosystems surrounding honey production in Malaysian forests. As native key pollinators in Malaysia, Apis dorsata and Heterotrigona itama forage on various plant/pollen species to collect honey. This study aims to generate a dataset that uncovers the presence of these plant/pollen species and their relative abundance in the honey of A. dorsata and H. itama. The information gathered from this study can be used to determine the geographical and botanical origin and authenticity of the honey produced by these two species.ResultsSequence data were obtained for both A. dorsata and H. itama. The raw sequence data for A. dorsata was 5 Mb, which was assembled into 5 contigs with a size of 6,098,728 bp, an N50 of 15,534, and a GC average of 57.42. Similarly, the raw sequence data for H. itama was 6.3 Mb, which was assembled into 11 contigs with a size of 7,642,048 bp, an N50 of 17,180, and a GC average of 55.38. In the honey sample of A. dorsata, we identified five different plant/pollen species, with only one of the five species exhibiting a relative abundance of less than 1%. For H. itama, we identified seven different plant/pollen species, with only three of the species exhibiting a relative abundance of less than 1%. All of the identified plant species were native to Peninsular Malaysia, especially the East Coast area of Terengganu.Data descriptionOur data offers valuable insights into honey’s geographical and botanical origin and authenticity. Metagenomic studies could help identify the plant species that honeybees forage and provide preliminary data for researchers studying the biological development of A. dorsata and H. itama. The identification of various flowers from the eDNA of honey that are known for their medicinal properties could aid in regional honey with accurate product origin labeling, which is crucial for guaranteeing product authenticity to consumers.

Remediation Opportunities for Arsenic-Contaminated Gold Mine Waste

Arsenic (As)-contaminated gold mine waste is a global problem and poses a significant risk to the ecosystem and community (e.g., carcinogenic, toxicity). Arsenic concentrations of 77,000 mg/kg and 22,000 mg/kg in mine waste have been reported for Canada and Australia, respectively. Research is investigating environmentally sustainable techniques to remediate As-rich mine waste. Biological techniques involving plants (phytoremediation) and soil amendments have been studied to bioaccumulate As from soil (phytoextraction) or stabilise As in the rhizosphere (phytostabilisation). Identified plant species for phytoremediation are predominately fern species, which are problematic for arid to semi-arid climates, typical of gold mining areas. There is a need to identify native plant species that are compatible with arid to semi-arid climates. Arsenic is toxic to plants; therefore, it is vital to assess soil amendments and their ability to reduce toxicity, enhance plant growth, and improve soil conditions. The effectiveness of a soil-amending phytoremediation technique is dependent on soil properties, geochemical background, and As concentrations/speciation; hence, it is vital to use field soil. There is a lack of studies involving mine waste soil collected from the field. Future research is needed to design soil-amending phytoremediation techniques with site-specific mine waste soil and native plant species.

IDENTIFICATION AND CHARACTERIZATION OF FEED PLANTS FOR Apis dorsata Binghami IN THE PINABETENGAN FOREST, MINAHASA

Apis Dorsata Binghami is a honey bee that is often found in the forest, which is conserved by the community, but there are also honey bees that are just left alone; the community preserves these honey bees because their honey can be traded and can also be used as medicine. This study aims to determine the plants that are a feed source for Apis Dorsata Binghami in the Pinabetengan Forest, Minahasa Regency. This research was conducted in June-August 2022. The data collected came from field survey data using descriptive methods and identified plant species with values of Reactive Density (KR), Relative Frequency (FR), Relative Dominance (DR), and Index Significant Value (INP). Plant diversity as a food source for Apis Dorsata Binghami has different types of plants based on their habitus or the characteristics of the plants themselves.

Analysis of Safety Concerns on Herbal Products with Assumed Phytoestrogenic Activity.

