Method for evaluating eating quality of apples
By analyzing the main component analysis, the content of the fruit shape, fruit surface and soluble solids of apples is processed and compared, and the non -destructive, convenient and accurate problems of apple quality detection in existing technologies have been solved. Accurate apple quality evaluation and grading.
Patent Information
- Application Number
- CN202411667667.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-20
- Publication Date
- 2025-01-21
AI Technical Summary
The existing technology is difficult to achieve lossless, convenient, accurate and objective detection and evaluation of apple quality, especially in the inspection of bulk fresh apples, which lacks unified grading standards and efficient online testing methods.
Using a method based on principal component analysis, a standard apple data set was constructed through data processing and comparison of apple fruit shape parameters, fruit surface parameters and soluble solid content to achieve simplified evaluation and classification of apple quality.
The fast, accurate and objective evaluation of Apple quality is implemented, suitable for apple quality evaluations of different varieties, reduced waste, and improved the objectivity of detection efficiency and classification.
Smart Images
Figure CN119334911A_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the technical field of fresh fruit quality detection, and in particular relates to a method for evaluating the edible quality of apples. Background Art
[0002] Apples have high nutritional value, are rich in vitamins and a variety of trace elements, and occupy an important position in the world fruit market. However, during the planting, picking and transportation of apples, insects, invading external forces or improper storage may cause the quality of apples to decline, and directly affect the entire apple industry and the economic benefits of fruit farmers. The size, color, nutritional components and functional characteristics of the fruit are the key research objects in the breeding and quality evaluation of most fruit varieties.
[0003] In the prior art, the quality detection of bulk fresh apples mostly adopts small batch sampling and conventional destructive test methods for detection and evaluation. This is not conducive to the detection of all fruits one by one, and it is impossible to realize repeated quality tracking experiments and online rapid detection of the same sample. In addition, destructive testing will also cause a certain amount of waste. At present, there are extensive studies on apple grading at home and abroad, including research on apple appearance quality including fruit color, size, fruit shape, smoothness, degree of damage, pests and diseases, maturity, etc., as well as research on internal quality, including sugar and acid content, hardness, etc. However, these studies are all aimed at testing certain indicators, and there is a lack of unified grading standards. Destructive testing is the most commonly used detection method, which is time-consuming and labor-intensive. Consumers and merchants mostly judge the quality of apples by visual inspection and feel, which is relatively subjective.
[0004] There is an urgent need in this field for a non-destructive, convenient, accurate and objective analysis and evaluation of apple quality, which can provide corresponding data support for the adjustment and optimization of regional variety structure and an evaluation method for evaluating the edible quality of apples. Summary of the invention
[0005] In order to solve the problems existing in the background technology, the purpose of the present invention is to provide a method for evaluating the edible quality of apples based on principal component analysis, which can clarify the relationship between the various quality indicators of apples, simplify the evaluation factors of apple quality, and determine the representative quality indicators of apples for evaluating the edible quality of apples. The method aims to evaluate the quality of apples by fewer parameters, which can be widely used in the quality evaluation of apples of different varieties, so as to provide corresponding data support for the screening of excellent apple varieties for the adjustment and optimization of regional variety structure.
[0006] To achieve the above object, the present invention provides the following technical solution: a method for evaluating the edible quality of apples, comprising the following steps:
[0007] S1: Processing each apple sample to be tested to obtain an apple sample data set, wherein the apple sample data set includes a fruit shape parameter, a fruit surface parameter, and a soluble solid content data subset; wherein the fruit shape parameter and the fruit surface parameter are obtained by photographing the apple sample all around to obtain an apple sample image, and processing the apple sample image; and the soluble solid content is measured by a near-infrared transmission spectrometer;
[0008] S2: constructing a standard apple dataset for each category of apples for different types of apples, wherein the corresponding standard apple dataset includes a standard fruit shape parameter, a standard fruit surface parameter and a standard soluble solid content data subset;
[0009] S3: performing a comparison and analysis on the data corresponding parameters of the apple sample data set and the standard apple data set;
[0010] S4: performing a first classification on the apple samples according to the comparison results.
