CN109409696B - Cut flower variety evaluation method and device - Google Patents
Cut flower variety evaluation method and device Download PDFInfo
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- CN109409696B CN109409696B CN201811171387.1A CN201811171387A CN109409696B CN 109409696 B CN109409696 B CN 109409696B CN 201811171387 A CN201811171387 A CN 201811171387A CN 109409696 B CN109409696 B CN 109409696B
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Abstract
The application provides a method for evaluating variety of cut flowers, which comprises the following steps: obtaining variety data of the cut flower variety to be evaluated; determining at least one index score of the cut flower variety to be evaluated according to the variety data and the cut flower variety evaluation model; determining the variety score and variety specificity index of the cut flower variety to be evaluated according to at least one index score and the cut flower variety evaluation model; and judging whether the cut flower variety to be evaluated is a specific variety or not according to the variety score, the variety specificity index and the cut flower variety evaluation model. And generating a variety score and a variety specificity index through the variety data and the cut flower variety evaluation model. The variety score is used as the comprehensive evaluation of the cut flower variety to be evaluated, and the variety specificity index is used as the screening index of whether the cut flower variety to be evaluated is the specific variety, so that whether the cut flower variety to be evaluated is the specific variety can be judged. Therefore, the method can effectively screen the specific variety in the cut flower variety while comprehensively evaluating the variety characters of the cut flower variety.
Description
Technical Field
The application relates to the field of fresh cut flowers, in particular to a cut flower variety evaluation method and device.
Background
In the conventional method for evaluating the cut flower variety, a single factor evaluation method, an analytic hierarchy process, an analysis of variance method and the like are used for comprehensively evaluating the variety character, the specificity of the cut flower variety is rarely considered, and the specific variety of the cut flower variety can not be effectively screened while the variety character of the cut flower variety is comprehensively evaluated.
Disclosure of Invention
In view of the above, an object of the present invention is to provide a method and an apparatus for evaluating a cut flower variety, which can comprehensively evaluate the variety characteristics of the cut flower variety and can efficiently screen a specific variety of the cut flower variety.
In order to achieve the above object, embodiments of the present application are implemented as follows:
in a first aspect, an embodiment of the present application provides a method for evaluating a variety of a cut flower, including: obtaining variety data of the cut flower variety to be evaluated; determining at least one index score of the cut flower variety to be evaluated according to the variety data and the cut flower variety evaluation model, wherein the index score represents the score of the cut flower variety to be evaluated on an index reflecting the characteristic features of the cut flower; determining the variety score of the cut flower variety to be evaluated according to the at least one index score and the cut flower variety evaluation model, and determining the variety specificity index of the cut flower variety to be evaluated according to the at least one index score and the cut flower variety evaluation model; and judging whether the cut flower variety to be evaluated is a specific variety or not according to the variety score, the variety specificity index and the cut flower variety evaluation model.
In the embodiment of the application, the index of the cut flower variety to be evaluated is scored by using the cut flower variety evaluation model through the variety data of the cut flower variety, the variety score and the variety specificity index are generated on the basis of the index score, the variety score is used as the comprehensive evaluation of the cut flower variety to be evaluated, the variety character of the cut flower variety to be evaluated can be comprehensively evaluated, the variety specificity index is used as the screening index for judging whether the cut flower variety to be evaluated is a specific variety, and whether the cut flower variety to be evaluated is the specific variety can be judged. Therefore, the method for evaluating the cut flower varieties provided by the embodiment of the application can comprehensively evaluate the variety characters of the cut flower varieties and can effectively screen specific varieties in the cut flower varieties.
In some optional implementations of the first aspect, the determining, according to the at least one index score and the cut flower variety evaluation model, a variety specificity index of the cut flower variety to be evaluated comprises: comparing each index score in the at least one index score with a main stream index score preset in the cut flower variety evaluation model and corresponding to each index score, wherein the main stream index score represents a score which accords with the public preference in indexes corresponding to the main stream index score; and counting the comparison result, and calculating the variety specificity index.
In the embodiment of the application, each index score of the cut flower variety to be evaluated is compared with a main flow index score preset in a cut flower variety evaluation model and corresponding to each index score, whether the variety property of the cut flower variety corresponding to the index score is the main flow variety property is judged, and according to the corresponding index score, the corresponding property of the cut flower variety to be evaluated is assigned and counted, so that the variety specificity index of the cut flower variety to be evaluated is obtained. Therefore, the method for evaluating a cut flower variety provided in the embodiment of the present application can more effectively screen a specific variety among cut flower varieties while comprehensively evaluating the variety traits of the cut flower varieties.
In some optional implementations of the first aspect, the determining whether the cut flower variety to be evaluated is a specific variety according to the variety score, the variety specificity index, and the cut flower variety evaluation model includes: comparing the variety specificity index with a first preset value in the cut flower variety evaluation model, and determining the variety as a non-specific variety if the variety specificity index is smaller than the first preset value; and comparing the variety score with a second preset value in the cut flower variety evaluation model for the variety specificity index which is greater than or equal to the first preset value, determining the variety score which is greater than or equal to the second preset value as the specific variety, and determining the variety score which is less than the second preset value as the non-specific variety.
In the embodiment of the application, whether the variety specificity of the cut flower variety to be evaluated meets the requirement or not is judged by comparing the calculated variety specificity index of the cut flower variety to be evaluated with the first preset value in the cut flower variety evaluation model. If the variety specificity index of the cut flower variety to be evaluated does not meet the requirement, the specificity of the cut flower variety is judged to be insufficient and the cut flower variety does not belong to a specific variety. When the variety specificity index of the cut flower variety to be evaluated meets the requirement, the variety score of the cut flower variety is compared with a second preset value in the cut flower variety evaluation model, and the variety score also meets the requirement, so that the variety can be judged as the specific variety; the non-specific cultivar is judged to be a non-specific cultivar because the cultivar specificity index corresponding to the trait specificity of the cultivar is specific enough to satisfy the requirement, but the cultivar score corresponding to the comprehensive evaluation is not specific enough to satisfy the requirement and does not meet the preference of people. The method for evaluating the cut flower varieties, provided by the embodiment of the application, can be used for comprehensively evaluating the variety properties of the cut flower varieties and simultaneously providing effective guarantee for screening specific varieties in the cut flower varieties to be evaluated.
