Morphological Methods Research Articles

A Novel Anatomical Approach to Complement Morphological and Ecological Methods for the Identification of Some Important Coastal Graminoids

A Novel Anatomical Approach to Complement Morphological and Ecological Methods for the Identification of Some Important Coastal Graminoids

Cuticular chemical compounds of puparial cases of three forensically important blow flies from Egypt: potential for accurate identification and forensic investigations

AbstractThe distinct and species-specific chemical compounds found on the insect cuticle have demonstrated effectiveness in various applications, including species identification. Accurate identification of fly species becomes challenging when only damaged empty puparial cases are available, making it difficult to use traditional morphological and molecular identification methods. This study aimed to analyze the chemical compositions of puparial exuviae from three forensically and medically important fly species; Lucilia sericata, Chrysomya albiceps, and Chrysomya marginalis. Gas chromatography/mass spectrometry (GC–MS) was employed to assess the chemical profiles of these exuviae and evaluate their accuracy in identifying Dipteran insects. The study revealed the presence of twelve classes of chemical compounds across the three species, with retention times ranging from 18.78 to 35.03. A total of forty-two compounds with chain lengths ranging from C12 to C45 were identified. The profiles of Ch. albiceps and L. sericata displayed similarities, with alcohol being the most abundant compound (28.6%) in L. sericata. However, alkanes, including n-alkanes, branched alkanes, and cycloalkanes, constituted the main components of the cuticles in the three species, with Ch. marginalis displaying the highest percentage. These findings represent an initial step towards utilizing hydrocarbon composition as a practical tool for distinguishing between forensic species in Egypt.

First detection of Candidatus Rickettsia tarasevichiae in Hyalomma marginatum ticks.

Ticks are important vectors of zoonotic diseases and play a major role in the circulation and transmission of many rickettsial species. The aim of this study was to investigate the carriage of Candidatus Rickettsia tarasevichiae (CRT) in a total of 1168 ticks collected in Inner Mongolia to elucidate the potential public health risk of this pathogen, provide a basis for infectious disease prevention, control and prediction and contribute diagnostic ideas for clinical diseases that present with fever in populations exposed to ticks. A total of four tick species, Haemaphysalis concinna (n = 21), Dermacentor nuttalli (n = 122), Hyalomma marginatum (n = 148), and Ixodes persulcatus (n = 877), were collected at nine sampling sites in Inner Mongolia, China, and identified by morphological and molecular biological methods. Reverse transcription PCR targeting the 16S ribosomal RNA (rrs), gltA, groEL, ompB and Sca4 genes was used to detect CRT DNA. Sequencing was used for pathogen species confirmation. The molecular epidemiological analysis showed that three species of ticks were infected with CRT, and the overall positive rate was as high as 42%. The positive rate of I. persulcatus collected in Hinggan League city was up to 96%, and that of I. persulcatus collected in Hulun Buir city was 50%. The pool positive rates of D. nuttalli and H. marginatum collected in Bayan Nur city and H. concinna collected in Hulun Buir city were 0%, 28% and 40%, respectively. This study revealed the high prevalence of CRT infection in ticks from Inner Mongolia and the first confirmation of CRT detected in H. marginatum in China. The wide host range and high infection rate in Inner Mongolia may dramatically increase the exposure of CRT to humans and other vertebrates. The role of H. marginatum in the transmission of rickettsiosis and its potential risk to public health should be further considered.

Detection and characterization of micro-organisms linked to unsealed drugs sold in Ihiagwa community, Owerri, Imo State, Nigeria.

