Method for determining suitable planting areas for different wine grape varieties

Abstract

The invention discloses a method for determining suitable planting areas of different wine grape varieties, and belongs to the field of agricultural production, and the method comprises the following steps: adopting a sugar maturation model (GSR) established based on European wine grape harvest time and sugar concentration data, correcting the model by using the data of Chinese wine grape production areas, and determining the suitable planting areas of different wine grape varieties; and the suitable planting areas of different wine grape varieties are further determined in combination with the grape freezing injury risk indexes before harvesting, so that the method has important significance for improving the quality of wine in China.

Description

Technical Field

[0001] The present invention belongs to the field of agricultural production, and particularly relates to a method for determining suitable planting areas for different wine grape varieties. Background Art

[0002] Grape vines are perennial crops that are highly sensitive to climate and are easily affected by climate conditions, among which temperature is the main influencing factor. High-quality wine grape fruits are the basis for brewing high-quality wines. There are obvious climate differences in different wine grape producing areas in China, which have the innate advantage of realizing wine diversification. However, the varieties of wine grapes planted in China are relatively single, and the planting area proportion of Cabernet Sauvignon alone reaches more than 50%.

[0003] In recent years, with the continuous expansion of wine grape planting bases in China, the rational layout of varieties has also been widely emphasized. Therefore, aiming at the unique local conditions of different wine grape producing areas, determining the suitable varieties for each producing area is an important means to improve the quality of Chinese wines. However, the existing methods for determining suitable planting areas for wine grape varieties mostly use empirical indicators established by foreign scholars for analysis. The climate characteristics of wine grape planting areas in Europe are mainly Mediterranean climate, and most of the empirical indicators studied by predecessors were established under Mediterranean climate, with low adaptability to the continental monsoon climate in China. Summary of the Invention

[0004] To solve the above technical problems, the present invention provides a method for determining suitable planting areas for different wine grape varieties, including:

[0005] Improving the original sugar ripening model based on daily meteorological data and main grape varieties to obtain an improved sugar ripening model;

[0006] Obtaining the harvest periods of different wine grape producing areas under different sugar concentration conditions based on the improved sugar ripening model;

[0007] Constructing an index for frost damage occurring before the harvest of wine grapes, and obtaining the comprehensive frost damage index of wine grapes based on the harvest periods of different varieties of wine grapes in different wine grape producing areas under different sugar concentration conditions and the index for frost damage occurring before the harvest of wine grapes;

[0008] Setting suitable planting areas for wine grapes at different levels based on the comprehensive frost damage index of wine grapes.

[0009] Preferably, the process of obtaining the improved sugar ripening model includes:

[0010] Calculating the number of days with a stable temperature above 10°C using the five-day moving average method as the start date of the model;

[0011] Fixing the heat accumulation temperature of different varieties under different sugar concentration conditions to determine the parameters of different wine grape varieties;

[0012] Improve the original sugar maturity model based on the start date and the parameters of the different wine grape varieties to obtain the improved sugar maturity model.

[0013] Preferably, the expression for determining the parameters of the different wine grape varieties is:

[0014] F * S-target = a × [S - target] + b;

[0015] where [S - target] is the target sugar concentration; a and b are constants for a given variety, and F * s-target is the accumulated temperature when the grape berries reach the target sugar concentration.

[0016] Preferably, the process of obtaining the comprehensive frost damage index of wine grapes includes:

[0017] The frequencies and days of frost damage occurrence at different degrees of different wine grape varieties in different wine grape growing regions at different sugar concentrations;

[0018] Calculate the comprehensive frost damage frequency index and the comprehensive frost damage days index based on the frost damage occurrence frequency and the frost damage occurrence days;

[0019] Calculate the comprehensive frost damage index of the wine grapes by calculating the average method with equal weights for the comprehensive frost damage frequency index and the comprehensive frost damage days index.

[0020] Preferably, the calculation expression of the comprehensive frost damage frequency index is:

[0021]

[0022] where FP is the comprehensive frost damage frequency index, and Fp n represents the frequency of frost damage, and W n is the weighted value of light, medium, and severe frost damage.

[0023] Preferably, the calculation expression of the comprehensive frost damage days index is:

[0024]

[0025] where FD is the comprehensive frost damage days index, and Fd n represents the number of days of frost damage.

[0026] Preferably, the process of calculating the comprehensive frost damage frequency index and the comprehensive frost damage days index by the average method with equal weights further includes: performing range normalization processing on the comprehensive frost damage frequency index and the comprehensive frost damage days index.

[0027] Preferably, the indexes of frost damage occurring before the harvesting of the wine grapes are as follows: when -2°C ≤ the daily minimum temperature < 0°C, it is mild; when -4°C ≤ the daily minimum temperature < -2°C, it is moderate; when the daily minimum temperature < -4°C, it is severe.

