A method and system for predicting and evaluating suitable growing areas for cigar tobacco products

Abstract

A method and system for predicting and evaluating suitable planting areas for cigar tobacco products, which collects and organizes basic data of a designated area, compares the collected basic data with the same type of data of a designated high-quality cigar planting area, analyzes the differences in key factors of cigar tobacco leaf growth characteristics between the designated area and the designated high-quality cigar planting area; determines key climate influencing factors affecting cigar tobacco planting and air-drying fermentation, and evaluates the suitable range and critical threshold of key meteorological elements in each stage of cigar production; selects key climate influencing factors as independent variables and quality changes as dependent variables, and uses a multivariate linear stepwise regression method to construct a dynamic prediction model for cigar tobacco quality based on key climate influencing factors; performs interannual prediction of cigar tobacco quality according to the dynamic prediction model for cigar tobacco quality, and screens suitable planting areas for cigar tobacco products in the designated area. The present invention provides a scientific basis for cigar introduction and planting zoning, and improves the production level and capacity of high-quality cigar tobacco leaves in my country.

Description

Technical Field

[0001] The invention relates to a method and system for predicting and evaluating suitable planting areas for cigar tobacco products, belonging to the technical field of tobacco leaf planting. Background Art

[0002] The core of a cigar is the cigar core, which determines the taste of the cigar and the aroma level during smoking. Cigar core tobacco is mainly air-cured tobacco, and some sun-cured tobacco can also be used as core material. Cigar core tobacco leaves are required to have a cigar aroma style, good taste, certain strength, appropriate strength, good burning properties, gray and white and tightly rolled. At present, the development of my country's cigar industry is still in its early stages, and domestic raw materials cannot support the sustained and stable development of China's cigar industry. With the country's gradual attention to the cigar industry, domestic cigars have made great breakthroughs in certain production technologies and have made great progress in the quality of cigar raw materials.

[0003] Judging from the current status of cigar tobacco production, there is still a lot of room for expansion in both quantity and quality. Due to the complexity of mountainous topography and the local nature of climatic conditions, it is urgent to carry out refined cigar tobacco climate suitability zoning in terms of moderate-scale planting planning and variety introduction, so as to provide a scientific basis for expanding the scale of cigar planting and optimizing the tobacco industry structure, and better adapt to the tobacco industry's market development strategy and the demand for special high-quality tobacco raw materials.

[0004] Meteorological conditions have a great impact on cigar tobacco production, but there is currently a lack of relevant forecasting and evaluation technical solutions for the study of climate suitability of cigar tobacco and the prediction of cigar tobacco quality, which cannot provide scientific support for introduction and planting zoning. Summary of the invention

[0005] To this end, the present invention provides a method and system for predicting and evaluating suitable growing areas for cigar tobacco products, which can realize the prediction and evaluation of climate-suitable growing areas for cigar tobacco leaves, so as to obtain high-quality cigar tobacco products.

[0006] In order to achieve the above object, the present invention provides the following technical solution: a method for predicting and evaluating suitable growing areas for cigar tobacco products, comprising the following steps:

[0007] Collect and organize basic data of designated areas, including basic geographic data, environmental measured data, tobacco chemical composition data, tobacco sensory data and tobacco physical index data;

[0008] Compare the collected basic data with the same type of data from the designated premium cigar growing areas, and analyze the differences in key factors of cigar tobacco leaf growth characteristics between the designated areas and the designated premium cigar growing areas;

[0009] Identify the key climate factors that affect cigar cultivation and air-curing fermentation, and assess the suitable range and critical thresholds of key meteorological elements at each stage of cigar production;

[0010] The key climate influencing factors were selected as independent variables and the quality change as dependent variable. The multivariate linear stepwise regression method was used to construct a dynamic prediction model of cigar quality based on key climate influencing factors.

[0011] Based on the dynamic prediction model of cigar quality, annual prediction of cigar quality is carried out, and suitable cigar growing areas in designated regions are screened.

[0012] As a preferred solution of the method for predicting and evaluating the suitable planting area for cigar tobacco products, the basic geographic data includes the altitude, longitude and latitude, and topographic features of the cigar tobacco planting area;

[0013] The environmental measured data include meteorological element data of meteorological observation stations in the cigar planting area and surrounding areas during the cigar tobacco seedling raising, cultivation, air-drying and fermentation stages, and the meteorological element data include temperature, precipitation, sunshine, wind, humidity and soil temperature;

[0014] The tobacco leaf chemical composition data include water-soluble total sugar, reducing sugar, total nitrogen, nicotine and potassium content;

[0015] The tobacco sensory data include aroma type, aroma quantity, miscellaneous smell, strength, aftertaste, combustibility, gray color and sweetness;

[0016] The tobacco leaf physical index data include single leaf weight, tobacco leaf stem content, and tobacco leaf length and width.

[0017] As a preferred scheme for the prediction and evaluation method of suitable growing areas for cigar tobacco products, the temperature suitability model, precipitation suitability model, sunshine suitability model and climate suitability model for cigar tobacco quality are constructed in units of ten days, and a dynamic prediction model for cigar tobacco quality using statistical methods is constructed.

[0018] As a preferred method for predicting and evaluating the suitable planting areas for cigar tobacco products, GIS technology is used to calculate and simulate the spatial distribution of various meteorological factors that affect the growth of cigar tobacco leaves in cigar planting areas, including:

[0019] Based on the collected and collated temperature and precipitation data of meteorological stations, multivariate statistical models between temperature, precipitation and geographical location and terrain factors were established.