The contamination of pharmaceutical products by micro-organisms poses a significant risk to public health. This study was conducted to detect and characterize micro-organisms associated with unsealed drugs sold in Ihiagwa community in Owerri, Imo State, Nigeria. A variety of microbiological techniques were employed to analyse samples from unsealed drug containers. The identification process involved morphological, biochemical and sugar utilization methods, aiding in the accurate determination of microbial species. Microbial contamination was observed in 42 (84 %) out of 50 samples, with contaminants including bacteria and fungi. The range of contamination is between 1.2±0.01×103 and 2.3±0.02×103 c.f.u. ml-1 for viable count, 0.1±0.02×102 and 0.3±0.01×102 c.f.u. g-1 for coliform count and 0.2±0.01×101 and 0.5±0.01×101 c.f.u. g-1 for fungi count. The identified microbes were Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Candida albicans and Aspergillus niger. The most common bacterial isolate was S. aureus (51.8 %), while C. albicans (73.3 %) was the most prevalent fungus. Among the pharmacies and healthcare facilities examined, the Uchems pharmacy had the highest proportion of bacterial isolates (37 %), followed by the Stepwise pharmacy (22.2 %), while the lowest proportion was found at the Roseline Health Clinic (7.4 %). The identification of potentially harmful micro-organisms in these unsealed drug container samples emphasizes the importance of stringent quality control measures and improved handling, storage and packaging practices to ensure product safety and efficacy, especially among pharmacetical dealers.

Classification of cotton water stress using convolutional neural networks and UAV-based RGB imagery

<p>Embracing smart irrigation management techniques empowers growers to irrigate with greater efficiency, thereby promoting sustainable agricultural production. In this context, growers often rely on crop evapotranspiration (ETc) as a key factor in making informed irrigation decisions, underscoring the significance of accurately determining and spatially mapping crop water status. Technological progress, exemplified by the emergence of unmanned aerial vehicles (UAVs), has brought about a revolutionary shift in agricultural monitoring. UAV platforms can capture high-resolution images with centimeter-level spatial accuracy and offer higher temporal coverage compared to satellite imagery. Considering these advancements, this study introduces a robust method for classifying water stress in cotton using a compact UAV platform and convolutional neural networks (CNN). The experiment was conducted at the USDA-ARS Cropping Systems Research Laboratory (CSRL) in Lubbock, Texas, where the cotton field was divided into 12 drip zones. The study included three replications to evaluate four irrigation treatments: “rainfed”, “full irrigation”, “percent deficit of full irrigation”, and “time delay of full irrigation”. The results demonstrated that the CNN model successfully classified the cotton water stress using the UAV-based RGB image, achieving an overall best prediction accuracy of approximately 91%. By segmenting the original cotton images into separate canopy and soil areas using morphological image processing methods, the authors also isolated and analyzed the individual contributions of these components to cotton water stress. Additionally, a random forest classifier revealed the relative importance of different image features in the classification process through feature importance analysis. These findings highlighted the state-of-the-art performance of the proposed system in cotton water stress classification and provided valuable insights into the key image features contributing to accurate classification. The authors concluded that integrating UAV-based RGB imagery and CNN models had great potential for assessing water stress in cotton.<strong></strong></p>

Classification of cotton water stress using convolutional neural networks and UAV-based RGB imagery

<p>Embracing smart irrigation management techniques empowers growers to irrigate with greater efficiency, thereby promoting sustainable agricultural production. In this context, growers often rely on crop evapotranspiration (ETc) as a key factor in making informed irrigation decisions, underscoring the significance of accurately determining and spatially mapping crop water status. Technological progress, exemplified by the emergence of unmanned aerial vehicles (UAVs), has brought about a revolutionary shift in agricultural monitoring. UAV platforms can capture high-resolution images with centimeter-level spatial accuracy and offer higher temporal coverage compared to satellite imagery. Considering these advancements, this study introduces a robust method for classifying water stress in cotton using a compact UAV platform and convolutional neural networks (CNN). The experiment was conducted at the USDA-ARS Cropping Systems Research Laboratory (CSRL) in Lubbock, Texas, where the cotton field was divided into 12 drip zones. The study included three replications to evaluate four irrigation treatments: “rainfed”, “full irrigation”, “percent deficit of full irrigation”, and “time delay of full irrigation”. The results demonstrated that the CNN model successfully classified the cotton water stress using the UAV-based RGB image, achieving an overall best prediction accuracy of approximately 91%. By segmenting the original cotton images into separate canopy and soil areas using morphological image processing methods, the authors also isolated and analyzed the individual contributions of these components to cotton water stress. Additionally, a random forest classifier revealed the relative importance of different image features in the classification process through feature importance analysis. These findings highlighted the state-of-the-art performance of the proposed system in cotton water stress classification and provided valuable insights into the key image features contributing to accurate classification. The authors concluded that integrating UAV-based RGB imagery and CNN models had great potential for assessing water stress in cotton.<strong></strong></p>

