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

被引:1
|
作者
L. Liu
M. O. Ngadi
机构
[1] McGill University,Department of Bioresource Engineering
来源
关键词
Hyperspectral imaging; Egg; Fertility; Embryo development; Image texture; Gabor filter; PCA; -means clustering;
D O I
暂无
中图分类号
学科分类号
摘要
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.
引用
收藏
页码:2503 / 2513
页数:10
相关论文
共 50 条
  • [21] Monitoring Polyurethane Foaming Reactions Using Near-Infrared Hyperspectral Imaging
    Chen, Xiaoyun
    Patankar, Kshitish A.
    Larive, Matthew
    APPLIED SPECTROSCOPY, 2021, 75 (01) : 46 - 56
  • [22] Prediction of sorghum oil content using near-infrared hyperspectral imaging
    Mendoza, Princess Tiffany D.
    Armstrong, Paul R.
    Peiris, Kamaranga H. S.
    Siliveru, Kaliramesh
    Bean, Scott R.
    Pordesimo, Lester O.
    CEREAL CHEMISTRY, 2023, 100 (03) : 775 - 783
  • [23] Early Detection of Bruises on Apples Using Near-infrared Hyperspectral Image
    Huang, Wenqian
    Zhang, Baihai
    Li, Jiangbo
    Zhang, Chi
    PIAGENG 2013: IMAGE PROCESSING AND PHOTONICS FOR AGRICULTURAL ENGINEERING, 2013, 8761
  • [24] Near-Infrared Imaging Using a High-Speed Monitoring Near Infrared Hyperspectral Camera (Compovision)
    Ishikawa, Daitaro
    Motomura, Asako
    Igarashi, Yoko
    Ozaki, Yukihiro
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2015, 35 (04) : 865 - 869
  • [25] Wood density prediction using near-infrared hyperspectral imaging for early selection of Eucalyptus grandis trees
    Roger Chambi-Legoas
    Mario Tomazello-Filho
    Cristiane Vidal
    Gilles Chaix
    Trees, 2023, 37 : 981 - 991
  • [26] Wood density prediction using near-infrared hyperspectral imaging for early selection of Eucalyptus grandis trees
    Chambi-Legoas, Roger
    Tomazello-Filho, Mario
    Vidal, Cristiane
    Chaix, Gilles
    TREES-STRUCTURE AND FUNCTION, 2023, 37 (03): : 981 - 991
  • [27] Near-infrared hyperspectral imaging for grading and classification of pork
    Barbin, Douglas
    Elmasry, Gamal
    Sun, Da-Wen
    Allen, Paul
    MEAT SCIENCE, 2012, 90 (01) : 259 - 268
  • [28] Near-infrared Hyperspectral Imaging of Atherosclerotic Tissue Phantom
    Ishii, K.
    Nagao, R.
    Kitayabu, A.
    Awazu, K.
    CLINICAL AND BIOMEDICAL SPECTROSCOPY AND IMAGING III, 2013, 8798
  • [29] Fabrication and evaluation of a near-infrared hyperspectral imaging system
    Katari, S.
    Wallack, M.
    Huebschman, M.
    Pantano, P.
    Garner, H.
    JOURNAL OF MICROSCOPY, 2009, 236 (01) : 11 - 17
  • [30] Hydration of hydrogels studied by near-infrared hyperspectral imaging
    Caponigro, Vicky
    Marini, Federico
    Gowen, Aoife
    JOURNAL OF CHEMOMETRICS, 2018, 32 (01)