In some optional implementations of the first aspect, the determining, according to the variety data and the cut flower variety evaluation model, at least one index score of the cut flower variety to be evaluated includes: and calling the cut flower variety evaluation model, and calculating an A score, a B score, a C score and a D score of the cut flower variety to be evaluated according to the variety data, wherein the A score represents the flower part character of the cut flower variety to be evaluated, the B score represents the overall ornamental effect of the cut flower variety to be evaluated, the C score represents the vase expression of the cut flower variety to be evaluated, and the D score represents the growth characteristic of the cut flower variety to be evaluated.
In the embodiment of the present application, by providing evaluation indexes of a plurality of dimensions: the evaluation indexes of multiple dimensions are provided, so that the specific varieties in the cut flower varieties can be screened more effectively while the variety properties of the cut flower varieties are comprehensively evaluated more accurately.
In some optional implementation manners of the first aspect, the calling the cut flower variety evaluation model, and calculating an a score, a B score, a C score, and a D score of the cut flower variety to be evaluated according to the variety data includes: calling the cut flower variety evaluation model, and calculating an A1 score, an A2 score, an A3 score and an A4 score according to the variety data, wherein the A1 score represents the flower color of the cut flower variety to be evaluated, the A2 score represents the flower type of the cut flower variety to be evaluated, the A3 score represents the flower diameter of the cut flower variety to be evaluated, and the A4 score represents the flower fragrance of the cut flower variety to be evaluated; calling the cut flower variety evaluation model, and calculating a B1 score, a B2 score and a B3 score according to the variety data, wherein the B1 score represents the flower laying density of the cut flower variety to be evaluated, the B2 score represents the flower and leaf contrast of the cut flower variety to be evaluated, and the B3 score represents the flower branch shape of the cut flower variety to be evaluated; calling the cut flower variety evaluation model, and calculating a C1 score and a C2 score according to the variety data, wherein the C1 score represents the vase life of the cut flower variety to be evaluated, and the C2 score represents the flowering rate of the cut flower variety to be evaluated; calling the cut flower variety evaluation model, and calculating a D1 score and a D2 score according to the variety data, wherein the D1 score represents the sprouting power of the cut flower variety to be evaluated, and the D2 score represents the cutting length of the cut flower variety to be evaluated.
In the embodiment of the present application, by providing evaluation indexes of a plurality of dimensions: a1 score, a2 score, A3 score, and a4 score; b1 score, B2 score, and B3 score; a C1 score and a C2 score; d1 score and D2 score. Respectively evaluating the flower color, the flower type, the flower diameter and the flower fragrance in the flower part characters of the cut flower variety; the flower density, the flower-leaf contrast and the flower branch shape in the whole ornamental effect; vial age and flowering rate in vial insertion performance; the indexes of the aspects of sprouting ability, cutting length and the like in the growth characteristics are scored, and the variety score corresponding to the comprehensive evaluation of the cut flower variety to be evaluated and the variety specificity index corresponding to the specificity of the cut flower variety to be evaluated are both from the index scores, so that the embodiment provides more precise evaluation indexes with multiple dimensions, and can more effectively screen specific varieties in the cut flower variety while more accurate comprehensive evaluation is carried out on the variety characters of the cut flower variety.
In a second aspect, an embodiment of the present application provides a cut flower variety evaluation device, including: the obtaining module is used for obtaining variety data of the cut flower variety to be evaluated; the index scoring module is used for determining at least one index score of the to-be-evaluated cut flower variety according to the variety data and the cut flower variety evaluation model, wherein the index score represents the score of the to-be-evaluated cut flower variety on an index reflecting the cut flower qualitative characteristics; the variety scoring module is used for determining the variety score of the cut flower variety to be evaluated according to the at least one index score and the cut flower variety evaluation model, and determining the variety specificity index of the cut flower variety to be evaluated according to the at least one index score and the cut flower variety evaluation model; and the judging module is used for judging whether the cut flower variety to be evaluated is a specific variety or not according to the variety score, the variety specificity index and the cut flower variety evaluation model.
In some optional implementations of the second aspect, the variety scoring module is further configured to compare each of the at least one index score with a main stream index score corresponding to each of the index scores preset in the cut flower variety evaluation model, where the main stream index score represents a score meeting public preference in indexes corresponding to the main stream index score; and counting the comparison result, and calculating the variety specificity index.
In some optional implementations of the second aspect, the determining module is further configured to compare the variety specificity index with a first preset value in the cut flower variety evaluation model, and determine that the variety is a non-specific variety if the variety specificity index is smaller than the first preset value; and comparing the variety score with a second preset value in the cut flower variety evaluation model for the variety specificity index which is greater than or equal to the first preset value, determining the variety score which is greater than or equal to the second preset value as the specific variety, and determining the variety score which is less than the second preset value as the non-specific variety.
In some optional implementation manners of the second aspect, the index scoring module is further configured to call the cut flower variety evaluation model, and calculate an a score, a B score, a C score and a D score of the cut flower variety to be evaluated according to the variety data, where the a score represents a flower part trait of the cut flower variety to be evaluated, the B score represents an overall ornamental effect of the cut flower variety to be evaluated, the C score represents a vase representation of the cut flower variety to be evaluated, and the D score represents a growth characteristic of the cut flower variety to be evaluated.
