Analysis of Volatile Bread Aroma for Evaluation of Bread Freshness Using an Electronic Nose (E-Nose)

ABSTRACT

This paper presents the use of a tin-oxide sensor array and self-organized map (SOM)-based E-nose for analysis of volatile bread aroma and explores its ability to cluster bread odor data according to the freshness of bread. A low cost tin-oxide sensor array based electronic nose system has been used for the classification of state of freshness of bread. The sensor data was acquired for a period of 3 weeks, and an unsupervised self-organizing map (SOM) model was trained using this data to correlate the sensor response to classify the bread as fresh and stale. A comparative evaluation of 3 week' of bread data was carried out using the SOM. The results suggest that the system developed is able to predict the state of bread as fresh and stale up to 98% accuracy if the test bread data sets are of the same week. The classification accuracy reduces to 75–85% if test bread data sets are from different weeks. The model is also applied on three different brands of bread and similar classification results are obtained.

Keywords:

• Bread flavors
• Bread freshness
• Code book vector
• Electronic nose
• Euclidean distance
• Fresh
• Quality control
• Self-organizing map (SOM)
• Shelf life
• Stale
• Tin oxide sensors

ACKNOWLEDGMENT

The authors B. Botre and D. Gharpure thank CSIR, India, for financial support.

Notes

W1, W2, and W3: Test bread data of week 1, 2, and 3, respectively. SOM1, SOM2, and SOM3: SOM model for week 1, 2, and 3 training data set, respectively.