A method and system for assessing climate carrying capacity of grain crops

Abstract

The invention relates to the technical field of agricultural production, and discloses a method and system for evaluating the climate carrying capacity of grain crops. The method comprises the following steps: analyzing grain crop information in a grain crop production area, determining a development cycle corresponding to the grain crops, collecting climate data parameters corresponding to each sub-development node; extracting climate data parameters of the same standard from each sub-development node, constructing a climate data parameter set, and generating an initial evaluation mark for the climate data parameter set; generating multiple climate data parameter sequences according to the initial evaluation mark, and calculating a climate data evaluation coefficient; normalizing the climate data evaluation coefficient to obtain a climate data evaluation coefficient processing set, and calculating a climate carrying capacity evaluation coefficient for a grain crop production area. The method can perform a comprehensive climate analysis through the climate data parameters, comprehensively evaluate the climate carrying capacity, ensure the evaluation accuracy and evaluation efficiency, more accurately predict the growth conditions and potential yield of grain crops, and provide a scientific basis for agricultural production.

Description

Technical Field

[0001] The present invention relates to the field of agricultural production technology, and in particular to a method and system for evaluating the climate carrying capacity of grain crops. Background Art

[0002] Food crops refer to cereal crops, tuber crops and legume crops. Cereal crops: mainly include wheat, rice, corn, etc., tuber crops: include sweet potatoes, potatoes, etc., legume crops: legume crops such as soybeans, broad beans, peas, etc. Food crops occupy an important position in global agricultural production. However, food crops are also one of the industries most directly affected by climate change. The temperature, precipitation and radiation resources affected by global climate change have a significant impact on food crops, and food security has become a hot topic in the face of climate change.

[0003] Traditional environmental carrying capacity assessment methods often focus on the limitations of natural resources such as land and water, while ignoring the impact of climate change on food crops. Traditional environmental carrying capacity assessment methods also have many limitations. Traditional methods mostly use static or empirical assessment models, which are difficult to accurately reflect the dynamics and complexity of climate change, resulting in the lack of guidance for assessment results in practical application scenarios. In addition, existing research also has certain bottlenecks in data acquisition, processing and analysis methods, which restricts the accuracy and efficiency of climate carrying capacity assessment. Summary of the invention

[0004] In view of this, the present invention proposes a method and system for assessing the climate carrying capacity of grain crops, which can comprehensively assess the climate carrying capacity through multi-dimensional and multi-level comprehensive climate analysis, thereby ensuring the assessment accuracy and efficiency of the climate carrying capacity of grain crops.

[0005] The present invention proposes a method for assessing the climate carrying capacity of grain crops, comprising:

[0006] Determine food crop information in a food crop production area, analyze the food crop information, determine a development cycle corresponding to the food crop, and collect climate data parameters corresponding to each sub-development node;

[0007] Extracting climate data parameters of the same standard from each child development node, constructing a climate data parameter set, and generating an initial evaluation mark for each climate data parameter set according to an ideal climate data parameter range, wherein the initial evaluation mark includes an ideal evaluation mark, a sub-ideal evaluation mark, and a super-ideal evaluation mark;

[0008] generating a plurality of climate data parameter sequences according to the initial evaluation marks, and calculating the climate data evaluation coefficients of the climate data parameter set according to the climate data parameter sequences;

[0009] All climate data assessment coefficients are normalized, a climate data assessment coefficient processing set is obtained based on the processing results, the climate data assessment coefficient processing set is analyzed, and the climate carrying capacity assessment coefficient of the grain crop production area is calculated based on the analysis results.

[0010] Further, when extracting climate data parameters of the same standard from each sub-development node, constructing a climate data parameter set, and generating an initial evaluation mark for each climate data parameter set according to an ideal climate data parameter range, it includes:

[0011] Comparing and analyzing the climate data parameter set and the ideal climate data parameter range, wherein the ideal climate data parameter range includes a first ideal climate data parameter and a second ideal climate data parameter;

[0012] If the climate data parameter in the climate data parameter set is within the ideal climate data parameter range, generating the ideal evaluation mark for the climate data parameter;

[0013] If the climate data parameter in the climate data parameter set is greater than the second ideal climate data parameter, generating the super-ideal evaluation mark for the climate data parameter;

[0014] If a climate data parameter in the climate data parameter set is less than the second ideal climate data parameter, the less-than-ideal assessment flag is generated for the climate data parameter.

