Sisay Mebre Abie, Paweł Suliga, Bjørg Egelandsdal, Daniel Münch
{"title":"将生物阻抗作为对普遍存在的火腿质量缺陷进行主观、目测评分的替代工具。","authors":"Sisay Mebre Abie, Paweł Suliga, Bjørg Egelandsdal, Daniel Münch","doi":"10.2478/joeb-2024-0008","DOIUrl":null,"url":null,"abstract":"<p><p>The detection of meat quality defects can involve both subjective and objective methods. PSE-like meat is linked to a common pork defect and can be caused by rapid post-mortem damage of muscle fibers. This damage can again be linked to various factors, such as a low ultimate pH or a higher slaughter weight. PSE-like defects are characterized by discoloration, structural damage, and excessive moisture loss. However, the lack of suitable instrument-based methods makes the detection of PSE-like defects difficult, and subjective methods typically suffer from poorer reproducibility. The objective of this study was to establish how subjective visual evaluation correlates with electrical impedance spectroscopy and with traditional quality parameters. To do so, visual scoring was performed together with measurements of bioimpedance, color, and pH in two ham muscles (Adductor, Semimembranosus) for 136 animals 24-hours post-mortem. When comparing with visual scoring, Pearson correlation analysis shows the strongest correlation for bioimpedance (<i>P<sub>y</sub></i> , r = -0.46, R<sup>2</sup> = 21%), followed by pH<sub>u</sub> (r = 0.44, R<sup>2</sup> = 19%). When using all five quality measures, i.e., <i>P<sub>y</sub></i> , pH<sub>u</sub>, and CIELAB <i>L</i> <sup>*</sup> <i>a</i> <sup>*</sup> <i>b</i> <sup>*</sup>, the multivariate regression model had a prediction error of 0.76 for the visual scores. This was close to the error describing the subjective bias of visual scoring, more specifically the prediction error between the two observers (0.85). In all, <i>P<sub>y</sub></i> showed the strongest correlation among instrument-based quality tests and alone may be used for predicting pork ham structural defects, i.e., as an instrument-based alternative for subjective, visual scoring. However, an instrument that combines <i>P<sub>y</sub></i> with pH and/or <i>L</i>*<i>a</i>*<i>b</i>* would improve the prediction of PSE-like quality defects.</p>","PeriodicalId":38125,"journal":{"name":"Journal of Electrical Bioimpedance","volume":"15 1","pages":"75-84"},"PeriodicalIF":0.0000,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11213458/pdf/","citationCount":"0","resultStr":"{\"title\":\"Bioimpedance as an alternative tool for subjective, visual scoring of a prevalent ham quality defect.\",\"authors\":\"Sisay Mebre Abie, Paweł Suliga, Bjørg Egelandsdal, Daniel Münch\",\"doi\":\"10.2478/joeb-2024-0008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The detection of meat quality defects can involve both subjective and objective methods. PSE-like meat is linked to a common pork defect and can be caused by rapid post-mortem damage of muscle fibers. This damage can again be linked to various factors, such as a low ultimate pH or a higher slaughter weight. PSE-like defects are characterized by discoloration, structural damage, and excessive moisture loss. However, the lack of suitable instrument-based methods makes the detection of PSE-like defects difficult, and subjective methods typically suffer from poorer reproducibility. The objective of this study was to establish how subjective visual evaluation correlates with electrical impedance spectroscopy and with traditional quality parameters. To do so, visual scoring was performed together with measurements of bioimpedance, color, and pH in two ham muscles (Adductor, Semimembranosus) for 136 animals 24-hours post-mortem. When comparing with visual scoring, Pearson correlation analysis shows the strongest correlation for bioimpedance (<i>P<sub>y</sub></i> , r = -0.46, R<sup>2</sup> = 21%), followed by pH<sub>u</sub> (r = 0.44, R<sup>2</sup> = 