Using machine-learning approaches to investigate the volatile-compound fingerprint of fishy off-flavour from beef with enhanced healthful fatty acids

IF 7.1 1区 农林科学 Q1 Agricultural and Biological Sciences Meat Science Pub Date : 2024-08-24 DOI:10.1016/j.meatsci.2024.109643
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Abstract

Machine learning classification approaches were used to discriminate a fishy off-flavour identified in beef with health-enhanced fatty acid profiles. The random forest approach outperformed (P < 0.001; receiver operating characteristic curve: 99.8 %, sensitivity: 99.9 % and specificity: 93.7 %) the logistic regression, partial least-squares discrimination analysis and the support vector machine (linear and radial) approaches, correctly classifying 100 % and 82 % of the fishy and non-fishy meat samples, respectively. The random forest algorithm identified 20 volatile compounds responsible for the discrimination of fishy from non-fishy meat samples. Among those, seven volatile compounds (pentadecane, octadecane, γ-dodecalactone, dodecanal, (E,E)-2,4-heptadienal, 2-heptanone, and ethylbenzene) were selected as significant contributors to the fishy off-flavour fingerprint, all being related to lipid oxidation. This fishy off-flavour fingerprint could facilitate the rapid monitoring of beef with enhanced healthy fatty acids to avoid consumer dissatisfaction due to fishy off-flavour.

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使用机器学习方法研究添加了健康脂肪酸的牛肉的腥味挥发性化合物特征
采用机器学习分类方法来鉴别牛肉中的腥味和健康强化脂肪酸。随机森林方法的表现优于(P < 0.001;接收器工作特征曲线:99.8 %;灵敏度:99.9 %;特异性:93.7 %):99.8 %,灵敏度:99.9 %,特异性:93.7 %),分别正确分类了 100 % 和 82 % 的腥味和非腥味肉类样品。随机森林算法确定了 20 种挥发性化合物,它们是区分腥味和非腥味肉类样品的主要成分。其中,7 种挥发性化合物(十五烷、十八烷、γ-十二内酯、十二醛、(E,E)-2,4-庚二烯醛、2-庚酮和乙苯)被选为腥味指纹的重要成分,它们都与脂质氧化有关。该腥杂味指纹图谱有助于快速监测健康脂肪酸含量提高的牛肉,避免消费者因腥杂味而产生不满。
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来源期刊
Meat Science
Meat Science 工程技术-食品科技
CiteScore
12.60
自引率
9.90%
发文量
282
审稿时长
60 days
期刊介绍: The aim of Meat Science is to serve as a suitable platform for the dissemination of interdisciplinary and international knowledge on all factors influencing the properties of meat. While the journal primarily focuses on the flesh of mammals, contributions related to poultry will be considered if they enhance the overall understanding of the relationship between muscle nature and meat quality post mortem. Additionally, papers on large birds (e.g., emus, ostriches) as well as wild-captured mammals and crocodiles will be welcomed.
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