Information processing method, program, and information processing device

Abstract

To provide a novel mechanism for effectively utilizing material analysis results.SOLUTION: An information processing method includes an information processing device executing the following steps of: acquiring a first request regarding a first function of a specific material or specific raw material among materials or raw materials that have the effect of increasing resistance to abiotic stress; acquiring a second request regarding a second function based on the first function specified by the first request; extracting one or more raw materials that meet the second request from management information that associates the presence or absence of each function for each material or raw material; and outputting a combination of a raw material selected from the extracted one or more raw materials and the specific material or specific raw material.SELECTED DRAWING: Figure 7

Description

[Technical field]

[0001] The present invention relates to an information processing method, a program, and an information processing device. [Background technology]

[0002] Conventionally, there have been materials that can be called biostimulants, which have the effect of increasing the resistance of plants to abiotic stress, and attempts have been made to provide these materials to plants to promote plant growth and improve the yield or quality of agricultural crops (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2022-66901 Summary of the Invention [Problem to be solved by the invention]

[0004] However, in the conventional technology, it has been difficult to evaluate materials given to plants. For example, although the appropriate material concentration and spraying method differ depending on the cultivation environment used and the conditions of the plant's physiological cycle, the action of the material has not been clarified, and there are cases where the material is given but is not effective when actually used at the production site. In this regard, if the raw materials contained in the material are analyzed to evaluate the material, it is thought that the action will be clarified based on the analysis results, but the reality is that no study has been made on how to utilize these materials.

[0005] Therefore, an object of the technology disclosed herein is to provide a new mechanism for effectively utilizing the analysis results of materials. [Means for solving the problem]

[0006] An information processing method according to one embodiment of the present disclosure includes an information processing device that executes the following steps: acquires a first request regarding a first function of a specific material or specific raw material among materials or raw materials that have the effect of increasing resistance to abiotic stress; acquires a second request regarding a second function based on the first function identified by the first request; extracts one or more raw materials that meet the second request from management information that associates the presence or absence of each function for each of the materials or raw materials; and outputs a combination of an raw material selected from the extracted one or more raw materials and the specific material or the specific raw material. Effect of the Invention

[0007] According to the present disclosure, it is possible to provide a new mechanism for effectively utilizing the analysis results of materials. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of a configuration of an information processing system according to an embodiment of the present disclosure. [Diagram 2] FIG. 13 is a diagram showing an example of each factor item information (part 1) in the present disclosure. [Diagram 3] FIG. 13 is a diagram showing an example of each factor item information (part 2) in the present disclosure. [Figure 4] FIG. 2 is a diagram illustrating an example of a library in the present disclosure. [Diagram 5] FIG. 1 is a diagram illustrating an example of a configuration of an information processing device according to an embodiment of the present disclosure. [Figure 6] FIG. 1 is a diagram illustrating an example of a configuration of an information processing device according to an embodiment of the present disclosure. [Figure 7] 11 is a flowchart illustrating an example of a process of an information processing device according to an embodiment of the present disclosure. [Figure 8] 11 is a flowchart illustrating an example of a first process according to an embodiment of the present disclosure. [Figure 9] 13 is a flowchart illustrating an example of a second process according to an embodiment of the present disclosure. [Figure 10]13 is a flowchart illustrating an example of a third process according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Preferred embodiments of the disclosed technology will be described with reference to the accompanying drawings. In each drawing, the same reference numerals denote the same or similar configurations.

[0010] [Embodiment] <System> Fig. 1 is a diagram showing an example of a configuration of an information processing system 1 according to an embodiment of the present disclosure. As shown in Fig. 1, the information processing system 1 includes an information processing device 10 and each of information processing devices 20A, 20B, 20C, and 20D (hereinafter also referred to as "each information processing device 20"), and each of the information processing devices 10 and 20 can transmit and receive data to and from each other via a network N.

[0011] First, the material to be evaluated in the technology of the present disclosure will be described. The material to be evaluated is an agricultural material also called a biostimulant (hereinafter, also referred to as "BS"), which is a biostimulant containing various substances and microorganisms that bring about better physiological conditions in plants and soil. This material has the potential to have a positive effect on plants in terms of plant health, stress resistance, yield and quality, post-harvest condition and storage, etc., by utilizing the natural power inherent to plants and their surrounding environment.

[0012] BS are usually made from natural ingredients, extracts from plants and animals, or metabolic products of microbial origin. BS may be these alone or in combination. Also, unlike pesticides, BS contain materials that have the effect of mitigating abiotic stress.

[0013] The effects of BS include, for example, suppression of active oxygen, activation of photosynthesis, promotion of flowering and fruiting, control of transpiration, regulation of osmotic pressure, improvement of the root zone environment, increase in root volume and improvement of root activity, etc., but it does not have all the effects.

