Method for representing tobacco stock and product matching degree based on low-tar evaluation index and application thereof

Abstract

The invention relates to a method for representing tobacco stock and product matching degree based on low tar evaluation indexes and application thereof, and the method comprises the following steps: (1) constructing a low tar evaluation index LT database of stock tobacco grades, and classifying tar classes of the stock tobacco grades according to LT values; and (2) calculating an overall guarantee period Z of the stock tobacco leaf grade and a guarantee production period W of each tar category, and representing the matching degree of each tar category stock and a product according to a result. According to the method, the database is constructed by using the low-tar evaluation index LT, the tar categories of the tobacco leaf grades are classified through the model, and the matching degree of the tar category stock and the product plan can be obtained by combining the comparison of the total guarantee period Z of the stock tobacco leaf grades and the guaranteed production period W of each tar category; the method can provide guidance for stock adjustment of tobacco leaf grades.

Description

Technical Field

[0001] The present invention relates to the technical field of tobacco leaves, and in particular to a method for characterizing the degree of matching between tobacco leaf inventory and products based on a low tar evaluation index and an application thereof. Background Art

[0002] Tobacco raw materials are the cornerstone of the development of cigarette industry enterprises. The rapid development of low-tar cigarette products requires not only low tar release of tobacco raw materials, but also the sensory quality of tobacco raw materials must take into account the aroma and satisfaction of tobacco. Therefore, the degree of low tar and high aroma of tobacco raw materials is one of the key factors that determine the quality of low-tar cigarette products. As an agricultural product, the tar release and sensory quality of tobacco leaves are greatly affected by ecology, region, variety, and part. At present, cigarette industry enterprises still count the tobacco raw materials in stock by year, origin, and grade. They cannot accurately judge the tar release level of each grade of tobacco raw materials and their contribution to the aroma, satisfaction, and tar release of the product. They cannot accurately, scientifically and effectively analyze the guarantee ability of tobacco raw materials in stock for products, cannot meet the high-precision raw material guarantee technology required for the rapid development of low-tar cigarettes, and cannot accurately characterize the matching degree between stock tobacco and current products based on their tar release. In addition, due to the particularity of the use of tobacco raw materials (generally they need to be stored in warehouses for 24 to 36 months before they can be used in product formulations), accurate evaluation of the matching degree between different tobacco raw material tar categories and products can help companies plan raw materials for development, lay out in advance, and overcome key technologies to improve raw material security.

[0003] CN115293444A provides a characterization method for the health index of stock tobacco raw materials, which includes the following steps: (1) comprehensive evaluation and functional division of stock tobacco raw materials; (2) application of statistical analysis methods to establish a functional component identification model; (3) functional component statistics of tobacco leaf formulas of various specifications; (4) calculation of the health index of stock tobacco raw materials based on the production plan model. The purpose of this characterization method is to guide the formulation of tobacco grade demand plans, guide tobacco sorting, cutting and formula module design, guide the maintenance of cigarette brand specification leaf group formulas, and improve the strategic guarantee level of tobacco raw materials based on brand production plans, brand raw material requirements and health index characterization results of stock tobacco raw materials.

[0004] CN113554299A discloses a system, method, device and electronic device for evaluating the comprehensive grade quality of tobacco leaves, including: a first storage module, which is used to store sampling inspection data information of tobacco leaves; a first processing module, which is connected to the first storage module, and is used to calculate the weights of tobacco leaves of various grades in various origins and the scores of sampling inspection results of various grades according to the sampling inspection data information, normalize the scores of sampling inspection results of various grades in various origins, and obtain the comprehensive scores of tobacco leaves of various origins according to the comprehensive scores of tobacco leaves quality, which are the sum of the normalized sampling inspection result scores of various grades multiplied by the grade weights of the corresponding grades; a sorting module, which is connected to the first processing module, and is sorted according to the comprehensive scores of tobacco leaves of various origins, and the comprehensive grade quality ranking of the sampled tobacco leaves of various origins is obtained. The system for evaluating the comprehensive grade quality of tobacco leaves improves the problem that the comprehensive grade quality of tobacco leaves of various origins cannot be accurately compared in the prior art.

