Estimation of Blood Concentration of Glucose in Cattle Using Near-Infrared Spectroscopy and Convolutional Neural Network

Abstract

Cattle blood tests are used for feed adjustment and early detection of disease. Conventional cattle blood tests pose infection risks and handling challenges. This paper proposes estimating blood glucose levels in cattle via near-infrared spectroscopy (NIRS) and a CNN model. Showing an accuracy of 94.67%, it demonstrates its effectiveness as one of the metrics in veterinary medicine.