Phytoestrogens (PEs) are plant-based compounds that can interact with estrogen receptors and are mainly used to treat menopausal complaints. However, the safety of products with assumed phytoestrogenic activity is not fully understood. This study aimed to identify plant species with assumed phytoestrogenic activity, review existing literature on their use and safety, and critically evaluate adverse reaction (AR) reports of single-herb, multi-herb, and mixed-multiple products, as submitted to the Netherlands Pharmacovigilance Centre Lareb and to VigiBase of the World Health Organization (WHO). In the Lareb database, the most commonly reported plant species to cause ARs (total of 67 reports) were Actaea racemosa L. (black cohosh) (47.8%), Humulus lupulus L. (hops) (32.8%), and Glycine max (L.) Merr. (soybean) (22.4%). In the VigiBase database (total of 21,944 reports), the top three consisted of Glycine max (L.) Merr. (71.4%), Actaea racemosa L. (11.6%), and Vitex agnus-castus L. (chaste tree) (6.4%). In the scoping review (total of 73 articles), Actaea racemosa L. (30.1%), Glycine max (L.) Merr. (28.8%), and Trifolium pratense L. (13.7%) were the most frequently mentioned plant species. ARs were most frequently reported in the system organ classes "gastrointestinal disorders", "skin and subcutaneous tissue disorders", "reproductive system and breast disorders", and "general disorders and administration site conditions". Furthermore, from the scoping review, it appeared that the use of products with assumed phytoestrogenic activity was associated with postmenopausal bleeding. It was concluded that, while the potential benefits of products with assumed phytoestrogenic activity have been extensively pursued, the potential occurrence of ARs after using these products is less well understood. This study highlights the need for further investigation and careful monitoring of these products to better understand their effects and ensure the safety and well-being of individuals using them.

Investigating the efficiency and capabilities of UAVs and Convolutional Neural Networks in the field of remote sensing as a land classification tool

The study aimed to determine the efficacy and capabilities of using high-resolution aerial imagery and a convolutional neural network (CNN) to identify plant species and monitor land cover and land change in the context of remote sensing. The full capabilities of a CNN were examined, including testing whether the platform could be used for land cover and the evaluation of land change over time. An unmanned aerial vehicle (UAV) was used to collect the aerial data of the study area. The CNN was encoded and operated in RStudio, while digitised data from the input imagery were used by the programme as training and validation data. The object in this respect was to learn about the relevant features of the landscape, and thereafter to classify the Opuntia invasive plant species. Accuracy assessments were carried out on the results to test the efficacy of the aerial imagery in terms of its accuracy and reliability. The classification achieved an overall accuracy of 93%, while the kappa coefficient score was 0.86. CNN was also able to predict the land coverage area of Opuntia to be within four percent (4%) of the ground truthing data. A change in land cover over time was detected by the programme after the manual clearing of the plant had been undertaken. This research has determined that the use of a CNN in remote sensing is a very powerful tool for supervised image classifications. It can be used for monitoring land cover in that it is able to accurately estimate the spatial distribution of plant species and to monitor the growth or decline in the species over time. As such, it is an efficient methodology and its use in remote sensing could be extended.

Inventory of Medicinal Plants in West Sumatra Province that has the Potential to Treat Diabetes Mellitus

This study aims to identify plant species with potential anti-diabetic properties. From March to June 2022, this research was conducted in West Sumatera, Indonesia, in 5 regencies, 56 villages, and through interviews with 179 community leaders. This survey and interview study is descriptive in nature. The findings revealed that there were 44 species belonging to 33 families. Leaves, seeds, bark, tubers, rhizomes, stems, fruit skins, and other plant components are utilized. Medicinal herbs are processed by boiling, squeezing, pounding, and drying. Various local wild and cultivated plants have the potential to be used as medicinal plants, particularly DM medicines.