[0015] Further, when a plurality of climate data parameter sequences are generated according to the initial evaluation mark, and the climate data evaluation coefficient of the climate data parameter set is calculated according to the climate data parameter sequences, it includes:

[0016] Generate an ideal climate data parameter sequence according to all climate data parameters carrying the ideal evaluation mark;

[0017] Generate a super-ideal climate data parameter sequence according to all climate data parameters carrying the super-ideal evaluation mark;

[0018] generating a less-than-ideal climate data parameter sequence according to all climate data parameters carrying the less-than-ideal assessment mark;

[0019] Calculating a super-ideal climate data factor of the super-ideal climate data parameter sequence, and calculating a sub-ideal climate data factor of the sub-ideal climate data parameter sequence;

[0020] Counting the number of ideal climate data parameters of the ideal climate data parameter sequence;

[0021] A climate data evaluation coefficient of the climate data parameter set is calculated according to the super-ideal climate data factor, the sub-ideal climate data factor and the number of ideal climate data parameters.

[0022] Furthermore, when calculating the super-ideal climate data factor of the super-ideal climate data parameter sequence, it includes:

[0023] Extracting the same climate data parameters from the super-ideal climate data parameter sequence and obtaining a plurality of sub-super-ideal climate data parameter sequences;

[0024] Count the number of the first subsequences of the sub-super-ideal climate data parameter sequence;

[0025] Extract one climate data parameter from each of all sub-super-ideal climate data parameter sequences, and calculate the first climate data parameter and value;

[0026] Calculating the sequence mean of the super-ideal climate data parameter sequence, eliminating all sub-super-ideal climate data parameter sequences that are smaller than the sequence mean, and counting the number of tail sub-sequences of the remaining sub-super-ideal climate data parameter sequences;

[0027] Extract one climate data parameter from each of the remaining sub-super-ideal climate data parameter sequences, and calculate the tail climate data parameter and value;

[0028] The super-ideal climate data factor of the super-ideal climate data parameter sequence is calculated according to the number of the first subsequences, the first climate data parameter and value, the number of the last subsequences and the last climate data parameter and value.

[0029] Further, when calculating the climate data evaluation coefficient of the climate data parameter set according to the super-ideal climate data factor, the sub-ideal climate data factor and the number of ideal climate data parameters, it includes:

[0030] The climate data evaluation coefficient of the sub-development node is calculated according to the following formula:

[0031] ;

[0032] Among them, a is the climate data evaluation coefficient of the climate data parameter sequence, e1 is the super-ideal climate data factor, e2 is the sub-ideal climate data factor, f1 is the first calculation coefficient, n1 is the number of climate data parameters in the super-ideal climate data parameter sequence, g i is the i-th climate data parameter in the super-ideal climate data parameter sequence, k i is the weight corresponding to the i-th climate data parameter, f2 is the second calculation coefficient, n2 is the number of climate data parameters in the suboptimal climate data parameter sequence, c jis the jth climate data parameter in the less-than-ideal climate data parameter sequence, d j is the weight corresponding to the jth climate data parameter, h is the adjustment number of the climate data evaluation coefficient, f1>0, f2>0.

[0033] Further, the adjustment number of the climate data evaluation coefficient is determined according to the following steps:

[0034] Presetting a first preset adjustment number, a second preset adjustment number, and a third preset adjustment number;

[0035] When n3 / (n1+n2)<1, the first preset adjustment number is selected as the adjustment number of the climate data evaluation coefficient;

[0036] When 1≤n3 / (n1+n2)<1.2, the second preset adjustment number is selected as the adjustment number of the climate data evaluation coefficient;

[0037] When 1.2≤n3 / (n1+n2), the third preset adjustment number is selected as the adjustment number of the climate data evaluation coefficient; wherein n3 is the number of ideal climate data parameters.

[0038] Further, when analyzing the climate data assessment coefficient processing set and calculating the climate carrying capacity assessment coefficient of the food crop production area based on the analysis result, it includes:

[0039] Extracting a maximum climate data evaluation coefficient and a minimum climate data evaluation coefficient from the climate data evaluation coefficient processing set;

[0040] Calculating a first coefficient difference between the maximum climate data evaluation coefficient and the minimum climate data evaluation coefficient;

[0041] Calculate the second coefficient difference between the maximum climate data evaluation coefficient and each remaining climate data evaluation coefficient respectively;

[0042] Calculating the difference ratios of the first coefficient difference and each second coefficient difference respectively, and determining the mean of the difference ratios corresponding to all the difference ratios;

[0043] Classify all difference ratios greater than or equal to the difference ratio mean into a first difference ratio sequence;

[0044] Classify all difference ratios that are smaller than the difference ratio mean into a second difference ratio sequence;

[0045] The climate carrying capacity assessment coefficient of the food crop production area is calculated based on the first difference ratio sequence and the second difference ratio sequence.