[0014] Next, an overview of a method for evaluating the effect of BS given to plants will be described, which is the premise of a new system realized by the information processing system 1 shown in Fig. 1. For example, the evaluation method disclosed in the present disclosure uses items that can be factors of biostimulation from the viewpoint of the physiological functions of plants, and calculates an index (evaluation value) for evaluating the effect of the material by weighting the items according to their influence.

[0015] This makes it possible to appropriately evaluate the effectiveness of materials such as BS, whose mechanism of action has not been elucidated and whose effects cannot be known without trying them, by using factor items that may be biological stimulants and weighting them according to the degree of influence of those factor items.

[0016] Next, for the raw materials that are included or may be included in the BS as analysis or evaluation results, data on the presence or absence of the effects or functions of the materials is collected, and management information (also called a library) that associates the presence or absence of each function for each material or raw material is generated. In the information processing system 1 shown in Figure 1, this library can be used to improve existing materials or develop new materials by combining raw materials.

[0017] Each of the information processing devices 10, 20 shown in FIG. 1 described above is, for example, a personal computer, a mobile terminal such as a smartphone, a tablet terminal, a server device, etc., and may be represented as the nth information processing device (n=1, 2, 3, etc.) to be distinguished from one another.

[0018] In addition, the information processing device 10 inputs or receives and acquires measurement values ​​(including analysis values) of each factor item of the material, calculates an evaluation value of the material, generates a library based on the effects of the material, and improves existing materials and develops new materials based on the library.

[0019] The information processing device 20 may send a request for a function related to a resource to the library held by the information processing device 10 for the purpose of improving an existing resource or developing a new resource, and may display the result of the request on the screen.

[0020] <Examples of library factor items> Here, the analysis content of the factor items for the raw materials included in the library will be described. Fig. 2 is a diagram showing an example of each factor item information (part 1) of the materials in this disclosure. Each factor item information of the materials shown in Fig. 2 includes each factor item that can be measured or analyzed in a laboratory. In addition, the factor items are classified into purpose (major item), type (medium item), and measurement / analysis (minor item), and are associated with an evaluation method.

[0021] In the example shown in FIG. 2, when the major item "Objective" is "Yield", the medium items include "Phenotype: High temperature" and "Phenotype: Normal". Furthermore, the medium items "Phenotype: High temperature" and "Phenotype: Normal" include the subitems "Above ground weight", "Above ground length", "Total biomass amount", "Root weight ratio", and "Root weight", and the analysis or measurement value of each subitem is stored in the memory of the information processing device 10. The evaluation method of the factor item related to "Yield" includes, for example, a comparative value (ratio) with the control. Furthermore, the "Above ground weight" and "Root weight" can be measured by actual measurement using, for example, a microbalance, the "Above ground length" can be measured by actual measurement using, for example, a ruler, and the "Total biomass amount" and "Root weight ratio" can be calculated.

[0022] The phenotype may be tested and evaluated for each minor item of the stress test. For example, the minor items may be tested and evaluated for each of the medium items "phenotype: osmotic pressure", "phenotype: oxidation", "phenotype: desiccation", "phenotype: injury", "phenotype: pests", and "phenotype: elements".

[0023] When the major item "purpose" is "stress", the medium item includes "expressed genes". The medium item "expressed genes" includes "osmotic stress response", "pest stress response", "high temperature stress response", "element stress response", "drought stress response", "injury stress response", and "oxidative stress response", and the analytical values ​​of each minor item are obtained, for example, by omics analysis and stored in the memory of the information processing device 10. Methods for evaluating factor items related to "stress" include, for example, the number of hits and "weighted average by P-Value". In addition, the minor item (analysis value) related to "expressed genes" can be obtained, for example, by gene expression analysis.

[0024] When the major item "Objective" is "Stimulus Response", the medium items include "Plant Hormone Analysis: Roots" and "Plant Hormone Analysis: Leaves". The medium items "Plant Hormone Analysis: Roots" and "Plant Hormone Analysis: Leaves" include "salicylic acid", "auxin", "gibberellin (GA1)", "gibberellin (GA4)", "abscisic acid", "cytokinin (tZ)", "ethylene", "jasmonic acid", "strigolactone", "brassinosteroid", and "florigen", and the analysis value or measurement value of each minor item is stored in memory 130. The evaluation method of the factor item related to "Stimulus Response" includes, for example, a measurement value by analysis. The minor item (analysis value or measurement value) related to "Plant Hormone Analysis" can be obtained, for example, by hormone analysis.