Floristic Survey of Deedwana Tehsil, District Nagaur, Rajasthan

Abstract: The present research paper presents a comprehensive floristic study of Deedwana Tehsil, District Nagaur, Rajasthan, aimed at documenting the plant diversity and understanding its ecological significance. The study involved extensive field surveys, specimen collections, and interviews with local experts to identify and classify the plant species within the region. The results revealed a diverse and unique assemblage of plant species in Deedwana Tehsil, representing various vegetation types and habitats. The enumeration of identified plant species showcased a rich floral diversity, including both native and exotic species. A total of 331 species of angiospermic plants belonging to 218 genera and 65 families were recorded including four series of natural vegetation in Deedwana tehsil: 1. Acacia nilotica-Maytenus emarginata-Balanites aegyptiaca series 2. Prosopis cineraria-Crotalaria burhia-Leptadaenia pyrotechnica series. 3. Prosopis cineraria- Capparis decidua-Tephrosia purpuria series and 4. Suaeda fruticosa-Cressa cretica–Heliotropium curassavicum series. (Quereishi, 2018). The study also provide information about the traditional uses of plants by local communities, providing insights into their cultural significance and medicinal applications. Traditional knowledge holders and local healers shared valuable information about medicinal plant practices, adding to the understanding of the region's traditional healthcare systems. The study also analyzed the major threats faced by the flora of Deedwana Tehsil, such as habitat loss, overgrazing, climate change, and unsustainable resource extraction. These findings highlighted the urgent need for conservation and sustainable management initiatives to protect the region's botanical wealth

Identification of types, flowering of bee plants and honey production of Apis cerana in Aornakan I and Kutatinggi villages, Pakpak Bharat regency, North Sumatra

One of the influential factors in the success of beekeeping is the availability of bee feed. Beekeepers need to know the types of food sources for bees and have a map of the sources of nectar and pollen in their area. This will help in planning the management of their colony. This research was conducted to identify the types and flowering of bee feed plants (Apis cerana) and to determine honey production. In this study used exploratory survey methods and interviews. Based on the study's results, there were 17 identified types of bee feed sources from forestry plants, 13 identified plant species from crops and 6 identified plant species that produce flowers. The flowering schedule for honey bee feed plants in Pakpak Bharat Regency for Kaliandra plants blooms in February - July, for Durian plants blooms in March, April - October, and November for Coffee plants flowers in April and August. Honey production in Pakpak Bharat District has a different frequency of harvest and production each month. For April, 11 members produced 42 bottles of honey. For May, 10 members produced 55 bottles, where the size per bottle was 600 ml.

LEVERAGING MACHINE LEARNING AND REMOTE SENSING FOR WILDLIFE CONSERVATION: A COMPREHENSIVE REVIEW

In recent years, the application of machine learning and remote sensing technologies in wildlife conservation has demonstrated tremendous promise. This article provides a comprehensive overview of the advancements in these fields and the impact they have had on various aspects of wildlife conservation. These technologies contribute to more efficient and effective conservation strategies by automating species identification, mapping and monitoring habitats, tracking population dynamics, detecting wildlife crime, and analysing animal vocalisations. This article talks about the development of machine learning algorithms capable of classifying bird and amphibian calls, differentiating fish species, and identifying plant species such as orchids and cacti has made automated species identification possible. Incorporating machine learning algorithms with remote sensing techniquesprovides significant advantages for mapping and monitoring habitats. This article discusses that images captured by camera trapswhen combined with acoustic analysis, can help in monitoring population by enabling automated detection and tracking. These technologies provide efficient and non-invasive approaches to monitor and manage animal populations, from estimating animal density using passive acoustics to identifying and tracking endangered species such as tigers, cheetahs, and sea turtles using camera trap images. The analysis of animal vocalisations using machine learning techniques has revealed information about species behaviour, population dynamics, and habitat quality. Examining the acoustic communication of species such as black rhinoceros and Yangtze finless porpoise has been the focus of research. Acoustic analysis provides a non-invasive method for comprehending the communication patterns of animals and their implications for conservation efforts. By utilising artificial intelligence and remote sensing data, conservationists can make informed decisions and take targeted actions to protect and preserve endangered species and their habitats. These technologies continued development and application hold great promise for the future of wildlife conservation.

