CN113688272B - Intelligent material selection method and device for agricultural product packaging - Google Patents
Intelligent material selection method and device for agricultural product packaging Download PDFInfo
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Abstract
The invention provides an intelligent material selection method and device for agricultural product packaging, wherein the method comprises the following steps: acquiring an image of a first agricultural product to obtain image information of the first agricultural product; extracting product characteristics to obtain first agricultural product packaging characteristics; obtaining a multi-dimensional material selection index, analyzing a first material selection database according to the multi-dimensional material selection index, and constructing a first material selection decision tree; obtaining first decision information of a first material selection decision tree based on the packaging characteristics of the first agricultural products and the first material selection decision tree, and obtaining first user-defined proportion information of a first user; and obtaining first preferred material information based on the first custom proportion information and the first recommended packaging material selection information. The technical problems that in the prior art, the packaging material is single, the individuation degree is not high, the scientific level and the intelligent level of the packaging material selection are not high, and the effect of maintaining the storage, transportation and sale quality of agricultural products is not good are solved.
Description
Technical Field
The invention relates to the field of agricultural product packaging, in particular to an intelligent material selection method and device for agricultural product packaging.
Background
The agricultural product package is to protect and decorate agricultural products or agricultural product processing products which are about to enter or enter the circulation field by using a certain container or material. Agricultural product packaging is an important condition for commodity circulation of agricultural products. In the circulation process, agricultural products such as grains, meat, eggs, fruits, tea leaves, honey and the like cannot be transported, stored, kept and sold without being packaged, and are delivered to the hands of consumers, the application of packaging machinery is not convenient, and the factory production and automation of agricultural product packaging are realized. Therefore, it is important to properly package agricultural products, such as the size, weight, material, and mode of each packaging unit. The method is carried out according to the requirements of target customers, the packaging principle and the packaging technical requirements so as to achieve the effects of protecting agricultural products, reducing loss, facilitating transportation, saving manpower, improving bin capacity, keeping the sanitation of the agricultural products, facilitating the identification and selective purchase of consumers, beautifying commodities, expanding sales and improving the marketing efficiency of the agricultural product market.
However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the inventors of the present application find that the above-mentioned technology has at least the following technical problems:
the technical problems of single packaging material, low individuation degree, low scientific level and intelligent level of packaging material selection and poor quality effect of maintaining the storage, transportation and sale of agricultural products exist in the prior art.
Disclosure of Invention
The embodiment of the application provides an intelligent material selection method and device for agricultural product packaging, and solves the technical problems that in the prior art, a packaging material is single, the individuation degree is not high, the scientific level and the intelligent level for packaging material selection are not high, and the quality effects of agricultural product storage, transportation and sale maintenance are poor. The method achieves the technical effects that through analysis of the packaging characteristics of the agricultural products and fitting of the requirements of users, personalized and targeted intelligent material selection is realized, the selected materials have positive effects on storage, transportation and sale of the agricultural products, and the accuracy of packaging material selection is further improved.
In view of the above problems, the embodiments of the present application provide an intelligent material selection method and device for agricultural product packaging.
In a first aspect, an embodiment of the present application provides an intelligent material selection method for a packaging of agricultural products, wherein the method includes: placing a first agricultural product in the first image acquisition device for image acquisition to obtain image information of the first agricultural product; extracting product features according to the first agricultural product image information to obtain first agricultural product packaging features; obtaining a multi-dimensional material selection index, wherein the multi-dimensional material selection index comprises a first material selection index, a second material selection index and a third material selection index, the first material selection index is colorable intensity, the second material selection index is danger of dissolved substances, and the third material selection index is processing chemical stability; analyzing a first material selection database according to the multi-dimensional material selection index to construct a first material selection decision tree; obtaining first decision information of the first material selection decision tree based on the first agricultural product packaging characteristic and the first material selection decision tree, wherein the first decision information is first recommended packaging material selection information; obtaining first user-defined proportion information of a first user; and obtaining first preferred material information based on the first custom proportion information and the first recommended package material selection information.
In another aspect, an embodiment of the present application provides an intelligent material selection device for agricultural product packaging, wherein the device includes: the first obtaining unit is used for placing a first agricultural product in a first image collecting device for image collection to obtain image information of the first agricultural product; the second obtaining unit is used for extracting product characteristics according to the first agricultural product image information to obtain first agricultural product packaging characteristics; a third obtaining unit, configured to obtain a multidimensional material selection index, where the multidimensional material selection index includes a first material selection index, a second material selection index, and a third material selection index, the first material selection index is colorable intensity, the second material selection index is a risk of a dissolved substance, and the third material selection index is processing chemical stability; the first construction unit is used for analyzing a first material selection database according to the multi-dimensional material selection index and constructing a first material selection decision tree; a fourth obtaining unit, configured to obtain first decision information of the first material selection decision tree based on the first agricultural product packaging characteristic and the first material selection decision tree, where the first decision information is first recommended packaging material selection information; a fifth obtaining unit, configured to obtain first custom weight information of a first user; a sixth obtaining unit, configured to obtain first preferred material information based on the first custom specific gravity information and the first recommended package material selection information.
