A method for detecting fruit preservatives

Abstract

The present invention relates to the field of preservative detection, and in particular to a fruit preservative detection method. The method comprises the following steps: extracting corresponding skin features by calling status data of surface fruits in a box before transportation; detecting the surface fruits at a first intermediate transportation station, identifying corresponding real-time skin features, determining skin deviation values ​​based on the skin features, and analyzing attachment quality characterization parameters of the surface fruits based on surface particle density of the surface fruits to mark the box; detecting and analyzing the fruits in the box; obtaining attachment change features of surface fruits at attachment abnormality stations, evaluating whether the fruits in the box meet attachment and shedding standards, determining whether attachment defects occur in the fruits in the box, marking the attachment abnormality stations, and issuing a prompt signal; obtaining a transportation distance from the marked attachment abnormality stations to a transportation destination station, determining whether the fruits in the box should be subjected to secondary coating of attachments, and dynamically and accurately evaluating the effectiveness of preservatives on the surfaces of the fruits during transportation.

Description

Technical Field

[0001] The present invention relates to the field of preservative detection, in particular to a method for detecting fruit preservatives. Background Art

[0002] In the post-harvest fruit supply chain, the entire process, from picking in the orchard to retail sales, is crucial for preserving fruit freshness. Therefore, the application of preservatives is a key means of extending shelf life and reducing spoilage. However, the real-world transportation environment is complex. High-frequency mechanical vibrations generated by transport vehicles on bumpy roads can cause friction and collisions between stacked fruits during transportation, potentially causing the preservative coating on the fruit's surface to fall off or become ineffective.

[0003] During the transportation of fruits, the shedding of surface preservatives may have a certain impact on the freshness and safety of the fruits. When the preservatives are reduced, mold or bacteria are more likely to grow. At the same time, the increase in oxygen contact may cause the fruits to brown or lose nutrients. Therefore, it is very important to develop an effective method for detecting the status of preservatives during transportation.

[0004] However, the prior art still has the following problems:

[0005] Only the residual concentration of preservatives is tested, without considering the shedding mechanism affected by the transportation environment and the impact of the physical state of the fruit on the wear of preservatives during transportation. The test indicators are single and not comprehensive, which in turn affects the accuracy of the test. Summary of the Invention

[0006] To this end, the present invention provides a fruit preservative detection method to overcome the problem in the prior art that only the residual concentration of preservatives is detected without considering the shedding mechanism affected by the transportation environment and the effect of the physical state of the fruit on the wear of the preservatives during transportation. The detection indicators are single and not comprehensive, which in turn affects the accuracy of the detection.

[0007] To achieve the above object, the present invention provides a method for detecting fruit preservatives, which comprises:

[0008] Retrieving the state data of the surface fruit in the box before transportation to extract the corresponding skin features, wherein the skin features include the area and number of attachment gaps;

[0009] Inspecting the surface fruit at the first intermediate transport station to identify corresponding real-time epidermal features, comparing the real-time epidermal features with the epidermal features to determine epidermal deviation values, analyzing attachment quality characterization parameters of the surface fruit in combination with surface particle density of the surface fruit, and marking the box based on the attachment quality characterization parameters;

[0010] Based on the marking results, the fruit in the box is inspected and analyzed, including obtaining distribution images of the fruit at several subsequent intermediate transport stations, determining the attachment characteristics of the fruit, and combining the average amplitude of the transport vehicle corresponding to the intermediate transport section to determine the distribution and attachment characterization parameters of the fruit, so as to identify abnormal attachment stations;

[0011] Obtaining attachment change characteristics of the surface fruit at the attachment abnormality site to evaluate whether the fruit in the box meets the attachment and detachment standards, determining whether the fruit in the box has attachment defects, marking the attachment abnormality site and issuing a prompt signal;

[0012] Obtaining the transportation distance between the marked attachment abnormality site and the transportation destination site, and determining whether to perform a secondary smearing of the attachment on the fruit in the box;

[0013] The fitting characteristics include the fitting area between adjacent fruits and the thickness of the concave portion of the fitted fruits, and the attachment change characteristics include the expansion amount of the notch area and the ratio of the notch area to the surface area.

