Department of Bioresource Engineering, McGill University,21, 111 Lakeshore Road, Ste-Anne-de-Bellevue, QC H9X 3V9, Canada.
Department of Agricultural and Environmental Engineering, Obafemi Awolowo University, Ile-Ife 220005, Osun State, Nigeria.
Sensors (Basel). 2020 Sep 28;20(19):5546. doi: 10.3390/s20195546.
Total hatching egg set (for both egg production chicks and broilers) in the Agriculture and Agri-Food Canada report 2017 was over 1.0 billion. With the fertility rate for this year observed to be around 82%, there were about 180 million unhatched eggs (worth over 300 million Canadian dollars) incubated in Canada for the year 2017 alone. These non-hatching (non-fertile) eggs can find useful applications as commercial table eggs or low-grade food stock if they can be detected early and isolated accordingly preferably prior to incubation. The conventional method of chicken egg fertility assessment termed candling, is subjective, cumbersome, slow, and eventually inefficient, leading to huge economic losses. Hence, there is a need for a non-destructive, fast and online prediction technology to assist with early chicken egg fertility identification problem. This paper reviewed existing non-destructive approaches including ultrasound and dielectric measurements, thermal imaging, machine vision, spectroscopy, and hyperspectral imaging. Hyperspectral imaging was extensively discussed, being an emerging new technology with great potential. Suggestions were finally proffered towards building futuristic robust model(s) for early detection of chicken egg fertility.
加拿大农业和农业食品部 2017 年的报告显示，总孵化蛋数（包括产蛋小鸡和肉鸡）超过 10 亿。今年的受精率约为 82%，仅 2017 年加拿大就有大约 1.8 亿枚未孵化的鸡蛋（价值超过 3 亿加元）被孵化。这些未孵化的（非受精的）鸡蛋如果能在早期被检测到并相应地隔离，最好是在孵化之前，就可以找到有用的商业用途，如作为商品蛋或低等级的食品原料。传统的鸡蛋受精评估方法——照蛋，具有主观性、繁琐、缓慢且效率低下等缺点，会导致巨大的经济损失。因此，需要一种非破坏性、快速和在线的预测技术来帮助解决早期鸡蛋受精识别问题。本文综述了现有的非破坏性方法，包括超声和介电测量、热成像、机器视觉、光谱学和高光谱成像。高光谱成像被广泛讨论，它是一种具有巨大潜力的新兴新技术。最后提出了建立未来用于早期检测鸡蛋受精的稳健模型的建议。