©Relationship between endophytic fungal diversity and colonization and soil factors of cultured blueberry roots in Guizhou Province, Southwest China.

Dark septate endophytes (DSEs) inhabit plant roots and soil in ecosystems and host plants worldwide. DSE colonization is influenced by cultivars, soil factors, and specific habitat conditions. The regular diversity of DSEs in blueberries in Guizhou, China, is still unclear. In this study, four cultivars (Gardenblue, Powderblue, O'Neal, and Legacy) in three areas (Gaopo, Majiang, and Fenggang) in Guizhou were used to identify DSEs by morphological and molecular biological methods and to clarify the relationship between DSE diversity and DSE colonization and soil factors of cultivated blueberries in Guizhou. The DSEs isolated from cultivated blueberry roots in 3 areas in Guizhou Province were different, belonging to 17 genera, and the dominant genera were Penicillium, Phialocephala, and Thozetella. DSEs isolated from Majiang belonged to 12 genera and 16 species, those from Gaopo belonged to 7 genera and 15 species, and those from Fenggang belonged to 5 genera and 7 species. Among the different blueberry varieties, 11 genera were isolated from O'Neal, 12 genera were isolated from Powderblue, 11 genera were isolated from Legacy and 13 genera were isolated from Gardenblue. Coniochaeta is endemic to O'Neal, Chaetomium and Curvularia are endemic to Powderblue, and Thielavia is endemic to Legacy. Correlation analysis showed that DSE diversity was significantly correlated with DSE colonization and soil factors.

Screening of Antagonistic Bacillus against Brown Rot in Dendrocalamus latiflorus and Preparation of Applying Bacterial Suspension.

The aim of this study was to isolate biocontrol bacteria that could antagonize brown rot of Dendrocalamus latiflorus, optimize the culture conditions, and develop an effective biocontrol preparation for brown rot of D. latiflorus. This study isolated a bacterium with an antagonistic effect on bamboo brown rot from healthy D. latiflorus rhizosphere soil. Morphology, molecular biology, and physiological biochemistry methods identified it as Bacillus siamensis. The following culturing media and conditions improved the inhibition effect of B. siamensis: the best culturing media were 2% sucrose, 1.5% yeast extract, and 0.7% potassium chloride; the optimal culturing time, temperature, pH, and inoculation amount were 48 h, 30℃, 6, and 20%. The optimum formula of the applying bacterial suspension was 14% sodium dodecyl benzene sulfonate emulsifier, 4% Na2HPO4·2H2O, 0.3% hydroxypropyl methylcellulose thickener, and 20% B. siamensis. The pot experiment results showed the control effect of applying bacterial suspension, diluted 1,000 times is still better than that of 24% fenbuconazole suspension. The applying bacterial suspension enables reliable control of brown rot in D. latiflorus.

Comparative study of spectral sensitivity, irradiance sensitivity, spatial resolution and temporal resolution in the visual systems of Ocypode quadrata and Aratus pisonii.

