Advancements In Biometric Techniques For Moroccan Argan Grove Goats.

Citation (APA 7)

Tami, H., Amellal, M., Ezzaky, Y., & Achemchem, F. (2024). Advancements In Biometric Techniques For Moroccan Argan Grove Goats. 16th AgroStat Conference (AgroStat 2024) (AGROSTAT2024), Bragança, Portugal. Zenodo. https://doi.org/10.5281/zenodo.14787662

Abstract

Biometrics, the science of identifying individuals based on unique physical or behavioral traits, has gained prominence in various fields, including agriculture and animal husbandry. This study highlights the use of biometric techniques in goats, focusing on their importance for breed identification, health monitoring, and livestock management. Goats possess distinctive biometric features such as facial patterns, iris structures, ear shapes, and body measurements, which can be effectively utilized for individual identification. Employing advanced technologies like image processing, machine learning, and 3D scanning allows for the precise and non-invasive capture and analysis of these traits. Biometric systems offer significant benefits, including enhanced traceability, improved breeding programs, and the prevention of livestock theft and fraud. Moreover, biometric data play a crucial role in health monitoring by enabling early disease detection and optimizing management practices. This emerging field promises to advance goat production systems, contribute to animal welfare, and promote sustainable livestock management practices. Future research aims to refine the accuracy of biometric identification systems and integrate biometric data with other agricultural technologies for comprehensive livestock management solutions. This work underscores the potential of biometric technologies to revolutionize goat farming, particularly in Moroccan argan groves, fostering advancements in breed improvement, health surveillance, and overall livestock management.