Method and system for determining planting proportion based on crop relationship

Abstract

The invention discloses a crop relationship-based planting proportion determination method and system. The method comprises the steps of obtaining crop data and determining a crop relationship according to the crop data; determining a crop combination; introducing an influence factor, and adjusting the influence factor; according to the adjusted influence factors, sales volume changes are determined, and the predicted sales volume is obtained; and generating the planting proportion of the crop combination. The system comprises a relation construction module, a combination determination module, an influence factor calculation module, a sales volume estimation module and a proportion calculation module. According to the invention, the planting proportion of the crop combination can be quantified according to the historical data so as to improve the benefit. The method can be widely applied to the technical field of agricultural planting.

Description

Technical Field

[0001] The present invention relates to the field of agricultural planting technology, and in particular to a method and system for determining a planting ratio based on crop relationships. Background Art

[0002] In modern agricultural planting, diversified planting is popular nowadays because it can enrich the farmland structure and has high practical significance. However, the current diversified planting is simply to introduce multiple crops to replace single crop planting. The planting ratio is not specifically quantified, which cannot fully improve economic benefits. There is also a lack of consideration of potential sales risks and adjustment of planting strategies. When the agricultural products planted by farmers face the risk of imbalance between sales and output in a certain quarter, there is a lack of specific quantification to make more accurate planting corrections. That is, the current planting plan lacks risk resistance. Summary of the invention

[0003] In view of this, in order to solve the technical problems that the existing planting methods do not specifically quantify the planting ratio of each crop and fail to fully utilize the substitution relationship between crops to improve the planting efficiency, the present invention proposes a method for determining the planting ratio based on the relationship between crops, and the method comprises the following steps:

[0004] obtaining crop data and determining crop relationships based on the crop data;

[0005] Among them, the crop relationship includes substitution and complementarity.

[0006] When the price of crop A changes, the sales volume of crop B changes in the same direction, that is, the two increase and decrease at the same time. This means that when the price or sales volume of one of A or B changes, consumers will turn to buy the other, that is, they believe that A and B are substitutable.

[0007] When the price of crop A changes, the sales volume of crop B changes in the opposite direction, that is, one increases and the other decreases, indicating that there is a dependency between A and B. When the price or sales volume of one changes, the other will produce the same change, that is, A and B are considered to be complementary.

[0008] determining a crop combination based on the crop relationship;

[0009] Based on the above crop relations, select crop combinations with substitutability and quantify the substitutability to further obtain the required planting ratio;

[0010] Introducing an impact factor, and adjusting the impact factor according to the crop data in the crop combination to obtain an adjusted impact factor;

[0011] Determine the sales volume change according to the adjusted impact factors to obtain the estimated sales volume;

[0012] A planting ratio of the crop combination is generated according to the expected sales volume.

[0013] In some embodiments, the step of obtaining crop data and determining crop relationships according to the crop data specifically includes:

[0014] Obtain sales and price data for each crop for the previous two years;

[0015] Performing a cross-price elasticity analysis on the crops according to the sales volume data and the price data to obtain a crop relationship;

[0016]

[0017] Among them, x represents the selected main crop, y represents the selected crop to be analyzed with the main crop, E xy represents the cross-price elasticity of crop x to crop y, ΔQ v / Q y It represents the percentage change in the sales volume of crop y, ΔP x / P x It represents the percentage change in the price of crop x.

[0018] If E xy is a positive value, that is, there is a substitution relationship between crops x and y, that is, when the sales volume of the main crop y decreases, the price of crop x will increase.

[0019] If E xy It is a negative value, that is, there is a complementary relationship between crops x and y, that is, when the sales volume of the main crop y decreases, the price of crop x will decrease.

[0020] In some embodiments, the step of determining the sales volume change according to the adjusted impact factor to obtain the estimated sales volume specifically includes:

[0021] Considering the main crop x, when there is no price change, define the first calculation formula for the expected total economic benefits;

[0022] The second calculation formula defines the expected total economic benefits when the price of the main crop x changes;

[0023] The first calculation formula and the second calculation formula are combined to solve the expected sales volume.

