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Evaluation of Endophytic Bacteria for Plant Growth Promotion and Pathogen Suppression Traits in Saccharum officinarum

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Journal of Agricultural Science and Technology(A) 2017年第8期7卷 537-545页

作者： Penumatsa Kishore Varma Kotam Vijay Krishna Kumar Vanapalli Chandra Sekhar Dandu Adilakshmi Madugula Suresh Nambala Raja Kumar Karnam Jayaehandra ravuri anitha Department of Plant Pathology Regional Agricultural Research Station Anakapalle 531001 Andhra Pradesh lndia Department of Genetics and Plant Breeding Regional Agricultural Research Station Anakapalle 531001 Andhra Pradesh lndia

Endophytes are beneficial microbes that are capable of promoting growth, besides protecting colonized plants against plant pathogens. These microbes are of either bacterial, fungal or actinomycetes in plants. In the study, the endophytic bacteria isolated from sugarcane with their characterization related to plant growth promotion and pathogen suppression have been reported. Roots, shoots and leaves of rooted tissue culture plantlets of sugarcane cultivars of 87A298 and 2009A107 were excised aseptically and isolated endophytic bacterial strains. The strains were identified using 16S rRNA gene sequence based homology. Molecular characterization of these strains was carried out for presence of antimicrobial genes. The results showed that the endophytes isolated from sugarcane tissue culture plantlets were of the genera Bacillus （B. amyloliquefaciens, B. subtilis, B. cereus, B. safensis, B. siamensis, B. aryabhattai, B. flexus and B. velezensis） and Paenibacillus pabuli. There were three antimicrobial peptides （AMPs） producing genes of bacilysin, bacillomycin and fengycin in B. amyloliquefaciens （SE1, SE7）, B. siamensis （SE4, SE16）, B. subtilis （SE2, SE3） and B. velezensis （SE15）. The biochemical characterization assays showed that some of these strains could produce hydrogen cyanide （HCN）, protease, cellulase and indole acetic acid （IAA）. Few strains （SE1 and SE4） were phosphate solubilizers, whereas nine isolates were found to be diazotrophs. Most of the bacterial isolates were found antagonistic to Fusarium sacchari, the sugarcane wilt pathogen under in vitro conditions. Overall, the results suggested the scope and potentiality of sugarcane endophytic bacteria, isolated from tissue culture plantlets, in promoting plant growth and suppression of sugarcane pathogen.

关键词： Bacillus Fusarium sacchari Paenibacillus antimicrobial peptides.

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Managerial perspectives of scaling up robotic-assisted surgery in healthcare systems:A systematic literature review

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Laparoscopic, Endoscopic and Robotic Surgery 2024年第3期7卷 113-122页

作者： Ravichandran anitha Komattu Chacko John Gnanadhas Jabarethina Sri Ramachandra Faculty of Management Sciences Sri Ramachandra Institute of Higher Education and Research(Category-I Deemed to be University)ChennaiIndia

Objectives Robotic-assisted surgery(RAS)is a minimally invasive technique practiced in multiple *** training is essential for the acquisition of RAS *** cost of RAS is considered to be high,which makes it a burden for institutes and unaffordable for *** systematic literature review(SLR)focused on the various RAS training methods applied in different surgical specialties,as well as the cost elements of RAS,and was to summarize the opportunities and challenges associated with scaling up *** An SLR was carried out based on the Preferred Reporting Items for Systematic reviews and Meta-Analyses reporting *** PubMed,EBSCO,and Scopus databases were searched for reports from January 2018 through January ***-text reviews and research articles in the English language from Asia-Pacific countries were *** that outlined training and costs associated with RAS were *** The most common training system is the da Vinci *** simulation technique,which includes dry-lab,wet-lab,and virtual reality training,was found to be a common and important *** cost of RAS encompasses the installation and maintenance costs of the robotic system,the operation theatre rent,personnel cost,surgical instrument and material cost,and other miscellaneous *** synthesis of SLR revealed the challenges and opportunities regarding RAS training and *** The results of this SLR will help stakeholders such as decision-makers,influencers,and end users of RAS to understand the significance of training and cost in scaling up RAS from a managerial *** any healthcare innovation to reach a vast population,cost-effectiveness and standard training are crucial.