[0020] The model prediction value is calculated for each DEM cell, and the climate residual is interpolated using the spatial interpolation method to obtain the rasterized residual; the DEM cell and the model prediction value are superimposed to obtain the spatial distribution map of temperature and precipitation in the cigar growing area.

[0021] As a preferred method for predicting and evaluating the suitable planting areas for cigar tobacco products, the optimal spatial interpolation model for interpolating climate residuals using the spatial interpolation method is a ternary spline function with longitude, latitude and altitude as independent variables.

[0022] As a preferred method for predicting and evaluating the suitable growing areas for cigar tobacco products, the root mean square error and mean absolute error indicators are used to evaluate the effect of temperature and precipitation interpolation in cigar growing areas, and the 3σ standard deviation is used to evaluate the stability of the temperature and precipitation interpolation errors in cigar growing areas.

[0023] Based on DEM data, the terrain factors of slope, aspect and terrain shielding were extracted, and the multi-factor simulation method was applied on the GIS platform to simulate the sunshine hours in the critical growth period of cigar planting areas.

[0024] As the preferred scheme for the prediction and evaluation method of suitable growing areas for cigar tobacco products, the climate factor analysis period is determined according to the meteorological conditions during the growing period that affect the production of cigar tobacco leaves, combined with the correlation analysis results of tobacco leaf yield, quality and meteorological conditions during the growing period in previous years; each climate factor is dimensionlessly normalized.

[0025] As a preferred scheme for the prediction and evaluation method of suitable planting areas for cigar tobacco products, the planting points of high-quality cigar planting areas and the grid points of cigar planting areas in designated areas are taken as different individuals in the m-dimensional space, and the similarity distance between any grid point and each planting point in the high-quality cigar planting area is calculated respectively, and the minimum similarity distance is selected as the similarity distance between this grid point and the high-quality cigar planting area;

[0026] By dividing the distance into similar levels, comparative analysis of climate factors between designated areas with similar climates to those of premium cigar growing areas is conducted;

[0027] According to the determined key climate influencing factors, the weights of each key climate influencing factor are determined using expert scoring, hierarchical analysis, and fuzzy comprehensive evaluation methods; the cigar tobacco eco-climate zoning is carried out through the zoning model, and the cigar tobacco eco-climate suitability zoning is carried out.

[0028] The present invention also provides a prediction and evaluation system for suitable growing areas of cigar tobacco products, comprising:

[0029] A basic data processing unit is used to collect and organize basic data of a designated area, wherein the basic data includes basic geographic data, environmental measured data, tobacco chemical composition data, tobacco sensory data, and tobacco physical index data;

[0030] A difference analysis unit is used to compare the collected basic data with the same type of data from the designated premium cigar growing area, and analyze the differences in key factors of cigar tobacco leaf growth characteristics between the designated area and the designated premium cigar growing area;

[0031] Meteorological element assessment unit, used to determine the key climate factors affecting cigar cultivation and air-curing fermentation, and to assess the suitable range and critical thresholds of key meteorological elements at each stage of cigar production;

[0032] The forecast model building unit is used to select key climate influencing factors as independent variables and quality changes as dependent variables, and adopt the multivariate linear stepwise regression method to build a dynamic forecast model for cigar quality based on key climate influencing factors;

[0033] The suitable planting area prediction and screening unit is used to make interannual predictions on the quality of cigars based on the dynamic prediction model of cigar quality and to screen suitable planting areas for cigars in designated areas.

[0034] As a preferred solution of the prediction and evaluation system for suitable growing areas of cigar tobacco products, in the basic data processing unit, the basic geographic data includes the altitude, longitude and latitude, and topographic features of the cigar tobacco growing area;

[0035] The environmental measured data include meteorological element data of meteorological observation stations in the cigar planting area and surrounding areas during the cigar tobacco seedling raising, cultivation, air-drying and fermentation stages, and the meteorological element data include temperature, precipitation, sunshine, wind, humidity and soil temperature;

[0036] The tobacco leaf chemical composition data include water-soluble total sugar, reducing sugar, total nitrogen, nicotine and potassium content;

[0037] The tobacco sensory data include aroma type, aroma quantity, miscellaneous smell, strength, aftertaste, combustibility, gray color and sweetness;

[0038] The tobacco leaf physical index data include single leaf weight, tobacco leaf stem content, and tobacco leaf length and width.

[0039] As a preferred solution for the prediction and evaluation system of suitable growing areas for cigar products, in the forecast model construction unit, a temperature suitability model, a precipitation suitability model, a sunshine suitability model and a climate suitability model for cigar quality are constructed in units of ten days, and a dynamic forecast model for cigar quality using a statistical method is constructed.

[0040] As a preferred solution of the prediction and evaluation system for suitable planting areas of cigar tobacco products, in the prediction and screening unit for suitable planting areas, GIS technology is used to calculate and simulate the spatial distribution of various meteorological factors affecting the growth of cigar tobacco leaves in the cigar planting area, including:

[0041] Based on the collected and collated temperature and precipitation data of meteorological stations, multivariate statistical models between temperature, precipitation and geographical location and terrain factors were established.

[0042] The model prediction value is calculated for each DEM cell, and the climate residual is interpolated using the spatial interpolation method to obtain the rasterized residual; the DEM cell and the model prediction value are superimposed to obtain the spatial distribution map of temperature and precipitation in the cigar growing area.