Early pioneering studies by Autrum on terrestrial arthropods first revealed that the visual systems of arthropods reflected their lifestyles and habitats. Subsequent studies have examined and confirmed Autrum's hypothesis that visual adaptions are driven by predator-prey interactions and activity cycles, with rapidly moving predatory diurnal species generally possessing better temporal resolution than slower moving nocturnal species. However, few studies have compared the vision between diurnal herbivores and nocturnal predators. In this study, the visual physiology of a nocturnal fast-moving predatory crab, the Atlantic ghost crab (Ocypode quadrata) and a diurnal herbivorous crab, the mangrove tree crab (Aratus pisonii), was examined. Spectral sensitivity, irradiance sensitivity and temporal resolution of the crabs were quantified using the electroretinogram (ERG), while the spatial resolution was calculated utilizing morphological methods. Both O. quadrata and A. pisonii had a single dark-adapted spectral sensitivity peak (494 and 499 nm, respectively) and chromatic adaptation had no effect on their spectral sensitivity, indicating that both species have monochromatic visual systems. The temporal resolution of O. quadrata was not significantly different from that of A. pisonii, but O. quadrata did possess a significantly greater spatial resolution and irradiance sensitivity. Both species possess an acute zone in the anterior region of their eyes. The data presented in this study will aid in the current understanding of the correlation between visual physiology and the life history of the animal.

Dual channel and multi-scale adaptive morphological methods for infrared small targets

Infrared small target detection is a challenging task. Morphological operators with a single structural element size are easily affected by complex background noise, and the detection performance is easily affected by multi-scale background noise environments. In order to enhance the detection performance of infrared small targets, we propose a dual channel and multi-scale adaptive morphological method (DMAM), which consists of three stages. Stages 1 and 2 are mainly used to suppress background noise, while stage 3 is mainly used to enhance the small target area. The multi-scale adaptive morphological operator is used to enhance the algorithm’s adaptability to complex background environments, and in order to further eliminate background noise, we have set up a dual channel module. The experimental results indicate that this method has shown superiority in both quantitative and qualitative aspects in comparison methods, and the effectiveness of each stage and module has been demonstrated in ablation experiments. The code and data of the paper are placed in https://pan.baidu.com/s/19psdwJoh-0MpPD41g6N_rw.

Organogel as Drug Delivery System: Review

Background: Gels are employed as a carrier medium/network for the delivery of topical medicines. Due to number of benefits gels are gaining attention day by day as a drug delivery system. Among gels Organogelare preferably active for incorporating lipophilic and hydrophilic drugs within the same gel network. Aim: To emphasize about the basics of Organogel. Their introduction types, composition, properties, methods of preparation and advantages and applications and most importantly as topical drug delivery system. Definition: The Organogel comes under the semi solid preparations with a definition of having two phases,one of which is organic liquid which gets immobilized by the other, that is an organogelators. Composition: Organogel are, “mixture of lipophilic liquid and solid lipid, in which solid lipid having concentrations (<10%) can entangle bulk liquid oil by formingthreedimensionalnetwork by the physical interaction of self-assembled organogelatorsin the bulk oil”2. Properties: Generally Organogel are thermodynamically stable system, viscoelastic, biphasic system, no irritating, have low degree of hydration in comparison to hydrogels. Exhibit morphological and rheological properties Method of Preparation: Solid fiber Matrix and fluid filled matrix are most common methods adopted for Organogel preparations. Characterization: viscoelasticity, pH, Firmness, In vitro drug, release, stability, phase transition, and structural features,Invitro release, skin permeability were discussed along with different factors that affectOrganogel. Applications: Organogel are used for both oral and topical delivery of number of drugs. They are used for local as well as are capable of systemic percutaneous absorption due to their lipophilic nature and penetration potentiates by the presence of penetration enhancer3. Keywords: Organogels, Organogelator, Solvents, Drug delivery system

Molecular characterization of biosurfactant-producing bacteria from a crude oil polluted soil in Nigeria