[0005] The above-mentioned comparative documents do not disclose a method for classifying tobacco grades by comprehensively considering the tar and sensory quality of tobacco leaf samples and characterizing the degree of matching between the inventory of each category and products. Therefore, providing a method for characterizing the degree of matching between tobacco leaf inventory and products based on the low tar evaluation index is of great significance for adjusting the inventory of tobacco leaf grades. Summary of the invention

[0006] In order to solve the above technical problems, the present invention provides a method for characterizing the matching degree between tobacco leaf inventory and products based on low tar evaluation index and its application. The present invention uses low tar evaluation index LT to construct a database, and classifies the tar categories of tobacco leaf grades through the model. At the same time, combined with the comparison of the overall guarantee cycle Z of the inventory tobacco leaf grade and the guaranteed production cycle W of each tar category, the matching degree between the tar category inventory and the pre-production product can be obtained. This method can provide guidance for the inventory adjustment of tobacco leaf grades.

[0007] To achieve this object, the present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides a method for characterizing the degree of matching between tobacco leaf inventory and products based on a low tar evaluation index, the method comprising the following steps:

[0009] (1) Construct a low tar evaluation index (LT) database for stock tobacco grades and classify the tar categories of stock tobacco grades according to LT values;

[0010] The calculation formula of the low tar evaluation index LT is as follows:

[0011]

[0012] Among them, A represents the weight of tobacco, B represents the nicotine in the smoke, C represents the aroma quality, D represents the aroma volume, and J represents the tar release; Indicates the grade of tobacco leaves The average value of Indicates the grade of tobacco leaves The average value of Indicates the grade of tobacco leaves The average value of Indicates the grade of tobacco leaves The average value of

[0013] (2) Calculate the overall guarantee period Z of the inventory tobacco grade and the guaranteed production period W of each tar type, and characterize the matching degree between the inventory and products of each tar type based on the results;

[0014] The calculation formula for the overall guarantee period Z of the stock tobacco grade is as follows:

[0015]

[0016] Where T represents the total inventory of tobacco leaf grades, x n represents the annual output of the nth specification product, y n It indicates the leaf consumption of a single box of cigarettes of the nth specification product;

[0017] The calculation formula for the guaranteed production cycle W of each tar type is as follows:

[0018]

[0019] Among them, W m represents the guaranteed production cycle of the mth tar type, T m represents the total inventory of tobacco leaf grade of mth tar category, Y i represents the annual consumption of the ith tobacco grade in the mth tar category, z n Indicates the proportion of tobacco leaves used in products of the nth specification.

[0020] In the present invention, the low tar evaluation index LT is first used to construct a database. The model simultaneously introduces four characteristic indicators: tobacco weight / tar release, smoke nicotine / tar release, aroma quality / tar release, and aroma volume / tar release. The aroma, satisfaction, filling capacity, and tar release of tobacco leaves are comprehensively considered. The tar categories of tobacco leaf grades are classified through the model. The obtained classification results characterize the evaluation index of low tar and high aroma of tobacco leaf grades in all inventory tobacco leaves, which can be directly used for the calculation of tar release of tobacco leaf group formulas, and the tobacco leaf grades with low tar evaluation indexes suitable for leaf group formulas of cigarette products with different tar releases are stored. At the same time, combined with the calculation of the overall guarantee period Z of the inventory tobacco leaf grade and the guaranteed production period W of each tar category, the matching degree between the tar category inventory and the pre-production product can be obtained through numerical results. This method can provide guidance for the inventory adjustment of tobacco leaf grades.

[0021] Preferably, the step (1) of constructing a low tar evaluation index LT database of tobacco leaf grades in stock comprises: calculating the low tar evaluation index LT of all tobacco leaf grades in stock to obtain a low tar evaluation index LT database.