[0043] As a preferred solution for the prediction and evaluation system of suitable growing areas for cigar tobacco products, the optimal spatial interpolation model for interpolating climate residuals using the spatial interpolation method is a ternary spline function with longitude, latitude and altitude as independent variables.

[0044] As the optimal solution for the prediction and evaluation system of suitable growing areas for cigar tobacco products, the root mean square error and mean absolute error indicators are used to evaluate the effect of temperature and precipitation interpolation in cigar growing areas, and the 3σ standard deviation is used to evaluate the stability of the temperature and precipitation interpolation errors in cigar growing areas.

[0045] Based on DEM data, the terrain factors of slope, aspect and terrain shielding were extracted, and the multi-factor simulation method was used under the GIS platform to simulate the sunshine hours that affect the key growth period of cigar planting areas.

[0046] According to the meteorological conditions during the growing period that affect the production of cigar tobacco leaves, combined with the correlation analysis results of tobacco leaf yield, quality and meteorological conditions during the growing period in previous years, the analysis period of climate factors was determined; and each climate factor was dimensionlessly normalized.

[0047] As a preferred solution for the prediction and evaluation system of suitable planting areas for cigar tobacco products, the planting points of high-quality cigar planting areas and the grid points of cigar planting areas in designated areas are taken as different individuals in the m-dimensional space, and the similarity distance between any grid point and each planting point in the high-quality cigar planting area is calculated respectively, and the minimum similarity distance is selected as the similarity distance between this grid point and the high-quality cigar planting area;

[0048] By dividing the distance into similar levels, comparative analysis of climate factors between designated areas with similar climates to those of premium cigar growing areas is conducted;

[0049] According to the determined key climate influencing factors, the weights of each key climate influencing factor are determined using expert scoring, hierarchical analysis, and fuzzy comprehensive evaluation methods; the cigar tobacco eco-climate zoning is carried out through the zoning model, and the cigar tobacco eco-climate suitability zoning is carried out.

[0050] The invention has the following advantages: collecting and collating basic data of the designated area, the basic data including basic geographical data, environmental measured data, tobacco chemical composition data, tobacco sensory data and tobacco physical index data; comparing the collected basic data with the same type of data of the designated high-quality cigar planting area, analyzing the key factor differences of the growth characteristics of cigar tobacco leaves in the designated area and the designated high-quality cigar planting area; determining the key climate influencing factors affecting the planting and air-drying fermentation of cigars, and evaluating the suitable range and critical threshold of the key meteorological elements in each stage of cigar production; selecting the key climate influencing factors as independent variables and the quality change as the dependent variable, and using the multivariate linear stepwise regression method to construct a dynamic prediction model of cigar quality based on key climate influencing factors; performing interannual prediction of cigar quality according to the dynamic prediction model of cigar quality, and screening the suitable planting area of ​​cigar products in the designated area. The invention can improve the sustainable development capacity of the cigar industry, provide a scientific basis for the introduction and planting zoning of cigars, and improve the production level and capacity of high-quality cigar tobacco leaves in my country. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0052] The structures, proportions, sizes, etc. illustrated in this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with the technology. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantial technical significance. Any structural modification, change in proportion or adjustment of size shall still fall within the scope of the technical contents disclosed in the present invention without affecting the effects and purposes that can be achieved by the present invention.

[0053] Figure 1 A schematic diagram of the process flow of the method for predicting and evaluating suitable growing areas for cigar tobacco products provided in an embodiment of the present invention;

[0054] Figure 2 Schematic diagram of a system for predicting and evaluating suitable growing areas for cigar tobacco products provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0055] The following is a description of the implementation of the present invention by specific embodiments. People familiar with the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] Example 1

[0057] See also Figure 1 Embodiment 1 of the present invention provides a method for predicting and evaluating suitable growing areas for cigar tobacco products, comprising the following steps:

[0058] S1. Collect and organize basic data of the designated area, including basic geographical data, environmental measured data, tobacco chemical composition data, tobacco sensory data and tobacco physical index data;

[0059] S2. Compare the collected basic data with the same type of data from the designated premium cigar growing areas, and analyze the differences in key factors of cigar tobacco leaf growth characteristics between the designated areas and the designated premium cigar growing areas;

[0060] S3. Determine the key climate factors that affect cigar cultivation and air-curing fermentation, and evaluate the suitable range and critical threshold of key meteorological elements in each stage of cigar production;

[0061] S4. Select key climate influencing factors as independent variables and quality changes as dependent variables, and use the multivariate linear stepwise regression method to construct a dynamic prediction model for cigar quality based on key climate influencing factors;

[0062] S5. Make annual predictions on the quality of cigars based on the dynamic prediction model for cigar quality, and select suitable growing areas for cigars in designated areas.

[0063] In this embodiment, by consulting relevant literature and collecting data, the climate, soil, and ecological factors of the origin of high-quality cigars and major cigar-growing areas in China were analyzed to clarify the growth characteristics of high-quality cigars during the growth period.

[0064] Specifically, the basic geographic data is the geographic information data of the cigar tobacco growing area, including the altitude, longitude and latitude, and topographic features of the cigar tobacco growing area. The measured environmental data includes the meteorological element data of the meteorological observation stations in the cigar growing area and the surrounding areas during the cigar tobacco seedling, cultivation, air-drying and fermentation stages. The meteorological element data include temperature, precipitation, sunshine, wind, humidity and soil temperature. The tobacco chemical composition data include water-soluble total sugar, reducing sugar, total nitrogen, nicotine and potassium content; the tobacco sensory data include aroma type, aroma volume, impurities, strength, aftertaste, combustibility, gray and sweetness; the tobacco physical index data include single leaf weight, tobacco stem content and tobacco leaf length and width.

