By a News Reporter-Staff News Editor at Life Science Weekly -- Data detailed on Life Science Research have been presented. According to news reporting from Jiangsu, People’s Republic of China, by NewsRx journalists, research stated, “The double-yolked (DY) egg is quite popular in some Asian countries because it is considered as a sign of good luck, however, the double yolk is one of the reasons why these eggs fail to hatch. The usage of automatic methods for identifying DY eggs can increase the efficiency in the poultry industry by decreasing egg loss during incubation or improving sale proceeds.”
Financial supporters for this research include National Key Technology Research and Development Program of China, National Natural Science Foundation of China (CN), Natural Science Foundation of the Higher Education Institutions of Jiangsu Province.
The news correspondents obtained a quote from the research from Nanjing Agricultural University, “In this study, two methods for DY duck egg identification were developed by using computer vision technology. Transmittance images of DY and single-yolked (SY) duck eggs were acquired by a CCD camera to identify them according to their shape features. The Fisher’s linear discriminant (FLD) model equipped with a set of normalized Fourier descriptors (NFDs) extracted from the acquired images and the convolutional neural network (CNN) model using primary preprocessed images were built to recognize duck egg yolk types. The classification accuracies of the FLD model for SY and DY eggs were 100% and 93.2% respectively, while the classification accuracies of the CNN model for SY and DY eggs were 98% and 98.8% respectively. The CNN-based algorithm took about 0.12 s to recognize one sample image, which was slightly faster than the FLD-based (about 0.20 s).”
According to the news reporters, the research concluded: “Finally, this work compared two classification methods and provided the better method for DY egg identification.”
For more information on this research see: Identification of double-yolked duck egg using computer vision. Plos One , 2017;12(12):e0190054. (Public Library of Science - www.plos.org; Plos One - www.plosone.org)
Our news journalists report that additional information may be obtained by contacting L. Ma, College of Food Science and Technology, Nanjing Agricultural University, Nanjing, Jiangsu, People’s Republic of China. Additional authors for this research include K. Sun, K. Tu, L. Pan and W. Zhang.
The direct object identifier (DOI) for that additional information is: https://doi.org/10.1371/journal.pone.0190054. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.
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CITATION: (2018-01-09), Findings from Nanjing Agricultural University Update Understanding of Life Science Research (Identification of double-yolked duck egg using computer vision), Life Science Weekly, 2977, ISSN: 1552-2474, BUTTER® ID: 014973260
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