In a third aspect, an embodiment of the present application provides an intelligent material selection device for agricultural product packaging, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method according to any one of the first aspect when executing the program.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
the first agricultural product is placed in the first image acquisition device for image acquisition, so that image information of the first agricultural product is obtained; extracting product features according to the first agricultural product image information to obtain first agricultural product packaging features; obtaining a multi-dimensional material selection index, wherein the multi-dimensional material selection index comprises a first material selection index, a second material selection index and a third material selection index, the first material selection index is colorable intensity, the second material selection index is danger of dissolved substances, and the third material selection index is processing chemical stability; analyzing a first material selection database according to the multi-dimensional material selection index to construct a first material selection decision tree; obtaining first decision information of the first material selection decision tree based on the first agricultural product packaging characteristic and the first material selection decision tree, wherein the first decision information is first recommended packaging material selection information; obtaining first user-defined proportion information of a first user; based on the first self-defined proportion information and the first recommended package material selection information, the technical scheme of obtaining the first preferred material information is provided, the embodiment of the application provides the intelligent material selection method and the intelligent material selection device for agricultural product packaging, personalized and targeted intelligent material selection is achieved by analyzing the packaging characteristics of the agricultural products and fitting the requirements of users, the selected materials have positive effects on storage, transportation and sale of the agricultural products, and the technical effect of further improving the accuracy of the package material selection is further achieved.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
Fig. 1 is a schematic flow chart of an intelligent material selection method for agricultural product packaging according to an embodiment of the present application;
fig. 2 is a schematic flow chart illustrating a first material selection index generated by an intelligent material selection method for agricultural product packaging according to an embodiment of the present application;
FIG. 3 is a schematic flow chart illustrating the generation of a second material selection indicator according to an embodiment of the present disclosure;
FIG. 4 is a schematic flow chart illustrating a third material selection indicator generated by the intelligent material selection method for agricultural product packaging according to the embodiment of the present application;
FIG. 5 is a schematic flow chart of a packaging combination analysis performed by the intelligent material selection method for agricultural product packaging according to the embodiment of the present application;
FIG. 6 is a schematic flow chart illustrating an analytic marketing strategy of an intelligent material selection method for agricultural product packaging according to an embodiment of the present application;
FIG. 7 is a schematic flow chart illustrating chemical stability analysis of an intelligent material selection method for agricultural product packaging according to an embodiment of the present application;
FIG. 8 is a schematic structural diagram of an intelligent material selection device for agricultural product packaging according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.
Description of reference numerals: the device comprises a first obtaining unit 11, a second obtaining unit 12, a third obtaining unit 13, a first constructing unit 14, a fourth obtaining unit 15, a fifth obtaining unit 16, a sixth obtaining unit 17, an electronic device 300, a memory 301, a processor 302, a communication interface 303 and a bus architecture 304.
Detailed Description
The embodiment of the application provides an intelligent material selection method and device for agricultural product packaging, and solves the technical problems that in the prior art, a packaging material is single, the individuation degree is not high, the scientific level and the intelligent level for packaging material selection are not high, and the quality effects of agricultural product storage, transportation and sale maintenance are poor. The method achieves the technical effects that through analysis of the packaging characteristics of the agricultural products and fitting of the requirements of users, personalized and targeted intelligent material selection is realized, the selected materials have positive effects on storage, transportation and sale of the agricultural products, and the accuracy of packaging material selection is further improved.
The agricultural product package is to protect and decorate agricultural products or agricultural product processing products which are about to enter or enter the circulation field by using a certain container or material. Agricultural product packaging is an important condition for commodity circulation of agricultural products. In the circulation process, agricultural products such as grains, meat, eggs, fruits, tea leaves, honey and the like cannot be transported, stored, kept and sold without being packaged, and are delivered to the hands of consumers, the application of packaging machinery is not convenient, and the factory production and automation of agricultural product packaging are realized. Therefore, it is important to properly package agricultural products, such as the size, weight, material, and mode of each packaging unit. The method is carried out according to the requirements of target customers, the packaging principle and the packaging technical requirements so as to achieve the effects of protecting agricultural products, reducing loss, facilitating transportation, saving manpower, improving bin capacity, keeping the sanitation of the agricultural products, facilitating the identification and selective purchase of consumers, beautifying commodities, expanding sales and improving the marketing efficiency of the agricultural product market. The technical problems of single packaging material, low individuation degree, low scientific level and intelligent level of packaging material selection and poor quality effect of maintaining the storage, transportation and sale of agricultural products exist in the prior art.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
the embodiment of the application provides an intelligent material selection method for agricultural product packaging, wherein the method comprises the following steps: placing a first agricultural product in the first image acquisition device for image acquisition to obtain image information of the first agricultural product; extracting product features according to the first agricultural product image information to obtain first agricultural product packaging features; obtaining a multi-dimensional material selection index, wherein the multi-dimensional material selection index comprises a first material selection index, a second material selection index and a third material selection index, the first material selection index is colorable intensity, the second material selection index is danger of dissolved substances, and the third material selection index is processing chemical stability; analyzing a first material selection database according to the multi-dimensional material selection index to construct a first material selection decision tree; obtaining first decision information of the first material selection decision tree based on the first agricultural product packaging characteristic and the first material selection decision tree, wherein the first decision information is first recommended packaging material selection information; obtaining first user-defined proportion information of a first user; and obtaining first preferred material information based on the first custom proportion information and the first recommended package material selection information.