[0065] At the same time, we also collect relevant information on foreign tobacco leaf origins and domestic high-quality cigar tobacco areas from agriculture, meteorology, tobacco and other departments; as well as information on major agricultural meteorological disasters and pests and diseases that affect tobacco leaf quality and yield.

[0066] In this embodiment, based on relevant data from national meteorological observation stations, automatic meteorological observation stations, and tobacco field microclimate observation stations, linear regression method, sliding average method, cumulative deviation method, Mann-Kendall method, and other methods are used to analyze the changing characteristics of factors such as temperature, precipitation, sunshine, evaporation, frost-free period, accumulated temperature ≥10°C and 80% guarantee rate, and number of days ≥20°C in tobacco-growing areas in different periods such as year, season, month, ten days, and different growing periods. At the same time, the evolution of extreme climate events that have a significant impact on tobacco leaf growth, such as continuous rain, heavy rain, hail, drought, and high temperature, are analyzed.

[0067] Specifically, by comparing the climate, soil, geography and other ecological and environmental factors and related tobacco leaf quality data in cigar-growing areas with the relevant data of major cigar-growing areas of origin of high-quality foreign cigars, the differences in key factors of the growth characteristics of cigar tobacco leaves in different regions are analyzed.

[0068] By analyzing and studying the relationship between the climate of the main varieties of cigar tobacco in the area and the quality and yield of tobacco leaves, the key climate influencing factors (heat, light and precipitation, etc.) that affect the seedling, cultivation, drying and fermentation of cigar tobacco leaves are determined, and the suitable range and critical threshold of key meteorological elements in each stage of cigar production are evaluated. Based on the cigar tobacco production and quality data and microclimate observation data, multivariate cluster analysis (k-means fast clustering method), correlation analysis, canonical correlation analysis and multivariate linear regression are carried out to establish a relationship model between the climate conditions during the transplanting period and the production and quality of cigar tobacco, and quantitatively analyze the impact of climate factors during the transplanting period on the production and quality of cigar tobacco.

[0069] In this embodiment, a temperature suitability model, a precipitation suitability model, a sunshine suitability model and a climate suitability model for cigar quality are constructed in units of ten days, and a dynamic prediction model for cigar quality using a statistical method is constructed.

[0070] Specifically, a dynamic prediction model for cigar quality with a step length of ten days was established, and key climate influencing factors were selected as independent variables, and quality changes were selected as dependent variables. The multivariate linear stepwise regression method was used to establish a dynamic prediction model for cigar quality based on key climate influencing factors. Fuzzy mathematical methods were used to comprehensively consider the impact of multiple meteorological factors such as temperature, precipitation, and sunshine on cigar quality. The temperature suitability model, precipitation suitability model, sunshine suitability model, and climate suitability model for cigar quality were constructed in units of ten days, and a dynamic prediction model for cigar quality based on statistical methods was established.

[0071] In this embodiment, GIS technology is used to calculate and simulate the spatial distribution of various meteorological factors that affect the growth of cigar tobacco leaves in the cigar planting area, including:

[0072] Based on the collected and collated temperature and precipitation data of meteorological stations, multivariate statistical models between temperature, precipitation and geographical location and terrain factors were established.

[0073] The model prediction value is calculated for each DEM cell, and the climate residual is interpolated using the spatial interpolation method to obtain the rasterized residual; the DEM cell and the model prediction value are superimposed to obtain the spatial distribution map of temperature and precipitation in the cigar growing area.

[0074] Specifically, the calculation equation is established as:

[0075]

[0076] (1) In the formula, Y i (k) represents the climate resource value of the i-th climate element at the grid point, k = (1, ..., n) represents the number of grids, b j is the unknown coefficient, X j is the jth geographic parameter, such as longitude, latitude, altitude, slope, aspect, etc., is the prediction model established between the ith climate element and geographic data, ΔE i is the comprehensive geographical residual.

[0077] In this embodiment, the optimal spatial interpolation model for interpolating climate residuals using the spatial interpolation method is a ternary spline function with longitude, latitude and altitude as independent variables.

[0078] Specifically, Anusplin is based on the interpolation theory of ordinary thin disk and local thin disk spline functions. Local thin disk smoothing spline is an extension of the thin disk smoothing spline prototype. In addition to the usual spline independent variables, it allows the introduction of linear covariate sub-models, such as the correlation between temperature and altitude, and between evaporation and water vapor pressure difference.

[0079] The theoretical model of local thin disk smoothing splines is expressed as follows:

[0080] z i =f(x i )+b T y i +e i (i=1, ..., N) (2)

[0081] (2) Where: z i is the dependent variable at point i in space; x i is the d-dimensional spline independent variable; f is the estimated value of x i A known smooth function; y i is a p-dimensional independent covariate; b is y i The p-dimensional coefficient; e i is a random error of the independent variable with an expected value of 0.