[0011] Preferably, the standard fruit shape parameters, standard fruit surface parameters, and standard soluble solid content described in step S2 are optimal parameters screened from historical fruit shape parameters. The above optimal parameters are artificially identified, and the above optimal parameters do not represent the maximum or minimum values among the parameters, but are values selected according to human needs. The above optimal parameters can change according to changes in human needs.
[0012] It should be noted that as the running time increases, historical data becomes more and more abundant, or user needs change, the previous standard Apple data set can be supplemented, replaced, and improved.
[0013] Preferably, the fruit shape parameters and the standard fruit shape parameters are represented by apple contour surface parameters, the function of the apple contour surface in the standard apple data set in a three-dimensional coordinate system is f(x, y, z), the function of the apple contour surface in the apple sample data set in the same three-dimensional coordinate system is g(x, y, z), and the comparison of the fruit shape parameters of the standard apple data set and the apple sample data set at a single point is represented by g(x, y, z)-f(x, y, z);
[0014] The comparison of the fruit shape parameters of the apple contour surface in the standard apple data set and the apple contour surface in the apple sample data set is represented by D, where:
[0015]
[0016] The smaller the D value is, the better.
[0017] Preferably, the fruit surface parameter is represented by an alienated area ratio, the maximum area of a single spot on the apple fruit surface in the standard apple data set is s0, and a single area of the apple fruit surface in the apple sample data set that is larger than s0 is called an alienated area, represented by s1; the alienated area ratio R is the percentage of the sum of the alienated areas s1 to the total apple fruit surface area A:
[0018]
[0019] The smaller the alienation area ratio is, the better.
[0020] Preferably, the comparison between the standard soluble solid content and the soluble solid content is represented by the difference W between the two, W=w0-w1, wherein w0 is the standard soluble solid content, w1 is the soluble solid content, and the smaller W is, the better.
[0021] The comparison result described in step S4 is preferably used to implement the first grading method for the apple samples based on the evaluation method composed of the sum of D, R, and W. Preferably, the apple samples are first graded according to parameter P, P = α1*D+α2*R+α3*W; wherein α1 is the influencing factor of the fruit shape parameters; α2 is the influencing factor of the fruit surface parameters; and α3 is the influencing factor of the soluble solids content, and the smaller P is, the better.
[0022] Preferably, the apple sample data set also includes a picking time data subset, wherein the picking time is the difference t1 between the time when the apple sample is measured and processed and the time when the apple sample is picked; the standard apple data set includes a standard picking time, wherein the standard picking time is the difference t0 between the time when the standard soluble solids content occurs and the time when the apple sample is picked.
[0023] The apple samples are subjected to a second classification according to t=t0-t1; if t≥3 days, the apple samples are suitable for storage and / or long-distance transportation; if t≤-3 days, the apple samples are suitable for juicing and / or short-distance transportation; if t is between -3 and 3 days, the apple samples are suitable for immediate consumption, immediate sale, storage, transportation and / or juicing.
[0024] Preferably, the apple sample data set also includes a storage time data subset.
[0025] Preferably, the storage time is the longest time that the apple sample can be stored at 0°C, 90% humidity, a carbon dioxide concentration not exceeding 5%, an ethylene concentration maintained at an optimal value, and the soluble solids content maintained within 10% of the standard soluble solids content.
[0026] The apple sample data is stored in a database. If the apple sample to be tested later is the same or substantially the same as the apple sample data that has been tested and stored, grading is performed directly according to the grading result of the stored apple sample image.
[0027] Compared with the prior art, the present invention has the following beneficial effects:
[0028] 1. The method for evaluating the edible quality of apples of the present invention evaluates the quality of apples through parameters such as fruit shape parameters, fruit surface parameters and soluble solid content, so that the evaluation method can be widely used in the quality evaluation of apples of different varieties and has wide applicability.
