Non-invasive Detection of Chick Embryo Gender Based on Body Motility and a Near-infrared Sensor

被引：3
|
作者：
Khaliduzzaman A. [1 ,3 ]
Fujitani S. [2 ]
Kashimori A. [2 ]
Suzuki T. [1 ]
Ogawa Y. [1 ]
Kondo N. [1 ]
机构：
[1] Graduate School of Agriculture, Kyoto University
[2] NABEL Co., Ltd.
[3] Faculty of Agricultural Engineering and Technology, Sylhet Agricultural University
来源：
Engineering in Agriculture, Environment and Food | 2021年 / 14卷 / 02期
关键词：
animal welfare; chick embryo; gender difference; machine learning; signal processing;
D O I：
10.37221/eaef.14.2_45
中图分类号：
学科分类号：
摘要：
Culling of male day-old chicks in layer production is a big global ethical issue. As gender differences exist in the activity of human fetuses, such a physiological difference may also be true for chick embryos. Hence, this study investigated embryo (ROSS 308) gender differences based on this body motility. A near-infrared (NIR) sensor was used to measure embryo motility and separated it in frequency domain. Principal component (PC) scores from body motility strength (i.e., signal power in frequency domain) were used for gender classification using machine learning approach. The formation of sex organ and hormonal differences to be the reason for the male to be significantly more active (p ＜0.05). The findings could contribute to resolving animal welfare issue. © 2021 Elsevier B.V.. All rights reserved.
引用
收藏
页码：45 / 53
页数：8
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