In some optional implementations of the second aspect, the index scoring module is further configured to invoke the cut flower variety evaluation model, and calculate an a1 score, an a2 score, an A3 score and an a4 score according to the variety data, where the a1 score represents the flower color of the cut flower variety to be evaluated, the a2 score represents the flower type of the cut flower variety to be evaluated, the A3 score represents the flower diameter of the cut flower variety to be evaluated, and the a4 score represents the flower fragrance of the cut flower variety to be evaluated; calling the cut flower variety evaluation model, and calculating a B1 score, a B2 score and a B3 score according to the variety data, wherein the B1 score represents the flower laying density of the cut flower variety to be evaluated, the B2 score represents the flower and leaf contrast of the cut flower variety to be evaluated, and the B3 score represents the flower branch shape of the cut flower variety to be evaluated; calling the cut flower variety evaluation model, and calculating a C1 score and a C2 score according to the variety data, wherein the C1 score represents the vase life of the cut flower variety to be evaluated, and the C2 score represents the flowering rate of the cut flower variety to be evaluated; calling the cut flower variety evaluation model, and calculating a D1 score and a D2 score according to the variety data, wherein the D1 score represents the sprouting power of the cut flower variety to be evaluated, and the D2 score represents the cutting length of the cut flower variety to be evaluated.
In a third aspect, an embodiment of the present application provides a server, where the server includes: a processor, a memory, a bus and a communication interface; the processor, the communication interface and the memory are connected by the bus. The memory is used for storing programs. The processor is configured to execute the method for evaluating a variety of a cut flower according to the first aspect or any optional implementation manner of the first aspect by calling a program stored in the memory.
In a fourth aspect, the present application provides a computer-readable storage medium having non-volatile program code executable by a processor, for storing program code, which, when read and executed by a computer, performs the method for evaluating variety of cut flowers according to the first aspect or any optional implementation manner of the first aspect.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
FIG. 1 is a block diagram showing a cut flower variety evaluation device according to a first embodiment of the present application;
fig. 2 is a block diagram illustrating a server according to a first embodiment of the present application;
FIG. 3 is a first flowchart showing a method for evaluating a variety of a cut flower according to a second embodiment of the present application;
FIG. 4 is a sub-flowchart of step S200 in a method for evaluating variety of cut flowers according to a second embodiment of the present application;
FIG. 5 is a sub-flowchart of step S300 in a method for evaluating variety of cut flowers according to a second embodiment of the present application;
FIG. 6 is a sub-flowchart of step S400 in a method for evaluating a variety of cut flowers according to a second embodiment of the present application;
FIG. 7 is a functional block diagram of a device for evaluating the variety of cut flowers according to a third embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without inventive step, are within the scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. The terms "first," "second," and the like are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance. Further, the term "and/or" in the present application is only one kind of association relationship describing the associated object, and means that three kinds of relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone.
First embodiment
Referring to fig. 1, the present embodiment provides a cut flower variety evaluation device 10, where the cut flower variety evaluation device 10 includes: a front end 11 and a server 20.
The front end 11 may comprise a smartphone, a tablet computer, a personal computer, or the like. The front end 11 can perform data communication with the server 20 through a network, when obtaining variety data of a cut flower variety to be evaluated, the front end 11 can send the variety data to the server 20, the server 20 can process the received variety data, generate at least one index score through a cut flower variety evaluation model preset in the server 20, generate a variety score and a variety specificity index according to the index score, judge whether the cut flower variety to be evaluated is a specific variety or not, and return information such as a judgment result, the variety score and the variety specificity index to the front end 11. Of course, the front end 11 may also directly input the obtained variety data into a cut flower variety evaluation model preset in the front end 11, and through the same processing steps, information such as a determination result, a variety score, and a variety specificity index about whether the cut flower variety to be evaluated is a specific variety is obtained. In the case where the front end 11 directly performs the cut flower variety evaluation method as the cut flower variety evaluation device 10, since the processing procedure from the execution of step S100 to the completion of the execution of step S400 does not coincide with that of the server 20, the following description will not be made on the case where the front end 11 performs the method. Since the cut flower variety evaluation method of the present application can be executed directly on the front end 11 and outputs data required by the user, the cut flower variety evaluation device 10 cannot be limited to the execution mode of the server 20.
Referring to fig. 2, the server 20 may be a web server, a database server, or a server cluster composed of a plurality of sub-servers. The server 20 can execute and realize a cut flower variety evaluation method related to the evaluation of cut flower varieties by data interaction with the front end 11.
Alternatively, the server 20 may include: memory 21, communication module 22, bus 23, and processor 24. The processor 24, the communication module 22 and the memory 21 are connected by a bus 23. The processor 24 is for executing executable modules, such as computer programs, stored in the memory 21. The components and configuration of server 20 shown in FIG. 2 are for example only, and not for limitation, and server 20 may have other components and configurations as desired.
The Memory 21 may include a high-speed Random Access Memory (Random Access Memory RAM) and may further include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. In the present embodiment, the memory 21 stores a program necessary for the processor 24 to execute the cut flower variety evaluation method.
The bus 23 may be an ISA bus, a PCI bus, an EISA bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 2, but this does not indicate only one bus or one type of bus.
The method performed by the flow process or the defined device disclosed in any of the embodiments of the present application may be applied to the processor 24, or may be implemented by the processor 24. After the processor 24 receives the execution instruction and calls the program stored in the memory 21 through the bus 23, the processor 24 controls the communication module 22 through the bus 23 to execute the flow of the cut flower variety evaluation method.
Second embodiment
Referring to fig. 3, in the method for evaluating variety of cut flowers according to the present embodiment, the method for evaluating variety of cut flowers may be described from the perspective of the server 20, wherein a trained neural network model is preset in the server 20 as a model for evaluating variety of cut flowers. The method for evaluating the variety of the cut flower can comprise the following steps: step S100, step S200, step S300, and step S400.
Step S100: and obtaining variety data of the cut flower variety to be evaluated.
Step S200: and determining at least one index score of the cut flower variety to be evaluated according to the variety data and the cut flower variety evaluation model, wherein the index score represents the score of the cut flower variety to be evaluated on an index reflecting the characteristic features of the cut flower.