Having thus described the general principles of the present application, various non-limiting embodiments thereof will now be described in detail with reference to the accompanying drawings.
Example one
As shown in fig. 1, the present application provides an intelligent material selection method for a packaging of agricultural products, wherein the method is applied to an intelligent material selection device for a packaging of agricultural products, the device is communicatively connected with an image acquisition device, and the method includes:
s100: placing a first agricultural product in the first image acquisition device for image acquisition to obtain image information of the first agricultural product;
s200: extracting product features according to the first agricultural product image information to obtain first agricultural product packaging features;
s300: obtaining a multi-dimensional material selection index, wherein the multi-dimensional material selection index comprises a first material selection index, a second material selection index and a third material selection index, the first material selection index is colorable intensity, the second material selection index is danger of dissolved substances, and the third material selection index is processing chemical stability;
specifically, the intelligent material selecting device of the agricultural product package is in communication connection with the image acquisition device, and the image acquisition device can acquire the graphic information of the agricultural product. The first agricultural product is any agricultural product needing to be packaged, and the first agricultural product is placed in the first image acquisition device for carrying out multi-group image acquisition, wherein the first image acquisition device comprises but is not limited to a camera, and image information of the first agricultural product is obtained and comprises the type, the color, the shape and the like of the first agricultural product. And performing product feature extraction on the first agricultural product image information, and after determining the type of the first agricultural product, obtaining the packaging requirements of the first agricultural product, such as hardness, shelf life, storage temperature and the like, based on big data. The choice of packaging material for the first agricultural product requires consideration of multi-dimensional indicators including colorable strength of the package, leachable substance risk, and processing chemistry stability. The colorable strength is an easy-coloring ability of the packaging material during printing and dyeing, the risk of the eluted substance is toxicity or risk of the eluted substance during shape processing of the packaging material, and the processing chemical stability is whether unstable ions or processing residues exist on the packaging material and adhere to the surface of agricultural products to destroy the agricultural products. By extracting the characteristics of the agricultural products, setting up a multi-dimensional material selection index and selecting the packaging materials according to the characteristics of the agricultural products, the material selection mode is scientific and reasonable, and the storage, transportation and sale of the agricultural products are facilitated.
S400: analyzing a first material selection database according to the multi-dimensional material selection index to construct a first material selection decision tree;
s500: obtaining first decision information of the first material selection decision tree based on the first agricultural product packaging characteristic and the first material selection decision tree, wherein the first decision information is first recommended packaging material selection information;
in particular, decision trees are a basic classification and regression method. Using decision trees for prediction requires the following process: any method may be used to collect the data. Such as collecting packaging characteristics of agricultural products based on image capture techniques and big data. Preparing data, sorting the collected data, sorting all the collected information according to a certain rule, and facilitating subsequent processing of the data to construct the first selected material database. Analyzing the data, any method can be used, and after the decision tree construction is completed, we can check whether the decision tree graph is in accordance with expectations. Training the algorithm, i.e., constructing a decision tree, also referred to as decision tree learning, is constructing a data structure of the decision tree. And testing an algorithm, and calculating the error rate by using an empirical tree. When the error rate reaches the acceptable range, the decision tree can be put into use. Using algorithms, the intrinsic meaning of the data can be better understood using decision trees. The first decision information of the first material selection decision tree is obtained by inputting the packaging characteristics of the first agricultural product into the constructed decision tree, so that the more appropriate first recommended packaging material selection information is quickly and accurately matched, the packaging material selection is carried out on the agricultural product based on the actual condition of the agricultural product, and the technical effect of improving the accuracy of intelligent packaging material selection is achieved.
S600: obtaining first user-defined proportion information of a first user;
s700: and obtaining first preferred material information based on the first custom proportion information and the first recommended package material selection information.
Specifically, the first user refers to a user who packages a first agricultural product, such as a farmer, an enterprise, a logistics company, and the like, which sells agricultural products. The proportion of each packaging element obtained according to the packaging requirement of a first user is first self-defined proportion information, if the user is a logistics company, the processing technology of the material in the transportation process is low in importance, the importance of the integrity of the packaging and the anti-extrusion capacity is high, and if the user is an agricultural product processing enterprise, the processing technology of the packaging material with safety, chemical stability and the like accounts for a large proportion. The materials are selected comprehensively based on user requirements, namely first self-defined proportion information and first recommended packaging material selection information, the first preferred material information is obtained and is the material selection information which is most suitable for the user, and the technical effects of improving the scientificity and pertinence of packaging material selection and improving the intelligent level can be achieved.
Further, as shown in fig. 2, the obtaining a multi-dimensional material selection index, where the multi-dimensional material selection index includes a first material selection index, a second material selection index, and a third material selection index, and the step S300 further includes:
s311: obtaining first coloring process flow information;
s312: analyzing the first coloring process flow information to obtain coloring process data and coloring element data;
s313: respectively carrying out coloring anti-penetration force analysis and coloring complexity analysis and calculation according to the coloring process data and the coloring element data to obtain a first coloring anti-penetration force and a first coloring complexity;
s314: and generating the first material selection index according to the first coloring anti-penetration force and the first coloring complexity.