[0028] On the other hand, the present invention also provides an electronic device, including a memory, a processor, and a computing program stored in the memory and operable on the processor, and when the processor executes the computing program, the method is implemented.

[0029] On the other hand, the present invention also provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the method is implemented.

[0030] Compared with the prior art, the present invention has the following advantages and technical effects:

[0031] Compared with the existing methods for determining the suitable planting areas of wine grapes, the present invention first improves the sugar ripening model, solving the problem that the current determination of the suitable planting areas of wine grapes mostly uses empirical indexes; the present invention also clarifies the suitable planting areas of different wine grape varieties under different sugar concentration conditions, making up for the problem that sugar concentration was not considered in the past; by calculating the comprehensive frost damage index of wine grapes and according to different grades of the comprehensive frost damage index of wine grapes, the suitable planting areas of wine grapes with different degrees are further determined. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The drawings forming a part of this application are used to provide a further understanding of this application. The schematic embodiments of this application and their descriptions are used to explain this application and do not constitute an improper limitation to this application. In the drawings:

[0033] Figure 1 is a schematic flow chart of the method according to an embodiment of the present invention;

[0034] Figure 2 is a schematic diagram of the predicted harvesting periods of six varieties under four target sugar concentrations according to an embodiment of the present invention;

[0035] Figure 3 is a schematic diagram of the comprehensive frost damage indexes of six varieties under four target sugar concentrations according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0036] It should be noted that, without conflict, the embodiments in this application and the features in the embodiments can be combined with each other. The following will refer to the drawings and combine the embodiments to detail this application.

[0037] It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0038] Embodiment 1

[0039] As Figure 1 shown, in this embodiment, a method for determining the suitable planting areas of different wine grape varieties is provided, including:

[0040] Verify the simulation effect of the grape sugar ripening model (GSR) in the Chinese wine grape production areas to determine the applicability of the model in different Chinese wine grape production areas.

[0041] Improve the grape sugar ripening model (GSR). First, change the start date of the model, and use the five-day moving average method to calculate the number of days with a stable temperature above 10°C as the start date of the model.

[0042] After determining the start date of the model, fix the heat accumulation temperature of 6 different varieties under different sugar concentration conditions to determine the parameters of 6 different wine grape varieties.

[0043] Use the revised model to determine that the harvest periods of 6 wine grape varieties in different northern Chinese wine grape production areas from 1961 to 2020 under different sugar concentration conditions are between July 16th and October 30th.

[0044] Set the index of frost damage occurring before the harvest of wine grapes as: -2°C ≤ daily minimum temperature < 0°C is mild, -4°C ≤ daily minimum temperature < -2°C is moderate, and daily minimum temperature < -4°C is severe. Calculate the occurrence frequencies (the percentage of frost years in the total number of years within a certain number of years) and days of different degrees of frost damage of 6 wine grape varieties in different northern Chinese wine grape production areas from 1961 to 2020 under different sugar concentrations.

[0045] Set the weight coefficients of mild, moderate, and severe frost damages as 0.17, 0.33, and 0.50 respectively, and calculate the comprehensive frost damage frequency index (the weighted average of different levels of frost damage frequencies) and the comprehensive frost damage day index (the weighted average of different levels of frost damage days).

[0046] In order to comprehensively evaluate the frost damage risk of wine grapes in different regions, perform range normalization on the comprehensive frost damage frequency index and the comprehensive frost damage day index to eliminate the influence of dimensions.

[0047] Set the weight coefficients of the comprehensive frost damage frequency index and the comprehensive frost damage day index as 0.5 and 0.5 respectively, and use the equal-weight averaging method to obtain the comprehensive frost damage index of wine grapes.

[0048] Set suitable planting areas for different degrees of wine grape varieties, where the comprehensive freeze injury index < 0.1 is the most suitable planting area, the comprehensive freeze injury index between 0.1 - 0.22 is the suitable planting area, the comprehensive freeze injury index between 0.22 - 0.35 is the relatively suitable planting area, and the comprehensive freeze injury index > 0.35 is the unsuitable planting area.

[0049] Example Two

[0050] In this example, a method for determining suitable planting areas for different wine grape varieties is provided, including:

[0051] (1) Verify the simulation effect of the Grapevine Sugar Ripeness (GSR) model in the Chinese wine grape production areas to determine the applicability of the model in the Chinese wine grape production areas. The calculation formula of the Grapevine Sugar Ripeness model is as follows in (1), T b and t 0 are fixed at 0 °C and the 91st day of the year (or April 1st) respectively, and do not change due to grape varieties. The accumulated temperature F * s-target varies depending on the variety and depends on the target sugar concentration in the berries of each variety (Table 1).