[0014] Furthermore, the process of determining the epidermal deviation value includes,

[0015] Obtain real-time skin features of surface fruits, including the current attachment gap area and the current attachment gap number;

[0016] Calculating a first difference between an attachment gap area and a current attachment gap area, and solving for a ratio of the first difference to the current attachment gap area as a first deviation value;

[0017] Calculating a second difference between the number of attachment gaps and the current number of attachment gaps, and solving for a ratio of the second difference to the current number of attachment gaps as a second deviation value;

[0018] The sum of the first deviation value and the second deviation value is used as the epidermis deviation value.

[0019] Furthermore, the process of analyzing the attachment quality characterization parameters of the surface fruit includes:

[0020] The ratio of the skin deviation value to the skin deviation threshold is used as the first adhesion quality feature;

[0021] The ratio of the surface particle density to the surface particle density threshold is used as the second adhesion quality feature;

[0022] The first attachment quality characteristic and the second attachment quality characteristic are weightedly summed to determine the attachment quality characterization parameter.

[0023] Furthermore, the corresponding box is marked based on the attachment quality characterization parameter, including:

[0024] If the attachment quality characterization parameter of the surface fruit is greater than or equal to the attachment quality characterization parameter threshold, the corresponding box is marked.

[0025] Furthermore, based on the marking results, the fruits in the box are tested and analyzed, including:

[0026] If any box is marked, the fruit in the marked box will be tested and analyzed.

[0027] Furthermore, the process of determining the distribution fit characterization parameters of the fruit includes:

[0028] The sum of the ratio of the fitting area between adjacent fruits to the fitting area threshold and the ratio of the concave thickness of the fitted fruits to the concave thickness threshold is used as the first distribution fitting feature;

[0029] The ratio of the average amplitude of the transport vehicle to the average amplitude threshold is used as the second distribution fitting feature;

[0030] The sum of the first distribution fit feature and the second distribution fit feature is determined as the distribution fit characterization parameter.

[0031] Further, identifying attachment abnormality sites includes,

[0032] If the distribution fitting characterization parameter corresponding to the fruit determined at any intermediate transport station is greater than or equal to the distribution fitting characterization parameter threshold, the intermediate transport station is identified as the attachment abnormality station.

[0033] Further, evaluating whether the fruit in the box meets the attachment and detachment standards includes:

[0034] If the expansion amount of the notch area of ​​the surface fruit is greater than the expansion amount threshold and / or the ratio of the notch area to the surface area is greater than the ratio threshold, it is determined that the fruit in the box does not meet the attachment and shedding standard.

[0035] Further, determining whether there is an attachment defect of the fruit in the box, marking the attachment abnormality site and issuing a prompt signal, including:

[0036] If any fruit in the box does not meet the shedding standard, it is determined that the fruit in the box has an attachment defect, the attachment abnormality site is marked and a prompt signal is issued.

[0037] Further, determining whether to apply the attachment to the fruit in the box for a second time includes:

[0038] If the transportation distance between the marked abnormal attachment site and the transportation destination site is greater than or equal to the transportation distance threshold, the fruit in the box is smeared a second time.

[0039] Compared with the existing technology, the present invention extracts corresponding skin features by calling the status data of the surface fruits in the box before transportation; detects the surface fruits at the first intermediate transportation station to identify the corresponding real-time skin features, compares them with the skin features, determines the skin deviation value, analyzes the attachment quality characterization parameters of the surface fruits in combination with the surface particle density of the surface fruits, and marks the box based on the attachment quality characterization parameters; detects and analyzes the fruits in the box according to the marking results; obtains the attachment change characteristics of the surface fruits at the attachment abnormality stations to evaluate whether the fruits in the box meet the attachment and shedding standards, determines whether the fruits in the box have attachment defects, marks the attachment abnormality stations and sends a prompt signal; obtains the transportation distance of the marked attachment abnormality stations from the transportation destination station, and determines whether the fruits in the box should be re-applied with attachments. The present invention can dynamically and accurately evaluate the effectiveness of preservatives on the surface of fruits during transportation.