[0022] Preferably, the classification in step (1) comprises: classifying the tar categories of middle tobacco leaves, upper tobacco leaves and imported tobacco in stock according to the low tar evaluation index LT.

[0023] Preferably, the middle tobacco leaves are divided into 8 tar categories according to LT≥5 (for example, 5.1, 5.2, 5.3, 5.5, 6, etc.), 4.5≤LT<5 (for example, 4.6, 4.7, 4.8, 4.9, etc.), 4.3≤LT<4.5 (for example, 4.35, 4.4, 4.45, etc.), 4.2≤LT<4.3 (for example, 4.22, 4.24, 4.26, 4.28, etc.), 4.0≤LT<4.2 (for example, 4.05, 4.1, 4.15, etc.), 3.9≤LT<4.0 (for example, 3.92, 3.94, 3.96, 3.98, etc.), 3.8≤LT<3.9 (for example, 3.82, 3.84, 3.86, 3.88, etc.) and LT<3.8 (for example, 3, 3.2, 3.4, 3.6, etc.).

[0024] Preferably, the upper tobacco leaves are LT≥4.2 (for example, 4.4, 4.6, 4.8, 5, 5.5, 6, etc.), 4.1≤LT<4.2 (for example, 4.12, 4.14, 4.16, 4.18, etc.), 4.0≤LT<4.1 (for example, 4.02, 4.04, 4.06, 4.08, etc.), 3.9≤LT<4.0 (for example, 3.92, 3.94, 3.96, 3.97 ...4.1≤LT<4.2 (for example, 4.1 98, etc.), 3.8≤LT<3.9 (for example, it can be 3.82, 3.84, 3.86, 3.88, etc.), 3.7≤LT<3.8 (for example, it can be 3.72, 3.74, 3.76, 3.78, etc.), 3.6≤LT<3.7 (for example, it can be 3.62, 3.64, 3.66, 3.68, etc.) and LT<3.6 (for example, it can be 3, 3.2, 3.4, 3.5, etc.) are divided into 8 tar categories.

[0025] Preferably, the imported smoke is divided into seven tar categories according to LT≥4.2 (for example, it can be 4.4, 4.6, 4.8, 5, 5.5, 6, etc.), 4.0≤LT<4.2 (for example, it can be 4.05, 4.1, 4.15, etc.), 3.9≤LT<4.0 (for example, it can be 3.92, 3.94, 3.96, 3.98, etc.), 3.8≤LT<3.9 (for example, it can be 3.82, 3.84, 3.86, 3.88, etc.), 3.7≤LT<3.8 (for example, it can be 3.72, 3.74, 3.76, 3.78, etc.), 3.6≤LT<3.7 (for example, it can be 3.62, 3.64, 3.66, 3.68, etc.) and LT<3.6 (for example, it can be 3, 3.2, 3.4, 3.5, etc.).

[0026] Preferably, the criteria for determining the degree of matching between the inventory of each tar type and the product in step (2) are:

[0027] The closer the values ​​of W and Z are, the higher the matching degree between the storage area and the product of the corresponding tar category.

[0028] Preferably, in step (2), when ZW>6, it indicates that the inventory of the tar category is insufficient; when |WZ|≤6, it indicates that the inventory of the tar category is highly matched with the product; and when WZ>6, it indicates that the inventory of the tar category is relatively high.

[0029] |WZ| represents the absolute value of the difference between W and Z.

[0030] In a second aspect, the present invention provides an application of the method for characterizing the degree of matching between tobacco leaf inventory and products based on the low tar evaluation index described in the first aspect in adjusting tobacco leaf grade inventory.