[0025] When the major item "purpose" is "nutrient absorption", the medium item includes "element". The medium item "element" includes "N", "P", ... "Mn", etc., and the analysis value or measurement value of each minor item is stored in the memory of the information processing device 10. The evaluation method of the factor item related to "nutrient absorption" includes, for example, a comparative value (ratio) with a control. The minor item related to "element" (analysis value or measurement value) can be obtained by elemental analysis.

[0026] Fig. 3 is a diagram showing an example of each factor item information (part 2) of a material in the present disclosure. Each factor item information shown in Fig. 3 includes each factor item that can be measured or analyzed in an actual field test. In the example shown in Fig. 3, when the major item "purpose" is "soil improvement", the medium items include "soil chemical analysis", "soil physical analysis", and "soil bacterial flora analysis".

[0027] The medium item "soil chemical analysis" includes the sub-items "N", "P", "K", and "other trace elements". The medium item "soil physical analysis" includes the sub-items "moisture content", "pH", "EC (electrical conductivity)", "air permeability", and "hardness". The medium item "soil bacterial flora analysis" includes the sub-items "bacteria species (diversity)" and "bacteria content ratio". The analysis or measurement values ​​of each sub-item are stored in the memory of the information processing device 10. The evaluation method of the factor item related to "soil improvement" includes, for example, a comparison with the previous year or a comparison of the target field. In addition, the sub-items related to "soil chemical analysis" can be obtained by soil analysis by collecting samples, the sub-items related to "soil physical analysis" can be obtained by soil analysis by each sensor, and the sub-items related to "soil bacterial flora analysis" can be obtained by soil nutrient analysis by collecting samples.

[0028] When the major item "purpose" is "stable production", the medium items include "resistance to various stresses" and "phenotype". The medium item "resistance to various stresses" includes the sub-items "disease resistance", "high temperature resistance", "drought resistance", and "salt damage resistance". The medium item "phenotype" includes the sub-item "yield". The analysis values ​​or measurements of each sub-item are stored in the memory of the information processing device 10. Methods for evaluating factor items related to "stable production" include, for example, comparisons with the previous year. In addition, the sub-items (measurements) related to "resistance to various stresses" can be obtained using observation and cultivation history data of the production area. The sub-items (measurements) related to "phenotype" can be obtained using harvest volume and cultivation history data of the production area.

[0029] When the major item "Objective" is "Profitability", the medium item includes "Metabolite Analysis". The medium item "Metabolite Analysis" includes the sub-items "Sugar Content", "Functional Components", "Amino Acids", "Vitamins", "Organic Acids", and "Bitterness". The analysis values ​​or measurement values ​​of each sub-item are stored in the memory of the information processing device 10. The evaluation method for factor items related to "Profitability" includes, for example, comparative values ​​(ratios) with a control. In addition, the sub-items (analysis values ​​or measurement values) related to "Metabolite Analysis" can be obtained by metabolite analysis.

[0030] <Weighting and evaluation value calculation example> The information processing device 10 acquires, from a plant given a material (e.g., BS) having the effect of enhancing resistance to abiotic stress, measurement values ​​or analysis values ​​of one or more factor items (FIGS. 2 and 3, etc.) related to the biostimulation factors of the plant. For example, the information processing device 10 may perform a process of measuring or analyzing data of each factor item using an analysis device or the like, and acquire the measurement values ​​or analysis values ​​obtained by this process via the network communication interface 120. In addition, in the case of factor items obtained by actually measuring the plant, a user or the like may input the measurement values ​​via the user interface 150, and the information processing device 10 may acquire the input measurement values.

[0031] The information processing device 10 weights each measurement value of each acquired factor item using each weight. For example, a weight is set for each factor item based on a priority. For example, a weight is assigned to each factor item based on the degree of influence of BS on yield, the degree of influence of BS on plant growth and stimulation, the order of action of plant physiology, etc.

[0032] Here, regarding weighting, an example of a weight setting procedure will be described. 1. Determine the priority of major factor items based on the degree of effect of the material on yield, the degree of effect on plant growth and stimulation, the order of action of plant physiology, etc. 2. Arrange the medium items (category A) within the same major item in order of priority. 3. Arrange the sub-items (category B) within the same medium item in order of priority. 4. Set weights for the medium items. The item with the highest priority among the medium items is used as the base point to determine the relative weighting of the other medium items. The base point is the largest number. 5. Set weights for each sub-item. Among the sub-items, the item with the highest priority is used as the base point to determine the relative weighting of the other sub-items. The base point is the largest number. The above-mentioned weight setting is an example, and the present invention is not limited to this example.