[0046] Further, when calculating the climate carrying capacity assessment coefficient of the food crop production area according to the first difference ratio sequence and the second difference ratio sequence, it includes:

[0047] The climate carrying capacity assessment coefficient of the food crop production area is calculated according to the following formula:

[0048] ;

[0049] Among them, p is the climate carrying capacity assessment coefficient of the grain crop production area, m1 is the number of difference ratios in the first difference ratio sequence, m2 is the number of difference ratios in the second difference ratio sequence, q t is the tth difference ratio in the first difference ratio sequence, u r is the rth difference ratio in the second difference ratio sequence.

[0050] Further, after calculating the climate carrying capacity assessment coefficient of the food crop production area based on the analysis results, it also includes:

[0051] The sown area of ​​grain crops in the grain crop production area is determined, and the product value between the sown area and the climate carrying capacity assessment coefficient is calculated and used as the total potential production of grain crops in the grain crop production area.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] The invention discloses a method and system for evaluating the climate carrying capacity of grain crops. The method analyzes grain crop information in a grain crop production area, determines the development cycle corresponding to the grain crops, collects climate data parameters corresponding to each sub-development node; extracts climate data parameters of the same standard from each sub-development node, constructs a climate data parameter set, and generates an initial evaluation mark for the climate data parameter set; generates multiple climate data parameter sequences according to the initial evaluation mark, and calculates climate data evaluation coefficients; normalizes the climate data evaluation coefficients to obtain a climate data evaluation coefficient processing set, and calculates the climate carrying capacity evaluation coefficients of the grain crop production area. Comprehensive climate analysis can be performed through climate data parameters, and climate carrying capacity can be comprehensively evaluated to ensure evaluation accuracy and evaluation efficiency, more accurately predict growth conditions and potential yields of grain crops, and provide a scientific basis for agricultural production.

[0054] On the other hand, the present application also provides a food crop climate carrying capacity assessment system, comprising:

[0055] A data collection module, used to determine the food crop information in the food crop production area, analyze the food crop information, determine the development cycle corresponding to the food crop, and collect climate data parameters corresponding to each sub-development node;

[0056] A tag generation module is used to extract climate data parameters of the same standard from each sub-development node, construct a climate data parameter set, and generate an initial evaluation tag for each climate data parameter set according to an ideal climate data parameter range, wherein the initial evaluation tag includes an ideal evaluation tag, a sub-ideal evaluation tag, and a super-ideal evaluation tag;

[0057] a coefficient calculation module, used to generate a plurality of climate data parameter sequences according to the initial evaluation mark, and calculate the climate data evaluation coefficients of the climate data parameter set according to the climate data parameter sequences;

[0058] The climate assessment module is used to normalize all climate data assessment coefficients, obtain a climate data assessment coefficient processing set based on the processing results, analyze the climate data assessment coefficient processing set, and calculate the climate carrying capacity assessment coefficient of the food crop production area based on the analysis results.

[0059] It can be understood that the above-mentioned food crop climate carrying capacity assessment system and method have the same beneficial effects and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0061] Figure 1 A schematic diagram of a process flow of a method for assessing the climate carrying capacity of food crops provided by an embodiment of the present invention;

[0062] Figure 2 A schematic diagram of the structure of a food crop climate carrying capacity assessment system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0063] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0064] like Figure 1As shown, in some embodiments of the present application, this embodiment provides a method for assessing the climate carrying capacity of food crops, including:

[0065] S110: determining food crop information in a food crop production area, analyzing the food crop information, determining a development cycle corresponding to the food crop, and collecting climate data parameters corresponding to each sub-development node;

[0066] In this embodiment, the food crops include wheat, rice, sweet potato, potato and the like.

[0067] In this embodiment, each food crop has a different development cycle, such as the development cycle of wheat is 250 days, and the development cycle of rice is 120 days.