关键词： da Vinci system Healthcare Robotic-assisted surgery Robotic surgery Robotic training Robotic surgery cost

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DeepRice: A deep learning and deep feature based classification of Rice leaf disease subtypes

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Artificial Intelligence in Agriculture 2024年第1期11卷 34-49页

作者： P.Isaac Ritharson Kumudha Raimond X.anitha Mary Jennifer Eunice Robert Andrew J Department of CSE Karunya Institute of Technology and Sciences CoimbatoreTamilnaduIndia Department of Robotics Engineering Karunya Institute of Technology and SciencesCoimbatoreIndia Department of Mechatronics Engineering Manipal Institute of TechnologyManipal Academy of Higher EducationManipalKarnataka 576104India Department of Computer Science and Engineering Manipal Institute of TechnologyManipal Academy of Higher EducationManipalKarnataka 576104India

Rice stands as a crucial staple food globally,with its enduring sustainability hinging on the prompt detection of rice leaf ***,efficiently detecting diseases when they have already occurred holds paramount importance for solving the cost of manual visual identification and chemical *** the recent past,the identification of leaf pathologies in crops predominantly relies on manual methods using specialized equipment,which proves to be time-consuming and *** study offers a remedy by harnessing Deep Learning(DL)and transfer learning techniques to accurately identify and classify rice leaf diseases.A comprehensive dataset comprising 5932 self-generated images of rice leaves was assembled along with the benchmark datasets,categorized into 9 classes irrespective of the extent of disease spread across the *** classes encompass diverse states including healthy leaves,mild and severe blight,mild and severe tungro,mild and severe blast,as well as mild and severe brown *** meticulous manual labelling and dataset segmentation,which was validated by horticulture experts,data augmentation strategies were implemented to amplify the number of *** datasets were subjected to evaluation using the proposed tailored Convolutional Neural Networks *** performance are scrutinized in conjunction with alternative transfer learning approaches like VGG16,Xception,ResNet50,DenseNet121,Inception ResnetV2,and Inception *** effectiveness of the proposed custom VGG16 model was gauged by its capacity to generalize to unseen images,yielding an exceptional accuracy of 99.94%,surpassing the benchmarks set by existing state-of-the-art ***,the layer wise feature extraction is also visualized as the interpretable AI.

关键词： Rice leaf disease Deep learning CNN Crop yield Agriculture Food security

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Ontology Based Ocean Knowledge Representation for Semantic Information Retrieval

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Computers, Materials & Continua 2022年第3期70卷 4707-4724页

作者： anitha Velu Menakadevi Thangavelu Department of Electronics and Communication Engineering Adhiyamaan College of EngineeringHosur635109Tamil NaduIndia

The drastic growth of coastal observation sensors results in copious data that provide weather *** intricacies in sensor-generated big data are heterogeneity and interpretation,driving high-end Information Retrieval(IR)*** Semantic Web(SW)can solve this issue by integrating data into a single platform for information exchange and knowledge *** paper focuses on exploiting the SWbase systemto provide interoperability through ontologies by combining the data concepts with ontology *** paper presents a 4-phase weather data model:data processing,ontology creation,SW processing,and query *** developed Oceanographic Weather Ontology helps to enhance data analysis,discovery,IR,and decision *** addition to that,it also evaluates the developed ontology with other state-of-the-art *** proposed ontology’s quality has improved by 39.28%in terms of completeness,and structural complexity has decreased by 45.29%,11%and 37.7%in Precision and *** Meteorological Satellite INSAT-3D’s ocean data is a typical example of testing the proposed *** experimental result shows the effectiveness of the proposed data model and its advantages in machine understanding and IR.

关键词： Heterogeneous climatic data information retrieval semantic web sensor observation services knowledge representation ontology

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Convective flow of Jeffrey nanofluid along an upright microchannel with Hall current and Buongiorno model:an irreversibility analysis

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Applied Mathematics and Mechanics(English Edition) 2023年第9期44卷 1613-1628页

作者： L.anitha B.J.GIREESHA Department of PG Studies and Research in Mathematics Kuvempu UniversityShankaraghatta 577451India Department of Mathematics Adichunchanagiri Institute of TechnologyChikkamagaluru 577102India

The thermal properties and irreversibility of the Jeffrey nanofluid through an upright permeable microchannel are analyzed by means of the Buongiorno *** effects of the Hall current,exponential space coefficient,nonlinear radiation,and convective and slip boundary conditions on the Jeffrey fluid flow are explored by deliberating the buoyant force and viscous *** non-dimensionalized equations are obtained by employing a non-dimensional system,and are further resolved by utilizing the shooting approach and the 4th-and 5th-order Runge-Kutta-Fehlberg *** obtained upshots conclude that the amplified Hall parameter will enhance the secondary flow *** improvement in the temperature parameter directly affects the thermal profile,and hence the thermal field declines.A comparative analysis of the Newtonian fluid and non-Newtonian fluid(Jeffrey fluid)is carried out with the flow across a porous *** the Bejan number,thermal field,and entropy generation,the Jeffrey nanofluid is more highly supported than the Newtonian fluid.

