Use of Electronic Nose and Tongue to Track Freshness of Cherry Tomatoes Squeezed for Juice Consumption: Comparison of Different Sensor Fusion Approaches

作者：Hong, Xuezhen; Wang, Jun^*

来源：Food and Bioprocess Technology, 2015, 8(1): 158-170.

DOI：10.1007/s11947-014-1390-y

• Electronic nose
• Electronic tongue
• Cherry tomato juice
• Track freshness
• Feature selection
• Sensor fusion

Fruits freshness is relatively easy to authenticate from their morphological characteristics while the act of processing fruits into juices makes it difficult to track/identify their freshness. Eight datasets, extracted from an e-nose and an e-tongue, and six sensor fusion approaches using both instruments, were applied to detect 100 % juices squeezed from cherry tomatoes with different post-harvest storage times (ST). Discrimination of the juices was mainly performed by canonical discriminant analysis (CDA) and library support vector machines (Lib-SVM). Tracking and prediction of physicochemical qualities (pH, soluble solids content (SSC), Vitamin C (VC), and firmness) of the fruit were performed using principle components regression (PCR). All eight datasets presented good classification results with classifiers trained by e-tongue dataset and fusion dataset 2 (stepwise selection) presented the best classification performances. Though quality regression models trained by either e-nose or e-tongue dataset were not robustness enough, sensor fusion approaches make it possible to build more robust prediction models that can correctly predict quality indices for a totally new juice sample. This study indicates the potential for tracking quality/freshness of fruit squeezed for juice consumption using the e-nose and e-tongue, and that sensor fusion approach would be better than individual utilization only if proper fusion approaches are used.

• 出版日期2015-1
• 单位浙江大学; 中国计量大学