[0040] In particular, the core function of preservatives is to form a protective barrier by completely covering the surface of the fruit. The area and number of gaps directly affect the continuity of the barrier. The present invention considers the adhesion of preservatives on the surface of the fruit affected by transportation. On the one hand, it can reflect the stability of preservative adhesion and the transportation quality of the fruit. On the other hand, it reflects the adhesion firmness of the preservative. The more gaps there are, the easier it is for the preservatives to fall off at the attachment points on the fruit surface. The larger the gap area, the wider the range of the single falling area. The anti-corrosion layer may be peeled off over a large area due to transportation vibration and friction, reflecting that the bonding strength between the attachment layer and the fruit surface is weak, and intuitively reflects the integrity of the anti-corrosion layer. At the same time, during transportation, the preservatives are affected by physical and chemical factors. The morphology of the fruit changes due to physical effects, resulting in a rough surface particle texture. The present invention then considers the number of particles per unit area, that is, the surface particle density. Granular protrusions will lead to the destruction of the continuity of the preservative film layer, and the exposed fruit skin area will increase, which will reduce the inhibition efficiency of the preservative on mold. Therefore, the present invention relies on the skin deviation value determined based on the comparison between the skin characteristics and the real-time skin characteristics combined with the surface particle density to analyze the attachment quality characterization parameters to characterize the stability of the preservative adhesion on the fruit surface during transportation, provide data support for the subsequent marking of the corresponding box, and then detect and analyze the fruit in the box. The present invention can dynamically and accurately evaluate the effectiveness of the preservative on the fruit surface during transportation.

[0041] In particular, the present invention detects and analyzes the marked fruits in the box, and detects the distribution and fit between adjacent fruits in the box. The larger the fitting area between adjacent fruits, the tighter the fruits are stacked, the higher the probability of mutual friction during transportation, and the more likely it is to cause preservatives to fall off; and the thickness of the depression of the fitted fruits can reflect the severity of the squeezing between the fruits, and thus indicate the severity of the physical damage to the fruit skin and the aggravation of the rupture of the preservative film layer on the fruit surface; and then comprehensively quantifies the environmental stress, considering the amplitude of the transport vehicle, and the aggravating effect on the tight stacking between fruits and the integrity of the preservatives. Therefore, the present invention determines the distribution and fit characterization parameters of the fruit through the fit characteristics of the fruit combined with the average amplitude of the transport vehicle, so as to characterize the influence of the transportation environment on the degree of fruit fit depression and the wear of attachments, and provide data support for the subsequent identification of abnormal attachment sites. The present invention can dynamically and accurately evaluate the effectiveness of preservatives on the surface of fruits during transportation.

[0042] In particular, the present invention analyzes the attachment changes of the surface fruit on the basis of determining the abnormal attachment sites. The expansion of the gap area reflects the dynamic increase of the preservative shedding during transportation, and identifies which sites or path segments cause the accelerated shedding. The proportion of the gap area to the surface area reflects the severity of the current preservative attachment and shedding. Through the above two characteristics, it is comprehensively evaluated whether the fruit in the box meets the attachment and shedding standards, dynamically tracked the attachment change trend of the preservative, and determined whether the fruit in the box has attachment defects, and then marked the corresponding abnormal attachment sites for easy quality traceability. The present invention can dynamically and accurately evaluate the effectiveness of preservatives on the surface of fruits during transportation.

