Abstract:

Brown rice stored at different conditions was analyzed by using an electronic nose (PEN3) from Airsense Company in Germany. Response values of PEN3 were subjected to principal component analysis (PCA) and linear discrimination analysis (LDA). Results indicated that electronic nose could identify brown rice samples stored at different temperatures and moisture by PCA and LDA methods. In addition, brown rice samples stored in different temperatures and O2 concentrations also could be well distinguished using LDA method, but the total contribution rate of LDA was lower than that of PCA. The water content and temperature had more significant effect on the response values of electronic nose than oxygen concentration. A crossinteraction was also observed between water content and temperature. The Loadings analysis proved that sensors W5C and W1S in the electronic nose PEN3 have an important impact during the detection, which could provide the guidance to optimize and screen matrix arrangement for better performance of electronic nose.

Key words: brown rice storage conditions, electronic nose, linear discrimination analysis (LDA), principal component analysis (PCA)