In particular, the dyeing method of the colored paper packaging product is commonly adsorptive dyeing. The first coloring process flow of the first agricultural product is obtained by commonly used synthetic dyes such as direct dyes and reactive dyes, and information such as dye components, dyeing time and a color fixing process of the first agricultural product is mastered. And further analyzing the first coloring process flow information to obtain coloring process data and coloring element data, wherein the coloring process data comprises coloring time, coloring agent varieties (organic pigments and inorganic pigments), coloring agent components, coloring agent quantity, physical and chemical properties of the packaging material, pH value, temperature, whiteness and the like, and the coloring element data is data for displaying a coloring effect after coloring, and comprises brightness, depth, color difference, color fastness, two-sided data and the like. Further, performing coloring anti-penetration force analysis and coloring complexity analysis calculation, wherein the coloring anti-penetration force is the capability of the colored packaging material for resisting outward color penetration, and the coloring complexity comprises color matching complexity, coloring process complexity and the like, and the first material selection index is generated according to the first coloring anti-penetration force and the first coloring complexity of the first agricultural product. The first material selection index considers the requirements of the coloring process on the packaging material, can perform material selection according to coloring process information corresponding to different user requirements, and can select the packaging material with the best coloring effect, so that the packaging color is clear, and the added value of agricultural products is improved.
Further, as shown in fig. 3, the obtaining a multi-dimensional material selection index, where the multi-dimensional material selection index includes a first material selection index, a second material selection index, and a third material selection index, and the step S300 further includes:
s321: obtaining first processing condition information;
s322: analyzing the components of the selected processing dissolved substances according to the first processing condition information to obtain first precipitated substances;
s323: obtaining a first risk coefficient by analyzing the risk of precipitating materials of the first precipitated substances;
s324: obtaining a second risk coefficient by analyzing the solubility of the residue after the material selection processing;
s325: and generating the second material selection index according to the first risk coefficient and the second risk coefficient.
Specifically, a packaging material is changed into a product package, different processes are required to be processed according to different packaging requirements, first processing condition information corresponding to the packaging requirement of the first agricultural product, including temperature, humidity, pressure, pH value and the like, during the processing of the packaging material, partial substances on the packaging material are dissolved out, the difficulty of the packaging process is increased, and the dissolved substances are subjected to physical and chemical analysis to obtain main components, namely the first precipitated substances. And analyzing the dangerousness of the first precipitated substance to analyze whether the first precipitated substance is toxic or harmful to agricultural products and consumers to obtain a first danger coefficient, possibly using chemical reagents in the processing process to cause residues on a packaging material, possibly dissolving and attaching the residues on the surface of the agricultural products due to respiration and transpiration of the agricultural products and water vapor generated in the packaging bag, and thus analyzing the solubility of the residues after material selection processing to obtain a second danger coefficient, and generating a second material selection index through the first danger coefficient and the second danger coefficient. The second material selection index is used for analyzing the material processing technology and carrying out danger analysis on dissolved substances in the material processing process, so that the selected packaging material has safety.
Further, as shown in fig. 4, the obtaining a multi-dimensional material selection index, where the multi-dimensional material selection index includes a first material selection index, a second material selection index, and a third material selection index, and the step S300 further includes:
s331: obtaining first free ion information by performing ion analysis on the processing ions of the first material;
s332: analyzing the chemical reaction rate according to the first free ion information and the first agricultural product information to obtain a first chemical stability coefficient;
s333: and when the first chemical stability coefficient is in a preset chemical stability coefficient, taking the first chemical stability coefficient as the third material selection index.
Specifically, organic and inorganic materials and reagents used in the processing technology of the first material selection are subjected to ion analysis, information collection is carried out on ions capable of being dissociated, chemical reaction rate analysis is carried out on the free ions and chemical reactions possibly occurring with the first agricultural products, the possibility of occurrence is analyzed, the first chemical stability coefficient is obtained, and the chemical stability coefficient is preset and can ensure that no chemical substances which are toxic and harmful to the agricultural products and human bodies can be generated under the condition. And when the first chemical stability coefficient is in a preset chemical stability coefficient, taking the first chemical stability coefficient as the third material selection index. The chemical stability of the material is limited, the material is non-toxic and harmless, and the health of human bodies is guaranteed, so that the material for packaging agricultural products meets the relevant national regulation and regulations, and the packaging material has higher chemical stability and improves the quality and stability of packaging.
Further, as shown in fig. 5, the embodiment of the present application further includes:
s810: obtaining a first shelf life and a first marketing distribution life for the first agricultural product;
s820: analyzing the sale-ready character of the first agricultural product according to the first guarantee period and the first marketing distribution period, and determining a first sale-ready period threshold value;
s830: and performing packaging combination analysis on the first recommended packaging material selection information according to the first sales-related period threshold value to obtain a first packaging material selection combination.
