Title:Image Based Breed Recognition of Cattle and Buffalos of India


Authors: Anjali Dewaskar, Bhumi Yadav, Ankita Galphat, Aarya Chhabra, Ganesh Patel, Manoj Agrawal


Published in: Volume 3 Issue 1 Jan June 2026, Page No.245-252


Keywords:AI, Image Recognition, Livestock,Breed identification, Deep Learning, Agriculture, In dia.


Abstract:India, being home to the world’s largest cattle and buffalo population, faces a major challenge in accurate breed identification. Farmers, dairy indus tries, and government agencies often rely on manual inspection, which is time-consuming, subjective, and prone to human error. Misidentification not only affects fair pricing and productivity analysis but also leads to misuse of government subsidy schemes. This study proposes an AI-based image recognition system for automated classification of Indian cattle and buffalo breeds. The model uses deep learning techniques, trained on diverse image datasets of local breeds such as Gir, Sahiwal, Murrah, and Mehsana. By analysing visual features like body structure, skin texture, and horn shape, the system can accurately predict the breed with minimal human intervention. The proposed approach aims to bridge the gap be tween traditional livestock management and modern digital solutions. It offers a practical, farmer-friendly tool that can support fair trade, enhance dairy pro ductivity, and ensure transparency in government livestock programs. This project demonstrates how integrating artificial intelligence with agriculture can empower rural communities and contribute to sus tainable livestock management in India.


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