UTTAR PRADESH JOURNAL OF ZOOLOGY

Individual animal identification is a milestone of modern livestock management, crucial for ensuring efficient and sustainable development within the livestock sector. This review provides a comprehensive examination of cattle identification through nose (muzzle) prints, a highly promising biometric application. It delves into the unique dermatoglyphic patterns of bovine muzzles, comparing their inherent uniqueness. The report traces the evolution of identification methodologies from traditional, often invasive, physical impression techniques to advanced digital approaches leveraging sophisticated image processing, machine learning, and deep learning algorithms. It highlights the significant advantages of muzzle print biometrics, including their non-invasive nature, contribution to animal welfare, and high accuracy in diverse applications such as disease control, traceability, and theft prevention. Furthermore, the review explores the challenges in real-world implementation, particularly concerning environmental factors and animal movement, and projects future advancements, emphasizing the synergistic integration of muzzle print technology within broader smart farming ecosystems encompassing the Internet of Things (IoT), predictive analytics, and blockchain. The major concern was on proper identification of cattle for registration and of cattle on an official test so that the possibility of swapping, false insurance claims and ownership disputes can be guarded. This technique will certainly help in livestock census to avoid duplication and also helpful in geographical tagging of specific breeds as no two breeds are having same nose muzzle pattern and it can be compared to human finger prints.