[0029] 2. The method for evaluating the edible quality of apples of the present invention is simple and direct by setting optimal parameters and judging by comparison principles.
[0030] 3. The method for evaluating the edible quality of apples of the present invention takes into account the application and storage of apples of different maturity levels, thereby achieving full utilization of apples and economical savings.
[0031] 4. The method for evaluating the edible quality of apples of the present invention evaluates and grades the quality of apples from the perspective of consumers eating fresh apples, is close to industry practice and consumers, and is highly practical. BRIEF DESCRIPTION OF THE DRAWINGS
[0032] Figure 1 The present invention is a flow chart of the method for evaluating the edible quality of apples. DETAILED DESCRIPTION
[0033] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0034] After extensive and in-depth research and a large number of screenings, the inventors have developed a method for evaluating the edible quality of apples for the first time. The method aims to evaluate the quality of apples by parameters such as fruit shape parameters, fruit surface parameters and soluble solid content, so that the evaluation method can be widely used in the quality evaluation of apples of different varieties, and has wide applicability; by setting the optimal parameters and judging by the comparison principle, it is simple and direct; the invention also takes into account the application and storage of apples of different maturity levels, so as to achieve full utilization of apples and economic savings; on this basis, the invention was completed.
[0035] The present invention will be further described below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, the accompanying drawings are schematic diagrams, so the device and apparatus of the present invention are not limited by the size or ratio of the schematic diagrams.
[0036] It should be noted that in the claims and description of this patent, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including one" do not exclude the existence of other identical elements in the process, method, article or device including the elements.
[0037] Example 1
[0038] The flowchart of the method for evaluating apples in this embodiment is as follows Figure 1 The method comprises:
[0039] Step S1: Processing each apple sample to obtain an apple sample data set of the apple sample, wherein the apple sample data set includes fruit shape parameters, fruit surface parameters and soluble solid content; wherein the fruit shape parameters and fruit surface parameters are obtained by photographing the apple sample all around to obtain an apple sample image, and processing the apple sample image; and the soluble solid content is measured by a near-infrared transmission spectrometer.
[0040] Step S2: constructing a standard apple data set for each category of apples for different types of apples, wherein the corresponding standard apple data set includes standard fruit shape parameters, standard fruit surface parameters and standard soluble solid content.
[0041] It should be noted that the parameters in the standard apple data set are all the optimal parameters selected from the historical apple parameters. For example, the standard fruit shape parameters are the optimal parameters selected from the historical fruit shape parameters; the standard fruit surface parameters are the optimal parameters selected from the historical fruit surface parameters; and the standard soluble solid content is the optimal parameter selected from the historical standard soluble solid content.
[0042] The above optimal parameters are artificially determined. The above optimal parameters do not represent the maximum or minimum values among the parameters, but are values selected according to human needs. The above optimal parameters can change according to changes in human needs.
[0043] It should be noted that as the running time increases, historical data becomes more and more abundant, or user needs change, the previous standard Apple data set can be replaced and improved.
[0044] Step S3: respectively compare and process the corresponding parameters of the data in the apple sample dataset and the data in the standard apple dataset.
[0045] The fruit shape parameters are represented by apple contour surface parameters. The comparison of the fruit shape parameters includes that the point parameters of the apple contour surface in the standard apple data set in a three-dimensional coordinate system are (x0, y0, z0), and the corresponding point parameters of the apple contour surface in the apple sample data set corresponding to the point parameters in the standard apple data set in the same three-dimensional coordinate system are (x1, y1, z1). Indicates the comparison of the fruit shape parameters at a specific point between the standard apple dataset and the apple sample dataset. In another preferred embodiment, the comparison is performed by the y value of the point parameter being the same as the corresponding point parameter.