Specifically, the first agricultural product has the first quality guarantee period, and is stored, transported and sold within the quality guarantee period, the period of transportation and sale is the first marketing distribution period, the sale-ready performance of the first agricultural product is analyzed according to the first quality guarantee period and the first marketing distribution period, namely whether the first agricultural product needs to be sold out quickly is analyzed, the phenomena of sale delay, expiration and the like are prevented, the first sale-ready period maximum value is determined, the recommended packaging material is subjected to combined analysis according to the first sale-ready period threshold value, for example, the first sale-ready period threshold value is larger, the first agricultural product can cover the local market, can be sold to other places, even is exported, the packaging for the first agricultural product is often combined packaging, the longer the transportation distance is, the more complex the packaging combination is, and the packaging design is more complex and diversified, the precise selection of each of the packaging materials of the first package combination selections has an effect on the look, price, etc. of the first agricultural product. Therefore, by analyzing the combined package and intelligently selecting the combined package material, the quality of the agricultural products can be improved, and the additional value of the agricultural products can be improved.
Further, as shown in fig. 6, the performing package combination analysis on the first recommended package material selection information according to the first immediate sale cycle threshold to obtain a first package material selection, and step S830 further includes:
s831: obtaining a first marketing coefficient by analyzing the marketing strategy of the first agricultural product, wherein the first marketing coefficient is long-time transportation marketing;
s832: when the first distribution coefficient is larger than a preset distribution coefficient, obtaining a first distribution transportation mode;
s833: obtaining a first package constraint characteristic based on the first distribution transportation mode;
s834: and carrying out packaging combination updating on the first recommended packaging material selection information according to the first packaging constraint characteristic to obtain a second packaging material selection.
Particularly, first agricultural product has certain marketing strategy when selling, and the agricultural product of transporting now accounts for than great, when carrying out unified packing, needs further to carry out the analysis to the combined package of different agricultural products, like Fujian honey shaddock, the 9~11 month harvest of each year, because Fujian honey shaddock taste is good and red heart shaddock, and nutritive value is abundant, receives the liking of consumer all over the country deeply, consequently needs transport to the foreign place for a long time and sell. The long-time transportation marketing can be regarded as the first distribution coefficient, predetermines the distribution coefficient and can regard as with the short distance delivery in city, works as when the first distribution coefficient is greater than predetermineeing the distribution coefficient, obtains first distribution transportation mode, like short distance freight train, long-distance freight train, aircraft etc. to obtain first packing restraint characteristic, if need vanning, ribbon, cold and fresh packing etc.. And carrying out packaging combination updating on the first recommended packaging material selection information to obtain a second packaging material combination selection. The problem of remote distribution is considered, the packaging material selection is focused more on exerting the combination advantages, and the material combination is optimized, so that the agricultural product packaging material is selected more accurately, and the packaging effect is better.
Further, as shown in fig. 7, when the first chemical stability coefficient is in a preset chemical stability coefficient, the step S333 further includes:
s3331: obtaining first package coating information, wherein the first package coating information comprises inner wall coating information and outer wall coating information;
s3332: obtaining first coating stability by analyzing the stability of the first free ion information and the first package coating information;
s3333: generating a second chemical stability based on the first coating stability;
s3334: and connecting the second chemical stability in parallel to the first chemical stability coefficient to generate the third material selection index.
Specifically, for the sake of beauty or for realizing a fresh-keeping function, coating is applied to the inner wall and the outer wall of the package to obtain first package coating information including inner wall coating information and outer wall coating information, whether interaction is generated between free ions and the coating is analyzed through stability analysis of the first free ion information and the first package coating information in a processing process, whether the coating is permeated and separated out is analyzed, negative influence is generated on agricultural products and consumers, and therefore stability of the coating is obtained. Carry out deep analysis to packaging material's chemical stability, can avoid because the improper incident that leads to producing poisonous and harmful substance to the human body of selecting for use of packaging material takes place, and then improve the security and the practicality of intelligence selection of materials.
To sum up, the intelligent material selection method and device for agricultural product packaging provided by the embodiment of the application have the following technical effects:
1. the first agricultural product is placed in the first image acquisition device for image acquisition, so that image information of the first agricultural product is obtained; extracting product features according to the first agricultural product image information to obtain first agricultural product packaging features; obtaining a multi-dimensional material selection index, wherein the multi-dimensional material selection index comprises a first material selection index, a second material selection index and a third material selection index, the first material selection index is colorable intensity, the second material selection index is danger of dissolved substances, and the third material selection index is processing chemical stability; analyzing a first material selection database according to the multi-dimensional material selection index to construct a first material selection decision tree; obtaining first decision information of the first material selection decision tree based on the first agricultural product packaging characteristic and the first material selection decision tree, wherein the first decision information is first recommended packaging material selection information; obtaining first user-defined proportion information of a first user; based on the first self-defined proportion information and the first recommended package material selection information, the technical scheme of obtaining the first preferred material information is provided, the embodiment of the application provides the intelligent material selection method and the intelligent material selection device for agricultural product packaging, personalized and targeted intelligent material selection is achieved by analyzing the packaging characteristics of the agricultural products and fitting the requirements of users, the selected materials have positive effects on storage, transportation and sale of the agricultural products, and the technical effect of further improving the accuracy of the package material selection is further achieved.