[0031] Compared with the prior art, the present invention has at least the following beneficial effects:

[0032] The present invention constructs a database by applying the low tar evaluation index LT and classifies the tar categories of tobacco leaf grades according to the results. At the same time, combined with the calculation results of the overall guarantee period Z of the inventory tobacco leaf grade and the guaranteed production period W of each tar category, the matching degree of tar category inventory and product output plan can be achieved. This method can provide guidance for the inventory adjustment of tobacco leaf grades. DETAILED DESCRIPTION

[0033] For the convenience of understanding the present invention, the present invention lists the following embodiments. It should be understood by those skilled in the art that the embodiments are only to help understand the present invention and should not be regarded as specific limitations of the present invention.

[0034] Example 1

[0035] This embodiment provides a method for characterizing the matching degree between tobacco leaf inventory and products based on a low tar evaluation index, the method comprising the following steps:

[0036] (1) Construct a low tar evaluation index (LT) database for stock tobacco grades, and classify the tar categories of middle tobacco leaves, upper tobacco leaves, and imported tobacco in the stock tobacco grades according to the LT value;

[0037] Among them, the calculation formula of low tar evaluation index LT is as follows:

[0038]

[0039] Among them, A represents the weight of tobacco, B represents the nicotine in the smoke, C represents the aroma quality, D represents the aroma volume, and J represents the tar release; Indicates the grade of tobacco leaves The average value of Indicates the grade of tobacco leaves The average value of Indicates the grade of tobacco leaves The average value of Indicates the grade of tobacco leaves The average value of

[0040] The classification criteria include:

[0041] Middle tobacco leaves are divided into eight tar categories according to LT ≥ 5, 4.5 ≤ LT < 5, 4.3 ≤ LT < 4.5, 4.2 ≤ LT < 4.3, 4.0 ≤ LT < 4.2, 3.9 ≤ LT < 4.0, 3.8 ≤ LT < 3.9 and LT < 3.8;

[0042] The upper tobacco leaves are divided into eight tar categories according to LT ≥ 4.2, 4.1 ≤ LT < 4.2, 4.0 ≤ LT < 4.1, 3.9 ≤ LT < 4.0, 3.8 ≤ LT < 3.9, 3.7 ≤ LT < 3.8, 3.6 ≤ LT < 3.7 and LT < 3.6;

[0043] Imported cigarettes are divided into seven tar categories according to LT ≥ 4.2, 4.0 ≤ LT < 4.2, 3.9 ≤ LT < 4.0, 3.8 ≤ LT < 3.9, 3.7 ≤ LT < 3.8, 3.6 ≤ LT < 3.7 and LT < 3.6;

[0044] (2) Calculate the overall guarantee period Z of the inventory tobacco grade and the guaranteed production period W of each tar type, and characterize the matching degree between the inventory and products of each tar type based on the results;

[0045] When ZW>6, it means that the inventory of this tar category is insufficient;

[0046] When |WZ|≤6, it means that the inventory and product of this tar category have a high degree of match;

[0047] When WZ>6, it means that the inventory of this tar category is high;

[0048] The calculation formula for the overall guarantee period Z of the stock tobacco grade is as follows:

[0049]

[0050] Where T represents the total inventory of tobacco leaf grades, x n represents the annual output of the nth specification product, y n It indicates the leaf consumption of a single box of cigarettes of the nth specification product;

[0051] The calculation formula for the guaranteed production cycle W of each tar type is as follows:

[0052]

[0053] Among them, W m represents the guaranteed production cycle of the mth tar type, T m represents the total inventory of tobacco leaf grade of mth tar category, Y i represents the annual consumption of the ith tobacco grade in the mth tar category, z n Indicates the proportion of tobacco leaves used in products of the nth specification;

[0054] The results are summarized in Table 1.

[0055] Table 1

[0056]

[0057]

[0058] The results show that the method according to the present invention can characterize the matching degree between the inventory and products of tobacco grades of each tar category. When ZW>6, the inventory can be supplemented by purchasing and allocating some tobacco grades with the same or similar low tar evaluation index as the corresponding category; when WZ>6, it can be corrected by adjusting the tobacco grade and annual allocation plan of the product leaf group formula. At the same time, the type and quantity of raw materials used can be predicted according to the product production plan and new product development layout, and inventory adjustments can be made in advance. For example, if the future product development trend is a low tar trend, low tar tobacco raw materials can be reserved in advance from the tobacco procurement and allocation end to supply products.

