Detecting Fertility and Early Embryo Development of Chicken Eggs Using Near-Infrared Hyperspectral Imaging

TLDR: A perfect detection of fertility prior to incubation was obtained and promising results were obtained when only the first three bands with maximum response of spectral transmission characteristics were used, which indicated the potential in applying hyperspectral imaging techniques to develop a real-time system for detecting fertility and early embryo development of chicken eggs.

Abstract: Early detection of infertile and non-hatchable eggs would benefit hatcheries and poultry breeding farms by saving space, handling costs, and preventing contamination from exploder eggs. Therefore, it would be advantageous to the hatchery industry of developing a non-destructive, rapid, and accurate method to detect the fertility and embryo development of eggs. For this purpose, a near-infrared hyperspectral imaging system was developed to detect fertility and early embryo development. A total of 174 white-shell chicken eggs including 156 fertile eggs and 18 infertile eggs were used in this study and all eggs were incubated in a commercial incubator for 4 days. Hyperspectral images were captured for all eggs on each day of incubation. After imaging on each day, developing embryos in randomly selected eggs were stopped by injecting sodium azide (NaN3). All the eggs were divided into two classes, fertile eggs and non-fertile eggs (including infertile eggs and dead embryos), and the data set of each class varied with day of incubation. The region of interest (ROI) of each hyperspectral image was segmented and the image texture information was extracted from the ROI of spectral images using Gabor filters. Two types of spectral transmission characteristics termed MS and MG, were obtained by averaging the spectral information of ROI and Gabor-filtered ROI, respectively. The dimensionality of the spectral transmission characteristics were reduced by PCA. The first three PCs were used for K-means clustering, as well as the first three bands with maximum responses of each spectral transmission characteristic. The best classification results were 100 % at day 0, 78.8 % at day 1, 74.1 % at day 2, 81.8 % at day 3, and 84.1 % at day 4. A perfect detection of fertility prior to incubation was obtained using only the first three bands of maximum responses of MS. The classification results suggested the usefulness of the image texture information for detection of early embryo development. Promising results were also obtained when only the first three bands with maximum response of spectral transmission characteristics were used, which indicated the potential in applying hyperspectral imaging techniques to develop a real-time system for detecting fertility and early embryo development of chicken eggs.