A method for correcting cigarette sensory standardization based on environmental parameters

Abstract

The application discloses a cigarette sensory standardization correction method based on environmental parameters, which comprises the following steps: S1. non-standard environmental sensory evaluation; S2. obtaining non-standard environmental parameters; S3. sensory evaluation under a standard environment; S4. calculating environmental deviation characteristics; S5. constructing a correction model; and S6. sensory evaluation correction. The correction method unifies and normalizes scattered sensory data obtained under different climate conditions to a standard dimension, and realizes efficient horizontal comparison of sensory data. By using the cigarette sensory standardization correction method based on environmental parameters, researchers do not need to frequently go back and forth between different altitudes and climate areas for field evaluation, and can quickly calculate the standard sensory performance of a product in a non-standard environment, thereby greatly reducing the research and development cost and period.

Description

Technical Field

[0001] This invention belongs to the field of sensory evaluation technology for tobacco products, specifically relating to a method for standardized calibration of cigarette sensory functions based on environmental parameters. Background Technology

[0002] Sensory quality of cigarettes is a core indicator for measuring the quality of cigarette products and determining their market suitability. It is primarily evaluated quantitatively through dimensions such as aroma, balance, off-flavors, irritation, and aftertaste. It serves as the core basis for cigarette formula development, production process optimization, and finished product quality control. Currently, the tobacco industry strictly adheres to the GB / T16447 standard for sensory evaluation of cigarettes, requiring R&D and quality control laboratories to conduct evaluation tests under fixed conditions of constant temperature, humidity, and standard pressure to ensure the consistency of evaluation data.

[0003] However, in actual industrial applications, the regional differences in cigarette consumption scenarios are enormous. Temperature, humidity, and atmospheric pressure vary significantly across different altitudes and climate zones. These environmental parameters directly affect the combustion state of cigarettes and the effect of smoke volatilization and diffusion, leading to a significant discrepancy between the actual sensory experience of end consumers and the laboratory standard evaluation results.

[0004] Current cigarette sensory evaluation technologies have significant shortcomings. The industry generally assumes that the evaluation environment is a standard operating condition, failing to quantitatively correct for multi-parameter coupling interference in non-standard end-user environments. Instead, it relies solely on rough adjustments based on human experience or directly uses laboratory standard data to benchmark end-user experience. This leads to the long-standing core pain point of "high-quality R&D and evaluation, but inconsistent end-user experience": cigarette formulas and process parameters optimized for standard operating conditions by R&D cannot adapt to the end-user consumption environments across different regions of the country. Sensory data from different regions and operating conditions cannot be compared, greatly reducing the accuracy and reference value of cigarette sensory evaluation data, thus hindering precise cigarette R&D, comprehensive quality control, and market adaptation optimization.

[0005] To address the above problems, this invention is proposed. Summary of the Invention

[0006] The purpose of this invention is to address the shortcomings of existing technologies by providing a cigarette sensory standardization correction method based on environmental parameters. This method includes the following steps: S1. Sensory evaluation in a non-standard environment; S2. Acquisition of non-standard environmental parameters; S3. Sensory evaluation under a standard environment; S4. Calculation of environmental deviation characteristics; S5. Construction of a correction model; S6. Sensory evaluation correction. This invention's correction method normalizes scattered sensory data acquired under different climatic conditions to a standardized dimension, achieving efficient horizontal comparison of sensory data. Using this invention's cigarette sensory standardization correction method based on environmental parameters, researchers no longer need to frequently travel to regions with different altitudes and climates for on-site evaluation. They can quickly calculate the standard sensory performance of the product in non-standard environments, significantly reducing R&D costs and time.

[0007] The objective of this invention is achieved through the following technical solution:

[0008] This invention provides a method for sensory standardization correction of cigarettes based on environmental parameters, which includes the following steps:

[0009] S1. Non-standard environmental sensory evaluation

[0010] Sensory evaluation values ​​under non-standard conditions are obtained by sensory evaluation of tobacco samples by smoking testers, and sensory evaluation index vectors under non-standard conditions are obtained. The index vector Includes aroma Coordination Mixed gases Irritating Aftertaste Scores across multiple sensory dimensions.

[0011] S2. Obtaining non-standard environmental parameters:

[0012] The actual temperature T, actual relative humidity H, and actual atmospheric pressure P were collected under non-standard testing conditions.

[0013] S3. Sensory evaluation under standard conditions

[0014] To obtain sensory evaluation values ​​under standard conditions, tobacco samples are subjected to sensory evaluation by tasters to obtain sensory evaluation index vectors under standard conditions. The index vector Includes aroma Coordination Mixed gases Irritating Aftertaste Scores across multiple sensory dimensions.

[0015] S4. Calculate environmental deviation characteristics

[0016] The environmental deviation characteristic variable between the actual test environment and the standard environment is calculated as follows:

[0017] Bounded humidity variable:

[0018] ;

[0019] Low humidity boundary variable:

[0020] ;

[0021] High humidity boundary variables:

[0022] ;

[0023] Low temperature variables:

[0024] ;

[0025] High temperature variables:

[0026] ;

[0027] Stress variables:

[0028] ;

[0029] Temperature and humidity interaction variables:

[0030] ;

[0031] S5. Constructing the calibration model

[0032] The data obtained in steps 1, 2, and 3 are used to calculate the relevant variables in step 4. These variables are then imported into the following model, and the relevant variables are obtained through fitting. coefficient.

[0033] ;

[0034] ;

[0035] in, The scores were: aroma (A) 32, harmony (H) 6, off-flavors (O) 12, irritation (I) 20, and aftertaste (R) 25.

