Tobacco Science and Technology
Tobacco Science and Technology is a peer reviewed journal since 2013 up to now. The journal is monthly publishing journal.The main scope of Tobacco Science and Technology) is Agricultural engineering/Agricultural science, Biological Engineering/ Biological science, bio-chemistry, chemistry, public health, pharmaceutical science and so on. Our journal welcome original papers from everywhere in the world.
Volume 58 , Issue 04
20 Nov 2025SUBMISSION DEADLINE
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Volume - 58 , Issue 04
30 Nov 2025PUBLISH ON
AIM AND SCOPES
Tobacco Science and Technology
Agricultural engineering
Agricultural science
Biological Engineering
Biological science
bio-chemistry
chemistry
public health
pharmaceutical science
All Published Jurnal
Tobacco Science and Technology
Effects of cigarette circumference and filter ventilation rate on releases of alkaline aroma components in mainstream cigarette smoke
In order to study the effect of circumference and filter ventilation rate on the release of alkaline flavor components in cigarette mainstream smoke, CH2Cl2 extraction and GC/MS analysis were used to measure the mainstream smoke of cigarette samples with different circumference and filter ventilation. The release amount of 21 kinds of basic flavor components in tobacco. The results showed that: The various basic flavor components and the total amount of basic flavor components released per gram of shredded tobacco showed an increasing trend with the increase of the circumference of the ciga
Counting method for filter rods based on Canny operator
In order to improve the accuracy of image edge detection, this paper studies the adaptive image edge detection technology based on discrete algorithm and classical Canny operator. First, the traditional sub-pixel edge detection method is illustrated based on the related literature research. Then, Canny operator is used for detection, the edge model of the quadric curve is established using discrete data, and the adaptive image edge parameters are obtained using one-dimensional gray moment. Experimental results show that the accuracy of feature detection is 99%, which can be applied to the p