[0059] The applicant declares that the above is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Those skilled in the art should understand that any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention shall fall within the protection scope and disclosure scope of the present invention.

Claims

1. A method for characterizing the matching degree between tobacco leaf inventory and products based on low tar evaluation index, characterized in that: The method comprises the following steps: (1) Construct a low tar evaluation index (LT) database for stock tobacco grades and classify the tar categories of stock tobacco grades according to LT values; The calculation formula of the low tar evaluation index LT is as follows: Among them, A represents the weight of tobacco, B represents the nicotine in the smoke, C represents the aroma quality, D represents the aroma volume, and J represents the tar release; Indicates the grade of tobacco leaves The average value of Indicates the grade of tobacco leaves The average value of Indicates the grade of tobacco leaves The average value of Indicates the grade of tobacco leaves The average value of (2) Calculate the overall guarantee period Z of the inventory tobacco grade and the guaranteed production period W of each tar type, and characterize the matching degree between the inventory and products of each tar type based on the results; The calculation formula for the overall guarantee period Z of the stock tobacco grade is as follows: Where T represents the total inventory of tobacco leaf grades, x n represents the annual output of the nth specification product, y n It indicates the leaf consumption of a single box of cigarettes of the nth specification product; The calculation formula for the guaranteed production cycle W of each tar type is as follows: Among them, W m represents the guaranteed production cycle of the mth tar type, T m represents the total inventory of tobacco leaf grade of mth tar category, Y i represents the annual consumption of the ith tobacco grade in the mth tar category, z n Indicates the proportion of tobacco leaves used in products of the nth specification.

2. The method according to claim 1, characterized in that The step (1) of constructing a low tar evaluation index LT database of the stock tobacco grades includes: calculating the low tar evaluation index LT of all tobacco grades in the stock to obtain a low tar evaluation index LT database.

3. The method according to claim 1 or 2, characterized in that: The classification in step (1) includes: classifying the tar categories of middle tobacco leaves, upper tobacco leaves and imported tobacco in stock according to the low tar evaluation index LT.

4. The method according to claim 3, characterized in that The middle tobacco leaves are divided into 8 tar categories according to LT≥5, 4.5≤LT<5, 4.3≤LT<4.5, 4.2≤LT<4.3, 4.0≤LT<4.2, 3.9≤LT<4.0, 3.8≤LT<3.9 and LT<3.

8.

5. The method according to claim 3, characterized in that: The upper tobacco leaves are divided into eight tar categories according to LT≥4.2, 4.1≤LT<4.2, 4.0≤LT<4.1, 3.9≤LT<4.0, 3.8≤LT<3.9, 3.7≤LT<3.8, 3.6≤LT<3.7 and LT<3.

6.

6. The method according to claim 3, characterized in that The imported cigarettes are divided into seven tar categories according to LT≥4.2, 4.0≤LT<4.2, 3.9≤LT<4.0, 3.8≤LT<3.9, 3.7≤LT<3.8, 3.6≤LT<3.7 and LT<3.

6.

7. The method according to any one of claims 1 to 6, characterized in that: The criteria for determining the matching degree between the inventory of each tar type and the product in step (2) are: The closer the values ​​of W and Z are, the higher the matching degree between the storage area and the product of the corresponding tar category.

8. The method according to any one of claims 1 to 7, characterized in that: Step (2) When ZW>6, it indicates that the inventory of the tar category is insufficient; when |WZ|≤6, it indicates that the inventory of the tar category and the product are highly matched; when WZ>6, it indicates that the inventory of the tar category is relatively high.

9. Application of the method for characterizing the degree of matching between tobacco leaf inventory and products based on the low tar evaluation index according to any one of claims 1 to 8 in adjusting tobacco leaf grade inventory.

Images