[0082] The function f and the coefficient vector b can be determined by minimization, i.e., least squares estimation:

[0083]

[0084] (3) In the formula, J m (f) is the measurement function, f(x i ) is a function of complexity, also called a roughness measure function, which is defined as the integral of the mth-order partial derivative of the function f; ρ is a smoothness parameter, which takes a positive value. When ρ approaches O infinitely, the fitted function approaches the exact interpolation; when ρ approaches infinity, the fitted function approaches the least squares polynomial, and the degree of the polynomial depends on the order m of the roughness measure function. The value of the smoothness parameter ρ is usually determined by minimizing the prediction error of the fitting surface determined by the generalized cross-validation, or it can be determined by the generalized maximum likelihood based on the Bayesian formula.

[0085] In this embodiment, the root mean square error and mean absolute error indicators are used to evaluate the effect of temperature and precipitation interpolation in the cigar growing area, and the 3σ standard deviation is used to evaluate the stability of the temperature and precipitation interpolation errors in the cigar growing area. Specifically, by eliminating the observation station data one by one, other stations are used to simulate and generate the predicted value of the station, and the actual observation values ​​are compared and analyzed to determine the error of the interpolation. Low-altitude and high-altitude sample points are used to test the error respectively, and the root mean square error and mean absolute error indicators are used to evaluate the effect of temperature and precipitation interpolation in the tobacco growing area, and the 3σ standard deviation is used to evaluate the stability of the temperature and precipitation interpolation errors in the tobacco growing area.

[0086] In this embodiment, based on DEM data, terrain factors such as slope, aspect, and terrain shielding degree are extracted, and a multi-factor simulation method is applied on a GIS platform to simulate the sunshine hours that affect the key growth period of the cigar planting area.

[0087] Specifically, based on DEM data, by extracting terrain factors such as slope, aspect, and terrain shielding, a multi-factor simulation method was used on the GIS platform to simulate the sunshine hours that affect the key growth period of Hubei tobacco production areas. In order to facilitate computer implementation, the available sunshine angle in a day was discretized, that is, divided into a series of differential units, and the sunshine time in each unit time was simulated. The sunshine hours in a day were obtained after integral summation, and finally the duration data was added to obtain the corresponding sunshine hours.

[0088] In this embodiment, the climate factor analysis period is determined based on the meteorological conditions during the growth period that affect the production of cigar tobacco leaves, combined with the analysis results of the correlation between tobacco leaf yield, quality and meteorological conditions during the growth period in previous years; and each climate factor is dimensionlessly normalized.

[0089] Specifically, the weight of each climate factor is determined by the standard deviation method. The standard deviation weight method is an objective weighting method driven by local differences. The determination of the indicator weight is based on the discrimination of each indicator among each sample. The indicator with a large standard deviation has a large discreteness and is given a higher weight. The indicator weight is:

[0090]

[0091]

[0092] In formula (4) and (5), w k is the weight of the kth factor, m is the number of factors; S k is the sample standard deviation of the kth indicator, x ik is the normalized value of the kth factor of the ith sample point, is the average of the normalized values ​​of each sample point of the kth indicator, and n is the number of samples.

[0093] In this embodiment, the high-quality cigar growing area smoking points and the designated area cigar growing area grid points are taken as different individuals in the m-dimensional space, and the similarity distance between any grid point and each high-quality cigar growing area smoking point is calculated respectively, and the minimum similarity distance is selected as the similarity distance between this grid point and the high-quality cigar growing area;

[0094] By dividing the distance into similar levels, a comparative analysis of the climate factors of the designated area with similar climate to that of the high-quality cigar growing areas was conducted.

[0095] Specifically, the Euclidean distance is used to measure the similarity between two individuals. Suppose there is a sample XX,

[0096]

[0097] (6) In the formula, n is the sample size, m is the number of factors, and each individual can be regarded as a point in the m-dimensional space. The improved Euclidean distance is:

[0098]

[0099] (7) In the formula, i and j are two grid points (stations) in space, m is the number of factors, x is normalized, and d ij It can be regarded as the similarity distance between point i and point j. The smaller the distance, the higher the similarity.

[0100] In this embodiment, based on the determined key climate influencing factors, the weights of each key climate influencing factor are determined using expert scoring, hierarchical analysis, and fuzzy comprehensive evaluation methods; the cigar tobacco eco-climate zoning is carried out through a zoning model to perform cigar tobacco eco-climate suitability zoning.

[0101] At the same time, we also refer to the topography, basic tobacco field distribution, expert experience, and take certain administrative regions into consideration, and finally carry out the ecological and climatic suitability zoning of cigar tobacco leaves.

[0102] The zoning model is:

[0103]

[0104] (8) In the formula, S is the ecological climate suitability evaluation index of each evaluation unit; W i is the relative weight of the i-th evaluation factor; S i is the quantitative evaluation of the index of the i-th evaluation factor; n is the number of evaluation factors.

[0105] In summary, the present invention collects and organizes basic data of the designated area, including basic geographical data, environmental measured data, tobacco chemical composition data, tobacco sensory data and tobacco physical index data; compares the collected basic data with the same type of data of the designated high-quality cigar planting area, analyzes the key factor differences of the growth characteristics of cigar tobacco leaves in the designated area and the designated high-quality cigar planting area; determines the key climate influencing factors affecting cigar planting and air-drying fermentation, and evaluates the suitable range and critical threshold of key meteorological elements in each stage of cigar production; selects key climate influencing factors as independent variables and quality changes as dependent variables, and adopts the multivariate linear stepwise regression method to construct a dynamic prediction model of cigar quality based on key climate influencing factors; performs interannual prediction of cigar quality according to the dynamic prediction model of cigar quality, and screens suitable planting areas for cigar products in the designated area. The present invention can improve the sustainable development capacity of the cigar industry, provide a scientific basis for cigar introduction and planting zoning, and improve the production level and capacity of high-quality cigar tobacco leaves in my country.