关键词： Jeffrey nanofluid entropy generation exponential heat source porous medium convective and slip boundary condition

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Repercussion of Hall effect and nonlinear radiation on Couette-Poiseuille flow of Casson-Williamson fluid through upright microchannel

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Applied Mathematics and Mechanics(English Edition) 2022年第12期43卷 1951-1964页

作者： B.J.GIREESHA L.anitha Department of Post Graduation Studies and Research in Mathematics Kuvempu UniversityShankaraghatta 577451India Department of Mathematics Adichunchanagiri Institute of TechnologyChikkamagaluru 577102India

The main aim of the present work is to investigate the flow and heat transport properties of non-Newtonian Casson-Williamson fluid through an upright microchannel along with entropy generation analysis,and explore the effects of convective boundary conditions,Couette-Poiseuille flow,and nonlinear *** movement of liquid is scrutinized with the Hall effect and exponential heat *** rheological characteristics of the Casson-Williamson fluid model are also *** considering the desirable similarity variables,the equations of motion are reduced to nonlinear ordinary differential *** Runge-Kutta-Fehlberg fourth-fifth order method along with the shooting method is adopted to solve these dimensionless *** detailed investigation is pictorially displayed to show the influence of effective parameters on the entropy generation and the Bejan *** of the major tasks of the exploration is to compare the Casson fluid and the Williamson *** results show that the rate of heat transfer in the Casson fluid is more remarkable than that in the Williamson fluid.

关键词： entropy generation Bejan number convective boundary condition Hall effect nonlinear radiation exponential heat source

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Asymmetric Consortium Blockchain and Homomorphically Polynomial-Based PIR for Secured Smart Parking Systems

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Computers, Materials & Continua 2023年第5期75卷 3923-3939页

作者： T.Haritha A.anitha School of Information Technology and Engineering Vellore Institute of TechnologyVelloreTamil NaduIndia

In crowded cities,searching for the availability of parking lots is a herculean task as it results in the wastage of drivers’time,increases air pollution,and traffic *** parking systems facilitate the drivers to determine the information about the parking lot in real time and book them depending on the *** the existing smart parking systems necessitate the drivers to reveal their sensitive information that includes their mobile number,personal identity,and desired *** disclosure of sensitive information makes the existing centralized smart parking systems more vulnerable to service providers’security breaches,single points of failure,and *** this paper,an Improved Asymmetric Consortium Blockchain and Homomorphically Computing Univariate Polynomial-based private information retrieval(IACB-HCUPPIR)scheme is proposed to ensure parking lots’availability with transparency security in a privacy-preserving smart parking *** specific,an improved Asymmetric Consortium Blockchain is used for achieving secure transactions between different parties interacting in the smart parking *** further adopted the method of Homomorphically Computing Univariate Polynomial-based private information retrieval(HCUPPIR)scheme for preserving the location privacy of *** results of IACB-HCUPPIR confirmed better results in terms of minimized computation and communication overload with throughput,latency,and response time with maximized drivers’privacy ***,the proposed fully homomorphic algorithm(FHE)was compared against partial-homomorphic encryption(PHE)and technique without encryption and found that the proposed model has quick communication in allocating the parking slots starting with 24.3 s,whereas PHE starts allocating from 24.7 s and the technique without encryption starts at 27.4 ***,we ensure the proposed model performs well in allocating parking slots with less time and high security with priv

关键词： Smart parking asymmetric consortium blockchain privacy preservation homomorphic encryption private information retrieval

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MRI Brain Tumor Segmentation with Intuitionist Possibilistic Fuzzy Clustering and Morphological Operations

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Computer Systems Science & Engineering 2022年第10期43卷 363-379页

作者： J.anitha M.Kalaiarasu Department of Information Technology Sri Ramakrishna Engineering CollegeCoimbatore641022India

Digital Image Processing(DIP)is a well-developed field in the biological sciences which involves classification and detection of *** medical science,automatic brain tumor diagnosis is an important *** tumor detection is performed by Computer-Aided Diagnosis(CAD)*** human image creation is greatly achieved by an approach namely medical imaging which is exploited for medical and research *** Automatic brain tumor detection from MRI images has become the emerging research area of medical *** tumor diagnosis mainly performed for obtaining exact location,orientation and area of abnormal *** and edema regions inference from brain magnetic resonance imaging(MRI)information is considered to be great challenge due to brain tumors complex structure,blurred borders,besides exterior features like *** noise compassion is mainly reduced along with segmentation stability by suggesting efficient hybrid clustering method merged with morphological process for brain cancer *** form of Median Modified Wiener filter(CMMWF)is chiefly deployed for denoising,and morphological operations which in turn eliminate nonbrain tissue,efficiently dropping technique’s sensitivity to *** proposed system contains the main phases such as preprocessing,brain tumor extraction and post *** segmentation is greatly achieved by presenting Intuitionist Possibilistic Fuzzy Clustering(IPFC)*** algorithm’s stability is greatly enhanced by this clustering along with clustering parameters sensitivity ***,the post processing of images are done through morphological operations along with Hybrid Median filtering(HMF)for attaining exact tumors ***,suggested algorithm is substantiated by comparing with other existing segmentation *** outcomes reveal that suggested algorithm achieves improved outcomes pertaining to accuracy,sensitivity,specificity,and recall.