[0046] Correspondingly, the function of the apple contour surface in the standard apple dataset in a three-dimensional coordinate system is f(x, y, z), and the function of the apple contour surface in the apple sample dataset in the same three-dimensional coordinate system is g(x, y, z), and the comparison of the fruit shape parameters of the standard apple dataset and the apple sample dataset at a single point is represented by g(x, y, z)-f(x, y, z);
[0047] The comparison of the fruit shape parameters of the apple contour surface in the standard apple data set and the apple contour surface in the apple sample data set is represented by D, where
[0048] The smaller the D value, the better.
[0049] The fruit surface parameters are expressed as the alienation area ratio. The maximum area of a single spot on the apple fruit surface in the standard apple data set is s0, and the single area of the apple fruit surface in the apple sample data set that is larger than s0 is called the alienation area, represented by s1; the alienation area ratio R is the percentage of the sum of the alienation areas s1 to the total apple fruit surface area A:
[0050] The smaller the alienation area ratio is, the better.
[0051] The comparison between the standard soluble solid content and the soluble solid content is represented by the difference W between the two, W=w0-w1, wherein w0 is the standard soluble solid content, w1 is the soluble solid content; wherein the smaller W is, the better.
[0052] Step S4: Implement a first grading of the apple samples according to the comparison results. Implement a first grading of the apple samples according to the scoring parameter P formed by the sum of D, R, and W, P=α1*D+α2*R+α3*W; wherein α1 is the influencing factor of the fruit shape parameter; α2 is the influencing factor of the fruit surface parameter; and α3 is the influencing factor of the soluble solids content. The values of α1, α2, and α3 may have different specific gravity according to people's needs, and the value may be variable. In another preferred embodiment, the smaller P is, the better. For example, the apple samples are divided into excellent, good, qualified, and unqualified according to the size of the P value.
[0053] Example 2
[0054] The steps S1-S4 are the same as those in Example 1 and will not be described in detail here.
[0055] The difference is that: the apple sample data set also includes a picking time data subset, and the picking time is the difference t1 between the time when the apple sample is measured and processed and the time when the apple sample is picked; the standard apple data set includes a standard picking time, and the standard picking time is the difference t0 between the time when the standard soluble solids content occurs and the time when the apple sample is picked.
[0056] The steps also include step S5: performing a second classification on the apple sample according to t=t0-t1. If t≥3 days, the apple sample is suitable for storage and / or long-distance transportation; if t≤-3 days, the apple sample is suitable for juicing and / or short-distance transportation; if t is between -3 and 3 days, the apple sample is suitable for immediate consumption, immediate sale, storage, transportation and / or juicing.
[0057] Example 3
[0058] The steps S1-S4 are the same as those in Example 1 and will not be described in detail here.
[0059] The difference is that the apple sample data set also includes a storage time data subset.
[0060] The steps also include step S5: performing a second classification on the apple sample according to the storage time. The storage time is the longest time that the apple sample can be stored under the conditions of 0°C, 90% humidity, no more than 5% carbon dioxide concentration, an optimal ethylene concentration, and the soluble solid content being within 10% of the standard soluble solid content.
[0061] The apple samples are screened into those suitable for long-distance transportation and those suitable for short-distance transportation according to the storage time, so as to ensure that the apples or apple processed products purchased by consumers have the best palatability and freshness.
[0062] It should be noted that the apple sample data can be stored in a database. If the apple sample to be tested later is the same or substantially the same as the apple sample data that has been tested and stored, grading can be performed directly based on the grading results of the stored apple sample images.
[0063] All documents mentioned in the present invention are cited as references in this application, just as each document is cited as reference individually. In addition, it should be understood that after reading the above teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the claims attached to this application.
Claims
1. A method for evaluating the edible quality of apples, characterized in that The steps include: S1: Processing an apple sample to be tested to obtain an apple sample data set, wherein the apple sample data set includes a fruit shape parameter, a fruit surface parameter, and a soluble solid content data subset; S2: constructing a standard apple dataset for each category of apples for different types of apples, wherein the corresponding standard apple dataset includes a standard fruit shape parameter, a standard fruit surface parameter and a standard soluble solid content data subset; S3: performing comparative analysis on the corresponding parameters of the apple sample dataset and the standard apple dataset respectively; S4: performing a first classification on the apple samples according to the comparison results.