[0024] The present invention also proposes a system for determining a planting ratio based on crop relationships, the system comprising:

[0025] a relationship building module, for acquiring crop data and determining crop relationships based on the crop data;

[0026] A combination determination module, which determines a crop combination based on the crop relationship;

[0027] An impact factor calculation module, used for introducing an impact factor and adjusting the impact factor according to the crop data in the crop combination to obtain an adjusted impact factor;

[0028] A sales volume estimation module, used to determine sales volume changes according to the adjusted influencing factors to obtain estimated sales volume;

[0029] A ratio calculation module is used to generate a planting ratio of the crop combination according to the expected sales volume.

[0030] Beneficial effect: Based on the above scheme, the present invention provides a method and system for determining the planting ratio based on the relationship between crops. Compared with the traditional multiple planting, the present invention specifically quantifies the planting ratio between different crops, which is more instructive for farmers' planting. In addition, when there are risks in the planting process, the ratio can be corrected to better adapt to actual needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a flow chart of the steps of a method for determining a planting ratio based on crop relationships of the present invention;

[0032] Figure 2 It is a structural block diagram of a system for determining a planting ratio based on crop relationships according to the present invention. DETAILED DESCRIPTION

[0033] The present invention aims to analyze the complementary and substitutive relationship between crops by analyzing the changes in sales volume and unit price between crops, and then determine the extent of the mutual influence between the main crops and the selected crops, and establish an economic benefit measurement equation to determine the planting ratio between the two crops, so as to better guide farmers to plant crops reasonably in the new year, and at the same time make corrections for the quarters with sales risks, so as to timely adjust the planting ratio of the next quarter.

[0034] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0035] It should be noted that, for the convenience of description, only the parts related to the relevant invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other.

[0036] It should be understood that the "system", "device", "unit" and / or "module" used in this application is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the word can be replaced by other expressions.

[0037] As shown in this application and claims, unless the context clearly indicates an exception, the words "a", "an", "a kind" and / or "the" do not refer to the singular, but also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of clearly identified steps and elements, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements. The elements defined by the sentence "includes a..." do not exclude the existence of other identical elements in the process, method, commodity or device that includes the elements.

[0038] In the description of the embodiments of the present application, "plurality" means two or more than two. The following terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features.

[0039] In addition, flow charts are used in the present application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, the various steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or a certain step or several steps of operations may be removed from these processes.

[0040] Reference Figure 1 , is a flow chart of an optional example of a method for determining a planting ratio based on crop relationships proposed in the present invention, which method can be applied to a computer device. The imaging method proposed in this embodiment may include but is not limited to the following steps:

[0041] Step S1, acquiring crop data and determining crop relationships according to the crop data;

[0042] Step S2, determining a crop combination based on the crop relationship;

[0043] Step S3, introducing an influencing factor, and adjusting the influencing factor according to the crop data in the crop combination to obtain an adjusted influencing factor;

[0044] Step S4, determining sales volume changes according to the adjusted influencing factors to obtain estimated sales volume;

[0045] Step S5: generating a planting ratio of the crop combination according to the estimated sales volume.

[0046] In some feasible embodiments, the step S1 specifically includes:

[0047] First, we collect statistical data of each crop from the previous year to obtain the increase or decrease ratio of sales volume and price of each crop compared with the previous year, and use it as the benchmark value for analysis. At the same time, we select the main crops to be planted in the first quarter of this year and use them as the main crops for analysis.

