College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China.
Meat Sci. 2012 Feb;90(2):373-7. doi: 10.1016/j.meatsci.2011.07.025. Epub 2011 Aug 5.
The aim of this study was to predict the total viable counts (TVC) in chilled pork using an electronic nose (EN) together with support vector machine (SVM). EN and bacteriological measurements were performed on pork samples stored at 4 °C for up to 10 days. Bacterial numbers on pork were determined by plate counts on agar. Principal component analysis (PCA) was used to cluster EN measurements. The model for the correlation between EN signal responses and bacterial numbers was constructed by using the SVM, combined with partial least squares (PLS). Correlation coefficients for training and validation were 0.94 and 0.88, respectively, which suggested that the EN system could be used as a simple and rapid technique for the prediction of bacteria numbers in pork.
本研究旨在利用电子鼻（EN）结合支持向量机（SVM）预测冷藏猪肉中的总活菌数（TVC）。在 4°C 下储存猪肉样品，直至 10 天，对其进行 EN 和细菌学测量。在琼脂上通过平板计数确定猪肉上的细菌数量。采用主成分分析（PCA）对 EN 测量值进行聚类。通过使用 SVM 结合偏最小二乘法（PLS），构建了 EN 信号响应与细菌数量之间的相关模型。训练和验证的相关系数分别为 0.94 和 0.88，这表明 EN 系统可作为一种简单快速的技术，用于预测猪肉中的细菌数量。