[0068] In this embodiment, a sub-development node is determined every seven days. For example, if the development cycle is 250 days, there are 35 sub-development nodes in total, and the number of sub-development nodes is 250 / 7, which is rounded up.

[0069] In this embodiment, the climate data parameters include temperature, solar radiation, precipitation, air pressure, humidity, etc. The climate data parameters corresponding to each sub-development node are the average climate data parameters corresponding to every seven days, which can be obtained from the local meteorological data station.

[0070] S120: extracting climate data parameters of the same standard from each child development node, constructing a climate data parameter set, and generating an initial evaluation mark for each climate data parameter set according to an ideal climate data parameter range, wherein the initial evaluation mark includes an ideal evaluation mark, a sub-ideal evaluation mark, and a super-ideal evaluation mark;

[0071] In some embodiments of the present application, when extracting climate data parameters of the same standard from each child development node, constructing a climate data parameter set, and generating an initial evaluation mark for each climate data parameter set according to an ideal climate data parameter range, it includes:

[0072] Comparing and analyzing the climate data parameter set and the ideal climate data parameter range, wherein the ideal climate data parameter range includes a first ideal climate data parameter and a second ideal climate data parameter;

[0073] If the climate data parameter in the climate data parameter set is within the ideal climate data parameter range, generating the ideal evaluation mark for the climate data parameter;

[0074] If the climate data parameter in the climate data parameter set is greater than the second ideal climate data parameter, generating the super-ideal evaluation mark for the climate data parameter;

[0075] If a climate data parameter in the climate data parameter set is less than the second ideal climate data parameter, the less-than-ideal assessment flag is generated for the climate data parameter.

[0076] In this embodiment, if the temperature is extracted from each child development node to construct a climate data parameter set, the temperature here is a climate data parameter of the same standard.

[0077] In this embodiment, the ideal climate data parameter range is determined according to the specific food crops, such as the ideal growth temperature of wheat is 15℃-22℃, and the ideal rainfall is 500mm-700mm, the ideal growth temperature of rice is 25℃ to 35℃, and the ideal growth rainfall is 500mm-1500mm, and the rest are not shown one by one.

[0078] The beneficial effect of the above technical solution is that the present invention compares and analyzes the climate data parameter set and the ideal climate data parameter range to generate ideal evaluation marks, sub-ideal evaluation marks and super-ideal evaluation marks, thereby laying the foundation for subsequent climate carrying capacity assessment.

[0079] S130: generating a plurality of climate data parameter sequences according to the initial evaluation mark, and calculating the climate data evaluation coefficient of the climate data parameter set according to the climate data parameter sequences;

[0080] In some embodiments of the present application, when a plurality of climate data parameter sequences are generated according to the initial evaluation mark, and the climate data evaluation coefficient of the climate data parameter set is calculated according to the climate data parameter sequences, the method includes:

[0081] Generate an ideal climate data parameter sequence according to all climate data parameters carrying the ideal evaluation mark;

[0082] Generate a super-ideal climate data parameter sequence according to all climate data parameters carrying the super-ideal evaluation mark;

[0083] generating a less-than-ideal climate data parameter sequence according to all climate data parameters carrying the less-than-ideal assessment mark;

[0084] Calculating a super-ideal climate data factor of the super-ideal climate data parameter sequence, and calculating a sub-ideal climate data factor of the sub-ideal climate data parameter sequence;

[0085] Counting the number of ideal climate data parameters of the ideal climate data parameter sequence;

[0086] A climate data evaluation coefficient of the climate data parameter set is calculated according to the super-ideal climate data factor, the sub-ideal climate data factor and the number of ideal climate data parameters.

[0087] In this embodiment, the number of ideal climate data parameters refers to the number of climate data parameters in the ideal climate data parameter sequence.

[0088] In some embodiments of the present application, when calculating the super-ideal climate data factor of the super-ideal climate data parameter sequence, it includes:

[0089] Extracting the same climate data parameters from the super-ideal climate data parameter sequence and obtaining a plurality of sub-super-ideal climate data parameter sequences;

[0090] Count the number of the first subsequences of the sub-super-ideal climate data parameter sequence;

[0091] Extract one climate data parameter from each of all sub-super-ideal climate data parameter sequences, and calculate the first climate data parameter and value;

[0092] Calculating the sequence mean of the super-ideal climate data parameter sequence, eliminating all sub-super-ideal climate data parameter sequences that are smaller than the sequence mean, and counting the number of tail sub-sequences of the remaining sub-super-ideal climate data parameter sequences;

[0093] Extract one climate data parameter from each of the remaining sub-super-ideal climate data parameter sequences, and calculate the tail climate data parameter and value;

[0094] The super-ideal climate data factor of the super-ideal climate data parameter sequence is calculated according to the number of the first subsequences, the first climate data parameter and value, the number of the last subsequences and the last climate data parameter and value.

