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Agriculture Fisheries Veterinary Medicine and Animal Husbandry Dataset

The Agriculture, Fisheries, Veterinary Medicine and Animal Husbandry Dataset is a curated collection Odia text by the Odia Virtual Academy (OVA). It covers agriculture, aquaculture, veterinary science, and animal husbandry, including crop science, irrigation, pest management, fishery practices, livestock management. Designed for language modelling and NLP research, the dataset supports domain adaptation, information extraction, and AI-assisted education in Odia for agricultural.

About Dataset

The Agriculture, Fisheries, Veterinary Medicine and Animal Husbandry Dataset is a meticulously curated collection of Odia tex by the Odia Virtual Academy (OVA). It brings together material across agriculture, aquaculture, veterinary science, and animal husbandry to reflect the breadth and complexity of these interrelated domains. The dataset encompasses topics such as crop physiology and production systems, soil health and management, irrigation practices, pest and disease management, post-harvest technology, and agricultural economics, as well as fishery science, aquaculture techniques, and coastal and inland fishing communities. It further covers veterinary medicine, animal welfare, livestock management, dairy and poultry production, nutrition, breeding, health management and traditional knowledge embedded in Odia-speaking communities. Curated by Odia Virtual Academy, the dataset emphasizes domain-relevant terminology, regional dialects, and domain-specific vocabularies to support accurate language modelling, information extraction, and domain adaptation for Odia NLP research and language modelling.

Purpose of Dataset

The Agriculture, Fisheries, Veterinary Medicine And Animal Husbandry Dataset Aims To Provide Odia Text Sourced From Digitized Agricultural, Aquaculture, Veterinary, And Animal-husbandry Literature And Related Materials. It Is Suitable For A Range Of Applications, Including Training Language Models, Building Domain-aware Nlp Tools (Such As Named-entity Recognition For Crops, Species, Diseases, And Agricultural Practices; Relation Extraction; And Multilingual Grounding), Implementing Ai-assisted Extension And Education For Farmers And Practitioners, And Enabling Content Generation That Aligns With Agricultural And Animal-science Contexts In Odia.