2. A method for evaluating the edible quality of apples according to claim 1, characterized in that: The fruit shape parameters and fruit surface parameters described in step S1 are obtained by photographing the apple sample all around to obtain an apple sample image, and then processing the apple sample image; the soluble solid content is determined by a near-infrared transmission spectrometer.
3. The method for evaluating the edible quality of apples according to claim 1, characterized in that: The fruit shape parameters and standard fruit shape parameters are represented by apple contour surface parameters.
4. A method for evaluating the edible quality of apples according to claim 3, characterized in that The method for expressing the apple contour surface parameters is as follows: the function of the apple contour surface in the standard apple data set in the three-dimensional coordinate system is f(x, y, z), and the function of the apple contour surface in the apple sample data set in the same three-dimensional coordinate system is g(x, y, z), and g(x, y, z)-f(x, y, z) is used to represent the comparison of the fruit shape parameters of the standard apple data set and the apple sample data set at a single point; The comparison of the fruit shape parameters of the apple contour surface in the standard apple data set and the apple contour surface in the apple sample data set is represented by D, where:
5. The method for evaluating the edible quality of apples according to claim 1, characterized in that: The fruit surface parameters are expressed by the proportion of alienated area.
6. A method for evaluating the edible quality of apples according to claim 5, characterized in that: The fruit surface parameters are expressed by the alienation area ratio. The maximum area of a single spot on the apple fruit surface in the standard apple data set is s0, and the single area of the apple fruit surface in the apple sample data set that is larger than s0 is called the alienation area, which is represented by s1. The alienation area ratio R is the percentage of the sum of the alienation areas s1 to the total apple fruit surface area A:
7. The method for evaluating the edible quality of apples according to claim 1, characterized in that: The comparison between the standard soluble solid content and the soluble solid content is represented by the difference W between the two, W=w0-w1, wherein w0 is the standard soluble solid content and w1 is the soluble solid content.
8. A method for evaluating the edible quality of apples according to claim 1, characterized in that The method for implementing the first classification of the apple samples according to the comparison results described in step S4 is: performing comparison and analysis based on the sum of the fruit shape parameter comparison value D, the alienation area ratio R, the soluble solids content and the soluble solids content difference W, and implementing the first classification of the apple samples according to the parameter P, P = α1*D+α2*R+α3*W; wherein α1 is the influencing factor of the fruit shape parameter; α2 is the influencing factor of the fruit surface parameter; and α3 is the influencing factor of the soluble solids content.
9. The method for evaluating the edible quality of apples according to claim 1, characterized in that: The apple sample data set also includes a picking time data subset or a storage time data subset, wherein the picking time is the difference t1 between the time when the apple sample is measured and processed and the time when the apple sample is picked; the standard apple data set includes a standard picking time, wherein the standard picking time is the difference t0 between the time when the standard soluble solid content occurs and the time when the apple sample is picked; The storage time is the longest time that the apple sample can be stored under the conditions of 0°C, 90% humidity, carbon dioxide concentration not exceeding 5%, ethylene concentration maintained at an optimal value and the soluble solids content maintained within 10% of the standard soluble solids content.
10. The method for evaluating the edible quality of apples according to claim 9, characterized in that: The method further comprises the step of performing a second classification on the apple samples according to the picking time, wherein the apple samples are second classified according to the picking time according to t=t0-t1, and if t≥3 days, the apple samples are suitable for storage and / or long-distance transportation; if t≤-3 days, the apple samples are suitable for juicing and / or short-distance transportation; If t is between -3 and 3 days, the apple sample is suitable for immediate consumption, immediate sale, storage, transportation and / or juicing.