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利用电子鼻评估猪排的细菌腐败情况。

Estimation of bacteriological spoilage of pork cutlets by electronic nose.

作者信息

Horváth Kinga M, Seregély Zs, Dalmadi I, Andrássy Eva, Farkas J

机构信息

Department of Refrigeration and Livestock Products' Technology, Corvinus University of Budapest, H-1118 Budapest, Hungary.

出版信息

Acta Microbiol Immunol Hung. 2007 Jun;54(2):179-94. doi: 10.1556/AMicr.54.2007.2.8.

Abstract

The utility of chemosensor array (EN) signals of head-space volatiles of aerobically stored pork cutlets as a non-invasive technique for monitoring their microbiological load was studied during storage at 4, 8 and 12 degrees C, respectively. The bacteriological quality of the meat samples was determined by standard total aerobic plate counts (TAPC) and colony count of selectively estimated Pseudomonas (PS) spp., the predominant aerobic spoilage bacteria. Statistical analysis of the electronic nose measurements were principal component analysis (PCA), and canonical discriminant analysis (CDA). Partial least squares (PLS) regression was used to model correlation between microbial loads and EN signal responses, the degree of bacteriological spoilage, independently of the temperature of the refrigerated storage. Sensor selection techniques were applied to reduce the dimensionality and more robust calibration models were computed by determining few individual sensors having the smallest cross correlations and highest correlations with the reference data. Correlations between the predicted and "real" values were given on cross-validated data from both data reduced models and for full calibrations using the 23 sensor elements. At the same time, sensorial quality of the raw cutlets was noted subjectively on faultiness of the odour and colour, and drip formation of the samples. These preliminary studies indicated that the electronic nose technique has a potential to detect bacteriological spoilage earlier or at the same time as olfactory quality deterioration.

摘要

研究了在4℃、8℃和12℃储存期间,有氧储存猪排顶空挥发物的化学传感器阵列(EN)信号作为监测其微生物负荷的非侵入性技术的效用。肉样的细菌学质量通过标准总需氧平板计数(TAPC)和选择性估计的假单胞菌(PS)属(主要的需氧腐败细菌)的菌落计数来确定。电子鼻测量的统计分析为主成分分析(PCA)和典型判别分析(CDA)。偏最小二乘(PLS)回归用于对微生物负荷与EN信号响应之间的相关性、细菌腐败程度进行建模,而不考虑冷藏储存温度。应用传感器选择技术来降低维度,并通过确定与参考数据具有最小交叉相关性和最高相关性的少数单个传感器来计算更稳健的校准模型。在数据简化模型的交叉验证数据以及使用23个传感器元件的完全校准中,给出了预测值与“实际”值之间的相关性。同时,根据气味和颜色的缺陷以及样品的滴水形成情况,主观记录了生猪排的感官质量。这些初步研究表明,电子鼻技术有可能在嗅觉质量恶化之前或同时检测到细菌腐败。

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