Method for judging industrial conformity of flue-cured tobacco quality based on climatic year type

Abstract

The invention discloses a method for judging industrial conformity of flue-cured tobacco quality based on climatic years, which comprises the following steps of: acquiring multi-year meteorological data of a certain planting area, and dividing the climatic years by performing Euclidean distance clustering on the meteorological data of different years; determining flue-cured tobacco chemical components and sensory quality data distribution characteristics under different climatic years; according to flue-cured tobacco chemical component and sensory quality data distribution characteristics under different climatic years, comparing with industrial flue-cured tobacco chemical component and sensory quality demand ranges, determining industrial demand conformity of flue-cured tobacco chemical components and sensory quality under different climatic years, and further obtaining a climatic year evaluation model; according to the method, the overall chemical components and sensory quality of the tobacco leaves in the same climatic year in a certain area can be evaluated in a large range by utilizing the constructed climatic year evaluation model, and the problems existing in an existing detection method are avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of tobacco, and in particular to a method for judging the industrial compliance of flue-cured tobacco quality based on climate year type. Background Art

[0002] The growing environment is fundamental to the development of flue-cured tobacco's distinctive flavor. Climatic factors, such as temperature, precipitation, and sunshine, play a crucial role in shaping tobacco growth and development, its inherent chemical composition, and its flavor by influencing the synthesis of aroma compounds and secondary metabolites, as well as carbohydrate and energy metabolism. Unacceptable climatic differences can lead to variations in the tobacco's chemical composition and sensory qualities, creating uncertainty in its quality and potentially deviating from industry standards.

[0003] To determine whether flue-cured tobacco meets the quality standards, quality evaluation is required. Existing methods rely primarily on routine chemical composition testing and sensory evaluation. These methods suffer from small sample sizes, large errors, cumbersome operations, and a lag effect. Furthermore, they fail to provide timely information on tobacco quality during the tobacco allocation period. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention aims to provide a method for determining the industrial compliance of flue-cured tobacco quality based on climatic year type. Using the constructed climatic year type assessment model, the overall chemical composition and sensory quality of tobacco leaves from the same climatic year type in a specific region can be assessed on a large scale, avoiding the problems of existing detection methods. To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0005] The present invention provides a method for judging the industrial compliance of flue-cured tobacco quality based on climate year type, comprising the following steps:

[0006] Obtain multi-year meteorological data of a certain planting area, and classify climate year types by performing Euclidean distance clustering on meteorological data of different years;

[0007] Determine the distribution characteristics of chemical composition and sensory quality data of flue-cured tobacco under different climate types;

[0008] Based on the distribution characteristics of the chemical composition and sensory quality data of flue-cured tobacco under different climatic years, and compared with the industrial demand range for the chemical composition and sensory quality of flue-cured tobacco, the compliance degree of the chemical composition and sensory quality of flue-cured tobacco under different climatic years with the industrial demand was determined, and then the climatic year evaluation model was obtained.

[0009] As a further implementation method, the specific steps for dividing climate annual types include:

[0010] The range of the flue-cured tobacco growing season is determined based on the actual growing period of the flue-cured tobacco in the planting area, and the meteorological data during the growing period of the flue-cured tobacco is divided into a period of 10-20 days each year;

[0011] In this planting area, the precipitation, temperature, and sunshine hours during the growth period are collected; based on the divided periods, the cumulative precipitation, average daily temperature, and average sunshine hours in each period are calculated;

[0012] With cumulative precipitation, average daily temperature, and average sunshine hours as input variables, the Euclidean distance clustering method was used to divide the multi-year climate into different annual types.

[0013] As a further implementation method, the fviz_nbclust() function of the factoextra package in R language is used to find the optimal number of clusters during the Euclidean distance clustering process.

[0014] As a further implementation, scree plot is used to obtain the optimal number of clusters during the Euclidean distance clustering process.

[0015] As a further implementation method, the newly collected flue-cured tobacco data were matched with the constructed climate year type assessment model to verify the judgment accuracy of flue-cured tobacco quality under different climate year types.

[0016] As a further implementation method, chemical composition indicators include nicotine, total nitrogen, reducing sugar, total sugar, potassium, chlorine, and starch.