[0033] The information processing device 10 inputs each weighted measurement value or each analysis value into a function related to the evaluation of the material, such as BS, to calculate the evaluation value of the material. For example, the information processing device 10 may obtain the sum of the weighted measurement values ​​or each analysis value as the evaluation value E of the material (Equation 1). E=Σwi×si...Equation 1 i:Factor item wi: weight of factor item i si: Measured value or each analysis value of factor item i

[0034] Furthermore, for example, when a predetermined value or more of data on the measured values ​​or analytical values ​​of each factor item for a material is collected, the information processing device 10 may obtain the evaluation value using a machine learning model that inputs the measured values ​​or analytical values ​​of each factor item and predicts the evaluation value. As an example, the calculation unit 115 may calculate the evaluation value by using a trained model that has performed supervised learning using training data including the measured values ​​or analytical values ​​of each factor item and the annotated evaluation value. Furthermore, the information processing device 10 may calculate a standard deviation as an example of the evaluation value.

[0035] When calculating the evaluation value as described above, the information processing device 10 can acquire each function possessed by an ingredient contained or that may be contained in a material. For example, for each ingredient of an amino acid (e.g., proline, glycine, etc.), an expressed gene and / or the expression level of the gene and each function (e.g., high temperature stress, low temperature stress, osmotic stress, injury stress, drought stress, oxidative stress, disease and pest stress, element stress, etc.) are associated with a library. As a specific example, in the library, an ingredient A is associated with a gene a having a high temperature stress function and its expression level a1, a gene b having a disease and pest stress function and its expression level b1, etc.

[0036] The library may also be associated with a BS, and may be associated with one or more active substances of the BS, a function of the BS, an effect factor that contributes to the function, an index related to the effect factor, and / or an evaluation value of the BS.

[0037] Fig. 4 is a diagram showing an example of a library in the present disclosure. In the example shown in Fig. 4, each active ingredient (M1, M2, M3, ...) is associated with an effect factor having each function (stress A, stress B, stress C, ...), such as gene expression based on the results of gene expression analysis, factors from elemental analysis (elements that cause the function), and factors from plant hormone analysis (hormones that cause the function). Each effect factor may also be associated with an index related to each factor, such as the amount of gene expression. Furthermore, since each active ingredient has a function that it does not exert, some functions may be left blank.

[0038] As a specific example of the library, the amino acid proline (e.g., drug substance M1) is registered in the library as having the gene Hsp101 (e.g., GA1) corresponding to a high temperature stress function (e.g., stress A) and its expression level (N1), and the gene EIN2 (e.g., GC1) corresponding to a pest stress function (e.g., stress C) and its expression level (N9). As the analysis progresses, genes expressed by gene expression analysis, plant hormones whose effects have been confirmed by hormone analysis, and elements whose effects have been confirmed by element analysis are registered in the corresponding function column for each drug substance. When expressed genes are registered in the library, the gene expression level may be registered as an index related to the factor.

[0039] 2 and 3 may be performed, and a predetermined BS with an evaluation value calculated may be registered in the library. For example, ingredients Mn to Mm included in the library may be ingredients included in a predetermined material, and each ingredient may be associated with a function to be exerted and an effect factor thereof.

[0040] Note that the evaluation value calculation may be performed by another information processing device, rather than by the information processing device 10, and the information processing device 10 may acquire a library from the other information processing device, or may acquire functions and factors for each ingredient to construct a library.

[0041] <Configuration> Fig. 5 is a diagram showing an example of a configuration of an information processing device 10 according to an embodiment of the present disclosure. Fig. 6 is a diagram showing an example of a configuration of an information processing device 20 according to an embodiment of the present disclosure. Below, the processing of each device will be described using a method of using a library as an example.

[0042] The information processing device 10 includes one or more processors (CPU: Central Processing Unit) 110, one or more network communication interfaces 120, a memory 130, a user interface 150, and one or more communication buses 170 for interconnecting these components.

[0043] The user interface 150 includes a display and an input device (such as a keyboard and / or a mouse, or some other pointing device), but does not necessarily have to be provided in the information processing device 10, and if provided, may be connected as an external device.

[0044] Memory 130 may be, for example, a high-speed random access memory (primary memory), such as DRAM, SRAM, or other random access solid-state memory, or may be a non-volatile memory (secondary memory), such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state memory devices.

[0045] Furthermore, the memory 130 may be a non-transitory computer-readable recording medium that stores a program, etc. Furthermore, the memory 130 may be either a main storage device (memory) or an auxiliary storage device (storage), or may include both.

[0046] As another example, memory 130 may be one or more storage devices located remotely from processor 110. In one embodiment, memory 130 stores programs, modules and data structures, or a subset thereof, that are executed by processor 110.