[0095] In this embodiment, if the climate data parameter in the super-ideal climate data parameter sequence is temperature, the same climate data parameter is extracted to obtain multiple sub-super-ideal climate data parameter sequences, such as {20, 20}, {22, 22, 22}, {25, 25, 25}, {26, 26}, all in ° C. The number of first sub-sequences is 4, and one climate data parameter is extracted from each of them, that is, 20, 22, 25, and 26. If the sequence mean is 23, the remaining sub-super-ideal climate data parameter sequences are {25, 25, 25}, {26, 26}, and the number of tail sub-sequences is 2, and one climate data parameter is extracted from each of them, that is, 25 and 26. The above is shown by way of example and is not specifically limited.

[0096] In this embodiment, the super-ideal climate data factor of the super-ideal climate data parameter sequence is calculated according to the following formula:

[0097] ;

[0098] Among them, w is the super-ideal climate data factor, y1 is the number of first subsequences, y2 is the number of last subsequences, y3 is the first climate data parameter and value, and y4 is the last climate data parameter and value.

[0099] The beneficial effect of the above technical solution is: the present invention calculates the super-ideal climate data factor of the super-ideal climate data parameter sequence according to the number of first subsequences, the first climate data parameters and values, the number of last subsequences and the last climate data parameters and values, thereby ensuring the calculation accuracy of the super-ideal climate data factor, providing a basis for the calculation of the climate data evaluation coefficient, and further ensuring the calculation accuracy of the climate data evaluation coefficient.

[0100] It should be noted that the calculation method of the suboptimal climate data factor is the same as that of the superoptimal climate data factor. In order to save space, it will not be repeated here.

[0101] In some embodiments of the present application, when calculating the climate data evaluation coefficient of the climate data parameter set according to the super-ideal climate data factor, the sub-ideal climate data factor and the number of ideal climate data parameters, it includes:

[0102] The climate data evaluation coefficient of the sub-development node is calculated according to the following formula:

[0103] ;

[0104] Among them, a is the climate data evaluation coefficient of the climate data parameter sequence, e1 is the super-ideal climate data factor, e2 is the sub-ideal climate data factor, f1 is the first calculation coefficient, n1 is the number of climate data parameters in the super-ideal climate data parameter sequence, g i is the i-th climate data parameter in the super-ideal climate data parameter sequence, k i is the weight corresponding to the i-th climate data parameter, f2 is the second calculation coefficient, n2 is the number of climate data parameters in the suboptimal climate data parameter sequence, c j is the jth climate data parameter in the less-than-ideal climate data parameter sequence, d j is the weight corresponding to the jth climate data parameter, h is the adjustment number of the climate data evaluation coefficient, f1>0, f2>0.

[0105] In this embodiment, max{e1, e2} refers to taking the larger value of e1 and e2. If e1 and e2 are equal, one of them is randomly selected.

[0106] The beneficial effect of the above technical solution is that the present invention calculates the climate data evaluation coefficient of the climate data parameter set according to the super-ideal climate data factor, the sub-ideal climate data factor and the number of ideal climate data parameters, thereby ensuring the calculation accuracy of the climate data evaluation coefficient and further ensuring the accuracy of the climate carrying capacity assessment.

[0107] In some embodiments of the present application, the adjustment number of the climate data evaluation coefficient is determined according to the following steps:

[0108] Presetting a first preset adjustment number, a second preset adjustment number, and a third preset adjustment number;

[0109] When n3 / (n1+n2)<1, the first preset adjustment number is selected as the adjustment number of the climate data evaluation coefficient;

[0110] When 1≤n3 / (n1+n2)<1.2, the second preset adjustment number is selected as the adjustment number of the climate data evaluation coefficient;

[0111] When 1.2≤n3 / (n1+n2), the third preset adjustment number is selected as the adjustment number of the climate data evaluation coefficient; wherein n3 is the number of ideal climate data parameters.

