Web based software for the study of USDA soil taxonomy and classification of newly found soil

United States Department of Agriculture (USDA) Soil Taxonomy is based on soil properties that can be objectively observed and measured in the natural conditions as they exist today. There are many soil classification systems but USDA Soil Taxonomy is most accepted worldwide. Ontologies are the new form of knowledge representation that acts in synergy with agents and Semantic Web Architecture. Soil ontology developed for USDA soil taxonomy has been used to develop a query interface that will help in detailed study of soil taxonomy, classification of new soil as well as exchange knowledge between software agents and systems. This is a web based application having N-tier architecture. Application development environment is NetBeans 6.9 editor and Protégé. Web development technology is Java Server Pages (JSP). Programming languages JAVA and SPARQL are used for querying. Client interface is developed with Hyper Text Markup Language (HTML), Cascading Style Sheet (CSS) and JavaScript. Third tier of software consist of database which is in MS-SQL server 2005. Other two layers are Web Ontology Language (OWL) Ontology layer and Semantic Web Framework layer. OWL layer contains soil taxonomy information in the form of Ontology. Semantic Web Framework layer is implemented using JENA. In the search panel user can search anything related to USDA Soil Taxonomy, which comprises of twelve orders. However, this software contains information about seven soil orders reported in India. Domain experts can see and edit the knowledge base (i.e. Soil Ontology) or can suggest anything related to the creation of Soil Taxonomy Ontology through WebProtégé

Identification of a suitable clustering method and allocation strategy for core set development in salt stress tolerant rice (Oryza sativa) germplasm

Preserving genetic diversity in repository of germplasm is essential for crop breeding programs. However, maintenance and protection of all the germplasms in gene bank is difficult due to its voluminous size. Hence the development of core set with minimum number of germplasm representing maximum genetic diversity of the population has become an alternative. From the available clustering methods and allocation strategies, identifying a suitable combination is essential for the development of species-specific core set. In the present study, data on 219 salt stress tolerant rice (Oryza sativa L.) germplasm accessions with 14 phenotypic traits and 2915 genome wide Single Nucleotide Polymorphisms (SNPs) is considered to identify a suitable combination of clustering method and allocation strategy for core set development. Eight different combinations consisting of two clustering methods, viz. Ward’s and UPGMA along with four different allocation strategies, viz. L, D, LD and NY allocation with three level of sampling intensities (20%, 25% and 30%) have been tried. Based on the study carried out during 2013-14 at Indian Agricultural Statistics Research Institute, New Delhi, it is concluded that the Ward’s clustering method with NY allocation, irrespective of sampling intensity, is suitable for developing core set with maximum diversity

IMAGE-BASED IDENTIFICATION OF MLB DISEASE OF MAIZE

Not AvailableIn recent years, deep learning techniques have become very popular in the field of image recognition and classification. Image-based diagnosis of diseases in crops using deep learning techniques has become trendy in the current scientific community. In this study, a deep convolutional neural network (CNN) model has been developed to identify the images of maydis leaf bight (MLB) (Cochliobolus heterostrophus) disease of maize (Zea mays L.) crop. A total of 1547 digital images of maize leaves (596 healthy and 951 infected with maydis leaf blight disease) have been collected from different agricultural farms using hand-held camera and smartphones. The images have been collected from the experimental plots of BCKV, West Bengal and ICAR-IARI, New Delhi during 2018–19. The architectural framework of popular state-of-the network ‘GoogleNet’ has been used to build the deep CNN model. The developed model has been successfully trained, validated and tested on the above-mentioned dataset. The trained model has achieved an overall accuracy of 99.14% on the separate test dataset.Not Availabl

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Not AvailableAcademic Management System (AMS) has been customized by the NAHEP Component 2 Project Team at ICAR-Indian Agricultural Statistics Research Institute (IASRI) for the implementation at various Agricultural Universities. It is a web enabled system for management of all the various academic activities of the university. The system caters to the needs of different users: Dean, Registrar, Professor, Head, Guide, Student, Teacher, Student, Administrators and Officials for performing their assigned tasks. This system has been designed in a modular approach with in-built work flows. AMS ensures that the individuals responsible for the next task are notified and receive the data they need to execute at their stage of process. At present five modules have been envisaged viz., Student Management, Student Management, Course Management, Administration Management and E-Learning. AMS facilitates in automation of various academic processes of the university and enhances the efficiency of the overall system by saving time and efforts involved in manual processes. It continues to be customized as per the respective needs of the various universities.Not Availabl

Not Available

Not AvailableAcademic Management System (AMS) has been customized by the NAHEP Component 2 Project Team at ICAR-Indian Agricultural Statistics Research Institute (IASRI) for the implementation at various Agricultural Universities. It is a web enabled system for management of all the various academic activities of the university. The system caters to the needs of different users: Dean, Registrar, Professor, Head, Guide, Student, Teacher, Student, Administrators and Officials for performing their assigned tasks. This system has been designed in a modular approach with in-built work flows. AMS ensures that the individuals responsible for the next task are notified and receive the data they need to execute at their stage of process. At present five modules have been envisaged viz., Student Management, Student Management, Course Management, Administration Management and E-Learning. AMS facilitates in automation of various academic processes of the university and enhances the efficiency of the overall system by saving time and efforts involved in manual processes. It continues to be customized as per the respective needs of the various universities.Not Availabl