[0048] Preliminary determination of complementarity and substitutability between crops:

[0049] First, we need to get the data for the previous two years. The price-related parameters are defined as follows:

[0050] Original price: P2; Price change over two years: ΔP = P1-P2

[0051] Subscript 1 represents the year before the current year, and subscript 2 represents the two years before the current year. Similarly, the sales volume related parameters are defined as follows:

[0052] Original sales volume: Q2; Change in sales volume between two years: ΔQ = Q1-Q2

[0053] After obtaining the above parameters of each crop, two crops are selected for cross-price elasticity analysis, wherein cross-price elasticity is used to measure the sensitivity of the sales volume of one crop to the price change of another crop. In the present invention, it is used to measure the changes in the sales volume of the selected crops planted in combination with the main crop when the price of the main crop changes. Specifically, when the price of the main crop drops, how much the sales volume of the crops planted in combination with it increases.

[0054] Substitute the corresponding parameters of the target crop combination into the cross-price elasticity calculation formula, which is defined as follows:

[0055]

[0056] Among them, x represents the selected main crop, y represents the selected crop to be analyzed with the main crop, E xy represents the cross-price elasticity of crop x to crop y, ΔQ v / Q y It represents the percentage change in the sales volume of crop y, ΔP x / P xIt represents the percentage change in the price of crop x.

[0057] If E xy is a positive value, that is, there is a substitution relationship between crops x and y, that is, when the sales volume of the main crop y decreases, the price of crop x will increase. xy It is a negative value, that is, there is a complementary relationship between crops x and y, that is, when the sales volume of the main crop y decreases, the price of crop x will decrease.

[0058] Therefore, it is preliminarily concluded that the relationship between the two crops is complementary or substitutable. In order to further verify the credibility of this relationship, a posteriori analysis is needed to further prove this result.

[0059] In some feasible embodiments, it also includes:

[0060] The crop relationships were verified based on the cross elasticity values.

[0061] Since the present invention is aimed at optimizing crop planting plans, accuracy needs to be ensured. The results obtained simply from the above cross-price elasticity analysis cannot guarantee accuracy. Therefore, a posteriori analysis of the above results is required for verification.

[0062] The cross-price elasticity value E between the two crops in the above cross-price elasticity analysis xy , and the relationship between the two parameters and the initial judgment are substituted into the subsequent Bayesian structural equation for testing.

[0063] First, define two prior parameters, alpha and beta, and let them obey the normal distribution with mean mu of 0 and standard deviation sigma of 0.5. Beta is the parameter of concern because it will reflect whether the preliminary relationship obtained in the previous article is feasible.

[0064] We define the observed value observed_elasticity, which is controlled by the two parameters alpha and beta, and set the standard deviation sigma to 0.1. This observed value will then be compared with the cross-price elasticity E calculated above. xy Association, used to calibrate and update parameter estimates in Bayesian inference.

[0065] Then let the model perform 3000 samplings to obtain the posterior distribution of alpha and beta, and get the mean beta of the beta of interest. mean , highest density interval (HDI) and R-hat and other information.

[0066] The obtained R-hat is then used to judge the convergence of the model. If its value is greater than 1.1, it means that the sampling has not converged, which is considered to lead to unreliable results.

[0067] Then, the beta value is analyzed, and the 3% and 97% quantiles of the HDI and its mean are selected. If the 3% HDI is greater than 0 and the mean is greater than 0, it is considered that there is a credible substitutability relationship between the two crops. If the 97% HDI is less than 0 and the mean is less than 0, it is considered that there is a credible complementary relationship between the two crops. Otherwise, it is considered untrustworthy, which suggests that farmers may not necessarily obtain an increase in economic benefits by planting these two crops together.

[0068] After the above two steps, a more reliable and accurate crop relationship analysis can be obtained. Subsequently, the above analysis can be performed with the main crops by continuously changing the crops to obtain a crop matching table around the main crops for farmers to choose.

[0069] In some feasible embodiments, the step S2 specifically includes:

[0070] In step S1, the relationship between the main crops and some crops is obtained, the complementarity and substitution between them are preliminarily determined and verified, and the cross-price elasticity E between the two crops in each combination is obtained. xy , and beta obtained from the posterior analysis mean ; Next, select a combination of crops with substitutability and quantify the substitutability to further obtain the required planting ratio.