Step S300: determining the variety score of the cut flower variety to be evaluated according to the at least one index score and the cut flower variety evaluation model, and determining the variety specificity index of the cut flower variety to be evaluated according to the at least one index score and the cut flower variety evaluation model.
Step S400: and judging whether the cut flower variety to be evaluated is a specific variety or not according to the variety score, the variety specificity index and the cut flower variety evaluation model.
The individual steps in the protocol of the present application will be described in detail below with reference to fig. 1-6.
In this embodiment, before performing step S100, variety data of the cut flower variety to be evaluated may be obtained, the variety data may be entered through the front end 11, and the front end 11 may transmit the variety data information of the cut flower variety to be evaluated to the server 20 through network communication.
Assume that 1: the method comprises the steps of evaluating a certain variety of Chinese flowering crabapple, randomly collecting data of 100 Chinese flowering crabapples of the variety, obtaining average data of the Chinese flowering crabapples in aspects of flower color, flower type, flower diameter, flower fragrance, flower laying density, flower and leaf contrast, flower branch shape, bottle cut life, flowering rate, sprouting force, cutting length and the like, and using the average data as variety data of the Chinese flowering crabapples. The variety data of the variety of the begonia can be input from the front end 11, and the front end 11 can transmit the variety data information of the variety of the begonia to the server 20 through network communication.
Assume 2: the evaluation of a certain kind of Chinese rose is needed, and the data of 100 Chinese roses of the kind is randomly collected to obtain average data about the flower color, the flower type, the flower diameter, the flower fragrance, the flower density, the flower and leaf contrast, the flower branch shape, the vase life, the flowering rate, the sprouting force, the cutting length and the like of the Chinese rose as the kind data of the Chinese rose. The data of the product of the rose can be input from the head end 11, and the head end 11 can transmit the product data information of the product of the rose to the server 20 by network communication.
Assume that 3: the evaluation of a certain variety of carnation is needed, and the data of 100 carnations of the variety are randomly collected to obtain the average data of the variety of carnation in the aspects of flower color, flower type, flower diameter, flower fragrance, flower density, flower and leaf contrast, flower branch shape, bottle cut life, flowering rate, sprouting force, collection and cutting length, etc. as the variety data of the variety of carnation. The variety data of the variety carnation can be input from the front end 11, and the front end 11 can transmit the variety data information of the variety carnation to the server 20 through network communication.
Referring to fig. 3, in this embodiment, after the front end 11 sorts the variety data, the server 20 may execute step S100, that is, the server 20 may obtain the variety data of the cut flower variety to be evaluated, which is sent by the front end 11 in real time through the network.
Continuing with the aforementioned assumption 1, the server 20 obtains breed data of the breed of begonia.
Continuing with the aforementioned assumption 2, the server 20 obtains the variety data of the variety of the rose.
Continuing with hypothesis 3 above, the server 20 obtains the variety data for the variety carnation.
Referring to fig. 4, after the server 20 obtains the variety data of the cut flower variety to be evaluated, the server 20 may continue to perform step S200. In this embodiment, step S200 may include: step S210, step S220, step S230, and step S240.
Step S210: calling the cut flower variety evaluation model, and calculating an A1 score, an A2 score, an A3 score and an A4 score according to the variety data, wherein the A1 score represents the flower color of the cut flower variety to be evaluated, the A2 score represents the flower type of the cut flower variety to be evaluated, the A3 score represents the flower diameter of the cut flower variety to be evaluated, and the A4 score represents the flower fragrance of the cut flower variety to be evaluated.
Step S220: calling the cut flower variety evaluation model, and calculating a B1 score, a B2 score and a B3 score according to the variety data, wherein the B1 score represents the flower arrangement density of the cut flower variety to be evaluated, the B2 score represents the flower and leaf contrast of the cut flower variety to be evaluated, and the B3 score represents the flower branch shape of the cut flower variety to be evaluated.
Step S230: calling the cut flower variety evaluation model, and calculating a C1 score and a C2 score according to the variety data, wherein the C1 score represents the vase life of the cut flower variety to be evaluated, and the C2 score represents the flowering rate of the cut flower variety to be evaluated.
Step S240: calling the cut flower variety evaluation model, and calculating a D1 score and a D2 score according to the variety data, wherein the D1 score represents the sprouting power of the cut flower variety to be evaluated, and the D2 score represents the cutting length of the cut flower variety to be evaluated.
In this embodiment, the server 20 may execute step S210, and the server 20 may score the flower color, flower type, flower diameter and flower fragrance data in the variety data of the obtained cut flower variety to be evaluated according to the index scoring criteria preset in the cut flower variety evaluation model, as a1 score, a2 score, A3 score and a4 score.
Continuing with the above hypothesis 1, the obtained variety data of the variety crabapple is scored to obtain an a1 score: 5 min; score a 2: 4, dividing; score a 3: 5 min; score a 4: and 5 minutes.
Continuing with hypothesis 2 described above, the obtained variety data of the variety of roses was scored to obtain an a1 score: 5 min; score a 2: 4, dividing; score a 3: 4, dividing; score a 4: and 2 minutes.
Continuing with the above hypothesis 3, the obtained variety data of the variety carnation is scored to obtain a1 score: 5 min; score a 2: 0 minute; score a 3: 5 min; score a 4: and 5 minutes.
After performing step S210, the server 20 proceeds to step S220. In this embodiment, the server 20 may score the flower laying density, the flower-leaf contrast and the flower branch modeling data in the variety data of the obtained cut flower variety to be evaluated according to the index scoring standard preset in the cut flower variety evaluation model, and use the score as a B1 score, a B2 score and a B3 score.
Continuing with hypothesis 1 described above, the obtained data of the variety of begonia was scored to obtain a B1 score: 5 min; b2 score: 4, dividing; b3 score: and 3 minutes.
Continuing with hypothesis 2 described above, the obtained variety data of the variety of roses was scored to obtain a B1 score: 5 min; b2 score: 3 min; b3 score: and 4, dividing.
Continuing with the above hypothesis 3, the obtained variety data of the variety carnation is scored to obtain a B1 score: 5 min; b2 score: 4, dividing; b3 score: and 5 minutes.