[0043] In particular, the present invention considers the preservation threshold of preservatives on fruits in the box during transportation, dynamically considers the remaining transportation distance, determines whether the existing amount of preservatives attached is sufficient to cover the preservation needs of the remaining transportation distance, and accurately supplements the antiseptic ability of the preservatives. On the basis of avoiding indiscriminate re-application of preservatives, it improves resource utilization and reduces transportation costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A schematic diagram of the steps of a method for detecting fruit preservatives according to an embodiment of the invention;

[0045] Figure 2 A logic decision diagram for marking corresponding boxes based on attachment quality characterization parameters according to an embodiment of the invention;

[0046] Figure 3 A logical decision diagram for identifying attachment abnormality sites for an embodiment of the invention;

[0047] Figure 4 This is a logic decision diagram for evaluating whether the fruit in the box meets the adhesion and detachment standards according to an embodiment of the invention. DETAILED DESCRIPTION

[0048] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0049] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0050] It should be noted that, in the description of the present invention, terms such as "upper", "lower", and "inner" indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0051] In addition, it should be noted that, in the description of the present invention, unless otherwise specified or limited, the term "installation" should be understood in a broad sense. For those skilled in the art, the specific meaning of the above terms in the present invention can be understood according to specific circumstances.

[0052] See also Figure 1 As shown, it is a schematic diagram of the steps of the fruit preservative detection method according to an embodiment of the present invention. The fruit preservative detection method according to an embodiment of the present invention comprises:

[0053] Step S1, calling the state data of the surface fruit in the box before transportation to extract the corresponding skin features, wherein the skin features include the area of ​​the attachment gap and the number of the attachment gaps;

[0054] Step S2: Detecting the surface fruit at the first intermediate transport station to identify corresponding real-time epidermal features, comparing the features with the epidermal features to determine an epidermal deviation value, analyzing an attachment quality characterization parameter of the surface fruit in combination with the surface particle density of the surface fruit, and marking the box based on the attachment quality characterization parameter;

[0055] Step S3, based on the marking results, performing detection and analysis on the fruits in the box, including obtaining distribution images of the fruits at several subsequent intermediate transport stations, determining the fitting characteristics of the fruits, and combining the average amplitude of the transport vehicles corresponding to the intermediate transport sections to determine the distribution and fitting characterization parameters of the fruits, so as to identify abnormal attachment stations;

[0056] Step S4, obtaining the attachment change characteristics of the surface fruit at the attachment abnormality site to evaluate whether the fruit in the box meets the attachment and falling-off standard, determining whether the fruit in the box has attachment defects, marking the attachment abnormality site and issuing a prompt signal;

[0057] Step S5, obtaining the transport distance between the marked attachment abnormality site and the transport destination site, and determining whether to perform secondary smearing of the attachment on the fruit in the box;

[0058] The fitting characteristics include the fitting area between adjacent fruits and the thickness of the concave portion of the fitted fruits, and the attachment change characteristics include the expansion amount of the notch area and the ratio of the notch area to the surface area.

[0059] It is understandable that the amount of preservatives applied on the surface of fruit should be compliant with national standards, and I will not elaborate on this.

[0060] Specifically, the attachment refers to the preservative, and further, the attachment-related characteristics involved also refer to the attachment-related characteristics of the preservative on the surface of the fruit, wherein the selection of the preservative complies with the relevant national laws and regulations.

[0061] Specifically, the state data includes epidermal characteristics, real-time epidermal characteristics, surface particle density, fit characteristics, and attachment change characteristics;

[0062] Among them, the preservatives and fruit skins have unique spectral characteristics under different wavelengths of light, such as reflectivity and absorptivity. The spectral information of each pixel on the entire fruit surface can be captured by a hyperspectral camera. Specifically, the fruit can be placed under a hyperspectral imaging system for scanning, and the spectral interval of each pixel can be analyzed using spectral imaging analysis software. Based on the known spectra of preservatives and fruit skins, the spectral imaging analysis software classifies each pixel as "applied" or "unapplied". The spectral imaging analysis software then automatically counts the number of "unapplied" pixels and converts it into area to determine the area of ​​the gap in the attachment. Accordingly, other data is identified and extracted, which will not be repeated here.

[0063] In practice, a vehicle-mounted vibration recorder is arranged on the floor of a vehicle compartment to monitor the amplitude of the vehicle in real time, wherein the vehicle is a vehicle carrying and transporting fruits.