[0071] In some feasible embodiments, the step S3 specifically includes:

[0072] When the sales volume of major crops in the previous quarter is significantly less than the output, the next quarter is considered to be a risky quarter for the major crops, and the planting ratio needs to be revised to better meet market demand and ensure the economic interests of farmers.

[0073] When the sales volume of major crops is significantly less than the output, it is necessary to consider the sales changes of each supplier during this period to correct the impact factor. Assume that there are i suppliers, {S1, S2, ..., S i}, respectively study the sales volume and price changes of the main crops and the selected alternative crops in the same period, and calculate the cross-price elasticity {E1, E2, ..., E i}, and the corresponding beta values ​​are {beta1, beta2, ..., beta i}, and obtain the influence factors of each supplier {ρ1, ρ2, ..., ρ i}, and determine the impact of each supplier on the final impact factor:

[0074]

[0075] where Δp i is the difference between the expected sales volume of the i-th purchaser and the sales volume of the current quarter. The difference Δτ is the output minus the sales volume.

[0076] The final correction of the influencing factor ρ′ is as follows:

[0077]

[0078] At this time, the sales volume and price of crops in the same period of the risk quarter should be selected as reference values, and the corrected influencing factors should be substituted into the model for determining the planting ratio to obtain the planting ratio of crops in the risk quarter and guide farmers to better plant.

[0079] In some feasible embodiments, the step S3 and the step S4 specifically include:

[0080] Explanation of the main parameters: E xy It represents the cross-price elasticity between crop x and crop y, reflecting the impact of changes in price and sales volume between crops x and y.

[0081] beta mean It reflects the most likely impact of cross-price elasticity, so the impact factor ρ can be defined, and its definition formula is as follows:

[0082] ρ=E xy ×beta mean

[0083] Based on this, we can establish a model to determine the planting ratio as follows:

[0084] 1) Based on the main crop x and the matching crop y in the previous quarter, the expected sales volume Q of the main crop x in this quarter is determined by the farmers. x , and given the initial price per kilogram of crops x, y x With P y , and yield per acre N x With N y , and give the corresponding planting cost per acre C x With C y

[0085] 2) When the price of main crop x does not change, the expected total economic benefit R is calculated as follows:

[0086]

[0087] 3) When the price of the main crop x changes as in the previous quarter, the sales volume of crop y will also change. Considering the seasonal effect, we choose E. xy With ρ, the formula for the change in sales volume of crop y in this case is as follows:

[0088]

[0089] At this time, if it is determined to be a risk quarter, it is replaced by the adjusted impact factor ρ′.

[0090] 4) Since the demand for crop y is greater than the supply, it will lead to an increase in price. Therefore, Q′ should be y Establish a connection with price changes.

[0091] First, we need to know the actual sales volume Q″ of crop y in the previous quarter y , and the final selling price P″ y , and then get the difference between the actual sales volume and the initial expected sales volume ΔQ′y, and the difference between the final selling price and the initial pricing ΔP′ y , from which we can define the price elasticity E of crop y itself in the previous quarter y as follows:

[0092]

[0093] Where P′ y Indicates the initial price of the previous quarter.

[0094] From this we can establish Q′ y The relationship with price changes is as follows:

[0095]

[0096] Q″ y Represents the estimated sales volume for the current quarter.

[0097] 5) When the price of main crop x changes, the calculation formula of expected total economic benefit R' is defined as follows:

[0098]

[0099] 6) Determine the expected sales volume Q of crop y y

[0100] Combining the economic benefit formulas of 2) and 5), we can solve for Q y The value of .