[0112] In this embodiment, the first preset adjustment number is preferably 0.9, the second preset adjustment number is preferably 1.1, and the third preset adjustment number is preferably 1.2. The specific adjustment can be further adjusted according to actual conditions.

[0113] The beneficial effect of the above technical solution is that the present invention selects the corresponding preset adjustment number according to the number of ideal climate data parameters, realizes the dynamic adjustment of the climate data evaluation coefficient, and ensures the comprehensiveness of the calculation of the climate data evaluation coefficient.

[0114] S140: normalizing all climate data assessment coefficients, obtaining a climate data assessment coefficient processing set based on the processing results, analyzing the climate data assessment coefficient processing set, and calculating the climate carrying capacity assessment coefficient of the grain crop production area based on the analysis results.

[0115] In some embodiments of the present application, when analyzing the climate data assessment coefficient processing set and calculating the climate carrying capacity assessment coefficient of the food crop production area based on the analysis result, it includes:

[0116] Extracting a maximum climate data evaluation coefficient and a minimum climate data evaluation coefficient from the climate data evaluation coefficient processing set;

[0117] Calculating a first coefficient difference between the maximum climate data evaluation coefficient and the minimum climate data evaluation coefficient;

[0118] Calculate the second coefficient difference between the maximum climate data evaluation coefficient and each remaining climate data evaluation coefficient respectively;

[0119] Calculating the difference ratios of the first coefficient difference and each second coefficient difference respectively, and determining the mean of the difference ratios corresponding to all the difference ratios;

[0120] Classify all difference ratios greater than or equal to the difference ratio mean into a first difference ratio sequence;

[0121] Classify all difference ratios that are smaller than the difference ratio mean into a second difference ratio sequence;

[0122] The climate carrying capacity assessment coefficient of the food crop production area is calculated based on the first difference ratio sequence and the second difference ratio sequence.

[0123] In this embodiment, the maximum climate data evaluation coefficient, the minimum climate data evaluation coefficient and each of the remaining climate data evaluation coefficients are climate data evaluation coefficients after normalization processing.

[0124] The beneficial effect of the above technical solution is: the present invention determines the first difference ratio sequence and the second difference ratio sequence, and calculates the climate carrying capacity assessment coefficient of the grain crop production area according to the first difference ratio sequence and the second difference ratio sequence, thereby avoiding errors caused by human participation, realizing a comprehensive assessment of the climate carrying capacity, and ensuring the assessment accuracy and efficiency.

[0125] In some embodiments of the present application, when calculating the climate carrying capacity assessment coefficient of the food crop production area according to the first difference ratio sequence and the second difference ratio sequence, it includes:

[0126] The climate carrying capacity assessment coefficient of the food crop production area is calculated according to the following formula:

[0127] ;

[0128] Among them, p is the climate carrying capacity assessment coefficient of the grain crop production area, m1 is the number of difference ratios in the first difference ratio sequence, m2 is the number of difference ratios in the second difference ratio sequence, q t is the tth difference ratio in the first difference ratio sequence, u r is the rth difference ratio in the second difference ratio sequence.

[0129] In some embodiments of the present application, after calculating the climate carrying capacity assessment coefficient of the food crop production area based on the analysis results, the method further includes:

[0130] The sown area of ​​grain crops in the grain crop production area is determined, and the product value between the sown area and the climate carrying capacity assessment coefficient is calculated and used as the total potential production of grain crops in the grain crop production area.

[0131] The beneficial effect of the above technical solution is that the present invention can more accurately predict the growth conditions and potential yields of food crops, providing a scientific basis for agricultural production.

[0132] like Figure 2 As shown, in another preferred embodiment based on the above embodiment, this embodiment provides a food crop climate carrying capacity assessment system, including:

[0133] A data collection module, used to determine the food crop information in the food crop production area, analyze the food crop information, determine the development cycle corresponding to the food crop, and collect climate data parameters corresponding to each sub-development node;

[0134] A tag generation module is used to extract climate data parameters of the same standard from each sub-development node, construct a climate data parameter set, and generate an initial evaluation tag for each climate data parameter set according to an ideal climate data parameter range, wherein the initial evaluation tag includes an ideal evaluation tag, a sub-ideal evaluation tag, and a super-ideal evaluation tag;

[0135] a coefficient calculation module, used to generate a plurality of climate data parameter sequences according to the initial evaluation mark, and calculate the climate data evaluation coefficients of the climate data parameter set according to the climate data parameter sequences;

[0136] The climate assessment module is used to normalize all climate data assessment coefficients, obtain a climate data assessment coefficient processing set based on the processing results, analyze the climate data assessment coefficient processing set, and calculate the climate carrying capacity assessment coefficient of the food crop production area based on the analysis results.

