British Poultry Science
Volume 64, 2023 - Issue 2
Management, Production & Environment
Non-invasive classification of single and double-yolk eggs using Vis-NIR spectroscopy and multivariate analysis
M. Syduzzamana Graduate School of Agriculture, Kyoto University, Sakyo-ku, Japan;b Faculty of Agricultural Engineering and Technology, Bangladesh Agricultural University, Mymensingh, Bangladesh
https://orcid.org/0000-0001-8124-7539
https://orcid.org/0000-0001-8124-7539, A. Khaliduzzamana Graduate School of Agriculture, Kyoto University, Sakyo-ku, Japan;c Faculty of Applied Science and Technology, Jashore University of Science and Technology, Jashore, Bangladesh;d Faculty of Agricultural Engineering and Technology, Sylhet Agricultural University, Sylhet, Bangladeshhttps://orcid.org/0000-0001-6621-8430
https://orcid.org/0000-0001-6621-8430, , , , & show all