[0106] Example 2

[0107] See also Figure 2 Embodiment 2 of the present invention further provides a prediction and evaluation system for suitable growing areas of cigar tobacco products, comprising:

[0108] A basic data processing unit 1 is used to collect and organize basic data of a designated area, wherein the basic data includes basic geographic data, environmental measured data, tobacco chemical composition data, tobacco sensory data, and tobacco physical index data;

[0109] The difference analysis unit 2 is used to compare the collected basic data with the same type of data from the designated high-quality cigar growing area, and analyze the differences in key factors of the growth characteristics of cigar tobacco leaves between the designated area and the designated high-quality cigar growing area;

[0110] Meteorological element assessment unit 3 is used to determine the key climate factors that affect cigar cultivation and air-curing fermentation, and to assess the suitable range and critical threshold of key meteorological elements at each stage of cigar production;

[0111] The forecast model building unit 4 is used to select key climate influencing factors as independent variables and quality changes as dependent variables, and adopt a multivariate linear stepwise regression method to build a dynamic forecast model for cigar quality based on key climate influencing factors;

[0112] The suitable planting area prediction and screening unit 5 is used to make an annual prediction of the quality of cigars according to the dynamic prediction model of the quality of cigars, and screen the suitable planting areas of cigars in the designated area.

[0113] In this embodiment, in the basic data processing unit 1, the basic geographic data includes the altitude, longitude and latitude, and topographic features of the cigar tobacco growing area;

[0114] The environmental measured data include meteorological element data of meteorological observation stations in the cigar planting area and surrounding areas during the cigar tobacco seedling raising, cultivation, air-drying and fermentation stages, and the meteorological element data include temperature, precipitation, sunshine, wind, humidity and soil temperature;

[0115] The tobacco leaf chemical composition data include water-soluble total sugar, reducing sugar, total nitrogen, nicotine and potassium content;

[0116] The tobacco sensory data include aroma type, aroma quantity, miscellaneous smell, strength, aftertaste, combustibility, gray color and sweetness;

[0117] The tobacco leaf physical index data include single leaf weight, tobacco leaf stem content, and tobacco leaf length and width.

[0118] In this embodiment, the forecast model building unit 4 builds a temperature suitability model, a precipitation suitability model, a sunshine suitability model and a climate suitability model for cigar quality in units of ten days, and builds a dynamic forecast model for cigar quality using a statistical method.

[0119] In this embodiment, the suitable planting area prediction and screening unit 5 uses GIS technology to calculate and simulate the spatial distribution of various meteorological factors affecting the growth of cigar tobacco leaves in the cigar planting area, including:

[0120] Based on the collected and collated temperature and precipitation data of meteorological stations, multivariate statistical models between temperature, precipitation and geographical location and terrain factors were established.

[0121] The model prediction value is calculated for each DEM cell, and the climate residual is interpolated using the spatial interpolation method to obtain the rasterized residual; the DEM cell and the model prediction value are superimposed to obtain the spatial distribution map of temperature and precipitation in the cigar growing area.

[0122] In this embodiment, the optimal spatial interpolation model for interpolating climate residuals using the spatial interpolation method is a ternary spline function with longitude, latitude and altitude as independent variables.

[0123] In this embodiment, the root mean square error and mean absolute error indicators are used to evaluate the effect of temperature and precipitation interpolation in the cigar growing area, and the 3σ standard deviation is used to evaluate the stability of the temperature and precipitation interpolation errors in the cigar growing area;

[0124] Based on DEM data, the terrain factors of slope, aspect and terrain shielding were extracted, and the multi-factor simulation method was used under the GIS platform to simulate the sunshine hours that affect the key growth period of cigar planting areas.

[0125] According to the meteorological conditions during the growing period that affect the production of cigar tobacco leaves, combined with the correlation analysis results of tobacco leaf yield, quality and meteorological conditions during the growing period in previous years, the analysis period of climate factors was determined; and each climate factor was dimensionlessly normalized.

[0126] In this embodiment, the high-quality cigar growing area smoking points and the designated area cigar growing area grid points are taken as different individuals in the m-dimensional space, and the similarity distance between any grid point and each high-quality cigar growing area smoking point is calculated respectively, and the minimum similarity distance is selected as the similarity distance between this grid point and the high-quality cigar growing area;

[0127] By dividing the distance into similar levels, comparative analysis of climate factors between designated areas with similar climates to those of premium cigar growing areas is conducted;

[0128] According to the determined key climate influencing factors, the weights of each key climate influencing factor are determined using expert scoring, hierarchical analysis, and fuzzy comprehensive evaluation methods; the cigar tobacco eco-climate zoning is carried out through the zoning model, and the cigar tobacco eco-climate suitability zoning is carried out.

[0129] It should be noted that the information interaction, execution process, etc. between the modules / units of the above-mentioned system are based on the same concept as the method embodiment in Example 1 of the present application, and the technical effects they bring are the same as those of the method embodiment of the present application. For specific contents, please refer to the description in the method embodiment shown in the previous part of the present application, and will not be repeated here.

[0130] Example 3

[0131] Embodiment 3 of the present invention provides a non-transitory computer-readable storage medium, in which a program code of a method for predicting and evaluating suitable growing areas for cigar tobacco products is stored. The program code includes instructions for executing the method for predicting and evaluating suitable growing areas for cigar tobacco products of embodiment 1 or any possible implementation thereof.