[0101] Generally speaking, the sales volume of crops is directly proportional to their planting volume. Consider the per-acre yield N of two crops. x With N y , then the planting ratio between the two crops as follows:

[0102]

[0103] This ratio shows that the farmland economic structure is relatively stable at this time. When the prices of major crops fluctuate, it can stabilize the income of farmers. At the same time, it can be combined and calculated multiple times to obtain the corresponding data table, so that farmers have more choices and better guidance for planting. At the same time, the above-mentioned crop y can be used as the main crop to further improve the layout of diversified planting.

[0104] The overall steps can be summarized as follows: according to the sales volume and unit price of the corresponding crops, the strength of the substitutability between the current main crops and other crops is analyzed through cross-price elasticity, and after the strength of the relationship is obtained, a posteriori analysis is conducted on these results to further ensure the accuracy of the above relationship; by quantifying the obtained substitutability, the planting ratio relationship between the current main crops and various substitutable crops is determined to guide farmers in planting crops; at the same time, the risk of a significant decline in the sales volume of the main crops is quantified, the existing ratio relationship is corrected, and farmers are guided in planting.

[0105] The present invention determines whether there is a substitution relationship between crops, and on this basis introduces corresponding influencing factors to measure the intensity of interaction between crops, and then determines the planting ratio through the established economic benefit measurement model; by considering the sales situation of buyers during this period compared with the same period, the influencing factors are corrected to guide farmers to allocate the planting ratio.

[0106] Based on the above scheme, the present invention also provides relevant data verification:

[0107] Recently, in a certain place in Shaoguan, the planting technology of sweet potatoes and corn has been improved, which has greatly boosted farmers' income. According to actual estimates, the basic information of these two crops is as follows, and subsequent fitting estimates are made based on the actual estimates of their possible quarterly fluctuations.

[0108] Corn information: yield per mu: 2,300 jin / mu; cost: 1,256 yuan / jin; unit price: 1.5 yuan / jin.

[0109] Sweet potato information: Yield per mu: 4,000 jin / mu; cost: 2,000 yuan / jin; unit price: 4 yuan / jin.

[0110] ΔP of corn x / P x The value is 4.2%; the ΔQ of sweet potato y / Q y The value is 5.4%; the price elasticity of the price difference between corn and sweet potatoes is calculated to be: 1.2857; the Bayesian posterior test verifies that the relationship is substitution, and obtains beta mean It is 0.629.

[0111] The resulting impact factor is 0.80871.

[0112] In the case where there is no risk, substituting the data into the economic benefit calculation model, the expected corn sales volume is 30,000 catties, and the price of corn dropped by 0.75 yuan in the previous quarter, and the final unit price was 0.75 yuan; at the same time, the output of sweet potatoes in the previous quarter was 3,000 catties, but the actual demand was 5,000 catties; the calculation shows that the planting ratio of corn to sweet potatoes in the next quarter is approximately 4.33:1.

[0113] The calculation of potential risk quarters is similar.

[0114] Table 1 Correction of some examples

[0115] Purchaser Reduction in purchase volume (catties) Impact Factor Contribution Impact Factor 1 10 2 / 7 0.6357 2 20 4 / 7 0.5472 3 5 1 / 7 0.4321 total 35 1 0.5561

[0116] Subsequent operations are calculated in the same way as S3 and S4.

[0117] like Figure 2 As shown, a system for determining a planting ratio based on crop relationships includes:

[0118] a relationship building module, for acquiring crop data and determining crop relationships based on the crop data;

[0119] A combination determination module, which determines a crop combination based on the crop relationship;

[0120] An impact factor calculation module, used for introducing an impact factor and adjusting the impact factor according to the crop data in the crop combination to obtain an adjusted impact factor;

[0121] A sales volume estimation module, used to determine sales volume changes according to the adjusted influencing factors to obtain estimated sales volume;

[0122] A ratio calculation module is used to generate a planting ratio of the crop combination according to the expected sales volume.