2. The marketing strategy of the instant sale period threshold is judged, the agricultural product is analyzed, the packaging combination analysis method is adopted, the remote distribution problem is considered, the packaging material selection is focused on exerting the combination advantages, and the material combination is optimized, so that the technical effects that the agricultural product composite packaging material is more accurately selected and the packaging effect is better are achieved.
Example two
Based on the same inventive concept as the intelligent material selecting method for the agricultural product package in the previous embodiment, as shown in fig. 8, the present embodiment provides an intelligent material selecting device for the agricultural product package, wherein the device comprises:
the first obtaining unit 11 is used for placing a first agricultural product in a first image collecting device for image collection to obtain image information of the first agricultural product;
a second obtaining unit 12, where the second obtaining unit 12 is configured to perform product feature extraction according to the first agricultural product image information to obtain a first agricultural product packaging feature;
a third obtaining unit 13, where the third obtaining unit 13 is configured to obtain a multidimensional material selection index, where the multidimensional material selection index includes a first material selection index, a second material selection index, and a third material selection index, the first material selection index is colorable intensity, the second material selection index is risk of dissolved substances, and the third material selection index is processing chemical stability;
a first constructing unit 14, where the first constructing unit 14 is configured to analyze a first material selection database according to the multidimensional material selection index to construct a first material selection decision tree;
a fourth obtaining unit 15, where the fourth obtaining unit 15 is configured to obtain first decision information of the first material selection decision tree based on the first agricultural product packaging characteristic and the first material selection decision tree, where the first decision information is first recommended packaging material selection information;
a fifth obtaining unit 16, where the fifth obtaining unit 16 is configured to obtain first custom weight information of a first user;
a sixth obtaining unit 17, where the sixth obtaining unit 17 is configured to obtain first preferred material information based on the first custom specific gravity information and the first recommended package material selection information.
Further, the apparatus comprises:
a seventh obtaining unit configured to obtain first coloring process flow information;
an eighth obtaining unit configured to obtain coloring process data and coloring element data by analyzing the first coloring process flow information;
a ninth obtaining unit configured to perform coloring anti-penetration power analysis and coloring complexity analysis calculation according to the coloring process data and the coloring element data, respectively, to obtain a first coloring anti-penetration power and a first coloring complexity;
a first generation unit configured to generate the first material selection index according to the first coloring anti-penetration power and the first coloring complexity.
Further, the apparatus comprises:
a tenth obtaining unit configured to obtain first processing condition information;
an eleventh obtaining unit configured to analyze a component of the selected process-released substance based on the first process condition information to obtain a first precipitated substance;
a twelfth obtaining unit configured to obtain a first risk coefficient by analyzing a risk of precipitating a material with respect to the first precipitated substance;
a thirteenth obtaining unit for obtaining a second risk coefficient by analyzing solubility of the residue after the material selection processing;
a second generating unit configured to generate the second material selection index according to the first risk coefficient and the second risk coefficient.
Further, the apparatus comprises:
a fourteenth obtaining unit configured to obtain first free ion information by performing ion analysis on the processing ions of the first material;
a fifteenth obtaining unit, configured to perform chemical reaction rate analysis according to the first free ion information and the first agricultural product information, so as to obtain a first chemical stability coefficient;
a first execution unit, configured to, when the first chemical stability coefficient is in a preset chemical stability coefficient, use the first chemical stability coefficient as the third material selection index.
Further, the apparatus comprises:
a sixteenth obtaining unit for obtaining a first shelf life and a first marketing distribution life of the first agricultural product;
a second execution unit, configured to analyze the sale-ready character of the first agricultural product according to the first warranty period and the first marketing distribution period, and determine a first sale-ready period threshold;
a seventeenth obtaining unit, configured to perform packaging combination analysis on the first recommended packaging material selection information according to the first immediate selling cycle threshold, so as to obtain a first packaging combination material selection.
Further, the apparatus comprises:
an eighteenth obtaining unit, configured to obtain a first distribution coefficient by analyzing a marketing strategy of the first agricultural product, where the first distribution coefficient is long-time transportation marketing;
a nineteenth obtaining unit configured to obtain a first distribution transportation mode when the first distribution coefficient is greater than a preset distribution coefficient;
a twentieth obtaining unit configured to obtain a first package constraint characteristic based on the first distributed transportation manner;
a twenty-first obtaining unit, configured to perform package combination updating on the first recommended package material selection information according to the first package constraint feature, so as to obtain a second package material selection.
Further, the apparatus comprises:
a twenty-second obtaining unit configured to obtain first package paint information, wherein the first package paint information includes inner wall paint information and outer wall paint information;
a twenty-third obtaining unit for obtaining a first coating stability by analyzing the stability of the first free ion information and the first package coating information;
a third generating unit for generating a second chemical stability based on the first dope stability;
a fourth generating unit, configured to connect the second chemical stability in parallel to the first chemical stability coefficient, and generate the third material selection indicator.
The electronic device of the embodiment of the present application is described below with reference to figure 9,
based on the same inventive concept as the intelligent material selection method for the agricultural product package in the previous embodiment, the embodiment of the present application further provides an intelligent material selection device for the agricultural product package, including: a processor coupled to a memory, the memory for storing a program that, when executed by the processor, causes an apparatus to perform the method of any of the first aspects.