Inventarisasi Dan Identifikasi Jenis Tumbuhan Famili Asteraceae Di Kawasan Jawa Barat

The introduction of the Asteraceae family is actually known for its many types. There is a family of Asteraceae which has spread widely to reach 125 to 300 genera and has around 20,000 to 25,000 species that have spread all over the world. This research was conducted in May-June 2023. The purpose of conducting this research was to determine the inventory and identification of plant species in the Asteraceae family in the Province of West Java. As well as to determine the morphology, characteristics, and habitus of the Asteraceae family in the Province of West Java. The method used in this study was a direct survey, and a review of literature studies to obtain other data sources. Based on the results of the research conducted, there are seven plant species in the Asteraceae family in the Province of West Java. The seven species are Asterai, Tithonia diversifolia, Sphagneticola trilobata, Chrysanthemum indicum, Chrysanthemum grandiflorum, Chrysanthemum himbeerrot, Chrysanthemum. These existing species describe distinct morphologies. Each type of plant has different benefits. The conclusion obtained from this study is that the Asteraceae family has many existing species, so it is expected to be able to find various species that are also able to conduct an inventory and identify plant species of the Asteraceae family in the West Java Province area in an objective and relevant manner.

The Impact of Nitrogen on the Yield Formation of Artemisia dubia Wall: Efficiency and Assessment of Energy Parameters.

With the increasing importance of energy crops, research on potential energy crops is carried out to identify plant species with high productivity and energy value. The field experiment with the new promising energy crop, Artemisia dubia (wormwood), was executed at the Vėžaičiai Branch of the LAMMC. The soil site was naturally acidic Retisol (pH 4.2-4.4). The species was investigated as an energy crop through the evaluation of its biomass productivity and some energetical qualities. According to the three investigation years, DM yield significantly varied depending on the growing season, cutting time and nitrogen rate. The highest average DM yield was observed in 2020-10.58 t ha-1. On average, the DM yield varied from 6.49 t ha-1 (first cutting) to 11.82 t ha-1 (third cutting). The DM yield was positively correlated with stem height and the mass of one stem. Nitrogen use efficiency (NUE) depended on the growing season, cutting time and nitrogen rate. Both N90 and N180 rates should be used for A. dubia fertilization. Energy growing analysis (including direct and indirect expenses) revealed that the highest share of energy expenses are due to indirect energy expenses (particularly nitrogen application). EUE (energy utilization efficiency) tends to decrease as a result of increasing nitrogen fertilization. Overall, A. dubia granules are characterized by a high calorific value.

A new species in genus Abutilon (Malvaceae) from Pakistan

In this research paper, a newly identified plant species of the genus Abutilon Mill., namely Abutilon jafrii F. Naseer, A. Noor & A. Rahman, is described and illustrated for the first time in the province of Sindh, Detailed morphological descriptions of the species along with the micro-morphological examinations of scanning electron microscopy (SEM) for the mericarps, seeds and pollens are presented. Additionally, Macro morphological characteristics including photographs of the plant habit with flowers, fruits, seeds and mericarps are provided. Through gross macro-morphological and micro-morphological investigations such as plant height, leaves texture and colour, pedicel of fruits and flowers, flowers diameter, sepal’s size in flowers and fruits, number of seeds per mericarp, pollen tectum exhibit significant differences in characters, which indicate that, it is a distinct species. Bangladesh J. Plant Taxon. 30(1): 43-51, 2023 (June)

Browsing by non-native invasive sambar deer dramatically impacts forest structure