[0052]

[0053] In the formula, T b represents the temperature threshold, T d represents the daily average temperature greater than T b , that is, the temperature accumulation starts when the daily average temperature exceeds T b this temperature threshold; t 0 is the start date, t GHD is the harvest period at the target sugar concentration, and F * s-target is the accumulated temperature when the grape berries reach the target sugar concentration.

[0054] Table 1

[0055]

[0056] (2) The first step in improving the original Grapevine Sugar Ripeness (GSR) model is to change the start date of the model (i.e., t 0 ). Since the original GSR model was constructed based on observed data of grape sugar concentration and harvest period in Europe, the main climate types in Europe are Mediterranean and Atlantic climates, and April 1st (i.e., t 0The average daily temperature after 91 days (i.e., = 91 days) is almost always higher than 10°C, and the climate conditions in the main wine grape growing regions of China are different. In addition, the minimum temperature required for grapes to sprout in the following year after dormancy is 10°C. Therefore, the five-day moving average method is used to calculate the number of days with a stable temperature above 10°C as the start date of the improved model.

[0057] (3) Different target sugar concentrations [S-target] and accumulated temperature F * s-target The value can be described by the linear function (2). The accumulated temperature of different varieties under different sugar concentration conditions is fixed. Therefore, after determining the start date of the model, the parameters a and b of different wine grape varieties are further determined. Based on the measured sugar concentration and harvest period data in the Chinese wine grape growing regions, as well as the collected daily average temperature data of the corresponding stations, the two parameters a and b are re-estimated by combining formulas (1) and (2).

[0058] F * S-target = a × [S-target] + b (2)

[0059] In the formula, [S-target] is the target sugar concentration; a and b are constants for a given variety, and the values of a and b are different for different varieties.

[0060] Example: The accumulated temperature F of Chardonnay grapes when reaching sugar concentrations of 170, 180, 190, and 200 g / L * s-target are 2723, 2772, 2813, and 2892 °C·d respectively. Based on formula (2), the values of a and b are determined to be 7.34 and 1680 respectively.

[0061] (4) As Figure 2 shown, according to the determined values of a and b, and the target sugar concentration [S-target], the accumulated temperature F at the target sugar concentration can be obtained according to formula (2) * s-target , and then substituting it into formula (1), the harvest period t of 6 wine grape varieties in different northern wine grape growing regions from 1961 to 2020 under different sugar concentration conditions is determined using the revised model GHD is between July 16 and October 30. Figure 2 Among them, S170, S180, S190, S200, and S210 represent sugar concentrations of 170, 180, 190, 200, and 210 g / L respectively, and CH, CS, M, PN, R, and S represent Chardonnay, Cabernet Sauvignon, Merlot, Pinot Noir, Riesling, and Syrah respectively. HM, YQ, YC, HN, WW, ZY, LK, PD, HL, MY, TG, and LF represent Hami, Yanqi, Yinchuan, Huinong, Wuwei, Zhangye, Longkou, Pingdu, Huailai, Miyun, Linfen, and Taigu respectively.

[0062] (5) According to the research on freeze injury of wine grapes by Zhang Lei et al. (2018), the indexes of freeze injury occurring before the harvest of wine grapes are set as follows: when -2°C ≤ daily minimum temperature < 0°C, it is mild; when -4°C ≤ daily minimum temperature < -2°C, it is moderate; when daily minimum temperature < -4°C, it is severe. Calculate the occurrence frequencies (Formula 3) and occurrence days of freeze injury at different degrees of six wine grape varieties in different sugar concentrations in different wine grape production areas in northern China from 1961 to 2020. The occurrence days of freeze injury refer to the number of days when the daily minimum temperature before harvest is lower than 0, -2, and -4°C.

[0063] Fp n =F n / Y×100% (3)

[0064] In the formula, F n represents the number of years when the grapevines are damaged by freeze injury before harvest, that is, the number of years when the daily minimum temperature before harvest is lower than 0, -2, and -4°C. The corresponding n values are 1, 2, and 3, representing mild, moderate, and severe degrees respectively; Y is the total number of years, with a value of 60 (from 1961 to 2020).

[0065] (6) According to the research on freeze injury of wine grapes by Zhang Lei et al. (2018), the ratios of mild, moderate, and severe freeze injuries are set as 1:2:3, and the weight coefficients are set as 0.17, 0.33, and 0.50 respectively. Calculate the comprehensive freeze injury frequency index (the weighted average of freeze injury frequencies at different levels) and the comprehensive freeze injury days index (the weighted average of freeze injury days at different levels).