[0064] Specifically, the process of determining the epidermal deviation value includes,

[0065] Obtain real-time skin features of surface fruits, including the current attachment gap area and the current attachment gap number;

[0066] Calculating a first difference between an attachment gap area and a current attachment gap area, and solving for a ratio of the first difference to the current attachment gap area as a first deviation value;

[0067] Calculating a second difference between the number of attachment gaps and the current number of attachment gaps, and solving for a ratio of the second difference to the current number of attachment gaps as a second deviation value;

[0068] The sum of the first deviation value and the second deviation value is used as the epidermis deviation value.

[0069] Specifically, the process of analyzing the attachment quality characterization parameters of the surface fruit includes:

[0070] The ratio of the skin deviation value to the skin deviation threshold is used as the first adhesion quality feature;

[0071] The ratio of the surface particle density to the surface particle density threshold is used as the second adhesion quality feature;

[0072] The first attachment quality characteristic and the second attachment quality characteristic are weightedly summed to determine the attachment quality characterization parameter.

[0073] Specifically, during the actual transportation process, the changes directly presented by the attachments can better reflect the quality status of the attachments. Therefore, in implementation, the surface deviation value is given priority. Therefore, a slightly higher weight is given to the first attachment quality feature calculated based on the surface deviation value. Therefore, when performing weighted summation, the weight of the first attachment quality feature is set to 0.6, and the weight of the second attachment quality feature is set to 0.4.

[0074] In this embodiment, the target mean of the skin deviation threshold and the surface particle density threshold represents the poor quality state of attachments attached to the fruit surface during transportation. By obtaining historical status data corresponding to several fruit transportations along the same transportation route, the historical data of the skin deviation value and the historical data of the surface particle size are called, and the mean skin deviation and the mean surface particle size are solved. Based on the purpose of setting the above two thresholds, the skin deviation threshold is determined as the product of the mean skin deviation and the deviation offset coefficient, and the surface particle size threshold is determined as the product of the mean surface particle size and the particle deviation coefficient, wherein the deviation offset coefficient is selected within the interval [1.25, 1.3], and the particle deviation coefficient is selected within the interval [1.2, 1.25].

[0075] Specifically, the core function of preservatives is to form a protective barrier by completely covering the surface of the fruit. The area and number of gaps directly affect the continuity of the barrier. The present invention then considers the adhesion of preservatives on the surface of the fruit affected by transportation. On the one hand, it can reflect the stability of preservative adhesion and the transportation quality of the fruit. On the other hand, it reflects the adhesion firmness of the preservative. The more gaps there are, the easier it is for the preservative to fall off at the attachment point on the fruit surface. The larger the gap area, the wider the range of the single shedding area. It may be that a large area of ​​the preservative layer is peeled off due to transportation vibration and friction, reflecting that the bonding strength between the attachment layer and the fruit surface is weak. In addition, it intuitively reflects the integrity of the preservative layer. For example, a large number of gaps and a large area indicate that the preservative layer is severely damaged, which may cause the fruit to be partially exposed to the external environment and accelerate the fruit's corruption process.

[0076] At the same time, during transportation, the preservatives undergo physical changes, such as vibration and friction, causing caking, drying and cracking, resulting in a rough surface. The present invention considers the number of particles per unit area, i.e., the density of surface particles. Particle protrusions can lead to the destruction of the continuity of the preservative film layer, increase the exposed fruit skin area, and reduce the inhibitory efficiency of the preservative against mold.

[0077] Therefore, the present invention relies on the skin deviation value determined based on the comparison between the skin characteristics and the real-time skin characteristics, combined with the surface particle density to analyze the attachment quality characterization parameters to characterize the stability of preservative adhesion on the surface of the fruit during transportation, providing data support for the subsequent marking of the corresponding box, and then detecting and analyzing the fruit in the box. The present invention can dynamically and accurately evaluate the effectiveness of preservatives on the surface of the fruit during transportation.

[0078] Specifically, see Figure 2 As shown, it is a logic decision diagram for marking corresponding boxes based on the attachment quality characterization parameters according to an embodiment of the present invention. Marking corresponding boxes based on the attachment quality characterization parameters includes:

[0079] If the attachment quality characterization parameter of the surface fruit is greater than or equal to the attachment quality characterization parameter threshold, the corresponding box is marked;

[0080] If the attachment quality characterization parameter of the surface fruit is less than the attachment quality characterization parameter threshold, there is no need to mark the corresponding box.