Large herbivores introduced to novel habitats can cause major ecosystem impacts. While impacts of overabundant deer have been documented around the world, there are few examples from Australia, where deer are non-native and natural predators are absent.Here, we outline the impacts of sambar deer in wet eucalypt forest understoreys of the Yarra Ranges National Park, south-eastern Australia. Using data obtained from a full and partial (permitting native herbivores) exclusion experiment over four years, we (i) demonstrate differences between native herbivore and introduced deer browsing, (ii) identify plant species commonly browsed by deer, and (iii) provide evidence that vegetation condition can recover in the absence of deer.While species richness and composition were unaffected, the exclusion of deer led to substantial recovery of several attributes of forest understorey vegetation. Treatments excluding deer (partial and full exclosures) saw increases in the cover of understorey trees, shrubs, ferns and climbers. Within the 1–2 m height class (the primary deer browse zone), vegetation cover-abundance increased 3–4 fold over time in full and partial exclusion plots compared to non-exclusion controls.Tree ferns (Dicksonia antarctica and Cyathea australis) were particularly impacted by deer, and browsing impacts to tree ferns were dramatically reduced from ∼50% of fronds browsed to negligible levels with deer exclusion. Deer exclusion also saw substantial reductions in browsing to individual trees, shrubs and ground ferns. The growth of commonly browsed trees, e.g. Pomaderris aspera, were demonstrably higher in partial and full exclosures than unfenced control plots. The low levels of browsing on trees and shrubs that persisted in partial exclosures probably indicates the background levels of browsing pressure attributable to native herbivores in these forests.In the absence of effective deer control, commonly browsed understorey trees, shrubs and tree ferns are likely to decrease substantially in cover over coming decades, potentially leading to increased light availability, drying of the understorey, and increased susceptibility to wildfire. The potential cascading ecological effects of unabated and increasing deer impacts may be substantial and pose major challenges to forest management.Despite management culls and recreational hunting in recent years, deer populations are increasing across Australia. As sambar populations increase, ecological impacts are likely to exacerbate. It is therefore critically important to reduce sambar numbers, before negative and potentially irreversible changes occur to forest structure, composition and function.

Scientific and traditional knowledge meet: diet of the lowland tapir Tapirus terrestris in the Orinoquia region of Colombia

The lowland tapir Tapirus terrestris is the second largest mammal in South America. It occupies a wide variety of ecosystems where it fulfills key functional roles. It is mainly folivorous, supplementing its diet with fruits, insects, and aquatic invertebrates. The lowland tapir is considered fundamental in shaping forest undergrowth and in seed dispersal processes. Despite its functional importance, ecological aspects related to diet, habitat use, and food preferences are still unknown in much of its geographic range. Currently, these aspects in the Colombian Orinoquia are unknown. We wanted to develop an approximation to the diet of the lowland tapir in the Colombian Orinoquia based on analysis of fecal samples and traditional knowledge derived from citizen science monitoring. Fecal samples were collected between October 2015 and July 2018 and vegetation monitoring and interviews with local communities were implemented. We recorded a total of 37 species of plants, 23 species of which were determined through traditional knowledge. The most representative species in fecal samples were Rudgea crassiloba, Attalea butyracea, Inga alba and Cecropia peltata. The plants most commonly recognized by local communities were Mauritia flexuosa, A. butyracea, Bellucia grossularioides and I. alba. Our results provide insight into the importance of tapirs in the consumption of large seeds such as M. flexuosa and A. butyracea that are considered of economic relevance for local communities. Incorporating citizen science monitoring allowed us to identify plant species that are taxonomically difficult to distinguish and to evaluate new information related to the natural history of cryptic species such as tapirs. This information is crucial to establish conservation strategies for the lowland tapir in the Orinoquia region of Colombia.

Investigating the use of pollen DNA metabarcoding to quantify bee foraging and effects of threshold selection.