Not Available

Not AvailableAcademic Management System (AMS) has been customized by the NAHEP Component 2 Project Team at ICAR-Indian Agricultural Statistics Research Institute (IASRI) for the implementation at various Agricultural Universities. It is a web enabled system for management of all the various academic activities of the university. The system caters to the needs of different users: Dean, Registrar, Professor, Head, Guide, Student, Teacher, Student, Administrators and Officials for performing their assigned tasks. This system has been designed in a modular approach with in-built work flows. AMS ensures that the individuals responsible for the next task are notified and receive the data they need to execute at their stage of process. At present five modules have been envisaged viz., Student Management, Student Management, Course Management, Administration Management and E-Learning. AMS facilitates in automation of various academic processes of the university and enhances the efficiency of the overall system by saving time and efforts involved in manual processes. It continues to be customized as per the respective needs of the various universities.Not Availabl

Not Available

Not AvailableAcademic Management System (AMS) has been customized by the NAHEP Component 2 Project Team at ICAR-Indian Agricultural Statistics Research Institute (IASRI) for the implementation at various Agricultural Universities. It is a web enabled system for management of all the various academic activities of the university. The system caters to the needs of different users: Dean, Registrar, Professor, Head, Guide, Student, Teacher, Student, Administrators and Officials for performing their assigned tasks. This system has been designed in a modular approach with in-built work flows. AMS ensures that the individuals responsible for the next task are notified and receive the data they need to execute at their stage of process. At present five modules have been envisaged viz., Student Management, Student Management, Course Management, Administration Management and E-Learning. AMS facilitates in automation of various academic processes of the university and enhances the efficiency of the overall system by saving time and efforts involved in manual processes. It continues to be customized as per the respective needs of the various universities.Not Availabl

Not Available

Not AvailableAcademic Management System (AMS) has been customized by the NAHEP Component 2 Project Team at ICAR-Indian Agricultural Statistics Research Institute (IASRI) for the implementation at various Agricultural Universities. It is a web enabled system for management of all the various academic activities of the university. The system caters to the needs of different users: Dean, Registrar, Professor, Head, Guide, Student, Teacher, Student, Administrators and Officials for performing their assigned tasks. This system has been designed in a modular approach with in-built work flows. AMS ensures that the individuals responsible for the next task are notified and receive the data they need to execute at their stage of process. At present five modules have been envisaged viz., Student Management, Student Management, Course Management, Administration Management and E-Learning. AMS facilitates in automation of various academic processes of the university and enhances the efficiency of the overall system by saving time and efforts involved in manual processes. It continues to be customized as per the respective needs of the various universities.Not Availabl

Not Available

Not AvailableAcademic Management System(AMS) has been customized by the NAHEP Component - 2 Project Team at ICAR-Indian Agricultural Statistics Research Institute (IASRI) for the implementation at various Agricultural Universities. It is a web enabled system for management of all the various academic activities of the university. The system caters to the needs of different users: Dean, Registrar, Professor, Head, Guide, Faculty, Teacher, Student, 1 Administrators and Officials for performing their assigned tasks. A System has been designed in a modular approach with in-built work flows. System ensures that the individuals responsible for the next task are notified and receive the data they need to execute at their stage of process. At present five modules have been envisaged viz., Student Management, Faculty Management, Course Management, Administration Management and E-Learning. AMS facilitates in automation of various academic processes of the university and enhances the efficiency of the overall system by saving time and efforts involved in manual processes. It continues to be customized as per the respective needs of the various universities. The Project supports the Country Partnership Strategy and addresses the three engagement areas of integration, transformation and inclusion. These engagement areas foresee increased agricultural productivity and support quality improvements of higher education to create a more skilled workforce that continuously improves the productivity of key sectors, including agriculture. The proposed Project is also a multi-Global Practice collaboration (Agriculture and Education) and is expected to support activities and results directly related to cross-cutting strategic areas of climate change, jobs and gender.Not Availabl

Not Available

Not AvailableAcademic Management System (AMS) has been customized by the NAHEP Component 2 Project Team at ICAR-Indian Agricultural Statistics Research Institute (IASRI) for the implementation at various Agricultural Universities. It is a web enabled system for management of all the various academic activities of the university. The system caters to the needs of different users: Dean, Registrar, Professor, Head, Guide, Student, Teacher, Student, Administrators and Officials for performing their assigned tasks. This system has been designed in a modular approach with in-built work flows. AMS ensures that the individuals responsible for the next task are notified and receive the data they need to execute at their stage of process. At present five modules have been envisaged viz., Student Management, Student Management, Course Management, Administration Management and E-Learning. AMS facilitates in automation of various academic processes of the university and enhances the efficiency of the overall system by saving time and efforts involved in manual processes. It continues to be customized as per the respective needs of the various universities.Not Availabl