[0017] As a further implementation method, sensory quality indicators include aroma quality, aroma quantity, concentration, strength, impurities, pungency, and aftertaste.

[0018] As a further implementation method, the calculated values ​​of the chemical composition index and the sensory quality index include the mean, standard error, 95% confidence interval upper limit, 95% confidence interval lower limit, maximum value and minimum value.

[0019] As a further implementation method, the degree of compliance is the number of flue-cured tobacco chemical composition and sensory quality indicators that meet the requirements under the same climate year type divided by the total sample size.

[0020] As a further implementation method, meteorological data from ten years are selected to perform climate year type clustering.

[0021] The beneficial effects of the present invention are as follows:

[0022] 1. The present invention uses a clustering method to divide similar years and analyzes the characteristics of tobacco leaf quality data under similar years. The suitable range of tobacco leaf quality is determined according to the divided climate years, and finally the year type category is used to determine the tobacco leaf quality range under the corresponding climate year. The quality of tobacco leaves under different years is compared with the industry's standards for tobacco leaf quality to determine whether they meet the requirements. The method of the present invention can evaluate the overall chemical composition and sensory quality of tobacco leaves of the same climate year in a certain area on a large scale, eliminating the need for indoor testing, avoiding the defects of single samples and small sample quantities, saving manpower and improving the efficiency of tobacco leaf quality judgment.

[0023] 2. Compared to traditional detection methods, the method of this invention boasts a larger data set, wider coverage, simpler operation, and greater statistical significance, approximating the true quality characteristics of tobacco leaves. Clustering is performed based on the current year's climate characteristics and historical climate year patterns. Once the year pattern is determined, the quality characteristics of the tobacco leaves for that year can be determined, as well as whether they meet industrial requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0025] Figure 1 This is a flow chart of a method for judging industrial compliance of flue-cured tobacco quality based on climate year type in an embodiment of the present invention;

[0026] Figure 2 Schematic diagram of obtaining the optimal clustering K value through scree plot in an embodiment of the present invention;

[0027] Figure 3 In the embodiment of the present invention, clustering is performed based on multi-year meteorological data to divide climate year types. DETAILED DESCRIPTION

[0028] It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used in the present invention have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0029] In a typical embodiment of the present invention, referring to Figure 1 As shown, a method for judging the industrial compliance of flue-cured tobacco quality based on climate year type includes the following steps:

[0030] S101. Obtain multi-year meteorological data of a certain planting area (Area A, the same below), and divide the meteorological data of different years into annual climate types by performing Euclidean distance clustering on the data.

[0031] S110. Determine the growing season range of the flue-cured tobacco based on the actual growing period of the flue-cured tobacco in site A, and divide the meteorological data during the growing period of the flue-cured tobacco into a period of 10-20 days.

[0032] In this embodiment, the flue-cured tobacco growing period in site A is from April 21 to September 17 each year. Meteorological data from 2014 to 2023 were selected, and the meteorological data during each flue-cured tobacco growing period were divided into a period of half a month (15 days) each year, for a total of ten periods (T1-T10). The divided periods are shown in Table 1.

[0033] Table 1A: Standards for the division of tobacco growth periods in regions

[0034]

[0035] S120. In this planting area, the three major meteorological elements of precipitation, temperature, and sunshine hours are collected during the growing period.

[0036] S130. Calculate the cumulative precipitation, average daily temperature, and average sunshine hours in each period based on the divided periods.

[0037] S140, using cumulative precipitation, average daily temperature, and average sunshine hours as input variables, use the fviz_nbclust() function of the R language factoextra package to find the optimal cluster number K. In this embodiment, the scree plot is used to obtain the optimal K value of 3, as shown in the following example. Figure 2 shown.

[0038] S150. In this embodiment, cumulative precipitation, average daily temperature, and average sunshine hours are used as input variables, and the Euclidean distance clustering method is used with a k value of 3 to perform clustering. The 10-year climate is divided into three categories, such as Figure 3 shown.

[0039] Using scree plot to cluster climate year types to obtain the optimal K value and reclassifying the year types according to the K value can significantly improve the model convergence speed and training accuracy.

[0040] S102. Determine the distribution characteristics of chemical composition and sensory quality data of flue-cured tobacco under different climate types.

[0041] S210. Determine the chemical composition characteristics of flue-cured tobacco under different climatic years.

