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

IF 4.4 1区 农林科学 Q1 AGRICULTURAL ENGINEERING Biosystems Engineering Pub Date : 2024-06-11 DOI:10.1016/j.biosystemseng.2024.05.016
Nanding Li , Dimas Firmanda Al Riza , Otieno Samuel Ouma , Mizuki Shibasaki , Wulandari , Moriyuki Fukushima , Tateshi Fujiura , Yuichi Ogawa , Naoshi Kondo , Tetsuhito Suzuki
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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.

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利用双成像系统,基于色度和动态眼球特征预测日本黑牛血液中的维生素 A 水平
积极控制血液中的维生素 A 水平对全球牛的肌肉脂肪发育至关重要。然而,牛在育肥阶段很容易出现维生素 A 缺乏或过量的情况,从而影响牛的生产性能、健康和牛肉质量。因此,有必要充分了解牛在整个生长阶段的维生素 A 水平,并建立相关模型。本研究旨在通过无创监测血液中的维生素 A 水平,帮助控制育肥过程,以生产出高毛重的牛肉。本研究使用自动双重成像系统捕捉牛眼表面和眼底图像,并在此基础上通过对 29 个眼部特征进行新颖的动态分析来预测血液中的维生素 A 水平。最佳 PLS 模型的预测值为 R2 = 0.82,RMSE = 6.50 IU-dL-1(相当于 0.02 μg - mL-1),具有临床意义。该系统可极大地促进养牛业的维生素 A 水平管理,有助于市场和行业对牛肉大理石纹的有效控制。
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来源期刊
Biosystems Engineering
Biosystems Engineering 农林科学-农业工程
CiteScore
10.60
自引率
7.80%
发文量
239
审稿时长
53 days
期刊介绍: Biosystems Engineering publishes research in engineering and the physical sciences that represent advances in understanding or modelling of the performance of biological systems for sustainable developments in land use and the environment, agriculture and amenity, bioproduction processes and the food chain. The subject matter of the journal reflects the wide range and interdisciplinary nature of research in engineering for biological systems.
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