Blood vitamin A level prediction in Japanese black cattle based on chromatic and dynamic eye features using double imaging system

Abstract

Proactive dietary control of blood vitamin A levels is crucial for the intramuscular fat development in cattle worldwide. However, cattle become susceptible to either vitamin A deficiency or excessive state during fattening stage, influencing cattle performance, health, and beef quality. A good understanding and modelling of vitamin A levels throughout the whole cattle growth phase is needed. This study aims to assist in controlling the fattening process for production of high-marbling beef through a non-invasive monitoring of blood vitamin A levels. Using an automatic double imaging system, this study captured both surface and fundus images of cattle eyes, and based on this, predicted blood vitamin A levels through a novel dynamic analysis of 29 eye features. The best PLS model had a prediction of R2 = 0.82 and RMSE = 6.50 IU·dL−1 (equivalent to 0.02 μg · mL−1), which is of a clinically meaningful accuracy. This system can greatly facilitate vitamin A levels management in cattle raising, contributing to the effective control of beef marbling for both the market and industry.