Most biosurfactant-producing microorganisms are hydrocarbon degraders. The research was conducted to isolate and characterize biosurfactant-producing bacteria from a crude oil polluted soil in Nigeria. Biosurfactant-producing bacteria were isolated from crude oil-polluted soil. Crude oil-polluted soil was collected by random sampling and its physicochemical analysis was done. Bacteria were isolated from the contaminated soil and screened for biosurfactant production. Organisms that showed the ability to produce biosurfactant were identified using morphological, biochemical and molecular methods. The physicochemical parameters of the soil showed a pH 6.9, electrical conductivity of 71.5, 2.55% carbon, 2.016% nitrogen and 5.98% phosphorus. The values of biosurfactant tests showed that organisms S2 and S13 were positive for biosurfactant production. The percentage emulsion indexes of the two selected organisms S2 and S13 were 59.09% and 57.14% respectively. The Blast analysis from the molecular identification showed that the isolated organisms were Gordonia alkanivorans for S2 and Tsukamurella inochensis for S13. This research showed that the isolated biosurfactant-producing bacteria are abundant in the crude oil polluted soil.

Permeability prediction of porous aerostatic bearings through 3D morphology and fractal calculation method

AbstractPorous ceramics for aerostatic bearing restrictors were fabricated using carboxymethyl cellulose and polystyrene microspheres as pore formers. The three‐dimensional morphology of the porous ceramics was nondestructively obtained using laser scanning confocal microscopy, and the processing information was eliminated by fitting the pore area fractal dimensions at different heights. A mathematical model was developed based on the assumption of elliptical tortuous capillaries to relate microstructural pore parameters to permeability by combining fractal theory, Darcy's law, and the gas conservation equation. The calculated permeability closely matched the experimental results, with an error of less than 3.5%. This method has promising potential as an alternative to pressure drop experiments. Moreover, the capacity of the fractal calculation model to establish a correlation between microstructural parameters and permeability paves a new way to design future porous aerostatic bearings.

Automatic dental age calculation from panoramic radiographs using deep learning: a two-stage approach with object detection and image classification

BackgroundDental age is crucial for treatment planning in pediatric and orthodontic dentistry. Dental age calculation methods can be categorized into morphological, biochemical, and radiological methods. Radiological methods are commonly used because they are non-invasive and reproducible. When radiographs are available, dental age can be calculated by evaluating the developmental stage of permanent teeth and converting it into an estimated age using a table, or by measuring the length between some landmarks such as the tooth, root, or pulp, and substituting them into regression formulas. However, these methods heavily depend on manual time-consuming processes. In this study, we proposed a novel and completely automatic dental age calculation method using panoramic radiographs and deep learning techniques.MethodsOverall, 8,023 panoramic radiographs were used as training data for Scaled-YOLOv4 to detect dental germs and mean average precision were evaluated. In total, 18,485 single-root and 16,313 multi-root dental germ images were used as training data for EfficientNetV2 M to classify the developmental stages of detected dental germs and Top-3 accuracy was evaluated since the adjacent stages of the dental germ looks similar and the many variations of the morphological structure can be observed between developmental stages. Scaled-YOLOv4 and EfficientNetV2 M were trained using cross-validation. We evaluated a single selection, a weighted average, and an expected value to convert the probability of developmental stage classification to dental age. One hundred and fifty-seven panoramic radiographs were used to compare automatic and manual human experts’ dental age calculations.ResultsDental germ detection was achieved with a mean average precision of 98.26% and dental germ classifiers for single and multi-root were achieved with a Top-3 accuracy of 98.46% and 98.36%, respectively. The mean absolute errors between the automatic and manual dental age calculations using single selection, weighted average, and expected value were 0.274, 0.261, and 0.396, respectively. The weighted average was better than the other methods and was accurate by less than one developmental stage error.ConclusionOur study demonstrates the feasibility of automatic dental age calculation using panoramic radiographs and a two-stage deep learning approach with a clinically acceptable level of accuracy.