19%). When using all five quality measures, i.e., <i>P<sub>y</sub></i> , pH<sub>u</sub>, and CIELAB <i>L</i> <sup>*</sup> <i>a</i> <sup>*</sup> <i>b</i> <sup>*</sup>, the multivariate regression model had a prediction error of 0.76 for the visual scores. This was close to the error describing the subjective bias of visual scoring, more specifically the prediction error between the two observers (0.85). In all, <i>P<sub>y</sub></i> showed the strongest correlation among instrument-based quality tests and alone may be used for predicting pork ham structural defects, i.e., as an instrument-based alternative for subjective, visual scoring. However, an instrument that combines <i>P<sub>y</sub></i> with pH and/or <i>L</i>*<i>a</i>*<i>b</i>* would improve the prediction of PSE-like quality defects.</p>\",\"PeriodicalId\":38125,\"journal\":{\"name\":\"Journal of Electrical Bioimpedance\",\"volume\":\"15 1\",\"pages\":\"75-84\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11213458/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Electrical Bioimpedance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/joeb-2024-0008\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"Biochemistry, Genetics and Molecular Biology\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Electrical Bioimpedance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/joeb-2024-0008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
引用次数: 0
摘要
肉质缺陷的检测可采用主观和客观两种方法。PSE 样肉与常见的猪肉缺陷有关,可能是由于肌肉纤维在死后迅速受损造成的。这种损伤也可能与各种因素有关,如最终 pH 值偏低或屠宰重量偏高。PSE 类缺陷的特点是变色、结构损坏和水分损失过多。然而,由于缺乏合适的仪器检测方法,因此很难检测出 PSE 类缺陷,而且主观检测方法的重现性通常较差。本研究的目的是确定主观视觉评估与电阻抗光谱仪和传统质量参数的相关性。为此,对 136 只动物死后 24 小时的两块火腿肌肉(内收肌、半膜肌)进行了视觉评分,同时测量了生物阻抗、颜色和 pH 值。与目测评分相比,皮尔逊相关分析表明,生物阻抗的相关性最强(Py ,r = -0.46,R2 = 21%),其次是 pHu(r = 0.44,R2 = 19%)。当使用所有五个质量测量指标,即 Py、pHu 和 CIELAB L * a * b * 时,多元回归模型对视觉评分的预测误差为 0.76。这与描述视觉评分主观偏差的误差接近,更确切地说,是两个观察者之间的预测误差(0.85)。总之,在基于仪器的质量检测中,Py 的相关性最强,可单独用于预测猪肉火腿的结构缺陷,即作为基于仪器的主观目测评分的替代方法。不过,将 Py 与 pH 值和/或 L*a*b* 结合使用的仪器将能更好地预测类似 PSE 的质量缺陷。
Bioimpedance as an alternative tool for subjective, visual scoring of a prevalent ham quality defect.
The detection of meat quality defects can involve both subjective and objective methods. PSE-like meat is linked to a common pork defect and can be caused by rapid post-mortem damage of muscle fibers. This damage can again be linked to various factors, such as a low ultimate pH or a higher slaughter weight. PSE-like defects are characterized by discoloration, structural damage, and excessive moisture loss. However, the lack of suitable instrument-based methods makes the detection of PSE-like defects difficult, and subjective methods typically suffer from poorer reproducibility. The objective of this study was to establish how subjective visual evaluation correlates with electrical impedance spectroscopy and with traditional quality parameters. To do so, visual scoring was performed together with measurements of bioimpedance, color, and pH in two ham muscles (Adductor, Semimembranosus) for 136 animals 24-hours post-mortem. When comparing with visual scoring, Pearson correlation analysis shows the strongest correlation for bioimpedance (Py , r = -0.46, R2 = 21%), followed by pHu (r = 0.44, R2 = 19%). When using all five quality measures, i.e., Py , pHu, and CIELAB L*a*b*, the multivariate regression model had a prediction error of 0.76 for the visual scores. This was close to the error describing the subjective bias of visual scoring, more specifically the prediction error between the two observers (0.85). In all, Py showed the strongest correlation among instrument-based quality tests and alone may be used for predicting pork ham structural defects, i.e., as an instrument-based alternative for subjective, visual scoring. However, an instrument that combines Py with pH and/or L*a*b* would improve the prediction of PSE-like quality defects.