[0047] The memory 130 stores data used by the information processing system 1. For example, the memory 130 stores information such as information on materials, one or more factor items related to factors of plant biostimulation, the measurement values ​​of each factor item, functions used to evaluate materials, evaluation values ​​of each material, and a library summarizing the functions of raw materials contained or that may be contained in the material. Note that the memory 130 may store only libraries acquired from another information processing device.

[0048] The processor 110 executes the programs stored in the memory 130 to configure a control unit 112, a first acquisition unit 113, a second acquisition unit 114, an extraction unit 115, a determination unit 116, an output unit 117, and an estimation unit 118.

[0049] The control unit 112 controls the processing of improving or developing a resource using the library. The control unit 112 controls the processing of the first acquisition unit 113, the second acquisition unit 114, the extraction unit 115, the determination unit 116, the output unit 117, and the estimation unit 118.

[0050] The first acquisition unit 113 acquires a first requirement regarding a first function of a specific material or specific raw material among materials or raw materials having an effect of enhancing resistance to abiotic stress. For example, the first acquisition unit 113 may specify a first function (e.g., a pest stress function) of an existing material or a certain raw material, and acquire a first requirement regarding the specified first function from the information processing device 20 or the user interface 150. Using the library illustrated in FIG. 4 as an example, the first acquisition unit 113 may acquire a first requirement regarding stress B from the information processing device 20 or the user interface 150.

[0051] Furthermore, the first acquisition unit 113 may specify an existing material or a certain raw material, acquire the specified existing material or a certain raw material from the information processing device 20 or the user interface 150, identify a first function possessed by the existing material or a certain raw material, and acquire a first request for the identified first function. Using the library illustrated in FIG. 4 as an example, the first acquisition unit 113 may acquire raw material M2 from the information processing device 20 or the user interface 150, identify stress B from raw material M2, and acquire a first request for stress B.

[0052] The second acquisition unit 114 acquires a second request for a second function based on the first function identified by the first request. For example, the second acquisition unit 114 acquires a second request for either the same function as the first function (e.g., osmotic stress function) identified by the first request, or a different function. Whether the function is the same as the first function or a different function may be set in advance. Using the library illustrated in FIG. 4 as an example, the second acquisition unit 114 acquires a second request for a function (stress B) that is the same as stress B (first function) or a different function (e.g., stress A). The second function may include multiple functions (e.g., stress A and stress C).

[0053] The extraction unit 115 extracts one or more raw materials that meet the second request from management information (library) that associates the presence or absence of each function with each material or raw material. For example, the extraction unit 115 extracts raw materials having the second function specified by the second request from the library. Using the library shown in FIG. 4 as an example, the extraction unit 115 may extract raw materials M1 and M4 that have stress A (second function). Furthermore, when there are multiple functions specified by the second request, the extraction unit 115 may extract raw materials that have all the functions and / or each raw material that has at least one function. It is preferable that the extracted one or more raw materials are identifiable as to which function they have.

[0054] The determination unit 116 selects at least one active ingredient from among one or more active ingredients extracted by the extraction unit 115. For example, the determination unit 116 may select at least one active ingredient based on a user operation or based on an index related to an effect factor. In the case of based on a user operation, the determination unit 116 may cause the information processing device 20 to output a list of one or more extracted active ingredients, and may acquire at least one active ingredient selected from the information processing device 20. In addition, in the case of based on an index related to an effect factor, the determination unit 116 may select a top predetermined number (at least one or more) of active ingredients in order of high effectiveness. Using the library shown in FIG. 4 as an example, the determination unit 116 may compare the index N1 of the effect factor GA1 with the index N4 of the effect factor GA4, and select, for example, an active ingredient M4 having GA4 that is likely to be highly effective. The determination unit 116 determines a combination of the selected active ingredient with a predetermined material or a predetermined active ingredient.

[0055] The output unit 117 outputs the combination determined by the determination unit 116, that is, the combination of the selected ingredient and the specified material or the specified ingredient. For example, the output unit 117 outputs the determined combination to the information processing device 20 that output the first request. Using the library shown in FIG. 4 as an example, the output unit 117 outputs a combination of an ingredient M4 having a second function (stress A) and an ingredient M2 having a first function (stress B). This combination can be a new material (new BS), or, if M2 is an existing material, can be an improvement of the existing material. The output unit 117 may also output one or more functions possessed by the ingredients included in the combination together with the combination of ingredients.

[0056] The above process provides a new mechanism for effectively utilizing the analysis results of materials. For example, by constructing a library that lists the presence or absence of each function for each ingredient that is or may be contained in a material based on the analysis results of the material, it becomes possible to use the library to develop new materials that combine desired functions, improve existing materials, etc.

