Chotimah, Khalid Saifullah, Fitri Nur Laily, Mayumi Puspita, Kombo Othman Kombo, Shidiq Nur Hidayat, Eko Tri Sulistyani, Wahyono, Kuwat Triyana
{"title":"电子鼻监测真空包装鸡肉在室温和冷藏条件下的新鲜度","authors":"Chotimah, Khalid Saifullah, Fitri Nur Laily, Mayumi Puspita, Kombo Othman Kombo, Shidiq Nur Hidayat, Eko Tri Sulistyani, Wahyono, Kuwat Triyana","doi":"10.1007/s11694-024-02847-6","DOIUrl":null,"url":null,"abstract":"<p>Monitoring chicken meat is a crucial process for food safety and consumer health, as it helps prevent the growth of harmful bacteria, minimizing the risk of foodborne illnesses. Currently, electronic nose (E-nose) technology plays a significant role in food quality assessment as it can detect changes in volatile compounds associated with food freshness. In this study, a self-designed, cost-efficient E-nose system was introduced to evaluate the freshness and bacterial growth of vacuum-packaged chicken meat stored at room temperature and refrigerator at 4 °C. Polynomial feature extraction with varying degrees was employed to extract important information from the sensor responses. Principal component analysis (PCA) and linear discriminant analysis (LDA) were implemented for data dimensionality reduction and classification. A support vector regression (SVR) model was built and employed to evaluate the bacteria population based on response patterns from the E-nose device. The LDA results clearly showed the classification of chicken meat freshness corresponding to different storage days and temperatures. The E-nose device with the SVR model combined with extracted parameters using a 2-degree polynomial provided good prediction results for the bacteria population with high <span>\\(\\:{{\\text{R}}_{\\text{T}}}^{2}\\)</span> scores of 0.99 and 0.99, <span>\\(\\:{{\\text{R}}_{\\text{C}\\text{V}}}^{2}\\)</span>scores of 0.97 and 0.93, and minimum <span>\\(\\:{\\text{R}\\text{M}\\text{S}\\text{E}}_{\\text{T}}\\)</span> scores of 0.08 and 0.11 log <span>\\(\\:\\text{C}\\text{f}\\text{u}/\\text{g}\\)</span>, and <span>\\(\\:{\\text{R}\\text{M}\\text{S}\\text{E}}_{\\text{C}\\text{V}}\\)</span> scores of 0.24 and 0.30 log <span>\\(\\:\\text{C}\\text{f}\\text{u}/\\text{g}\\)</span>, at room and refrigerated temperatures, respectively. The results indicate that the developed E-nose system could be used as a fast, portable, low-cost, and non-destructive measurement tool in evaluating the bacterial growth of chicken meat with high relative accuracy.</p>","PeriodicalId":631,"journal":{"name":"Journal of Food Measurement and Characterization","volume":"305 1","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Electronic nose-based monitoring of vacuum-packaged chicken meat freshness in room and refrigerated storage\",\"authors\":\"Chotimah, Khalid Saifullah, Fitri Nur Laily, Mayumi Puspita, Kombo Othman Kombo, Shidiq Nur Hidayat, Eko Tri Sulistyani, Wahyono, Kuwat Triyana\",\"doi\":\"10.1007/s11694-024-02847-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Monitoring chicken meat is a crucial process for food safety and consumer health, as it helps prevent the growth of harmful bacteria, minimizing the risk of foodborne illnesses. Currently, electronic nose (E-nose) technology plays a significant role in food quality assessment as it can detect changes in volatile compounds associated with food freshness. In this study, a self-designed, cost-efficient E-nose system was introduced to evaluate the freshness and bacterial growth of vacuum-packaged chicken meat stored at room temperature and refrigerator at 4 °C. Polynomial feature extraction with varying degrees was employed to extract important information from the sensor responses. Principal component analysis (PCA) and linear discriminant analysis (LDA) were implemented for data dimensionality reduction and classification. A support vector regression (SVR) model was built and employed to evaluate the bacteria population based on response patterns from the E-nose device. The LDA results clearly showed the classification of chicken meat freshness corresponding to different storage days and temperatures. The E-nose device with the SVR model combined with extracted parameters using a 2-degree polynomial provided good prediction