[0081] The threshold value of the surface parameter of adhesion quality is selected in the interval [1.64,1.72].

[0082] Specifically, based on the marking results, the fruits in the box are tested and analyzed, including:

[0083] If any box is marked, the fruit in the marked box will be tested and analyzed.

[0084] Specifically, the process of determining the distribution fit characterization parameters of the fruit includes:

[0085] The sum of the ratio of the fitting area between adjacent fruits to the fitting area threshold and the ratio of the concave thickness of the fitted fruits to the concave thickness threshold is used as the first distribution fitting feature;

[0086] The ratio of the average amplitude of the transport vehicle to the average amplitude threshold is used as the second distribution fitting feature;

[0087] The sum of the first distribution fit feature and the second distribution fit feature is determined as the distribution fit characterization parameter.

[0088] In this embodiment, the purpose of setting the fitting area threshold and the depression thickness threshold is to characterize the situation where the degree of fitting and squeezing of adjacent fruits is more intense. The historical status data corresponding to several fruit transportations on the same transportation path is obtained, the historical data of the fitting area between adjacent fruits and the historical data of the depression thickness of the fitted fruits are called, and the average fitting area and the average depression thickness are solved. Based on the purpose of setting the above two thresholds, the fitting area threshold is determined as the product of the average fitting area and the area deviation coefficient, and the average depression thickness is determined as the product of the average depression thickness and the thickness deviation coefficient, wherein the area deviation coefficient is selected within the interval [1.15, 1.2], and the thickness deviation coefficient is selected within the interval [1.05, 1.1].

[0089] The purpose of setting the average amplitude threshold is to characterize the situation where the transportation environment factors have a greater interference effect on the quality of the fruit itself and its attachments. By calling the historical average amplitude data of the transportation tools corresponding to several fruit transportations on the same transportation route, the average amplitude mean of the corresponding intermediate transportation section is solved. Based on the purpose of setting the average amplitude threshold, the average amplitude threshold is determined as the product of the average amplitude mean and the amplitude deviation coefficient, wherein the amplitude deviation coefficient is selected within the interval [1.2, 1.25].

[0090] Specifically, the present invention detects and analyzes the marked fruits in the box, detecting the distribution and fit between adjacent fruits in the box. The larger the fit area between adjacent fruits, the denser the stacking of the fruits, and the higher the probability of mutual friction during transportation, which is more likely to cause preservatives to fall off. The thickness of the depressions in the fit of the fruits can reflect the severity of the squeezing between the fruits, and thus the severity of the physical damage to the fruit skin and the degree of rupture of the preservative film on the fruit surface. The present invention then comprehensively quantifies the environmental stress, taking into account the amplitude of the transport vehicle. For example, the higher the average amplitude of the transport vehicle, the more frequent the mechanical impact on the preservative film, which will aggravate the impact on the compactness of the stacking of the fruits and the integrity of the preservatives.

[0091] Therefore, the present invention determines the distribution fit characterization parameters of the fruit by combining the fit characteristics of the fruit with the average amplitude of the transportation vehicle, so as to characterize the influence of the transportation environment on the degree of fruit fit depression and the wear of the attachments, and provide data support for the subsequent identification of abnormal attachment sites. The present invention can dynamically and accurately evaluate the effectiveness of preservatives on the surface of fruits during transportation.

[0092] Specifically, see Figure 3 As shown, it is a logical decision diagram for identifying abnormal attachment sites according to an embodiment of the present invention. Identifying abnormal attachment sites includes:

[0093] If the distribution fitting characterization parameter corresponding to the fruit determined at any intermediate transport station is greater than or equal to the distribution fitting characterization parameter threshold, the intermediate transport station is identified as the attachment abnormality station.

[0094] The distribution fitting parameter threshold is selected in the interval [3.25,3.31].