After performing step S220, the server 20 proceeds to step S230. In this embodiment, the server 20 may score the vase life and flowering rate data in the variety data of the obtained cut flower variety to be evaluated according to the index scoring standard preset in the cut flower variety evaluation model, as the C1 score and the C2 score.
Continuing with hypothesis 1 described above, the obtained data of the variety of begonia was scored to obtain a C1 score: 5 min; c2 score: and 3 minutes.
Continuing with hypothesis 2 described above, the obtained variety data of the variety of roses was scored to obtain a C1 score: 5 min; c2 score: and 3 minutes.
Continuing with the above hypothesis 3, the obtained variety data of the variety carnation is scored to obtain a C1 score: 5 min; c2 score: and 1 point.
After performing step S230, the server 20 proceeds to step S240. In this embodiment, the server 20 may score the sprouting ability and the cutting length data in the variety data of the obtained cut flower variety to be evaluated according to the preset index scoring standard in the cut flower variety evaluation model, and the data are used as the D1 score and the D2 score.
Continuing with hypothesis 1 described above, the obtained data of the variety of begonia was scored to obtain a D1 score: 5 min; d2 score: and 4, dividing.
Continuing with hypothesis 2 described above, the obtained variety data of the variety of roses was scored to obtain a D1 score: 3 min; d2 score: and 5 minutes.
Continuing with the above hypothesis 3, the obtained variety data of the variety carnation is scored to obtain a D1 score: 5 min; d2 score: and 5 minutes.
It should be noted that the indexes used in this example are only for convenience of description, specific indexes may be set according to actual situations, a scoring mechanism of the indexes may also be adjusted at appropriate time, and are not limited, and the execution sequence of step S210, step S220, step S230, and step S240 is not sequential, and may be adjusted at will, and only the set index score needs to be obtained, so that the present application should not be considered as a limitation.
Referring to fig. 5, after the server 20 performs the determination of the at least one index score of the variety of the cut flower to be evaluated, the server 20 may continue to perform step S300. In this embodiment, step S300 may include: step S310 and step S320.
Step S310: and comparing each index score in the at least one index score with a main stream index score preset in the cut flower variety evaluation model and corresponding to each index score, wherein the main stream index score represents a score which accords with the public preference in indexes corresponding to the main stream index score.
Step S320: and counting the comparison result, and calculating the variety specificity index.
In this embodiment, during the execution of step S310 by the server 20, the server 20 compares each index score in the index scores with a main stream index score preset in the cut flower variety evaluation model and corresponding to each index score, so as to obtain a difference between the index score and the main stream index score of the cut flower variety to be evaluated, where each index difference is represented by a 1-d 2.
Continuing with hypothesis 1 above, the indices for the breed data for this breed of crabapple are scored as follows: score a 1: 5 min; score a 2: 4, dividing; score a 3: 5 min; score a 4: 5 min; b1 score: 5 min; b2 score: 4, dividing; b3 score: 3 min; c1 score: 5 min; c2 score: 3 min; d1 score: 5 min; d2 score: and 4, dividing. The difference value between the index score and the mainstream score is as follows: a 1: 0 minute; a 2: 1 minute; a 3: 0 minute; a 4: 1 minute; b 1: 0 minute; b 2: 0 minute; b 3: 1 minute; c 1: 1 minute; c 2: 0 minute; d 1: 0 minute; d 2: and 0 point.
Continuing with hypothesis 2 above, the index scores for the breed data for this breed of rose are as follows: score a 1: 4, dividing; score a 2: 4, dividing; score a 3: 4, dividing; score a 4: 2 min; b1 score: 5 min; b2 score: 3 min; b3 score: 3 min; c1 score: 4, dividing; c2 score: 3 min; d1 score: 3 min; d2 score: and 4, dividing. The difference value between the index score and the mainstream score is as follows: a 1: 0 minute; a 2: 0 minute; a 3: 1 minute; a 4: 2 min; b 1: 4, dividing; b 2: 1 minute; b 3: 0 minute; c 1: 1 minute; c 2: 0 minute; d 1: 2 min; d 2: and 2 minutes.
Continuing with hypothesis 3 above, the index scores for the variety data for this variety of carnation are as follows: score a 1: 5 min; score a 2: 0 minute; score a 3: 5 min; score a 4: 5 min; b1 score: 5 min; b2 score: 4, dividing; b3 score: 5 min; c1 score: 5 min; c2 score: 1 minute; d1 score: 5 min; d2 score: and 5 minutes. The difference value between the index score and the mainstream score is as follows: a 1: 0 minute; a 2: 5 min; a 3: 0 minute; a 4: 1 minute; b 1: 0 minute; b 2: 0 minute; b 3: 1 minute; c 1: 1 minute; c 2: 4, dividing; d 1: 0 minute; d 2: and 0 point.
After performing step S310, the server 20 continues to perform step S320, and the server 20 may count the result and determine that the breed specificity index is up. In this embodiment, the manner of determining the variety specificity index is to compare the differences, and the largest difference is taken as the variety specificity index of the cut flower variety to be evaluated. Therefore, the manner of obtaining the variety specificity index of the cut flower variety to be evaluated in the present example should not be construed as limiting the present application.
Continuing with hypothesis 1 above, the varietal specificity index for this variety of begonia was 1.
Continuing with hypothesis 2 above, the breed specificity index for this breed of rose was 4.
Continuing with hypothesis 3 above, the variety specificity index for this variety carnation is 5.
In this embodiment, after step S320 is executed, the server 20 may further sum up each index score of the cut flower varieties to be evaluated, so as to obtain the variety score of the cut flower varieties to be evaluated.
Continuing with hypothesis 1 above, the variety of this variety, Malus spectabilis, scored 48.
Continuing with hypothesis 2 above, the cultivar score of this cultivar, rose, was 37 points.
Continuing with hypothesis 3 above, the variety score for this variety of carnation was 45 points.