results for the bacteria population with high <span>\\\\(\\\\:{{\\\\text{R}}_{\\\\text{T}}}^{2}\\\\)</span> scores of 0.99 and 0.99, <span>\\\\(\\\\:{{\\\\text{R}}_{\\\\text{C}\\\\text{V}}}^{2}\\\\)</span>scores of 0.97 and 0.93, and minimum <span>\\\\(\\\\:{\\\\text{R}\\\\text{M}\\\\text{S}\\\\text{E}}_{\\\\text{T}}\\\\)</span> scores of 0.08 and 0.11 log <span>\\\\(\\\\:\\\\text{C}\\\\text{f}\\\\text{u}/\\\\text{g}\\\\)</span>, and <span>\\\\(\\\\:{\\\\text{R}\\\\text{M}\\\\text{S}\\\\text{E}}_{\\\\text{C}\\\\text{V}}\\\\)</span> scores of 0.24 and 0.30 log <span>\\\\(\\\\:\\\\text{C}\\\\text{f}\\\\text{u}/\\\\text{g}\\\\)</span>, at room and refrigerated temperatures, respectively. 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引用次数: 0
摘要
监测鸡肉是食品安全和消费者健康的关键过程,因为它有助于防止有害细菌的滋生,最大限度地降低食源性疾病的风险。目前,电子鼻(E-nose)技术在食品质量评估中发挥着重要作用,因为它可以检测与食品新鲜度相关的挥发性化合物的变化。在这项研究中,采用了一种自主设计、经济高效的电子鼻系统,用于评估真空包装鸡肉在室温和 4 °C 冰箱中的新鲜度和细菌生长情况。该系统采用了不同程度的多项式特征提取,以从传感器响应中提取重要信息。采用主成分分析(PCA)和线性判别分析(LDA)进行数据降维和分类。根据电子鼻设备的响应模式,建立并使用了支持向量回归(SVR)模型来评估细菌种群。LDA 结果清楚地显示了与不同储存天数和温度相对应的鸡肉新鲜度分类。电子鼻装置与 SVR 模型相结合,使用 2 度多项式提取参数,为细菌种群提供了良好的预测结果,\(\:{{text{R}}_\{text{T}}}^{2}\)得分高达 0.99 和 0.99,\(\:{{text{R}}_{text{C}/text{V}}}^{2}\)得分为 0.97 和 0.93, and minimum \(\:{\text{R}\text{M}\text{S}\text{E}}_{\text{T}}\) scores of 0.08 and 0.11 log \(\:\text{C}\text{f}\text{u}/\text{g}\), and \(\:{\text{R}\text{M}\text{S}\text{E}}_{text{C}\text{V}}\) scores of 0.在室温和冷藏温度下分别为 0.24 和 0.30 log (\:\text{C}\text{f}\text{u}/\text{g})。结果表明,所开发的电子鼻系统可作为一种快速、便携、低成本和非破坏性的测量工具,以较高的相对准确度评估鸡肉中细菌的生长情况。
Electronic nose-based monitoring of vacuum-packaged chicken meat freshness in room and refrigerated storage
Monitoring chicken meat is a crucial process for food safety and consumer health, as it helps prevent the growth of harmful bacteria, minimizing the risk of foodborne illnesses. Currently, electronic nose (E-nose) technology plays a significant role in food quality assessment as it can detect changes in volatile compounds associated with food freshness. In this study, a self-designed, cost-efficient E-nose system was introduced to evaluate the freshness and bacterial growth of vacuum-packaged chicken meat stored at room temperature and refrigerator at 4 °C. Polynomial feature extraction with varying degrees was employed to extract important information from the sensor responses. Principal component analysis (PCA) and linear discriminant analysis (LDA) were implemented for data dimensionality reduction and classification. A support vector regression (SVR) model was built and employed to evaluate the bacteria population based on response patterns from the E-nose device. The LDA results clearly showed the classification of chicken meat freshness corresponding to different storage days and temperatures. The E-nose device with the SVR model combined with extracted parameters using a 2-degree polynomial provided good prediction results for the bacteria population with high \(\:{{\text{R}}_{\text{T}}}^{2}\) scores of 0.99 and 0.99, \(\:{{\text{R}}_{\text{C}\text{V}}}^{2}\)scores of 0.97 and 0.93, and minimum \(\:{\text{R}\text{M}\text{S}\text{E}}_{\text{T}}\) scores of 0.08 and 0.11 log \(\:\text{C}\text{f}\text{u}/\text{g}\), and \(\:{\text{R}\text{M}\text{S}\text{E}}_{\text{C}\text{V}}\) scores of 0.24 and 0.30 log \(\:\text{C}\text{f}\text{u}/\text{g}\), at room and refrigerated temperatures, respectively. The results indicate that the developed E-nose system could be used as a fast, portable, low-cost, and non-destructive measurement tool in evaluating the bacterial growth of chicken meat with high relative accuracy.
期刊介绍:
This interdisciplinary journal publishes new measurement results, characteristic properties, differentiating patterns, measurement methods and procedures for such purposes as food process innovation, product development, quality control, and safety assurance.
The journal encompasses all topics related to food property measurement and characterization, including all types of measured properties of food and food materials, features and patterns, measurement principles and techniques, development and evaluation of technologies, novel uses and applications, and industrial implementation of systems and procedures.