[0095] Specifically, see Figure 4 As shown, it is a logical decision diagram for evaluating whether the fruit in the box meets the adhesion and shedding standard according to an embodiment of the present invention. The evaluation of whether the fruit in the box meets the adhesion and shedding standard includes:

[0096] If the expansion amount of the notch area of ​​the surface fruit is greater than the expansion amount threshold and / or the ratio of the notch area to the surface area is greater than the ratio threshold, it is determined that the fruit in the box does not meet the attachment and shedding standard.

[0097] In this embodiment, the purpose of setting the expansion amount threshold and the ratio threshold is to characterize the situation where the incremental amount of attachments falling off during transportation is large and the falling off is more serious. The site corresponding to the abnormal attachment site is determined, and the historical gap area expansion data corresponding to the site during several fruit transportations on the same transportation route are obtained. The mean expansion amount is solved. Based on the purpose of setting the expansion amount threshold, the expansion amount threshold is determined as the product of the mean expansion amount and the expansion deviation coefficient. The ratio threshold is selected within the interval [3%, 5%], wherein the expansion deviation coefficient is selected within the interval [1.2, 1.25].

[0098] Specifically, the present invention analyzes the attachment changes of the surface fruit on the basis of determining the abnormal attachment sites. The expansion of the gap area reflects the dynamic increase of the preservative shedding during transportation, and identifies which sites or path segments cause the accelerated shedding. The proportion of the gap area to the surface area reflects the severity of the current preservative attachment and shedding. Through the above two characteristics, it is comprehensively evaluated whether the fruit in the box meets the attachment and shedding standards, dynamically tracked the attachment change trend of the preservative, and determined whether the fruit in the box has attachment defects, and then marked the corresponding abnormal attachment sites for easy quality traceability. The present invention can dynamically and accurately evaluate the effectiveness of preservatives on the surface of fruits during transportation.

[0099] Specifically, determining whether there is an attachment defect in the fruit in the box, marking the attachment abnormality site and issuing a prompt signal, including:

[0100] If any fruit in the box does not meet the shedding standard, it is determined that the fruit in the box has an attachment defect, the attachment abnormality site is marked and a prompt signal is issued.

[0101] Specifically, determining whether to apply the attachment to the fruit in the box for the second time includes:

[0102] If the transport distance between the marked attachment abnormal site and the transport destination site is greater than or equal to the transport distance threshold, the fruit in the box is smeared a second time;

[0103] If the transportation distance between the marked attachment abnormality site and the transportation destination site is less than the transportation distance threshold, there is no need to apply a second coating to the fruit in the box.

[0104] In this embodiment, the purpose of setting the transportation distance threshold is to characterize the situation where the preservation effect of fruits is poor when the current attachment quality state is maintained and transported to the destination site, and the historical data of transportation distances from the marked attachment abnormality site to several transportation destination sites are obtained for several times, and the average transportation distance is solved. Based on the purpose of setting the transportation distance threshold, the average transportation distance is determined as the transportation distance threshold.

[0105] Specifically, the present invention considers the preservation threshold of preservatives on fruits in the box during transportation, dynamically considers the remaining transportation distance, determines whether the existing amount of preservatives attached is sufficient to cover the preservation needs of the remaining transportation distance, and accurately supplements the antiseptic ability of the preservatives. On the basis of avoiding indiscriminate re-application of preservatives, it improves resource utilization and reduces transportation costs.

[0106] If the fruit preservative detection method of the present invention is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program code, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0107] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