[0042] Calculate the chemical composition of flue-cured tobacco leaves from the same vintage, including the mean, standard error, upper and lower limits of the 95% confidence interval, maximum and minimum values ​​for nicotine, total nitrogen, reducing sugars, total sugars, potassium, chloride, and starch. This determines the fluctuation range of each chemical component indicator for tobacco leaves from the same vintage. For this example, the statistical data for the chemical composition of flue-cured tobacco leaves is shown in Table 2.

[0043] Table 2 Statistical overview of chemical components of lower and middle leaves in different climatic years in region A

[0044]

[0045]

[0046] S220. Determine the sensory quality data characteristics of flue-cured tobacco under different climate types.

[0047] Calculate the sensory quality of flue-cured tobacco leaves from the same vintage, including the mean, standard error, upper and lower limits of the 95% confidence interval, maximum and minimum values ​​for aroma, aroma volume, concentration, strength, off-flavor, pungency, and aftertaste. This also determines the fluctuation range of each sensory quality indicator for tobacco leaves from the same vintage. For this example, the sensory quality statistics for flue-cured tobacco leaves are shown in Table 3.

[0048] Table 3 Statistical overview of sensory quality of middle leaves in different climatic years in region A

[0049]

[0050] S103. Determine the compliance of chemical composition and sensory quality of flue-cured tobacco in different years with industrial requirements.

[0051] S310. Obtain the required range of chemical composition and sensory quality of flue-cured tobacco from the production area by a certain industry, as shown in Tables 4 and 5.

[0052] Table 4 The range of chemical composition quality requirements of a certain industrial enterprise for flue-cured tobacco in the central region

[0053]

[0054] Table 5 Sensory quality requirements of an industrial enterprise for flue-cured tobacco in the central region

[0055]

[0056] 2) Based on the distribution range of chemical composition and sensory quality of flue-cured tobacco under similar climate year types, compare with the industry's requirements for chemical composition and sensory quality of flue-cured tobacco in Region A to evaluate whether the quality of flue-cured tobacco under each climate year type meets the industry requirements. The degree of compliance is the number of flue-cured tobacco chemical composition or sensory quality indicators that meet the requirements under the same climate year type divided by the total sample size. For example, the total number of samples obtained under year type I is 100, and the number of samples with reducing sugar content within the quality target range of 25-30% is 50. The degree of compliance is the proportion of samples that meet the target in the total number of samples. For this example, the degree of compliance of each indicator of flue-cured tobacco chemical composition and sensory quality under different climate year types is shown in Tables 6 and 7.

[0057] Table 6 Compliance of chemical composition of flue-cured tobacco to industrial requirements under different climate types in region A

[0058]

[0059] Table 6 shows that there are significant differences in the compliance of flue-cured tobacco chemical composition under different climate year types. The compliance of all indicators (except total nitrogen) under climate year type II is higher than that of year types I and III. Among them, the compliance of total sugar, potassium, and chlorine content under year type II reached 100%. The compliance of total alkaloid content reached 66.67%, significantly higher than the 27.78% of year type I and the 47.06% of year type III. In summary, climate year type II is the ideal condition for the chemical composition of flue-cured tobacco to best meet industrial requirements, while climate year types I and III have certain deficiencies in certain indicators, especially the low compliance of reducing sugar and total sugar.

[0060] Table 7: Compliance of sensory quality of flue-cured tobacco to industrial requirements under different climate types in region A (%)

[0061]

[0062] As shown in Table 7, climate year type III had the highest compliance for aroma quality (85.00%), followed by climate year types II (77.78%) and I (53.33%). The compliance for aroma quantity was highest in climate year type II (55.56%), while the compliance for climate year types I and III was lower, at 46.67% and 45.00%, respectively. The compliance for concentration and strength reached 100% in climate year type II, demonstrating the most outstanding performance. The compliance for concentration in climate year types I and III was 73.33% and 75.00%, respectively, and the compliance for strength was 80.00% and 75.00%, respectively. In summary, climate year type II performed best in terms of concentration and strength, while climate year type III had greater advantages in terms of aroma quality, miscellaneous notes, and irritation. Climate year type I had relatively low compliance across all indicators, especially in terms of aroma quality and aroma quantity.