The electronic device 300 includes: processor 302, communication interface 303, memory 301. Optionally, the electronic device 300 may also include a bus architecture 304. Wherein, the communication interface 303, the processor 302 and the memory 301 may be connected to each other through a bus architecture 304; the bus architecture 304 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus architecture 304 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 9, but this does not indicate only one bus or one type of bus.
The communication interface 303 may be any device, such as a transceiver, for communicating with other devices or communication networks, such as an ethernet, a Radio Access Network (RAN), a Wireless Local Area Network (WLAN), a wired access network, and the like.
The memory 301 may be, but is not limited to, a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an electrically erasable Programmable read-only memory (EEPROM), a compact disk read-only memory (CD-ROM) or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. The memory may be self-contained and coupled to the processor through a bus architecture 304. The memory may also be integral to the processor.
The memory 301 is used for storing computer-executable instructions for executing the present application, and is controlled by the processor 302 to execute. The processor 302 is configured to execute the computer-executable instructions stored in the memory 301, so as to implement the intelligent material selection method for the agricultural product package provided by the above-mentioned embodiments of the present application.
Optionally, the computer-executable instructions in the embodiments of the present application may also be referred to as application program codes, which are not specifically limited in the embodiments of the present application.
The embodiment of the application provides an intelligent material selection method for agricultural product packaging, wherein the method comprises the following steps: placing a first agricultural product in the first image acquisition device for image acquisition to obtain image information of the first agricultural product; extracting product features according to the first agricultural product image information to obtain first agricultural product packaging features; obtaining a multi-dimensional material selection index, wherein the multi-dimensional material selection index comprises a first material selection index, a second material selection index and a third material selection index, the first material selection index is colorable intensity, the second material selection index is danger of dissolved substances, and the third material selection index is processing chemical stability; analyzing a first material selection database according to the multi-dimensional material selection index to construct a first material selection decision tree; obtaining first decision information of the first material selection decision tree based on the first agricultural product packaging characteristic and the first material selection decision tree, wherein the first decision information is first recommended packaging material selection information; obtaining first user-defined proportion information of a first user; and obtaining first preferred material information based on the first custom proportion information and the first recommended package material selection information.
Those of ordinary skill in the art will understand that: the various numbers of the first, second, etc. mentioned in this application are only used for the convenience of description and are not used to limit the scope of the embodiments of this application, nor to indicate the order of precedence. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one" means one or more. At least two means two or more. "at least one," "any," or similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one (one ) of a, b, or c, may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or multiple.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the application to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device including one or more available media integrated servers, data centers, and the like. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The various illustrative logical units and circuits described in this application may be implemented or operated upon by design of a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.
The steps of a method or algorithm described in the embodiments herein may be embodied directly in hardware, in a software element executed by a processor, or in a combination of the two. The software cells may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. For example, a storage medium may be coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may be disposed in a terminal. In the alternative, the processor and the storage medium may reside in different components within the terminal. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Although the present application has been described in conjunction with specific features and embodiments thereof, it will be evident that various modifications and combinations can be made thereto without departing from the spirit and scope of the application. Accordingly, the specification and figures are merely exemplary of the present application as defined in the appended claims and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of the present application. It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations.
Claims (9)
1. An intelligent material selection method for agricultural product packaging, wherein the method is applied to an intelligent material selection device for agricultural product packaging, the device is in communication connection with a first image acquisition device, and the method comprises the following steps:
placing a first agricultural product in the first image acquisition device for image acquisition to obtain image information of the first agricultural product;
extracting product features according to the first agricultural product image information to obtain first agricultural product packaging features;
obtaining a multi-dimensional material selection index, wherein the multi-dimensional material selection index comprises a first material selection index, a second material selection index and a third material selection index, the first material selection index is colorable intensity, the second material selection index is danger of dissolved substances, and the third material selection index is processing chemical stability;
analyzing a first material selection database according to the multi-dimensional material selection index to construct a first material selection decision tree;
obtaining first decision information of the first material selection decision tree based on the first agricultural product packaging characteristic and the first material selection decision tree, wherein the first decision information is first recommended packaging material selection information;
obtaining first user-defined proportion information of a first user;
and obtaining first preferred material information based on the first custom proportion information and the first recommended package material selection information.
2. The method of claim 1, wherein the obtaining a multi-dimensional material selection indicator comprises a first material selection indicator, a second material selection indicator, and a third material selection indicator, the method further comprising:
obtaining first coloring process flow information;
analyzing the first coloring process flow information to obtain coloring process data and coloring element data;
respectively carrying out coloring anti-penetration force analysis and coloring complexity analysis and calculation according to the coloring process data and the coloring element data to obtain a first coloring anti-penetration force and a first coloring complexity;
and generating the first material selection index according to the first coloring anti-penetration force and the first coloring complexity.