Claims

1. A method for detecting fruit preservatives, characterized in that: include: Retrieving the state data of the surface fruit in the box before transportation to extract the corresponding skin features, wherein the skin features include the area and number of attachment gaps; Inspecting the surface fruit at the first intermediate transport station to identify corresponding real-time epidermal features, comparing the real-time epidermal features with the epidermal features to determine epidermal deviation values, analyzing attachment quality characterization parameters of the surface fruit in combination with surface particle density of the surface fruit, and marking the box based on the attachment quality characterization parameters; Based on the marking results, the fruit in the box is inspected and analyzed, including obtaining distribution images of the fruit at several subsequent intermediate transport stations, determining the attachment characteristics of the fruit, and combining the average amplitude of the transport vehicle corresponding to the intermediate transport section to determine the distribution and attachment characterization parameters of the fruit, so as to identify abnormal attachment stations; Obtaining attachment change characteristics of the surface fruit at the attachment abnormality site to evaluate whether the fruit in the box meets the attachment and detachment standards, determining whether the fruit in the box has attachment defects, marking the attachment abnormality site and issuing a prompt signal; Obtaining the transportation distance between the marked attachment abnormality site and the transportation destination site, and determining whether to perform a secondary smearing of the attachment on the fruit in the box; The fitting characteristics include the fitting area between adjacent fruits and the thickness of the concave portion of the fitted fruit, and the attachment change characteristics include the expansion of the gap area and the ratio of the gap area to the surface area. The process of analyzing the attachment quality characterization parameters of the surface fruit includes: The ratio of the skin deviation value to the skin deviation threshold is used as the first adhesion quality feature; The ratio of the surface particle density to the surface particle density threshold is used as the second adhesion quality feature; Determine the attachment quality characterization parameter by performing a weighted summation of the first attachment quality characteristic and the second attachment quality characteristic; The process of determining the distribution fit characterization parameters of the fruit includes: The sum of the ratio of the fitting area between adjacent fruits to the fitting area threshold and the ratio of the concave thickness of the fitted fruits to the concave thickness threshold is used as the first distribution fitting feature; The ratio of the average amplitude of the transport vehicle to the average amplitude threshold is used as the second distribution fitting feature; The sum of the first distribution fit feature and the second distribution fit feature is determined as the distribution fit characterization parameter.

2. The method for detecting fruit preservatives according to claim 1, wherein The process of determining the epidermal deviation value includes, Obtain real-time skin features of surface fruits, including the current attachment gap area and the current attachment gap number; Calculating a first difference between an attachment gap area and a current attachment gap area, and solving for a ratio of the first difference to the current attachment gap area as a first deviation value; Calculating a second difference between the number of attachment gaps and the current number of attachment gaps, and solving for a ratio of the second difference to the current number of attachment gaps as a second deviation value; The sum of the first deviation value and the second deviation value is used as the epidermis deviation value.

3. The method for detecting fruit preservatives according to claim 1, wherein The corresponding box is marked based on the attachment quality characterization parameter, including: If the attachment quality characterization parameter of the surface fruit is greater than or equal to the attachment quality characterization parameter threshold, the corresponding box is marked.

4. The method for detecting fruit preservatives according to claim 3, wherein: According to the marking results, the fruits in the box are tested and analyzed, including: If any box is marked, the fruit in the marked box will be tested and analyzed.

5. The method for detecting fruit preservatives according to claim 1, wherein Identify attachment abnormality sites, including, If the distribution fitting characterization parameter corresponding to the fruit determined at any intermediate transport station is greater than or equal to the distribution fitting characterization parameter threshold, the intermediate transport station is identified as the attachment abnormality station.

6. The method for detecting fruit preservatives according to claim 1, wherein Assess whether the fruit in the box meets the standards for attachment and detachment, including: If the expansion amount of the notch area of ​​the surface fruit is greater than the expansion amount threshold and / or the ratio of the notch area to the surface area is greater than the ratio threshold, it is determined that the fruit in the box does not meet the attachment and shedding standard.

7. The method for detecting fruit preservatives according to claim 6, wherein: Determine whether there is an attachment defect in the fruit in the box, mark the attachment abnormality site and send a prompt signal, including: If any fruit in the box does not meet the shedding standard, it is determined that the fruit in the box has an attachment defect, the attachment abnormality site is marked and a prompt signal is issued.

8. The method for detecting fruit preservatives according to claim 1, wherein: Determine whether to apply the attachment to the fruit in the box for the second time. include, If the transportation distance between the marked abnormal attachment site and the transportation destination site is greater than or equal to the transportation distance threshold, the fruit in the box is smeared a second time.

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