DNA metabarcoding of pollen is a useful tool for studying bee foraging ecology. However, several questions about this method remain unresolved, including the extent to which sequence read data is quantitative, which type of sequence count removal threshold to use and how that choice affects our ability to detect rare flower visits, and how sequence artefacts may confound conclusions about bee foraging behavior. To address these questions, we isolated pollen from five plant species and created treatments comprised of pollen from each species alone and combinations of pollen from multiple species that varied in richness and evenness. We used ITS2 and rbcL metabarcoding to identify plant species in the samples, compared the proportion of pollen by mass to the proportion of sequencing reads for each plant species in each treatment, and analyzed the sequencing data using both liberal and conservative thresholds. We collected pollen from foraging bees, analyzed metabarcoding data from those samples using each threshold, and compared the differences in the pollinator networks constructed from the data. Regardless of the threshold used, the relationship between the proportion of pollen by mass and sequencing reads was inconsistent, suggesting that the number of sequence reads is a poor proxy for pollen abundance in mixed-species samples. Using a liberal threshold resulted in greater detection of original plant species in mixtures but also detected additional species in mixtures and single-species samples. The conservative threshold reduced the number of additional plant species detected, but several species in mixtures were not detected above the threshold, resulting in false negatives. Pollinator networks produced using the two thresholds differed and illustrated tradeoffs between detection of rare species and estimation of network complexity. Threshold selection can have a major effect on conclusions drawn from studies using metabarcoding of bee pollen to study plant-pollinator interactions.

The Development of Plants Booklet in Cilongok District, Banyumas Regency as a Learning Supplement for Classification of Living Things for Junior High Schools

During the Covid-19 pandemic, learning at SMP Negeri 2 Cilongok was carried out online. Material for classification of living things is science learning material for class VII in the 2013 curriculum. The teaching materials used in the form of textbooks and Student Worksheets (LKS) are not able to help students understand the material and study independently because they have not utilized plants in the surrounding environment. The types of plants in Cilongok District, Banyumas Regency have the potential as a source of learning, but the use of plants as a source of learning directly requires a longer time. Therefore a learning supplement is developed that is easy to understand and easy for students to use for independent study, namely the Plants Booklet in Cilongok District, Banyumas Regency which contains pictures and descriptions. The research aims to identify plant species in Cilongok District, Banyumas Regency, to analyze the validity and readability of booklets as learning supplements. The method used is Research and Development (R&D) research. The booklet product trial was carried out at Cilongok 2 Public Middle School involving class VII F students and science teachers. Based on the results of the identification of plant species in Cilongok District, Banyumas Regency, 60 species were found that were relevant to be used as learning resources in Plantae material. The results of material and media validation in the booklet showed very good results with a percentage of material validation of 81.3% and media validation of 96.5%. The booklet readability test showed a high category with an average percentage of 83.3%. Based on the results of the study it can be concluded that the Plant Booklet in Cilongok District, Banyumas Regency was stated to be valid and easily understood by students to be used as a supplement to learning material on the classification of living things.

Hyperparameter-tuned batch-updated stochastic gradient descent: Plant species identification by using hybrid deep learning

The accurate identification of plant species is crucial for the conservation of biodiversity. However, traditional methods for identifying plant species are often complicated, time-consuming, and prone to errors. Therefore, it is essential to address these challenges and develop automated identification methods to enhance the efficiency and accuracy of plant species identification. In this study, a step-by-step method was utilized to identify and classify plant species. The dataset was first loaded, and then preprocessing was performed to remove noisy data. Following that, data augmentation was carried out to improve model accuracy. The deep convolutional neural network (CNN) and visual geometry group-16 (VGG-16) were then employed to extract only the relevant features, owing to their efficient learning capabilities. Feature-level fusion was accomplished by utilizing dimensionality reduction, and enhanced Spearman's principal component analysis (ESPCA) was employed to address the overfitting problem, eliminate redundant data, and reduce storage space and training time requirements. For classification, the hyperparameter-tuned batch-updated stochastic gradient descent (HP-BSGD) method was utilized. The Flavia and Swedish datasets were utilized in the experiments. The proposed hybrid classifier yielded excellent results due to its high convergence speed, good computational effectiveness, and high flexibility. To validate the experimental results, performance and comparative analyses were carried out using standard metrics. The analytical results demonstrated the superior efficiency and suitability of the proposed method in the classification of plant species over existing methods. The hybrid method achieved approximately 97% and 98.85% accuracy in the Flavia and Swedish datasets, respectively, when considering combined features. The performance of the proposed method was further enhanced by considering leaves at different stages, such as seedlings, tiny, mature, and dried leaves.

