Non-Destructive Assessment of Chicken Egg Fertility

Abstract

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.

Chicken Egg Fertility Identification using FOS and BP-Neural Networks on Image Processing

“…Kurtosis (𝑎4) is a calculation of the relative sharpness of the histogram curve of an image using components such as the standard deviation to the power of 4 and the standard deviation divisor (6).…”

“…The identification process is carried out using the observation method using light directed at the egg so that the contents of the egg can be seen (candling) [1]- [3]. This identification is still being made manually (done by humans) [1], [4], or there are already several tools from various studies [5], [6], both simulators and implementations [7]- [9]. Even though the tools already exist, there are still many researchers doing development to get better results.…”

“…Image processing in the identification of egg embryos begins with image acquisition which has different methods and tools [4], [11], [12]. Several acquisition processes were carried out using thermal cameras [6], [13], hyperspectral [6], [7], [10], and digital cameras [4], [14]. This study uses a smartphone camera and a candling process to obtain a digital image.…”

Functional assessment of avian embryo quality during incubation

“…Неоплодотворенные яйца составляют до 20 % из всего объема инкубированных яиц курицы [6]. Эти яйца при своевременном обнаружении можно, не только исключить из производственного процесса, но и использовать в пищу (для низкосортной продукции), тем самым увеличив экономические показатели производства.…”

“…Авторы публикации [6] рассматривают существующие методы неразрушающего контроля, включая ультразвуковые и диэлектрические измерения, тепловую визуализацию, машинное зрение, спектроскопию и гиперспектральную визуализацию. Представлена технология гиперспектральной съемки, как метод, адекватный для решения проблемы классификации фертильности куриных яиц.…”