[0057] The first acquisition unit 113 may also acquire a first request regarding a first function identified from one or more functions of one or more raw materials included in a library (an example of management information). For example, in the case of using the library illustrated in FIG. 4 as an example, when raw material M1 is specified, the first acquisition unit 113 acquires a first request regarding functions (stress A and stress C) possessed by raw material M1. The first request may include both functions (stress A and stress C) in the first request, or may include a more effective function (one of stress A and stress C) in the first request. The first acquisition unit 113 may determine whether the effect is high using an index (measured value or analysis value) related to the effect factor. In addition, when there are multiple functions, the user may be allowed to select one function.

[0058] Through the above processing, the information processing system 1 allows the user to specify raw materials that are contained or may be contained in a material, and makes it possible to support the development of new materials that are a combination of raw materials that have the functions desired by the user, based on the raw materials.

[0059] As described above, the second function may be specified by selecting either the same function as the first function or a function different from the first function. For example, the second function may be specified by selecting either the same function as the first function or a function different from the first function by the second acquisition unit 114 as a default setting, or the second function may be specified by selecting either the same function as the first function or a function different from the first function by the user.

[0060] Through the above processing, if the first function and the second function are the same, it is possible to suggest materials that enhance this function, and if the first function and the second function are different functions, it is possible to suggest new materials that combine the desired functions.

[0061] As described above, the management information (library) may associate, for each raw material, effect factors identified by the analysis results of the material with indexes related to the effect factors. For example, the library may associate expressed genes and the expression levels of the genes obtained by gene expression analysis, elements analyzed by elemental analysis and the analysis values ​​of the elements (compared with the control), and hormones analyzed by hormone analysis and the analysis values ​​of the hormones.

[0062] This makes it possible, for example, when there are multiple effect factors having the same function, to select an active ingredient based on an index related to the effect factor.

[0063] As described above, the effect factors may include at least one of gene expression based on the results of gene expression analysis, factors based on elemental analysis, and factors based on plant hormone analysis. In addition, the effect factors may include factors obtained by soil chemistry analysis, metabolite analysis, etc.

[0064] This allows the results of a variety of analyses to be included in the library, and allows the selection of drug combinations, or candidate combinations, based on a variety of factors.

[0065] Furthermore, the estimation unit 118 estimates the evaluation value of the material obtained by combining ingredients using the evaluation function of the material. For example, the estimation unit 118 may calculate an estimate of the evaluation value by substituting each index (measured value or analytical value) of each effect factor of the combined ingredients into the above formula (1).

[0066] The above process makes it possible to predict the effect of materials when each ingredient is combined using the estimated evaluation value. Furthermore, by using this estimated value, the estimation unit 118 can predict the rank of new materials and improved materials based on their effects.

[0067] The output unit 117 may also recommend a combination of ingredients using the evaluation values ​​estimated by the estimation unit 118. For example, when there are a plurality of combinations, the output unit 117 may recommend the combination with the highest evaluation using the estimated values ​​of the evaluation values ​​of each combination.

[0068] With the above processing, even if there are multiple combinations, it is possible to automatically select the combination that is estimated to be optimal based on the estimated evaluation value, thereby improving the reliability of the recommendation function.

[0069] 6 is a diagram illustrating an example of an information processing device 20 according to an embodiment of the disclosure. The information processing device 20 includes one or more processors (e.g., CPUs) 210, one or more network communication interfaces 220, a memory 230, a user interface 250, and one or more communication buses 270 for interconnecting these components.

[0070] The user interface 250 includes a display and an input device (such as a keyboard and / or a mouse or some other pointing device).

[0071] Memory 230 is, for example, a high-speed random access memory (main storage device) such as DRAM, SRAM, or other random access solid-state storage device. Memory 230 may also be a non-volatile memory (secondary storage device) such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state storage devices. Memory 230 may also be a non-transitory computer-readable recording medium that stores programs and the like. Memory 230 may also be either a main storage device (memory) or a secondary storage device (storage), or may include both.

[0072] The memory 230 stores data and programs used by the information processing system 1. For example, the memory 230 stores application programs for mobile terminals in the information processing system 1.

[0073] The processor 210 executes the programs stored in the memory 230 to configure a control unit 212 that controls requests for materials, etc. on the client side. For example, the control unit 212 includes a web browser or an application that makes requests for materials, etc.

[0074] The web browser enables browsing of web pages of a platform (library utilization platform) that improves existing materials or develops or proposes new materials provided by the information processing device 10. The web browser appropriately displays and transitions between web pages, provides information, and transmits and receives data. For example, the web browser uses the web page to transmit a request set or input by a user to the information processing device 10. The transmitted information is, for example, information such as a first request including a specified material, a specified raw material, or a specified function.