[0132] The computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more available media. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0133] Example 4

[0134] Embodiment 4 of the present invention provides an electronic device, including: a memory and a processor;

[0135] The processor and the memory communicate with each other via a bus; the memory stores program instructions executable by the processor, and the processor calls the program instructions to execute the method for predicting and evaluating suitable growing areas for cigar products of Example 1 or any possible implementation thereof.

[0136] Specifically, the processor can be implemented by hardware or by software. When implemented by hardware, the processor can be a logic circuit, an integrated circuit, etc.; when implemented by software, the processor can be a general-purpose processor implemented by reading software codes stored in a memory. The memory can be integrated in the processor or can be located outside the processor and exist independently.

[0137] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center.

[0138] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0139] Although the present invention has been described in detail above by general description and specific embodiments, it is obvious to those skilled in the art that some modifications or improvements can be made to the present invention. Therefore, these modifications or improvements made without departing from the spirit of the present invention all belong to the scope of protection claimed by the present invention.

Claims

1. A method for predicting and evaluating suitable growing areas for cigar tobacco products, characterized in that: The following steps are involved: Collect and organize basic data of the designated area, including basic geographical data, environmental measurement data, tobacco leaf chemical composition data, tobacco leaf sensory data, and tobacco leaf physical index data; Compare the collected basic data with the same type of data from designated premium cigar growing areas to analyze the differences in key factors of cigar tobacco leaf growth characteristics between the designated areas and designated premium cigar growing areas; Identify the key climate factors that affect cigar cultivation and air-curing and fermentation, and assess the suitable ranges and critical thresholds of key meteorological elements at each stage of cigar production; The key climate influencing factors were selected as independent variables and the quality change as the dependent variable. The multivariate linear stepwise regression method was used to construct a dynamic prediction model of cigar quality based on the key climate influencing factors. Conduct interannual predictions of cigar quality based on a dynamic cigar quality prediction model, and screen suitable cigar growing areas in designated regions; Based on ten-day periods, we constructed temperature suitability models, precipitation suitability models, sunshine suitability models, and climate suitability models for cigar quality, and also constructed a dynamic prediction model for cigar quality using statistical methods. GIS technology was used to estimate and simulate the spatial distribution of various meteorological factors affecting cigar tobacco growth in cigar-growing areas, including: Based on the collected and collated temperature and precipitation data of meteorological stations, multivariate statistical models between temperature, precipitation and geographical location and topographic factors were established. The model prediction value is calculated for each DEM cell, and the climate residual is interpolated using spatial interpolation methods to obtain rasterized residuals. The DEM cells and model prediction values ​​are superimposed to obtain the spatial distribution map of temperature and precipitation in the cigar growing area. The calculation equation is established as: Where Y i (k) represents the climate resource value of the i-th climate element at the grid point, k = (1, ..., n) represents the number of grids, b j is the unknown coefficient, X j is the jth geographic parameter, is the prediction model established between the i-th climate factor and geographic data, ΔE i is the comprehensive geographical residual; The high-quality cigar growing area smoking points and the designated area cigar smoking area grid points are regarded as different individuals in the m-dimensional space. The similarity distance between any grid point and each high-quality cigar growing area smoking point is calculated respectively, and the minimum similarity distance is selected as the similarity distance between this grid point and the high-quality cigar growing area. By dividing the distance into similarity levels, a comparative analysis of climate factors between designated areas with similar climates to those of premium cigar growing areas was conducted; Based on the identified key climate influencing factors, the weights of each key climate influencing factor were determined using expert scoring, hierarchical analysis, and fuzzy comprehensive evaluation methods; the cigar tobacco eco-climate zoning was carried out using a zoning model, and the eco-climate suitability zoning for cigar tobacco was carried out; The zoning model is: Where S is the eco-climate suitability evaluation index of each evaluation unit; W i is the relative weight of the i-th evaluation factor; S i is the quantitative evaluation of the index of the i-th evaluation factor; n is the number of evaluation factors.

2. The method for predicting and evaluating suitable growing areas for cigar products according to claim 1, characterized in that: The basic geographic data include the altitude, longitude and latitude, and topographic features of the cigar tobacco growing area; The environmental measured data includes meteorological element data from meteorological observation stations in the cigar-growing area and surrounding areas during the cigar tobacco seedling, cultivation, air-conditioning and fermentation stages. The meteorological element data includes air temperature, precipitation, sunshine, wind, humidity and soil temperature; The tobacco leaf chemical composition data include water-soluble total sugar, reducing sugar, total nitrogen, nicotine and potassium content; The sensory data of tobacco leaves include aroma type, aroma quantity, off-flavor, strength, aftertaste, burning property, gray color and sweetness; The tobacco leaf physical index data include single leaf weight, tobacco leaf stem content, and tobacco leaf length and width.

3. The method for predicting and evaluating suitable growing areas for cigar tobacco products according to claim 1, characterized in that: The optimal spatial interpolation model for interpolating climate residuals using the spatial interpolation method is a ternary spline function with longitude, latitude and altitude as independent variables.