ANOMALIES IN LANGUAGES WITH DIFFERENT SYSTEMS

In the article, the grammatical anomalies of languages with different systems are widely discussed. It is considered relevant for linguistics to shed light on many controversial issues for the investigation of existing grammatical anomalies. This study compares the morphological methods used to form separate categories in Azerbaijani and English languages. It investigates grammatical anomalies in these languages using a comparison method and provides extensive information about each language involved in the research. The study brought together materials from languages with different systems and conducted a comparative analysis of the exceptions and anomalies in their grammatical forms. It was determined that these observed grammatical anomalies and exceptions have a genetic or typological nature.

Rosacea treatment with mussel adhesive protein delivered via microneedling: Invivo and clinical studies.

Rosacea is a prevalent chronic dermatological condition marked by facial inflammation and erythema, significantly compromising the quality of life for affected individuals. Current treatment methods for rosacea are not considered ideal because of the complex etiology of the disease. Mussel adhesive protein (MAP) is a glycoprotein derived from the foot gland of mussels. The protein exhibits anti-inflammatory properties, relieves skin itching, and promotes wound healing. We aimed to explore the feasibility of using MAP administered via microneedle delivery for treating rosacea and the potential molecular mechanism involved. The therapeutic effect and mechanism of MAP microneedle delivery in an LL-37-induced rosacea-like mouse model were observed using morphological and histological methods. Twenty-seven patients with erythematotelangiectatic rosacea (ETR) underwent treatment once every 1 month, with three treatments constituting one treatment course. The therapeutic effect was evaluated by comparing the clinical images taken at baseline, after the first treatment course, and after the second treatment course. The red value, CEA, and GFSS score were also calculated. In response to the microneedle delivery of MAP, innate immunity, inflammatory infiltration, and abnormal neurovascular regulation improved significantly in rosacea-like mice. In the clinical experiments, the microneedle delivery of MAP significantly improved the symptoms of erythema, flushing, and telangiectasia in patients with ETR, and no obvious adverse reactions were observed. MAP delivered by microneedling is effective and safe for treating ETR.

Isolation and Screening of Cellulolytic Bacteria from Yak (Bos grunniens) Excreta from Lahaul Valley Region for Pre-treatment of Paddy Straw in Himachal Pradesh

The present study was conducted during August, 2021 at Department of Agricultural Engineering, College of Agriculture, CSK Himachal Pradesh Krishi Vishvavidyalaya, Palampur to isolate and identify the cellulolytic bacteria from yak dung, yak dung manure and soil samples from spiti region in Lahaul-Spiti district of Himachal Pradesh. The bacterial isolates were identified by using morphological and biochemical standard methods, and identification based on Bergey’s Manual of Determinative Bacteriology. Cellulolytic bacteria from mentioned samples were isolated and cultured on CMC (Carboxymethyl cellulose) agar medium. The activity of cellulolytic bacterial was conducted based on halo area and cellulolytic index on CMC agar medium. Among 24 isolates of bacteria, 08 isolates were identified as cellulolytic bacteria. Furthermore, our isolates with higher cellulolytic index were identified as the Bacillus and Pseudomonas genus. Out of eight efficient cellulolytic isolates were identified as Bacillus spp. (06) three from yak dung manure, two from yak dung and one from soil sample and Pseudomonas spp. (02) one from yak dung manure and one from soil sample. Most Efficient cellulose degrading isolates of Bacillus spp. and Pseudomonas spp. were employed for biological pretreatment of paddy straw for two weeks and then run in laboratory biogas digester along with control digester. These digester sets were under observation from the second day of run upto three weeks and it was observed that the there was 10% hike in biogas production as compare to control digester on 22nd days at laboratory condition.