It should be noted that the manner of obtaining the variety score in this embodiment is direct summation, and in other embodiments, the weighted value may also be selected for summation, so as to obtain the variety score of the cut flower variety to be evaluated. Therefore, the manner of obtaining the variety score of the cut flower variety to be evaluated in the embodiment should not be a limitation of the present application.
Referring to fig. 6, after the server 20 performs the determination of the at least one index score of the variety of the cut flower to be evaluated, the server 20 may continue to perform step S400. In this embodiment, step S400 may include: step S410 and step S420.
Step S410: and comparing the variety specificity index with a first preset value in the cut flower variety evaluation model, and determining the variety which is smaller than the first preset value as a non-specific variety.
Step S420: and comparing the variety score with a second preset value in the cut flower variety evaluation model for the variety specificity index which is greater than or equal to the first preset value, determining the variety score which is greater than or equal to the second preset value as the specific variety, and determining the variety score which is less than the second preset value as the non-specific variety.
In this embodiment, in the process of executing step S410 by the server 20, the server 20 may compare the variety specificity index of the cut flower variety to be evaluated with the first preset value in the cut flower variety evaluation model, and determine that the variety is a non-specific variety if the variety specificity index is smaller than the first preset value. For example, 4 may be set here, and in other embodiments, the first preset value may be set to 3 or another numerical value, which is not limited.
Continuing with the assumption 1, the variety specificity index of the variety of the begonia is 1, and is smaller than the first preset value 4, and the variety of the begonia is judged to be a non-specific variety.
Continuing with the aforementioned assumption 2, the variety specificity index of the variety of rose is 4, which is equal to the first preset value of 4, and step S420 is performed.
Continuing with the aforementioned assumption 3, if the variety specificity index of the variety carnation is 5, which is greater than the first preset value 4, step S420 is executed.
In this embodiment, in the process of executing step S420 by the server 20, the server 20 may compare the variety scores of the cut flower varieties to be evaluated with the second preset value in the cut flower variety evaluation model, determine that the varieties with the score greater than or equal to the second preset value are specific varieties, and determine that the varieties with the score less than the second preset value are non-specific varieties. Here, different second preset values are generally set according to different flower genera, for example, the same second preset value is set for all varieties of begonia in the present embodiment: 40 minutes; different roses are also provided with a second non-uniform preset value, for example, the second preset value of a bush rose is 41 minutes, and the second preset value of a vine rose is 43 minutes; the second preset value for carnation is 42 minutes.
Continuing with hypothesis 1 described above, the variety Malus spectabilis was judged to be a non-specific variety and was not judged again.
Continuing with the assumption 2, for the Chinese rose of the variety, which belongs to the vine Chinese rose, calling a second preset value: and (6) comparing the score with the score of 37 varieties of the varieties, and judging the varieties as non-specific varieties when the score of the varieties is less than a second preset value.
Continuing with the aforementioned assumption 3, for the carnation of this variety, the second preset value is called: and (5) 42 points, comparing the score with a score of 45 points of the variety, judging the variety to be the specific variety if the score of the variety is greater than a second preset value.
After the determination is completed, that is, after the server 20 completes the step S400, the data of the cut flower variety to be evaluated may include: each index score, breed specificity index, and decision result are sent to the front end 11, all or in part, via network communication.
Continuing with the aforementioned assumption 1, the server 20 transmits data to the head end 11, the evaluation data of the variety of begonia is as follows:
and (3) index scoring: and (3) flower color grading: 5 min; and (3) scoring the flower type: 4, dividing; and (3) scoring the flower diameter: 5 min; grading the flower fragrance: 5 min; floral density scoring: 5 min; flower and leaf contrast scoring: 4, dividing; and (3) grading the flower branch shape: 3 min; bottle plug life scoring: 5 min; and (3) scoring the flowering rate: 3 min; and (3) sprouting branch force scoring: 5 min; cutting length scoring: 4, dividing; variety scoring: 48 minutes; variety specificity index: 1; non-specific species.
Continuing with the aforementioned assumption 2, the server 20 transmits data to the head end 11, the evaluation data of the variety of roses is as follows:
and (3) index scoring: and (3) flower color grading: 4, dividing; and (3) scoring the flower type: 4, dividing; and (3) scoring the flower diameter: 4, dividing; grading the flower fragrance: 2 min; floral density scoring: 5 min; flower and leaf contrast scoring: 3 min; and (3) grading the flower branch shape: 3 min; bottle plug life scoring: 4, dividing; and (3) scoring the flowering rate: 3 min; and (3) sprouting branch force scoring: 3 min; cutting length scoring: 4, dividing; variety scoring: 37 minutes; variety specificity index: 4; non-specific species.
Continuing with the aforementioned assumption 3, the server 20 transmits data to the head end 11, the evaluation data of the carnation of the variety as follows: and (3) index scoring: and (3) flower color grading: 5 min; and (3) scoring the flower type: 0 minute; and (3) scoring the flower diameter: 5 min; grading the flower fragrance: 5 min; floral density scoring: 5 min; flower and leaf contrast scoring: 4, dividing; and (3) grading the flower branch shape: 5 min; bottle plug life scoring: 5 min; and (3) scoring the flowering rate: 1 minute; and (3) sprouting branch force scoring: 5 min; cutting length scoring: 5 min; variety scoring: dividing by 45 min; variety specificity index: 5; specific variety.
It should be noted that, in the embodiment, because of the requirement of step description, the example is only for convenience of description of the implementation step, and the validity of the example is subject to practical conditions, and the example adopted by the example should not be considered as a limitation to the present application.
