Identification of green tea grade using different feature of response signal from E-nose sensors

Identification of green tea grade using different feature of response signal from E-nose sensors

Author: Huichun Yu and Jun Wang and Hongmei Zhang and Yong Yu and Cong Yao

Detection of tea grade by a human taste panel is affected by external factors and usually inaccurate, but it might be promising to use an electronic nose (E-nose). In this paper an investigation has been made to determine the grade of different tea samples using an E-nose. Feature vectors of the teas with different quality grade (Labeled: T120, T600, T800, T1200 and T1800) were extracted from the E-nose response signals, and the data were processed by using the principle components analysis (PCA) and linear discriminant analysis (LDA). Using the average and integrated value of feature vectors, 100% correct classification by LDA was achieved for five different tea samples with different qualities. The results indicated that the E-nose was capable of discriminating different grades of green teas.

 

Get the whole article here

Shipping Icon Free Shipping + Free Returns
Subscription Details Icon
We stand behind our teas and teaware, and want you to be not just satisfied with them, but thrilled. If for any reason you're not, just let us know and we'll do our best to make it right.

{property.value} {property.value} {property.value} Include jar: {property.value}
×
You definitely need tools!
Perfect coldbrew everytime
The ideal way to store your matcha
The ideal way to store your matcha