[0075] The control unit 212 may also enable execution of functions provided by the library utilization platform by executing an installed client application. The control unit 212 has a communication control unit 213, an operation control unit 214, and a display control unit 215 to execute the processes related to library utilization of the present disclosure on the client side.

[0076] The communication control unit 213 outputs a first request for a specific material, a specific ingredient, or a first function designated by the user to the information processing device 10. In addition, the communication control unit 213 acquires the combination results of each ingredient transmitted from the information processing device 10.

[0077] The operation control unit 214 receives user operations on UI widgets displayed on each screen or key input, and transmits operation information to an application of the information processing device 20 or outputs the operation information to the information processing device 10. For example, the operation control unit 214 receives the above-mentioned first request and outputs the first request to the information processing device 10.

[0078] The display control unit 215 controls the display of each screen related to the library utilization platform on the display 251 based on each screen information acquired by the communication control unit 213. For example, the display control unit 215 controls the display of a first request screen, a combination result screen, and the like.

[0079] <Processing Procedure> Next, a description will be given of each process of the information processing system 1. Fig. 7 is a flowchart showing an example of a process of the information processing device 10 according to an embodiment of the present disclosure.

[0080] In step S102, the control unit 112 of the information processing device 10 acquires the type of combination. The type of combination indicates the type of function for combining the originals, and the control unit 112 acquires a setting value indicating whether the functions are the same or different. Note that this setting value may be set to any value by default, or may be selected and set by the user. Also, this step S102 may be executed after step S104 described later.

[0081] In step S104, the first acquisition unit 113 of the information processing device 10 acquires a first requirement regarding a first function of a specific material or specific ingredient among materials or ingredients having an effect of increasing resistance to abiotic stress.

[0082] In step S106, the second acquisition unit 114 of the information processing device 10 acquires a second request regarding a second function based on the first function specified by the first request.

[0083] In step S108, the extraction unit 115 of the information processing device 10 extracts one or more raw materials that meet the second requirement from management information (library) that associates the presence or absence of each function with each material or raw material.

[0084] In step S110, the determination unit 116 of the information processing device 10 selects at least one raw material from the list of one or more raw materials extracted by the extraction unit 115, and determines a combination of the selected raw material with a specified material or a specified raw material.

[0085] In step S112, the output unit 117 of the information processing device 10 outputs the combination determined by the determination unit 116, i.e., the combination of the selected ingredient and the specified material or the specified ingredient. The output destination is, for example, the information processing device 20 that transmitted the first request or the display of the information processing device 10.

[0086] Next, each process in the above-mentioned steps S104 to S110 has three patterns as shown below, which will be explained in order. The first pattern is a first process that accepts user designation (FIG. 8), the second pattern is a second process that is semi-automatic processing (FIG. 9), and the third pattern is a third process that is automatic processing (FIG. 10).

[0087] Fig. 8 is a flowchart showing an example of a first process in an embodiment of the present disclosure. In step S202 shown in Fig. 8, the first acquisition unit 113 accepts designation of a target function (first function) from a user and acquires a first request for the first function. The user may be a user who uses the information processing device 10 or a user who uses the information processing device 20.

[0088] In step S204, the second acquisition unit 114 identifies a function different from or the same as the target function identified by the first request, using the setting value in step 102, and acquires a second request for the identified function (second function).

[0089] In step S206, the extraction unit 115 refers to the library and extracts one or more ingredients that meet the second request. For example, the extraction unit 115 extracts ingredients having the second function specified by the second request, lists them, and displays them on a display or the like. The display of the output destination may be the display of the information processing device 10 or the display of the information processing device 20.

[0090] In step S208, the determining unit 116 receives a designation of a desired active ingredient from the extraction list by the user, selects the received active ingredient, and determines a combination of the selected active ingredient with a predetermined material or a predetermined active ingredient.

[0091] Through the above process, the user can specify a material having a function desired by the user while using the information processing system 1.

[0092] Fig. 9 is a flowchart showing an example of the second process according to an embodiment of the present disclosure. Steps S302 and S304 shown in Fig. 9 are similar to steps S202 and S204 shown in Fig. 8, and therefore description thereof will be omitted.

[0093] In step S306, the determination unit 116 automatically determines a combination from the list extracted by the extraction unit 115, and displays a list of candidates for the combined materials on the display. At this time, the determination unit 116 may use the evaluation value estimated by the estimation unit 118 to display the combinations in descending order of evaluation value.

[0094] In step S308, the determination unit 116 accepts a combination desired by the user from among the combination candidates based on a user operation, and determines the accepted combination as the final combination.

[0095] The above process automates the generation of combination candidates, and saves the user the trouble of selecting them. In addition, the use of estimated evaluation values ​​allows the user to select combination candidates using objective indicators.