Molecular phylogenetic analysis of Tulipa (Liliaceae) from Aksu-Zhabagly Nature Reserve

Barcodes are conserved sequences of genomic, plastid and mitochondrial DNA that can be utilized to uniquely identify an unidentified specimen to its species when conventional identification methods are inapplicable. Among prokaryotic and eukaryotic species, nuclear ribosomal internal transcribed spacer (ITS) sections are one of the most often utilized DNA markers in DNA barcoding and phylogenetic research. In addition to the ribosomal genes, the plastid genes are the most suitable for identifying plant species. The Aksu-Zhabagly Nature Reserve is the oldest nature reserve in Central Asia and is home to 1,312 vascular plant species, 44 of which are categorized as threatened or endangered in Kazakhstan's red data book. In this study, a collection of specimens of uncommon tulip species was compiled, along with their morphological identification and DNA barcoding. The ITS region and parts of the matK and ycf1b genes of tulip plastid DNA were sequenced. The evolutionary link between species of tulips was investigated. Phylogenetic study predicted two Tulipa subclades. Tulipa species have substantially preserved MatK genes. Tulips' ycf1b gene has evolved more slowly than other Liliaceae family members. Nuclear and plastid DNA sequences investigated Tulipa species evolutionary relationships. The findings about the ITS region of nuclear DNA were more definite. Overall, our work shows that genetic data will be important in determining species concepts in this genus, however, even with a molecular perspective pulling apart closely related taxa can be extremely challenging.

Oil Palm Plantation and Plant Species Diversity in Kolaka District, Indonesia

Knowledge of the types of plant species in the world continues to progress even though there are still many plant species whose types and benefits are not yet known. These plant species concentrate in an area both in residential areas, pastures, agricultural land, and plantation land. The research aims to identify plant species in mature oil palm plantation areas in Kolaka Regency by selecting Watubangga and Tanggetada subdistricts as survey locations and has been carried out from January to August 2022 by dividing the mature oil palm area into 3 villages in each subdistrict as research samples. The results of the survey and identification were analyzed using the summed dominance ratio formula to determine the level of dominance of plant species in controlling growth facilities. The findings of plant species in mature oil palm plantation areas in Watubangga Subdistrict, Polenga Village (highest-Cyperus rotundus L. 3.0738%, lowest-Solanum torvum Sw. 1.8637%), Kastura Village (highest-Brachiaria miliformis 4.1470%, lowest-Euphorbia hirta L 1.5057%), Kukutio Village (highest-Pennisetum purpureum Schumach 3.8447%, lowest-Chromolaena odorata (L.) King. 1.6317%). Tanggetada Subdistrict, Pundaipa Village (highest-Asystasia coromandeliana Ness 3.8541%, lowest-Cyrtococcum acrescens 1.4968%), Tinggo Village (highest-Imperata cylindrica (L.) P. Beauv. 4.9256%, lowest-Chromolaena odorata (L.) King 1.6079%), Oneeha Village (highest-Pennisetum purpureum Schumach, 3.8447%, lowest-Chromolaena odorata (L.) King. 1.6317%). This finding can be concluded that each area of mature oil palm plantations has several different and varied plant species and there are invasive plants that can eliminate native plants such as Chromolaena odorata (L.) King. and Imperata cylindrica (L.) P. Beauv.