Third embodiment
Referring to fig. 7, an embodiment of the present application provides a cut flower variety evaluation device function module 100, where the cut flower variety evaluation device function module 100 is applied to a front end 11 and/or a server 20, and the cut flower variety evaluation device function module 100 includes:
the obtaining module 110 is used for obtaining variety data of the cut flower variety to be evaluated;
the index scoring module 120 is configured to determine at least one index score of the to-be-evaluated cut flower variety according to the variety data and the cut flower variety evaluation model, where the index score represents a score of the to-be-evaluated cut flower variety on an index reflecting the cut flower trait;
a variety scoring module 130, configured to determine a variety score of the cut flower variety to be evaluated according to the at least one index score and the cut flower variety evaluation model, and determine a variety specificity index of the cut flower variety to be evaluated according to the at least one index score and the cut flower variety evaluation model;
and the judging module 140 is configured to judge whether the cut flower variety to be evaluated is a specific variety according to the variety score, the variety specificity index and the cut flower variety evaluation model.
In this embodiment, the variety scoring module 130 is further configured to compare each of the at least one index score with a main stream index score preset in the cut flower variety evaluation model and corresponding to each index score, where the main stream index score represents a score meeting public preference in indexes corresponding to the main stream index score; and counting the comparison result, and calculating the variety specificity index.
In this embodiment, the determining module 140 is further configured to compare the variety specificity index with a first preset value in the cut flower variety evaluation model, and determine that the variety is a non-specific variety if the variety specificity index is smaller than the first preset value; and comparing the variety score with a second preset value in the cut flower variety evaluation model for the variety specificity index which is greater than or equal to the first preset value, determining the variety score which is greater than or equal to the second preset value as the specific variety, and determining the variety score which is less than the second preset value as the non-specific variety.
In this embodiment, the index scoring module 120 is further configured to call the cut flower variety evaluation model, and calculate an a score, a B score, a C score and a D score of the cut flower variety to be evaluated according to the variety data, where the a score represents a flower part character of the cut flower variety to be evaluated, the B score represents an overall ornamental effect of the cut flower variety to be evaluated, the C score represents a vase expression of the cut flower variety to be evaluated, and the D score represents a growth characteristic of the cut flower variety to be evaluated.
In this embodiment, the index scoring module 120 is further configured to invoke the cut flower variety evaluation model, and calculate an a1 score, an a2 score, an A3 score, and an a4 score according to the variety data, where the a1 score represents the flower color of the cut flower variety to be evaluated, the a2 score represents the flower shape of the cut flower variety to be evaluated, the A3 score represents the flower diameter of the cut flower variety to be evaluated, and the a4 score represents the flower fragrance of the cut flower variety to be evaluated; calling the cut flower variety evaluation model, and calculating a B1 score, a B2 score and a B3 score according to the variety data, wherein the B1 score represents the flower laying density of the cut flower variety to be evaluated, the B2 score represents the flower and leaf contrast of the cut flower variety to be evaluated, and the B3 score represents the flower branch shape of the cut flower variety to be evaluated; calling the cut flower variety evaluation model, and calculating a C1 score and a C2 score according to the variety data, wherein the C1 score represents the vase life of the cut flower variety to be evaluated, and the C2 score represents the flowering rate of the cut flower variety to be evaluated; calling the cut flower variety evaluation model, and calculating a D1 score and a D2 score according to the variety data, wherein the D1 score represents the sprouting power of the cut flower variety to be evaluated, and the D2 score represents the cutting length of the cut flower variety to be evaluated.
It should be noted that, as those skilled in the art can clearly understand, for convenience and brevity of description, the specific working process of the system described above may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.
In summary, an embodiment of the present application provides a method for evaluating a variety of a cut flower, including: obtaining variety data of the cut flower variety to be evaluated; determining at least one index score of the cut flower variety to be evaluated according to the variety data and the cut flower variety evaluation model, wherein the index score represents the score of the cut flower variety to be evaluated on an index reflecting the characteristic features of the cut flower; determining the variety score of the cut flower variety to be evaluated according to the at least one index score and the cut flower variety evaluation model, and determining the variety specificity index of the cut flower variety to be evaluated according to the at least one index score and the cut flower variety evaluation model; and judging whether the cut flower variety to be evaluated is a specific variety or not according to the variety score, the variety specificity index and the cut flower variety evaluation model.
The method comprises the steps of scoring indexes of a cut flower variety to be evaluated by using a cut flower variety evaluation model through variety data of the cut flower variety, generating a variety score and a variety specificity index on the basis of the index score, taking the variety score as comprehensive evaluation of the cut flower variety to be evaluated, comprehensively evaluating the variety characters of the cut flower variety to be evaluated, taking the variety specificity index as a screening index of whether the cut flower variety to be evaluated is a specific variety, and judging whether the cut flower variety to be evaluated is the specific variety. Therefore, the method for evaluating the cut flower varieties provided by the embodiment of the application can comprehensively evaluate the variety characters of the cut flower varieties and can effectively screen specific varieties in the cut flower varieties.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (6)
1. A method for evaluating a variety of a cut flower, comprising:
obtaining variety data of the cut flower variety to be evaluated;
determining at least one index score of the cut flower variety to be evaluated according to the variety data and the cut flower variety evaluation model, wherein the index score represents the score of the cut flower variety to be evaluated on an index reflecting the characteristic features of the cut flower;
determining the variety score of the cut flower variety to be evaluated according to the at least one index score and the cut flower variety evaluation model, taking the variety score as the comprehensive evaluation of the cut flower variety to be evaluated, and determining the variety specificity index of the cut flower variety to be evaluated according to the at least one index score and the cut flower variety evaluation model;
judging whether the cut flower variety to be evaluated is a specific variety or not according to the variety score, the variety specificity index and the cut flower variety evaluation model;
wherein, the determining the variety specificity index of the cut flower variety to be evaluated according to the at least one index score and the cut flower variety evaluation model comprises the following steps:
comparing each index score in the at least one index score with a main stream index score preset in the cut flower variety evaluation model and corresponding to each index score, wherein the main stream index score represents a score which accords with the public preference in indexes corresponding to the main stream index score;
counting the comparison result, and determining the index with the maximum difference value between the index score and the corresponding main stream index score as the breed specificity index;
wherein, the judging whether the cut flower variety to be evaluated is a specific variety according to the variety score, the variety specificity index and the cut flower variety evaluation model comprises the following steps:
comparing the variety specificity index with a first preset value in the cut flower variety evaluation model, and determining the variety as a non-specific variety if the variety specificity index is smaller than the first preset value;
and comparing the variety score with a second preset value in the cut flower variety evaluation model for the variety specificity index which is greater than or equal to the first preset value, determining the variety score which is greater than or equal to the second preset value as a specific variety, and determining the variety score which is less than the second preset value as a non-specific variety.
