To study the effectiveness of classification algorithms in cigarette sensory quality evaluation, chemical components such as total sugar, protein, potassium, etc. are taken as condition attributes, and ID3, C4.5, rough set, BP neural network, support vector machine, and k-nearest-neighbor are adopted to predict cigarette sensory quality index, such as luster, aroma, harmony, offensive odor, irritation and aftertaste. The experimental results show that harmony reaches the best classification accuracy with about 95%, and the effectiveness of luster and offensive odor are slightly below the harmony with 85%-90% by SVM and KNN, while aroma has the worst result. In addition, offensive odor and aftertaste are fairly accurate with about 70%. As a whole, SVM and KNN have the better performance in the prediction of cigarette sensory quality than the other classification algorithms.

The application of data mining in cigarette sensory quality evaluation: An experimental study

The chemical components of tobacco leaf determine the quality of tobacco leaf. Based on the tobacco named Yunyan 87 in this paper, we analyzed the relationship between the three tobacco leaf grades of B2F, C3F, X2F and its main chemical components. Further, the multi-class logistic regression model was used to explore the differences in the effects of different chemical components on tobacco leaf grades. The results showed that total alkaloid, total nitrogen, reducing sugar, total sugar, potassium and starch had significant effects on tobacco leaf grades. Compared with grade X2F, reducing sugar and potassium had negative impact on the relative probability of grade B2F and grade C3F, while total alkaloid, total nitrogen, total sugar and starch had positive impact on the relative probability of grade B2F and grade C3F.

Research on the Effect of Chemical Component on Tobacco Grading

To analyze the influence of main chemical indices of flue-cured tobacco on overall sensory coziness.35 tobacco chemical indices in 50 domestic and imported representative tobacco leaves were analyzed and verified.Meanwhile,a comprehensive sensory coziness evaluation was conducted on the 50 samples.The data of chemical indicators and sensory evaluation were analyzed by multiple correlation coefficient method.The results showed that: nicotine,ratio of N to nicotine,the ratio of reducing sugar to nicotine,petroleum ether extracts and sensory comfort as a whole was significantly related(P 0.05).Other chemical parameters and sensory coziness of 10 indice correlation scores were not statistically significant(P 0.05).According to the multiple correlation coefficient and significance level,the specific influence degree order of main chemical components of tobacco on the sensory comfort was nicotine ratio of N to nicotine the ratio of reducing sugar to nicotine petroleum ether extract.

Correlation Analysis of Sensory Coziness and Main Chemical Indices of Flue-cured Tobacco

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Correlation Analysis of Sensory Coziness and Main Chemical Indices of Flue-cured Tobacco