4. The method for predicting and evaluating suitable growing areas for cigar tobacco products according to claim 3, characterized in that: The root mean square error and mean absolute error were used to evaluate the interpolation effect of temperature and precipitation in the cigar growing area, and the 3σ standard deviation was used to evaluate the stability of the interpolation error of temperature and precipitation in the cigar growing area. Based on DEM data, the terrain factors of slope, aspect and terrain shielding were extracted, and the multi-factor simulation method was applied on the GIS platform to simulate the sunshine hours affecting the critical growth period in cigar planting areas.

5. The method for predicting and evaluating suitable growing areas for cigar tobacco products according to claim 4, characterized in that: Based on the meteorological conditions during the growing period that affect cigar tobacco production, and combined with the correlation analysis results of tobacco yield, quality and meteorological conditions during the growing period in previous years, the analysis period of climate factors was determined; and each climate factor was dimensionlessly normalized.

6. A prediction and evaluation system for suitable growing areas of cigar tobacco products, characterized in that: include: A basic data processing unit is used to collect and organize basic data of a designated area, including basic geographical data, environmental measurement data, tobacco chemical composition data, tobacco sensory data, and tobacco physical index data; A difference analysis unit is used to compare the collected basic data with the same type of data from the designated premium cigar growing area, and analyze the differences in key factors of cigar tobacco leaf growth characteristics between the designated area and the designated premium cigar growing area; The meteorological element assessment unit is used to determine the key climate factors that affect cigar cultivation and air-curing and fermentation, and to assess the suitable range and critical thresholds of key meteorological elements at each stage of cigar production; The forecast model construction unit is used to select key climate influencing factors as independent variables and quality changes as dependent variables, and use the multivariate linear stepwise regression method to construct a dynamic forecast model for cigar quality based on key climate influencing factors; The suitable planting area prediction and screening unit is used to make interannual predictions of cigar quality based on the cigar quality dynamic prediction model and screen suitable planting areas for cigars in designated areas; In the forecast model construction unit, a temperature suitability model, a precipitation suitability model, a sunshine suitability model and a climate suitability model for cigar quality are constructed in units of ten days, and a dynamic forecast model for cigar quality using a statistical method is constructed; In the suitable planting area prediction and screening unit, GIS technology is used to calculate and simulate the spatial distribution of various meteorological factors affecting cigar tobacco growth in cigar planting areas, including: Based on the collected and collated temperature and precipitation data of meteorological stations, multivariate statistical models between temperature, precipitation and geographical location and topographic factors were established. The model prediction value is calculated for each DEM cell, and the climate residual is interpolated using spatial interpolation methods to obtain rasterized residuals. The DEM cells and model prediction values ​​are superimposed to obtain the spatial distribution map of temperature and precipitation in the cigar growing area. The calculation equation is established as: Where Y i (k) represents the climate resource value of the i-th climate element at the grid point, k = (1, ..., n) represents the number of grids, b j is the unknown coefficient, X j is the jth geographic parameter, is the prediction model established between the i-th climate factor and geographic data, ΔE i is the comprehensive geographical residual; The high-quality cigar growing area smoking points and the designated area cigar smoking area grid points are regarded as different individuals in the m-dimensional space. The similarity distance between any grid point and each high-quality cigar growing area smoking point is calculated respectively, and the minimum similarity distance is selected as the similarity distance between this grid point and the high-quality cigar growing area. By dividing the distance into similarity levels, a comparative analysis of climate factors between designated areas with similar climates to those of premium cigar growing areas was conducted; Based on the identified key climate influencing factors, the weights of each key climate influencing factor were determined using expert scoring, hierarchical analysis, and fuzzy comprehensive evaluation methods; the cigar tobacco eco-climate zoning was carried out using a zoning model, and the eco-climate suitability zoning for cigar tobacco was carried out; The zoning model is: Where S is the eco-climate suitability evaluation index of each evaluation unit; W i is the relative weight of the i-th evaluation factor; S i is the quantitative evaluation of the index of the i-th evaluation factor; n is the number of evaluation factors.

7. The cigar tobacco suitable growing area prediction and evaluation system according to claim 6, characterized in that: In the basic data processing unit, the basic geographic data includes the altitude, longitude and latitude, and topographic features of the cigar tobacco growing area; The environmental measured data includes meteorological element data from meteorological observation stations in the cigar-growing area and surrounding areas during the cigar tobacco seedling, cultivation, air-conditioning and fermentation stages. The meteorological element data includes air temperature, precipitation, sunshine, wind, humidity and soil temperature; The tobacco leaf chemical composition data include water-soluble total sugar, reducing sugar, total nitrogen, nicotine and potassium content; The sensory data of tobacco leaves include aroma type, aroma quantity, off-flavor, strength, aftertaste, burning property, gray color and sweetness; The tobacco leaf physical index data include single leaf weight, tobacco leaf stem content, and tobacco leaf length and width; The optimal spatial interpolation model for interpolating climate residuals using spatial interpolation method is a ternary spline function with longitude, latitude and altitude as independent variables; The root mean square error and mean absolute error were used to evaluate the interpolation effect of temperature and precipitation in the cigar growing area, and the 3σ standard deviation was used to evaluate the stability of the interpolation error of temperature and precipitation in the cigar growing area. Based on DEM data, the topographic factors of slope, aspect and terrain shielding were extracted, and the multi-factor simulation method was applied on the GIS platform to simulate the sunshine hours during the critical growth period in the cigar planting area. Based on the meteorological conditions during the growth period that affect cigar tobacco production, combined with the correlation analysis results of tobacco yield, quality and meteorological conditions during the growth period over the years, the analysis period of climate factors was determined; Each climate factor was dimensionlessly normalized.

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