[0063] S104. Based on the constructed method for classifying flue-cured tobacco quality using climate year types, newly collected flue-cured tobacco data is matched with the constructed climate year type model to verify the accuracy of flue-cured tobacco quality judgment under different climate year types. The accuracy and reliability of the model can be evaluated through testing with actual flue-cured tobacco data.

[0064] This embodiment uses a clustering method to divide similar years and analyzes the characteristics of tobacco leaf quality data under similar years. The suitable range of tobacco leaf quality is determined based on the divided climate years, and finally the year type category is used to determine the tobacco leaf quality range under the corresponding climate year. The quality of tobacco leaves under different years is compared with the industry's standards for tobacco leaf quality to determine whether they meet the requirements. The method of this embodiment can evaluate the overall chemical composition and sensory quality of tobacco leaves of the same climate year in a certain area on a large scale, eliminating the need for indoor testing, avoiding the defects of single samples and small sample quantities, saving manpower and improving the efficiency of tobacco leaf quality judgment.

[0065] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A method for judging the industrial compliance of flue-cured tobacco quality based on climate year type, characterized in that: The following steps are involved: Obtain multi-year meteorological data of a certain planting area, and classify climate year types by performing Euclidean distance clustering on meteorological data of different years; Determine the distribution characteristics of chemical composition and sensory quality data of flue-cured tobacco under different climate types; Based on the distribution characteristics of the chemical composition and sensory quality data of flue-cured tobacco under different climatic years, and compared with the industrial demand range for the chemical composition and sensory quality of flue-cured tobacco, the compliance degree of the chemical composition and sensory quality of flue-cured tobacco under different climatic years with the industrial demand was determined, and then the climatic year evaluation model was obtained.

2. The method for judging the industrial compliance of flue-cured tobacco quality based on climate year type according to claim 1, characterized in that: The specific steps for dividing climate annual types include: The range of the flue-cured tobacco growing season is determined based on the actual growing period of the flue-cured tobacco in the planting area, and the meteorological data during the growing period of the flue-cured tobacco is divided into a period of 10-20 days each year; In this planting area, the precipitation, temperature, and sunshine hours during the growth period are collected; based on the divided periods, the cumulative precipitation, average daily temperature, and average sunshine hours in each period are calculated; With cumulative precipitation, average daily temperature, and average sunshine hours as input variables, the Euclidean distance clustering method was used to divide the multi-year climate into different annual types.

3. The method for judging the industrial compliance of flue-cured tobacco quality based on climate year type according to claim 2, characterized in that: In the process of Euclidean distance clustering, the fviz_nbclust() function of the R language factoextra package is used to find the optimal number of clusters.

4. The method for judging the industrial compliance of flue-cured tobacco quality based on climate year type according to claim 3, characterized in that: In the process of clustering using Euclidean distance, scree plot was used to obtain the optimal number of clusters.

5. The method for judging the industrial compliance of flue-cured tobacco quality based on climate year type according to claim 1, characterized in that: The newly collected flue-cured tobacco data were matched with the constructed climate year type assessment model to verify the accuracy of judging the quality of flue-cured tobacco under different climate year types.

6. The method for judging the industrial compliance of flue-cured tobacco quality based on climate year type according to claim 1, characterized in that: Chemical composition indicators include nicotine, total nitrogen, reducing sugar, total sugar, potassium, chloride, and starch.

7. The method for judging the industrial compliance of flue-cured tobacco quality based on climate year type according to claim 1, characterized in that: Sensory quality indicators include aroma quality, aroma quantity, concentration, strength, impurities, pungency, and aftertaste.

8. The method for judging the industrial compliance of flue-cured tobacco quality based on climate year type according to claim 1, characterized in that: The calculated values ​​of chemical composition indicators and sensory quality indicators include mean, standard error, 95% confidence interval upper limit, 95% confidence interval lower limit, maximum value and minimum value.

9. The method for judging the industrial compliance of flue-cured tobacco quality based on climate year type according to claim 1, characterized in that: The degree of compliance is the number of flue-cured tobacco chemical compositions and sensory quality indicators that meet the requirements under the same climate year type divided by the total sample size.

10. The method for judging the industrial compliance of flue-cured tobacco quality based on climate year type according to claim 1, characterized in that: Meteorological data from ten years were selected to cluster climate types.

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