2. The method for evaluating variety of cut flower according to claim 1, wherein the determining at least one index score of the variety of cut flower to be evaluated according to the variety data and the evaluation model of variety of cut flower comprises:
and calling the cut flower variety evaluation model, and calculating an A score, a B score, a C score and a D score of the cut flower variety to be evaluated according to the variety data, wherein the A score represents the flower part character of the cut flower variety to be evaluated, the B score represents the overall ornamental effect of the cut flower variety to be evaluated, the C score represents the vase expression of the cut flower variety to be evaluated, and the D score represents the growth characteristic of the cut flower variety to be evaluated.
3. The method for evaluating the variety of the cut flower according to claim 2, wherein the calling the variety evaluation model to calculate the a score, the B score, the C score and the D score of the variety of the cut flower to be evaluated according to the variety data comprises:
calling the cut flower variety evaluation model, and calculating an A1 score, an A2 score, an A3 score and an A4 score according to the variety data, wherein the A1 score represents the flower color of the cut flower variety to be evaluated, the A2 score represents the flower type of the cut flower variety to be evaluated, the A3 score represents the flower diameter of the cut flower variety to be evaluated, and the A4 score represents the flower fragrance of the cut flower variety to be evaluated;
calling the cut flower variety evaluation model, and calculating a B1 score, a B2 score and a B3 score according to the variety data, wherein the B1 score represents the flower laying density of the cut flower variety to be evaluated, the B2 score represents the flower and leaf contrast of the cut flower variety to be evaluated, and the B3 score represents the flower branch shape of the cut flower variety to be evaluated;
calling the cut flower variety evaluation model, and calculating a C1 score and a C2 score according to the variety data, wherein the C1 score represents the vase life of the cut flower variety to be evaluated, and the C2 score represents the flowering rate of the cut flower variety to be evaluated;
calling the cut flower variety evaluation model, and calculating a D1 score and a D2 score according to the variety data, wherein the D1 score represents the sprouting power of the cut flower variety to be evaluated, and the D2 score represents the cutting length of the cut flower variety to be evaluated.
4. A cut flower variety evaluation device is characterized by comprising:
the obtaining module is used for obtaining variety data of the cut flower variety to be evaluated;
the index scoring module is used for determining at least one index score of the to-be-evaluated cut flower variety according to the variety data and the cut flower variety evaluation model, wherein the index score represents the score of the to-be-evaluated cut flower variety on an index reflecting the cut flower qualitative characteristics;
the variety scoring module is used for determining the variety score of the cut flower variety to be evaluated according to the at least one index score and the cut flower variety evaluation model, taking the variety score as the comprehensive evaluation of the cut flower variety to be evaluated, and determining the variety specificity index of the cut flower variety to be evaluated according to the at least one index score and the cut flower variety evaluation model;
the judging module is used for judging whether the cut flower variety to be evaluated is a specific variety or not according to the variety score, the variety specificity index and the cut flower variety evaluation model;
the variety scoring module is further configured to compare each index score in the at least one index score with a main stream index score preset in the cut flower variety evaluation model and corresponding to each index score, wherein the main stream index score represents a score meeting public preference in indexes corresponding to the main stream index score; counting the comparison result, and determining the index with the maximum difference value between the index score and the corresponding main stream index score as the breed specificity index;
the judgment module is further used for comparing the variety specificity index with a first preset value in the cut flower variety evaluation model, and determining the variety as a non-specific variety if the variety specificity index is smaller than the first preset value; and comparing the variety score with a second preset value in the cut flower variety evaluation model for the variety specificity index which is greater than or equal to the first preset value, determining the variety score which is greater than or equal to the second preset value as a specific variety, and determining the variety score which is less than the second preset value as a non-specific variety.
5. The cut flower variety evaluation device according to claim 4,
the index scoring module is further used for calling the cut flower variety evaluation model and calculating an A score, a B score, a C score and a D score of the cut flower variety to be evaluated according to the variety data, wherein the A score represents the flower part character of the cut flower variety to be evaluated, the B score represents the overall ornamental effect of the cut flower variety to be evaluated, the C score represents the vase expression of the cut flower variety to be evaluated, and the D score represents the growth characteristics of the cut flower variety to be evaluated.
6. The cut flower variety evaluation device according to claim 5,
the index scoring module is further used for calling the cut flower variety evaluation model and calculating an A1 score, an A2 score, an A3 score and an A4 score according to the variety data, wherein the A1 score represents the flower color of the cut flower variety to be evaluated, the A2 score represents the flower type of the cut flower variety to be evaluated, the A3 score represents the flower diameter of the cut flower variety to be evaluated, and the A4 score represents the flower fragrance of the cut flower variety to be evaluated; calling the cut flower variety evaluation model, and calculating a B1 score, a B2 score and a B3 score according to the variety data, wherein the B1 score represents the flower laying density of the cut flower variety to be evaluated, the B2 score represents the flower and leaf contrast of the cut flower variety to be evaluated, and the B3 score represents the flower branch shape of the cut flower variety to be evaluated; calling the cut flower variety evaluation model, and calculating a C1 score and a C2 score according to the variety data, wherein the C1 score represents the vase life of the cut flower variety to be evaluated, and the C2 score represents the flowering rate of the cut flower variety to be evaluated; calling the cut flower variety evaluation model, and calculating a D1 score and a D2 score according to the variety data, wherein the D1 score represents the sprouting power of the cut flower variety to be evaluated, and the D2 score represents the cutting length of the cut flower variety to be evaluated.
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