[0036] The correction function is obtained as follows:

[0037] ;

[0038] ;

[0039] ;

[0040] ;

[0041] ;

[0042] S6. Sensory evaluation correction

[0043] Steps 1 and 2 are used to obtain sensory evaluation values ​​and environmental parameters under non-standard conditions, and steps 4 and 5 are used to obtain sensory values ​​calibrated under standard conditions.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] 1. Researchers no longer need to frequently travel to regions with different altitudes and climates for on-site evaluation. They can quickly calculate the standard sensory performance of the product in non-standard environments, which greatly reduces research and development costs and time.

[0046] 2. The correction method of this invention normalizes scattered sensory data obtained under different climatic conditions to a standard dimension, thereby achieving efficient horizontal comparison of sensory data. Attached Figure Description

[0047] none. Detailed Implementation

[0048] The present invention will be described below with reference to specific embodiments, but the implementation of the present invention is not limited thereto. Experimental methods not specifically described in the embodiments generally use conventional conditions and conditions described in manuals, or conditions recommended by the manufacturer. The general equipment, materials, reagents, etc., used are all commercially available unless otherwise specified.

[0049] Example 1

[0050] Ten types of cigarettes, P1 to P10, were selected. Three non-standard smoking environments were set up for each cigarette, resulting in 30 sets of paired data. Each set of data included five sensory values ​​related to temperature, humidity, pressure, the non-standard environment, and the actual five sensory values ​​of the same cigarette under standard conditions. Sensory evaluations were conducted by no fewer than nine trained evaluators. The results are shown in Table 1.

[0051] Table 1. Environmental conditions and paired sensory values ​​of 30 training samples

[0052]

[0053]

[0054]

[0055] Ridge regression without intercept constraint was adopted, with ridge parameter λ=0.003, and physical symbol constraints such as low humidity, high temperature, low temperature, and pressure quadratic terms were set. The five model coefficients are shown in Table 2. Cross-validation was performed by grouping according to cigarette specifications, and the validation results are shown in Table 3.

[0056] Table 2. Five Model Coefficients

[0057]

[0058] Table 3. Model fitting and grouped cross-validation results for Example 1

[0059]

[0060] The R² values ​​for the five training sets range from 0.9599 to 0.9682, the R² values ​​for the grouped cross-validation range from 0.8806 to 0.9433, and the RMSE values ​​for the cross-validation range from 0.1360 to 0.5713.

[0061] Example 2

[0062] Four other types of cigarettes, V1 to V4, which were not involved in the modeling of Example 1, were selected. Three sets of non-standard environments were set for each type of cigarette, forming a total of 12 independent verification samples. The sensory values ​​of the non-standard environments, as well as temperature, humidity, and pressure, were input into the calibration model to obtain the predicted values ​​of the standard state. These predicted values ​​were then compared with the actual evaluation results of the standard state at 22 ℃, 60% relative humidity, and 1.00 atm. The results are shown in Tables 4 and 5.

[0063] Table 4. Environmental values, predicted standard values, actual values, and deviations of the validation samples.

[0064]

[0065] Table 5. Item prediction performance on the independent validation set

[0066]

[0067] The mean MAPE of each of the five items for the 12 validation samples was 3.197%, and the maximum value was 3.999%; the mean deviation of the total score of the five items was 1.698%, and the maximum value was 3.342%; the maximum relative deviation of all individual predictions was 4.475%, all of which were less than 5%, indicating good prediction and correction effects.

[0068] The present invention has been described above by way of example. It should be noted that any simple modifications, alterations or other equivalent substitutions that can be made by those skilled in the art without creative effort without departing from the core of the present invention fall within the protection scope of the present invention.

Claims

1. A method for sensory standardization correction of cigarettes based on environmental parameters, characterized in that, It includes the following steps: S1. Non-standard environmental sensory evaluation: Sensory evaluation values ​​under non-standard conditions are obtained by sensory evaluation of tobacco samples by smoking testers, and sensory evaluation index vectors under non-standard conditions are obtained. ; S2. Obtaining non-standard environmental parameters: Collect actual temperature T, actual relative humidity H, and actual atmospheric pressure P under non-standard test conditions; S3. Sensory evaluation under standard conditions: Sensory evaluation values ​​under standard conditions are obtained by sensory evaluation of tobacco samples by smoking testers, and sensory evaluation index vectors under standard conditions are obtained. ; S4. Calculate environmental deviation characteristics: The environmental deviation characteristic variable between the actual test environment and the standard environment is calculated as follows: Bounded humidity variables: ； Low humidity boundary variables: ； High humidity boundary variables: ； Low temperature variables: ； High temperature variables: ； Stress variables: ； Temperature and humidity interaction variables: ； S5. Construct the calibration model: The data obtained in steps 1, 2, and 3 are used to calculate the relevant variables in step 4. These variables are then imported into the following model, and the relevant variables are obtained through fitting. coefficient; ； ； in, The scores are: aroma (A) 32, harmony (H) 6, off-flavors (O) 12, irritation (I) 20, and aftertaste (R) 25. The correction function is obtained as follows: ； ； ； ； ； S6. Sensory evaluation correction: Through steps S1 and S2, sensory evaluation values ​​and environmental parameters under non-standard conditions are obtained, and through steps S4 and S5, sensory values ​​calibrated under standard conditions are obtained.

2. The cigarette sensory standardization correction method based on environmental parameters according to claim 1, characterized in that, In step S1, the index vector Includes aroma Coordination Mixed gases Irritating Aftertaste Scores across multiple sensory dimensions.

3. The cigarette sensory standardization correction method based on environmental parameters according to claim 1, characterized in that, In step S3, the index vector Includes aroma Coordination Mixed gases Irritating Aftertaste Scores across multiple sensory dimensions.

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