Comparison of Sensory Qualities in Eggs from Three Breeds Based on Electronic Sensory Evaluations

文献类型： 外文期刊

第一作者： Dong, Xiaoguang

作者： Dong, Xiaoguang;Gao, Libing;Zhang, Haijun;Wang, Jing;Qiu, Kai;Qi, Guanghai;Wu, Shugeng

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关键词： egg; sensory; electronic nose; electronic tongue; discrimination

期刊名称：FOODS （ 影响因子：4.35； 五年影响因子：4.957 ）

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年卷期： 2021 年 10 卷 9 期

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收录情况： SCI

摘要： The present study was conducted on three commercial laying breeder strains to evaluate differences of sensory qualities, including texture, smell, and taste parameters. A total of 140 eggs for each breed were acquired from Beinong No.2 (B) laying hens, Hy-Line Brown (H) laying hens, and Wuhei (W) laying hens. Sensory qualities of egg yolks and albumen from three breeds were detected and discriminated based on different algorithms. Texture profile analysis (TPA) showed that the eggs from three breeds had no differences in hardness, adhesiveness, springiness, and chewiness other than cohesiveness. The smell profiles measured by electronic nose illustrated that differences existed in all 10 sensors for albumen and 8 sensors for yolks. The taste profiles measured by electronic tongue found that the main difference of egg yolks and albumen existed in bitterness and astringency. Principal component analysis (PCA) successfully showed grouping of three breeds based on electronic nose data and failed in grouping based on electronic tongue data. Based on electronic nose data, linear discriminant analysis (LDA), fine k-nearest neighbor (KNN) and linear support vector machine (SVM) were performed to discriminate yolks, albumen, and the whole eggs with 100% classification accuracy. While based on electronic tongue data, the best classification accuracy was 96.7% for yolks by LDA and fine tree, 88.9% for albumen by LDA, and 87.5% for the whole eggs by fine KNN. The experiment results showed that three breeds' eggs had main differences in smells and could be successfully discriminated by LDA, fine KNN, and linear SVM algorithms based on electronic nose.

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