[0123] The contents of the above method embodiments are all applicable to the present system embodiments. The functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0124] A device for determining planting ratio based on crop relationship:

[0125] at least one processor;

[0126] at least one memory for storing at least one program;

[0127] When the at least one program is executed by the at least one processor, the at least one processor implements the method for determining the planting ratio based on crop relationships as described above.

[0128] The contents of the above method embodiments are all applicable to the present device embodiments. The functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0129] A storage medium stores processor-executable instructions, which are used to implement a method for determining a planting ratio based on crop relationships as described above when executed by the processor.

[0130] The contents of the above method embodiments are all applicable to the present storage medium embodiments. The functions specifically implemented by the present storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0131] The above is a specific description of the preferred implementation of the present invention, but the invention is not limited to the embodiments. Those skilled in the art may make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A method for determining a planting ratio based on crop relationships, characterized in that: The following steps are involved: obtaining crop data and determining crop relationships based on the crop data; determining a crop combination based on the crop relationship; Introducing an impact factor, and adjusting the impact factor according to the crop data in the crop combination to obtain an adjusted impact factor; Determine the sales volume change according to the adjusted impact factors to obtain the estimated sales volume; A planting ratio of the crop combination is generated according to the expected sales volume.

2. A method for determining a planting ratio based on crop relationships according to claim 1, characterized in that: Also includes: The crop relationships were verified based on the cross elasticity values.

3. The method for determining the planting ratio based on crop relationships according to claim 1, characterized in that: The step of obtaining crop data and determining crop relationships according to the crop data specifically includes: Obtain sales and price data for each crop; Performing a cross-price elasticity analysis on the crops according to the sales volume data and the price data to obtain a crop relationship; The crop relationships include substitution relationships and complementary relationships.

4. A method for determining a planting ratio based on crop relationships according to claim 3, characterized in that: The calculation formula of cross-price elasticity analysis is as follows: Among them, E xy represents the cross-price elasticity of crop x to crop y, ΔQ y / Q y represents the percentage change in sales volume of crop y, ΔP x / P x Indicates the percentage change in the price of crop x.

5. A method for determining a planting ratio based on crop relationships according to claim 4, characterized in that: The adjustment formula of the impact factor is as follows: Among them, ρ i represents the initial impact factor of the i-th supplier, Δp i It represents the difference between the expected sales volume of the ith purchaser and the sales volume of the current quarter, and Δτ is the output minus the sales volume.

6. A method for determining a planting ratio based on crop relationships according to claim 5, characterized in that: The step of determining the sales volume change according to the adjusted influencing factors to obtain the estimated sales volume specifically includes: Based on the two cases of unchanged price and changed price, the expected total economic benefits under different conditions are constructed to obtain a set of equations; Solving the system of equations generates estimated sales.

7. The method for determining the planting ratio based on crop relationships according to claim 2, characterized in that: The step of verifying the crop relationship based on the cross elasticity value specifically includes: Substituting the cross elasticity value and the crop relationship into a Bayesian model for testing; Defining a priori parameters and making the prior parameters subject to normal distribution; Define observations; Instruct the Bayesian model to perform sampling and generate a posterior distribution of the prior parameters to obtain a mean, a highest density interval, and R-hat; The crop relationship is tested according to the prior parameters and the corresponding mean, highest density interval and R-hat to obtain a verification result.

8. A system for determining planting ratios based on crop relationships, characterized in that: include: a relationship building module, for acquiring crop data and determining crop relationships based on the crop data; A combination determination module, which determines a crop combination based on the crop relationship; An impact factor calculation module, used for introducing an impact factor and adjusting the impact factor according to the crop data in the crop combination to obtain an adjusted impact factor; A sales volume estimation module, used to determine sales volume changes according to the adjusted influencing factors to obtain estimated sales volume; A ratio calculation module is used to generate a planting ratio of the crop combination according to the expected sales volume.

9. A device for determining a planting ratio based on crop relationships, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements a method for determining a planting ratio based on crop relationships as described in any one of claims 1 to 7.

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