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Using 5 grades of conventional cigarette finished tobacco as the research object, multiple linear regression analysis method was used to study the influence of physical indicators of cut tobacco on its rebound characteristics, and a prediction model for tobacco rebound characteristics based on BP neural network was constructed. The results showed that the degree of influence of physical indicators of cut tobacco on the rebound characteristics of tobacco was ranked from large to small as follows: broken tobacco rate>medium tobacco rate>long tobacco rate>filling value>elasticity>moisture content. Among them, medium tobacco rate, long tobacco rate, elasticity, and moisture content were positively correlated with the rebound characteristics of tobacco, while broken tobacco rate and filling value were negatively correlated with the rebound characteristics of tobacco. In the constructed BP neural network prediction model, the comparison between the predicted value of the test set and the true value R² was 0.965 7, the overall model accuracy reached 98. 10%. The difference between the predicted and measured values of cut tobacco rebound characteristics was small, and the model had high prediction accuracy and reliability, which could be used for accurate estimation of cut tobacco rebound characteristics. [ABSTRACT FROM AUTHOR]

In order to study the relationships between shatter resistance index and physical characteristics of tobacco leaves, correlation analysis, factor analysis, and gray correlation analysis were carried out on the tobacco leaves shatter resistance index and physical characteristics index, and the tobacco leaves of different regions were grouped according to the analysis results. The result showed as follows: shatter resistance index of tobacco leaves was significantly positively correlated with tensile strength, elongation, recovery, and thickness, and significantly negatively correlated with brittleness, shear force, cohesion, elasticity, adhesion, and penetration. Fac-1 (determined by tensile strength, cohesion, elasticity, recovery, adhesion, penetration), Fac-2 (determined by shear force, thickness), Fac-3(determined by elongation, brittleness and hardness) and Fac-4 (determined by adhesion) common factors were extracted from 12 physical characteristics, and the cumulative contribution rate was 88. 201%, the contribution rate of Fac-1 is significantly higher than the other three common factors, indicating that Fac-1 had the most significant impact. According to the contribution rate of the common factors and the factor score coefficient matrix, the comprehensive factor score model of the physical characteristics of tobacco leaf was established as F = 0.46FFac-1 +0.23FFac-2 +0.20FFac-3 +0.11FFac-4. Fac-3 had the greatest impact on the shatter resistance index of tobacco leaves, and Fac-4 had the least impact. According to cluster analysis, the tobacco leaves were divided into 4 categories, so that the comprehensive physical characteristics of the same category of tobacco leaves were closer, and the process parameters could be adjusted and processed into groups to reduce the breaking of tobacco leaves during processing. [ABSTRACT FROM AUTHOR]