关键词： Morphological Image Processing(MIP) Magnetic Resonance Imaging(MRI) brain tumor clustering K-means clustering image segmentation Fuzzy-CMeans(FCM)

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Indoor versus outdoor scene recognition for navigation of a micro aerial vehicle using spatial color gist wavelet descriptors

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Visual Computing for Industry,Biomedicine,and Art 2019年第1期2卷 192-204页

作者： anitha Ganesan Anbarasu Balasubramanian Department of Aerospace Engineering Madras Institute of TechnologyAnna UniversityChennai 600044India

In the context of improved navigation for micro aerial vehicles,a new scene recognition visual descriptor,called spatial color gist wavelet descriptor(SCGWD),is *** was developed by combining proposed Ohta color-GIST wavelet descriptors with census transform histogram(CENTRIST)spatial pyramid representation descriptors for categorizing indoor versus outdoor scenes.A binary and multiclass support vector machine(SVM)classifier with linear and non-linear kernels was used to classify indoor versus outdoor scenes and indoor scenes,*** this paper,we have also discussed the feature extraction methodology of several,state-of-the-art visual descriptors,and four proposed visual descriptors(Ohta color-GIST descriptors,Ohta color-GIST wavelet descriptors,enhanced Ohta color histogram descriptors,and SCGWDs),in terms of experimental *** proposed enhanced Ohta color histogram descriptors,Ohta color-GIST descriptors,Ohta color-GIST wavelet descriptors,SCGWD,and state-of-the-art visual descriptors were evaluated,using the Indian Institute of Technology Madras Scene Classification Image Database two,an Indoor-Outdoor Dataset,and the Massachusetts Institute of Technology indoor scene classification dataset[(MIT)-67].Experimental results showed that the indoor versus outdoor scene recognition algorithm,employing SVM with SCGWDs,produced the highest classification rates(CRs)—95.48%and 99.82%using radial basis function kernel(RBF)kernel and 95.29%and 99.45%using linear kernel for the IITM SCID2 and Indoor-Outdoor datasets,*** lowest CRs—2.08%and 4.92%,respectively—were obtained when RBF and linear kernels were used with the MIT-67 *** addition,higher CRs,precision,recall,and area under the receiver operating characteristic curve values were obtained for the proposed SCGWDs,in comparison with state-of-the-art visual descriptors.

关键词： Micro aerial vehicle Scene recognition Navigation Visual descriptors Support vector machine

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Feature Extraction and Classification of Plant Leaf Diseases Using Deep Learning Techniques

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Computers, Materials & Continua 2022年第10期73卷 233-247页

作者： K.anitha S.Srinivasan Department of Electronics and Communication Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical Sciences(SIMATS)Saveetha UniversityThandalamChennai602105India Instituteof Bio-Medical Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical Sciences(SIMATS)Saveetha UniversityThandalamChennai602105India

In India’s economy, agriculture has been the most significantcontributor. Despite the fact that agriculture’s contribution is decreasing asthe world’s population grows, it continues to be the most important sourceof employment with a little margin of difference. As a result, there is apressing need to pick up the pace in order to achieve competitive, productive,diverse, and long-term agriculture. Plant disease misinterpretations can resultin the incorrect application of pesticides, causing crop harm. As a result,early detection of infections is critical as well as cost-effective for *** diagnose the disease at an earlier stage, appropriate segmentation of thediseased component from the leaf in an accurate manner is critical. However,due to the existence of noise in the digitally captured image, as well asvariations in backdrop, shape, and brightness in sick photographs, effectiverecognition has become a difficult task. Leaf smut, Bacterial blight andBrown spot diseases are segmented and classified using diseased Apple (20),Cercospora (60), Rice (100), Grape (140), and wheat (180) leaf photos in thesuggested work. In addition, a superior segmentation technique for the ROIfrom sick leaves with living backdrop is presented here. Textural features of thesegmented ROI, such as 1st and 2nd order WPCA Features, are discoveredafter segmentation. This comprises 1st order textural features like kurtosis,skewness, mean and variance as well as 2nd procedure textural features likesmoothness, energy, correlation, homogeneity, contrast, and entropy. Finally,the segmented region of interest’s textural features is fed into four differentclassifiers, with the Enhanced Deep Convolutional Neural Network provingto be the most precise, with a 96.1% accuracy.

关键词： Convolutional neural network wavelet based pca features leaf disease detection agriculture disease remedies bat algorithm

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