3. The method of claim 1, wherein the obtaining a multi-dimensional material selection indicator comprises a first material selection indicator, a second material selection indicator, and a third material selection indicator, the method further comprising:
obtaining first processing condition information;
analyzing the components of the selected processing dissolved substances according to the first processing condition information to obtain first precipitated substances;
obtaining a first risk coefficient by analyzing the risk of precipitating materials of the first precipitated substances;
obtaining a second risk coefficient by analyzing the solubility of the residue after the material selection processing;
and generating the second material selection index according to the first risk coefficient and the second risk coefficient.
4. The method of claim 1, wherein the obtaining a multi-dimensional material selection indicator comprises a first material selection indicator, a second material selection indicator, and a third material selection indicator, the method further comprising:
obtaining first free ion information by performing ion analysis on the processing ions of the first material;
performing chemical reaction rate analysis according to the first free ion information and the first agricultural product image information to obtain a first chemical stability coefficient;
and when the first chemical stability coefficient is in a preset chemical stability coefficient, taking the first chemical stability coefficient as the third material selection index.
5. The method of claim 1, wherein the method further comprises:
obtaining a first shelf life and a first marketing distribution life for the first agricultural product;
analyzing the sale-ready character of the first agricultural product according to the first guarantee period and the first marketing distribution period, and determining a first sale-ready period threshold value;
and performing packaging combination analysis on the first recommended packaging material selection information according to the first sales-related period threshold value to obtain a first packaging material selection combination.
6. The method of claim 5, wherein the first recommended package option information is subjected to a package combination analysis according to the first sale-as-you-go threshold to obtain a first package combination option, the method further comprising:
obtaining a first marketing coefficient by analyzing the marketing strategy of the first agricultural product, wherein the first marketing coefficient is long-time transportation marketing;
when the first distribution coefficient is larger than a preset distribution coefficient, obtaining a first distribution transportation mode;
obtaining a first package constraint characteristic based on the first distribution transportation mode;
and carrying out packaging combination updating on the first recommended packaging material selection information according to the first packaging constraint characteristic to obtain a second packaging material selection.
7. The method according to claim 4, wherein when the first chemical stability coefficient is within a preset chemical stability coefficient, the first chemical stability coefficient is used as the third material selection index, and the method further comprises:
obtaining first package coating information, wherein the first package coating information comprises inner wall coating information and outer wall coating information;
obtaining first coating stability by analyzing the stability of the first free ion information and the first package coating information;
generating a second chemical stability based on the first coating stability;
and connecting the second chemical stability in parallel to the first chemical stability coefficient to generate the third material selection index.
8. An intelligent material selection device for agricultural product packaging, wherein the device comprises:
the first obtaining unit is used for placing a first agricultural product in a first image collecting device for image collection to obtain image information of the first agricultural product;
the second obtaining unit is used for extracting product characteristics according to the first agricultural product image information to obtain first agricultural product packaging characteristics;
a third obtaining unit, configured to obtain a multidimensional material selection index, where the multidimensional material selection index includes a first material selection index, a second material selection index, and a third material selection index, the first material selection index is colorable intensity, the second material selection index is a risk of a dissolved substance, and the third material selection index is processing chemical stability;
the first construction unit is used for analyzing a first material selection database according to the multi-dimensional material selection index and constructing a first material selection decision tree;
a fourth obtaining unit, configured to obtain first decision information of the first material selection decision tree based on the first agricultural product packaging characteristic and the first material selection decision tree, where the first decision information is first recommended packaging material selection information;
a fifth obtaining unit, configured to obtain first custom weight information of a first user;
a sixth obtaining unit, configured to obtain first preferred material information based on the first custom specific gravity information and the first recommended package material selection information.
9. An intelligent material selection device for agricultural product packaging, comprising: a processor coupled to a memory, the memory for storing a program that, when executed by the processor, causes an apparatus to perform the method of any of claims 1-7.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102267148A (en) * | 2010-06-01 | 2011-12-07 | 陶相臣 | Material for natural bamboo packaging and machining process thereof |
| JP2012240732A (en) * | 2011-05-23 | 2012-12-10 | Seiko:Kk | Bag for storing farm product |
| CN111949815A (en) * | 2020-08-17 | 2020-11-17 | 西南石油大学 | Artificial intelligent corrosion material selection system based on image recognition technology and working method |
| CN112775034A (en) * | 2021-01-22 | 2021-05-11 | 攀枝花学院 | Visual sorting equipment for sorting agricultural products |
| CN112906750A (en) * | 2021-01-25 | 2021-06-04 | 浙江大学 | Hyperspectral image-based material analysis method and system |
-
2021
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102267148A (en) * | 2010-06-01 | 2011-12-07 | 陶相臣 | Material for natural bamboo packaging and machining process thereof |
| JP2012240732A (en) * | 2011-05-23 | 2012-12-10 | Seiko:Kk | Bag for storing farm product |
| CN111949815A (en) * | 2020-08-17 | 2020-11-17 | 西南石油大学 | Artificial intelligent corrosion material selection system based on image recognition technology and working method |
| CN112775034A (en) * | 2021-01-22 | 2021-05-11 | 攀枝花学院 | Visual sorting equipment for sorting agricultural products |
| CN112906750A (en) * | 2021-01-25 | 2021-06-04 | 浙江大学 | Hyperspectral image-based material analysis method and system |
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