[0137] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0138] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0139] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0140] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for assessing the climate carrying capacity of food crops, characterized in that: include: Determine food crop information in a food crop production area, analyze the food crop information, determine a development cycle corresponding to the food crop, and collect climate data parameters corresponding to each sub-development node; Extracting climate data parameters of the same standard from each child development node, constructing a climate data parameter set, and generating an initial evaluation mark for each climate data parameter set according to an ideal climate data parameter range, wherein the initial evaluation mark includes an ideal evaluation mark, a sub-ideal evaluation mark, and a super-ideal evaluation mark; generating a plurality of climate data parameter sequences according to the initial evaluation marks, and calculating the climate data evaluation coefficients of the climate data parameter set according to the climate data parameter sequences; Normalizing all climate data assessment coefficients, obtaining a climate data assessment coefficient processing set based on the processing results, analyzing the climate data assessment coefficient processing set, and calculating the climate carrying capacity assessment coefficient of the food crop production area based on the analysis results; When extracting climate data parameters of the same standard from each sub-development node, constructing a climate data parameter set, and generating an initial evaluation mark for each climate data parameter set according to an ideal climate data parameter range, it includes: Comparing and analyzing the climate data parameter set and the ideal climate data parameter range, wherein the ideal climate data parameter range includes a first ideal climate data parameter and a second ideal climate data parameter; If the climate data parameter in the climate data parameter set is within the ideal climate data parameter range, generating the ideal evaluation mark for the climate data parameter; If the climate data parameter in the climate data parameter set is greater than the second ideal climate data parameter, generating the super-ideal evaluation mark for the climate data parameter; If a climate data parameter in the climate data parameter set is less than the second ideal climate data parameter, generating the less-than-ideal assessment mark for the climate data parameter; When a plurality of climate data parameter sequences are generated according to the initial evaluation mark, and the climate data evaluation coefficient of the climate data parameter set is calculated according to the climate data parameter sequences, the method comprises: Generate an ideal climate data parameter sequence according to all climate data parameters carrying the ideal evaluation mark; Generate a super-ideal climate data parameter sequence according to all climate data parameters carrying the super-ideal evaluation mark; generating a less-than-ideal climate data parameter sequence according to all climate data parameters carrying the less-than-ideal assessment mark; Calculating a super-ideal climate data factor of the super-ideal climate data parameter sequence, and calculating a sub-ideal climate data factor of the sub-ideal climate data parameter sequence; Counting the number of ideal climate data parameters of the ideal climate data parameter sequence; Calculate the climate data evaluation coefficient of the climate data parameter set according to the super-ideal climate data factor, the sub-ideal climate data factor and the number of ideal climate data parameters; When calculating the super-ideal climate data factor of the super-ideal climate data parameter sequence, it includes: Extracting the same climate data parameters from the super-ideal climate data parameter sequence and obtaining a plurality of sub-super-ideal climate data parameter sequences; Count the number of the first subsequences of the sub-super-ideal climate data parameter sequence; Extract one climate data parameter from each of all sub-super-ideal climate data parameter sequences, and calculate the first climate data parameter and value; Calculating the sequence mean of the super-ideal climate data parameter sequence, eliminating all sub-super-ideal climate data parameter sequences that are smaller than the sequence mean, and counting the number of tail sub-sequences of the remaining sub-super-ideal climate data parameter sequences; Extract one climate data parameter from each of the remaining sub-super-ideal climate data parameter sequences, and calculate the tail climate data parameter and value; Calculate the super-ideal climate data factor of the super-ideal climate data parameter sequence according to the number of the first subsequences, the first climate data parameter and value, the number of the last subsequences and the last climate data parameter and value; When calculating the climate data evaluation coefficient of the climate data parameter set according to the super-ideal climate data factor, the sub-ideal climate data factor and the number of ideal climate data parameters, it includes: The climate data evaluation coefficient of the sub-development node is calculated according to the following formula: Among them, a is the climate data evaluation coefficient of the climate data parameter sequence, e1 is the super-ideal climate data factor, e2 is the sub-ideal climate data factor, f1 is the first calculation coefficient, n1 is the number of climate data parameters in the super-ideal climate data parameter sequence, g i is the i-th climate data parameter in the super-ideal climate data parameter sequence, k i is the weight corresponding to the i-th climate data parameter, f2 is the second calculation coefficient, n2 is the number of climate data parameters in the suboptimal climate data parameter sequence, c j is the jth climate data parameter in the less-than-ideal climate data parameter sequence, d j is the weight corresponding to the jth climate data parameter, h is the adjustment number of the climate data evaluation coefficient, f1>0, f2>0; Determine the adjustment factor for the climate data evaluation coefficient according to the following steps: Presetting a first preset adjustment number, a second preset adjustment number, and a third preset adjustment number; When n3 / (n1+n2)<1, the first preset adjustment number is selected as the adjustment number of the climate data evaluation coefficient; When 1≤n3 / (n1+n2)<1.2, the second preset adjustment number is selected as the adjustment number of the climate data evaluation coefficient; When 1.2≤n3 / (n1+n2), the third preset adjustment number is selected as the adjustment number of the climate data evaluation coefficient; wherein n3 is the number of ideal climate data parameters.

