Prospects for the Development of an Artificial Intelligence: Parasites Diagnosis System in Mithun and Allied Bovines
Jayanta Kumar Chamuah*
ICAR-NRC on Mithun, Medziphema, Nagaland (797 106), India
Livika T. Awomi
ICAR-NRC on Mithun, Medziphema, Nagaland (797 106), India
Bikash Sarma
National Institute of Technology Nagaland, Chumoukedima, Nagaland (797 103), India
Imnatemjen Aier
ICAR-NRC on Mithun, Medziphema, Nagaland (797 106), India
S.S. Hanah
ICAR-NRC on Mithun, Medziphema, Nagaland (797 106), India
Meena Das
ICAR-Research Complex for NEH Region, Umiam, Barapani, Meghalaya (793 103), India
DOI: NIL
Keywords: Artificial intelligence, Machine learning, CNN, Parasites
Abstract
Parasites have detrimental effects on animal health and welfare, leading to clinical and subclinical parasitism. While parasitic infections may not always exhibit obvious disease symptoms, they result in reduced production, including slowed growth, decreased appetite and poor feed conversion. Microscopy is a commonly used method to diagnose livestock parasitic infections, but it presents challenges such as being time-consuming, labour-intensive, requiring specialized equipment and trained researchers. The NEH (North Eastern Hill) region of India faces additional difficulties in finding experts promptly due to limited resources and geographical constraints, resulting in economic losses for farmers, including reduced milk output, meat production and occasional animal mortality. To address this problem, a smart system utilizing AI (Artificial Intelligence) could offer a viable solution by accurately identifying and diagnosing parasitic infections. Such a system would mitigate the scarcity of professionals in the NEH region, providing effective identification and diagnostics of parasite management in livestock.
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