Onion Fusarium Basal Rot Disease Control by Arbuscular Mycorrhizal Fungi and Trichoderma harzianum

Soilborne pathogens reduce 60% of the yield of onion crops. A common fungal pathogen causing wilt disease and severe losses is Fusarium basal rot (FBR). In this study, the combination of Arbuscular Mycorrhizal Fungi (AMF) with Trichoderma harzianum was investigated against FBR. Onion samples were collected from the Ankara–Polatlı region. Among the isolates, isolate S6 was identified as F. oxysporum f. sp. cepae (FOC) using morphological and molecular methods and pathogenicity tests. Different combinations of AMF (Funneliformis mosseae pure strain and the commercial AMF) and T. harzianum were inoculated on susceptible onion cultivars (Seç, Gence, and Şampiyon). The effects of the treatments on FOC biocontrol were studied under growth chamber conditions. The results showed that Şampiyon was the most resistant, while Gence was the most susceptible to basal rot disease. Different colonization rates (8.91–24%), spore densities (16.4–50.4 spore/10 g soil), and the extent to which a plant needs mycorrhizal conditions to grow to its maximum potential (i.e., mycorrhizal dependencies—18.3–51.9%) were recorded by treatment. Both single and combined applications of AMF and Trichoderma applications suppressed FOC. Suppressive effects were more pronounced when the F. mosseae pure strain was used alone (when F. mosseae was used, disease severity decreased from 90 to 68%, p < 0.05). The F. mosseae pure strain also showed the best plant growth promotion and phosphorus content release. The results indicate an interesting potential use of F. mosseae and the combination of AMF with T. harzianum in the management of FOC in onions.

Application of DNA barcode ITS2to identify herbal medicinal materials

Nowadays, the demand for using herb plants to treat and protect human health is increasing. Along with the growing herbal market, the adulteration of herbal medicinal materials is increasing in many countries, including Vietnam. It is difficult to determine the origin of herbal medicinal materials by morphological or chemical methods when they are substituted by herbs from closely related species or adulterated intentionally by materials from unrelated plants or processed materials. Therefore, it is necessary to use molecular methods based on DNA markers. ITS is a highly conservative nuclear ribosomal marker that has been widely used in the identification of plant species. In this study, the ITS2 marker was used to identify 8 herbal medicinal materials, including 2 samples of polyscias(DLTN, DLBG), 2 samples of morinda (BKTN, BKQN), 2 samples of black zingiber (GDTN, GDYB) and 2 samples of black curcuma (NDTN, NDYB). Gene analysis and sequencing results showed that the DLTN and DLBG were Polyscias fruticosa; BKTN and BKQN were different species, Gynochthodes officinalis (BKTN) and Morinda officinalis (BKQN); GDTN and GDYB were Kaempferia parviflora; NDTN and NDYB were Curcuma caesia. The research results show that the ITS2 indicator can be used to identify medicinal species.

Isolation and identification of a new Bacillus glycinifermentans strain from date palm rhizosphere and its effect on barley seeds under heavy metal stress.

Soil contamination by heavy metals is one of the major problems that adversely decrease plant growth and biomass production. Inoculation with the plant growth-promoting rhizobacteria (PGPR) can attenuate the toxicity of heavy metals and enhancing the plant growth. In this study, we evaluated the potential of a novel extremotolerant strain (IS-2T) isolated from date palm rhizosphere to improve barley seedling growth under heavy metal stress. The species-level identification was carried out using morphological and biochemical methods combined with whole genome sequencing. The bacterial strain was then used in vitro for inoculating Hordeum vulgare L. exposed to three different Cr, Zn, and Ni concentrations (0.5, 1, and 2mM) in petri dishes and different morphological parameters were assessed. The strain was identified as Bacillus glycinifermentans species. This strain showed high tolerance to pH (6-11), salt stress (0.2-2M), and heavy metals. Indeed, the minimum inhibitory concentrations at which bacterium was unable to grow were 4mM for nickel, 3mM for zinc, more than 8mM for copper, and 40mM for chromium, respectively. It was observed that inoculation of Hordeum vulgare L. under metal stress conditions with Bacillus glycinifermentans IS-2T stain improved considerably the growth parameters. The capacity of the IS-2T strain to withstand a range of abiotic stresses and improve barley seedling development under lab conditions makes it a promising candidate for use as a PGPR in zinc, nickel, copper, and chromium bioremediation.