2. The method for assessing the climate carrying capacity of food crops according to claim 1, characterized in that: When analyzing the climate data assessment coefficient processing set and calculating the climate carrying capacity assessment coefficient of the food crop production area based on the analysis result, it includes: Extracting a maximum climate data evaluation coefficient and a minimum climate data evaluation coefficient from the climate data evaluation coefficient processing set; Calculating a first coefficient difference between the maximum climate data evaluation coefficient and the minimum climate data evaluation coefficient; respectively calculating a second coefficient difference between the maximum climate data evaluation coefficient and each of the remaining climate data evaluation coefficients; Calculating the difference ratios of the first coefficient difference and each second coefficient difference respectively, and determining the mean of the difference ratios corresponding to all the difference ratios; Classify all difference ratios greater than or equal to the difference ratio mean into a first difference ratio sequence; Classify all difference ratios that are less than the difference ratio mean into a second difference ratio sequence; The climate carrying capacity assessment coefficient of the food crop production area is calculated based on the first difference ratio sequence and the second difference ratio sequence.

3. The method for assessing the climate carrying capacity of food crops according to claim 2, characterized in that: When calculating the climate carrying capacity assessment coefficient of the food crop production area according to the first difference ratio sequence and the second difference ratio sequence, it includes: The climate carrying capacity assessment coefficient of the food crop production area is calculated according to the following formula: Among them, p is the climate carrying capacity assessment coefficient of the grain crop production area, m1 is the number of difference ratios in the first difference ratio sequence, m2 is the number of difference ratios in the second difference ratio sequence, q t is the tth difference ratio in the first difference ratio sequence, u r is the rth difference ratio in the second difference ratio sequence.

4. The method for assessing the climate carrying capacity of food crops according to claim 1, characterized in that: After calculating the climate carrying capacity assessment coefficient of the food crop production area based on the analysis results, it also includes: The sown area of ​​grain crops in the grain crop production area is determined, and the product value between the sown area and the climate carrying capacity assessment coefficient is calculated and used as the total potential production of grain crops in the grain crop production area.

5. A food crop climate carrying capacity assessment system, applied to the food crop climate carrying capacity assessment method according to any one of claims 1 to 4, characterized in that: include: A data collection module, used to determine the food crop information in the food crop production area, analyze the food crop information, determine the development cycle corresponding to the food crop, and collect climate data parameters corresponding to each sub-development node; A tag generation module is used to extract climate data parameters of the same standard from each sub-development node, construct a climate data parameter set, and generate an initial evaluation tag for each climate data parameter set according to an ideal climate data parameter range, wherein the initial evaluation tag includes an ideal evaluation tag, a sub-ideal evaluation tag, and a super-ideal evaluation tag; a coefficient calculation module, used to generate a plurality of climate data parameter sequences according to the initial evaluation mark, and calculate the climate data evaluation coefficients of the climate data parameter set according to the climate data parameter sequences; The climate assessment module is used to normalize all climate data assessment coefficients, obtain a climate data assessment coefficient processing set based on the processing results, analyze the climate data assessment coefficient processing set, and calculate the climate carrying capacity assessment coefficient of the food crop production area based on the analysis results.

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