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Discriminating Eggs from Two Local Breeds Based on Fatty Acid Profile and Flavor Characteristics Combined with Classification Algorithms
This study discriminated fatty acid profile and flavor characteristics of Beijing You Chicken (BYC) as a precious local breed and Dwarf Beijing You Chicken (DBYC) eggs. Fatty acid profile and flavor characteristics were analyzed to identify differences between BYC and DBYC eggs. Four classification...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Korean Society for Food Science of Animal Resources
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8564318/ https://www.ncbi.nlm.nih.gov/pubmed/34796322 http://dx.doi.org/10.5851/kosfa.2021.e47 |
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author | Dong, Xiao-Guang Gao, Li-Bing Zhang, Hai-Jun Wang, Jing Qiu, Kai Qi, Guang-Hai Wu, Shu-Geng |
author_facet | Dong, Xiao-Guang Gao, Li-Bing Zhang, Hai-Jun Wang, Jing Qiu, Kai Qi, Guang-Hai Wu, Shu-Geng |
author_sort | Dong, Xiao-Guang |
collection | PubMed |
description | This study discriminated fatty acid profile and flavor characteristics of Beijing You Chicken (BYC) as a precious local breed and Dwarf Beijing You Chicken (DBYC) eggs. Fatty acid profile and flavor characteristics were analyzed to identify differences between BYC and DBYC eggs. Four classification algorithms were used to build classification models. Arachidic acid, oleic acid (OA), eicosatrienoic acid, docosapentaenoic acid (DPA), hexadecenoic acid, monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), unsaturated fatty acids (UFA) and 35 volatile compounds had significant differences in fatty acids and volatile compounds by gas chromatography-mass spectrometry (GC-MS) (p<0.05). For fatty acid data, k-nearest neighbor (KNN) and support vector machine (SVM) got 91.7% classification accuracy. SPME-GC-MS data failed in classification models. For electronic nose data, classification accuracy of KNN, linear discriminant analysis (LDA), SVM and decision tree was all 100%. The overall results indicated that BYC and DBYC eggs could be discriminated based on electronic nose with suitable classification algorithms. This research compared the differentiation of the fatty acid profile and volatile compounds of various egg yolks. The results could be applied to evaluate egg nutrition and distinguish avian eggs. |
format | Online Article Text |
id | pubmed-8564318 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Korean Society for Food Science of Animal Resources |
record_format | MEDLINE/PubMed |
spelling | pubmed-85643182021-11-17 Discriminating Eggs from Two Local Breeds Based on Fatty Acid Profile and Flavor Characteristics Combined with Classification Algorithms Dong, Xiao-Guang Gao, Li-Bing Zhang, Hai-Jun Wang, Jing Qiu, Kai Qi, Guang-Hai Wu, Shu-Geng Food Sci Anim Resour Article This study discriminated fatty acid profile and flavor characteristics of Beijing You Chicken (BYC) as a precious local breed and Dwarf Beijing You Chicken (DBYC) eggs. Fatty acid profile and flavor characteristics were analyzed to identify differences between BYC and DBYC eggs. Four classification algorithms were used to build classification models. Arachidic acid, oleic acid (OA), eicosatrienoic acid, docosapentaenoic acid (DPA), hexadecenoic acid, monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), unsaturated fatty acids (UFA) and 35 volatile compounds had significant differences in fatty acids and volatile compounds by gas chromatography-mass spectrometry (GC-MS) (p<0.05). For fatty acid data, k-nearest neighbor (KNN) and support vector machine (SVM) got 91.7% classification accuracy. SPME-GC-MS data failed in classification models. For electronic nose data, classification accuracy of KNN, linear discriminant analysis (LDA), SVM and decision tree was all 100%. The overall results indicated that BYC and DBYC eggs could be discriminated based on electronic nose with suitable classification algorithms. This research compared the differentiation of the fatty acid profile and volatile compounds of various egg yolks. The results could be applied to evaluate egg nutrition and distinguish avian eggs. Korean Society for Food Science of Animal Resources 2021-11 2021-11-01 /pmc/articles/PMC8564318/ /pubmed/34796322 http://dx.doi.org/10.5851/kosfa.2021.e47 Text en © Korean Society for Food Science of Animal Resources https://creativecommons.org/licenses/by-nc/3.0/This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Article Dong, Xiao-Guang Gao, Li-Bing Zhang, Hai-Jun Wang, Jing Qiu, Kai Qi, Guang-Hai Wu, Shu-Geng Discriminating Eggs from Two Local Breeds Based on Fatty Acid Profile and Flavor Characteristics Combined with Classification Algorithms |
title | Discriminating Eggs from Two Local Breeds Based on Fatty Acid Profile
and Flavor Characteristics Combined with Classification
Algorithms |
title_full | Discriminating Eggs from Two Local Breeds Based on Fatty Acid Profile
and Flavor Characteristics Combined with Classification
Algorithms |
title_fullStr | Discriminating Eggs from Two Local Breeds Based on Fatty Acid Profile
and Flavor Characteristics Combined with Classification
Algorithms |
title_full_unstemmed | Discriminating Eggs from Two Local Breeds Based on Fatty Acid Profile
and Flavor Characteristics Combined with Classification
Algorithms |
title_short | Discriminating Eggs from Two Local Breeds Based on Fatty Acid Profile
and Flavor Characteristics Combined with Classification
Algorithms |
title_sort | discriminating eggs from two local breeds based on fatty acid profile
and flavor characteristics combined with classification
algorithms |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8564318/ https://www.ncbi.nlm.nih.gov/pubmed/34796322 http://dx.doi.org/10.5851/kosfa.2021.e47 |
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