[0096] Fig. 10 is a flowchart showing an example of the third process according to an embodiment of the present disclosure. Steps S404 and S406 shown in Fig. 10 are similar to steps S304 (step S204 shown in Fig. 8) and S306 shown in Fig. 9, and therefore will not be described.

[0097] In step S402, the first acquisition unit 113 automatically selects a target function (first function) and acquires a first request for the first function. For example, the first acquisition unit 113 selects functions of raw materials or existing materials registered in the library in order at a predetermined timing (for example, once a month).

[0098] In step S408, the determination unit 116 accepts a combination desired by the user from among the combination candidates, and determines the accepted combination as the final combination. Note that the determination unit 116 may automatically determine a combination predicted to be optimal using the evaluation value estimated by the estimation unit 118.

[0099] By the above process, it is possible to automate the selection of target functions and the generation of combination candidates, or even the determination of a combination, thereby saving the user the trouble of making a selection.

[0100] Although one embodiment of the present disclosure has been described above in detail, the present disclosure is not limited to the above embodiment, and various modifications and changes are possible within the scope of the claims. For example, in the present disclosure, with respect to the processes executed by each of the information processing devices 10 and 20, some of the processes may be transferred to another information processing device, a plurality of information processing devices may be appropriately integrated, or all the processes may be executed by one device. In addition, each of the information processing devices 10 and 20 may be managed by one organization, or may be managed by different organizations.

[0101] For example, the determination unit 116 may preferentially combine raw materials having effect factors with high priority or high weight using the priority or weight associated with the effect factors for calculating the evaluation value for the combination of raw materials. As described above, the library in the example shown in Fig. 4 has a data structure including data of each raw material that may be included in the material, function items that the raw materials may have, which are searched for by the information processing device 10 upon request, and factor items with which the effects of each function are compared by the information processing device 10, and raw materials are selected by the information processing device 10 based on the factor items, and one or more raw materials are combined as candidates for the material. As described above, an index related to the factor item may be associated with the factor item. [Explanation of symbols]

[0102] 1...information processing system, 10, 20...information processing device, 110...processor, 112...control unit, 113...first acquisition unit, 114...second acquisition unit, 115...extraction unit, 116...determination unit, 117...output unit, 118...estimation unit, 130...memory, 210...processor, 230...memory, 212...control unit, 213...communication control unit, 214...operation control unit, 215...display control unit

Claims

1. An information processing device, Obtaining a first requirement regarding a first function of a specific material or specific active ingredient among the materials or active ingredients having the effect of increasing resistance to abiotic stress; obtaining a second request for a second function based on the first function identified by the first request; extracting one or more ingredients that meet the second requirement from management information that associates the presence or absence of each function for each of the materials or ingredients; outputting a combination of an ingredient selected from the extracted one or more ingredients and the specified material or the specified ingredient; An information processing method for performing the above.

2. Obtaining the first request includes: obtaining the first request regarding the first function identified from one or more functions of one or more original entities included in the management information; The information processing method according to claim 1 .

3. The information processing method according to claim 1 , wherein the second function is selected and specified as either a function that is the same as the first function or a function that is different from the first function.

4. The information processing method according to claim 1 , wherein the management information associates, for each of the raw materials, an effect factor identified by an analysis result of the material with an index related to the effect factor.

5. The information processing method according to claim 4 , wherein the effect factors include at least one of gene expression based on a result of gene expression analysis, a factor based on elemental analysis, and a factor based on plant hormone analysis.

6. The information processing device, The information processing method according to claim 1 , further comprising the step of estimating an evaluation value of the combination of materials using an evaluation function of the materials.

7. The outputting step includes: The information processing method according to claim 6 , further comprising recommending the combination using the estimated evaluation value.

8. In the information processing device, Obtaining a first requirement regarding a first function of a specific material or specific active ingredient among the materials or active ingredients having the effect of increasing resistance to abiotic stress; obtaining a second request for a second function based on the first function identified by the first request; extracting one or more ingredients that meet the second requirement from management information that associates the presence or absence of each function for each of the materials or ingredients; outputting a combination of an ingredient selected from the extracted one or more ingredients and the specified material or the specified ingredient; A program that executes the following.

9. An acquisition unit that acquires a first requirement regarding a first function of a specific material or specific ingredient among materials or ingredients having an effect of increasing resistance to abiotic stress; an acquisition unit that acquires a second request regarding a second function based on the first function specified by the first request; an extraction unit that extracts one or more raw materials that meet the second requirement from management information that associates the presence or absence of each function with each of the materials or raw materials; an output unit that outputs a combination of an ingredient selected from the extracted one or more ingredients and the specified material or the specified ingredient; An information processing device comprising:

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