[0066]

[0067] In the formula, Fp n and Fd n represent the frequency and number of days of freeze injury respectively; W n is the weighted value of mild, moderate, and severe freeze injuries.

[0068] (7) In order to comprehensively evaluate the freeze injury risk of wine grapes in different regions, perform range normalization on the comprehensive freeze injury frequency index and the comprehensive freeze injury days index to eliminate the influence of dimension.

[0069] (8) As Figure 3 shown, according to the research on freeze injury of wine grapes by Zhang Lei et al. (2018), using the equal - weight averaging method, set the weight coefficients of the comprehensive freeze injury frequency index and the comprehensive freeze injury days index as 0.5 and 0.5 respectively to obtain the comprehensive freeze injury index of wine grapes.

[0070] (9) According to the research on freeze injury of wine grapes by Zhang Lei et al. (2018), different degrees of suitable planting areas for wine grapes are set. Among them, the comprehensive freeze injury index < 0.1 is the most suitable planting area, the comprehensive freeze injury index between 0.1 - 0.22 is the suitable planting area, the comprehensive freeze injury index between 0.22 - 0.35 is the relatively suitable planting area, and the comprehensive freeze injury index > 0.35 is the unsuitable planting area.

[0071] On the other hand, this embodiment also provides an electronic device, including a memory, a processor, and a computing program stored in the memory and executable on the processor. When the processor executes the computing program, the method is implemented.

[0072] On the other hand, this embodiment also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method is implemented.

[0073] The above is only a preferred specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed in this application should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A method for determining suitable planting areas for different wine grape varieties, characterized in that: include: The original sugar maturity model was improved based on daily meteorological data and main grape varieties to obtain an improved sugar maturity model; Based on the improved sugar maturity model, the harvest period of different varieties of wine grapes in different wine grape producing areas under different sugar concentration conditions is obtained; Constructing an index of frost damage before harvesting wine grapes, and obtaining a comprehensive frost damage index for wine grapes based on the harvest periods of different varieties in different wine grape producing areas under different sugar concentration conditions and the index of frost damage before harvesting wine grapes; Based on the comprehensive frost damage index of wine grapes, suitable planting areas of wine grapes of different degrees are set.

2. The method according to claim 1, characterized in that The process of obtaining the improved sugar maturation model comprises: The five-day moving average method was used to calculate the number of days that stably passed 10°C as the start date of the model; Fix the heat accumulation temperature of different varieties under different sugar concentration conditions to determine the parameters of different wine grape varieties; The original sugar ripening model is improved based on the start date and the parameters of the different wine grape varieties to obtain the improved sugar ripening model.

3. The method according to claim 2, characterized in that The expression for determining the parameters of different wine grape varieties is: F * S-target =a×[S-target]+b; Where [S-target] is the target sugar concentration; a and b are constants for a given variety, and F * s-target It is the accumulated temperature when the grape berries reach the target sugar concentration.

4. The method according to claim 1, characterized in that The process of obtaining the comprehensive freezing damage index of wine grapes includes: The frequency and number of days of freezing damage of different wine grape varieties in different wine grape producing areas at different sugar concentrations; Calculate the comprehensive frequency index of freezing damage and the comprehensive number of days of freezing damage based on the freezing damage frequency and the number of days of freezing damage; The comprehensive frost damage frequency index and the comprehensive frost damage day index are calculated based on the equal-weighted averaging method to obtain the comprehensive frost damage index for wine grapes.

5. The method according to claim 4, characterized in that The calculation expression of the comprehensive frequency index of frost damage is: Among them, FP is the comprehensive frequency index of frost damage, Fp n Indicates the frequency of freezing damage, W n It is the weighted value of light, moderate and severe frost damage.

6. The method according to claim 4, characterized in that The calculation expression of the comprehensive freezing damage days index is: Among them, FD is the comprehensive number of days of frost damage, Fd n Indicates the number of days of frost damage.

7. The method according to claim 1, characterized in that The process of calculating the comprehensive frequency index of frost damage and the comprehensive day index of frost damage based on the equal-weighted averaging method also includes: performing range normalization processing on the comprehensive frequency index of frost damage and the comprehensive day index of frost damage.

8. The method according to claim 1, characterized in that: The indicators of frost damage before the wine grapes are harvested are: -2℃ ≤ daily minimum temperature <0℃ for mild damage, -4℃ ≤ daily minimum temperature <-2℃ for moderate damage, and daily minimum temperature <-4℃ for severe damage.

9. An electronic device comprising a memory, a processor, and a computing program stored in the memory and executable on the processor, characterized in that: When the processor executes the computing program, the method described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method described in any one of claims 1 to 7 is implemented.

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