CN111855930B - Grain nutrient detection device and method - Google Patents

Grain nutrient detection device and method Download PDF

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CN111855930B
CN111855930B CN202010701698.5A CN202010701698A CN111855930B CN 111855930 B CN111855930 B CN 111855930B CN 202010701698 A CN202010701698 A CN 202010701698A CN 111855930 B CN111855930 B CN 111855930B
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王防修
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Abstract

The invention discloses a device and a method for detecting grain nutrients, which relate to the technical field of grain production and processing, and comprise the following steps: the device comprises a sampling module, an analysis module and a detection module; the sampling module is used for acquiring the current nutrient content of the grain product in the processing process; the analysis module is used for calculating a reference value of a preset nutrient content data set according to a preset reference value calculation rule to obtain a nutrient content reference value; the analysis module is further used for carrying out relative quantity calculation on the current nutrient content according to a preset relative quantity calculation rule and the nutrient content reference value to obtain the total amount of the current relative nutrient; and the detection module is used for comparing the current relative nutrient total amount with the nutrient content reference value and determining a detection result according to a comparison result. The invention monitors the nutrient change process in the processing process by detecting the nutrient of the grains in the production process of the grain products, and is beneficial to production adjustment.

Description

Grain nutrient detection device and method
Technical Field
The invention relates to the technical field of grain production and processing, in particular to a grain nutrient detection device and method.
Background
At present, the current situation of grain processing is to meet the requirements of consumers on the taste and appearance of grain products, so that a large amount of raw grains are over-processed, and the over-processing can cause a large amount of loss of nutrients in the grains. With the change of the concept of consumers, more and more consumers begin to annotate nutrition, food processing enterprises need to gradually adjust the balance among taste, appearance and nutrients, and the food processing enterprises cannot monitor the nutrients of the food in the processing process at present, so that the processing and adjustment become more difficult.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide a grain nutrient detection device and method, and aims to solve the technical problem that grain nutrients cannot be detected in the grain production and processing process in the prior art.
In order to achieve the above object, the present invention provides a grain nutrient detection device, including:
the sampling module is used for acquiring the current nutrient content of the grain product in the processing process;
the analysis module is used for calculating a reference value of a preset nutrient content data set according to a preset reference value calculation rule to obtain a nutrient content reference value;
the analysis module is further used for carrying out relative quantity calculation on the current nutrient content according to a preset relative quantity calculation rule and the nutrient content reference value to obtain the total amount of the current relative nutrient;
and the detection module is used for comparing the current relative nutrient total amount with the nutrient content reference value and determining a detection result according to a comparison result.
Preferably, the analysis module is further configured to perform mean calculation on the nutrient content in the preset nutrient content data set to obtain a nutrient content average value;
the analysis module is further used for sequencing the nutrient content in the preset nutrient content data set to obtain a nutrient content median;
the analysis module is further used for calculating the relative nutrient content corresponding to the content of each nutrient in the preset nutrient content data set according to the average nutrient content or the median of the nutrient content;
the analysis module is further used for obtaining the total relative nutrient content according to the relative nutrient content, and taking the average nutrient content value, the median nutrient content value and the total relative nutrient content as nutrient content reference values.
Preferably, the analysis module is further configured to calculate the current nutrient content according to the average nutrient content value or the median nutrient content value to obtain a current relative nutrient content;
the analysis module is also used for obtaining the total amount of the current relative nutrients according to the content of the current relative nutrients.
Preferably, the detection module is further configured to perform a difference between the current relative nutrient total amount and the relative nutrient total amount to obtain a content difference value;
the detection module is further configured to compare the content difference value with a preset threshold value, and determine that the detection result is qualified when the content difference value is smaller than the preset threshold value.
Preferably, the sampling module is further configured to obtain an initial nutrient content of the grain before processing, and generate the preset nutrient content data set according to the initial nutrient content.
Preferably, the sampling module is further configured to obtain a reference nutrient content of the processed grain, and generate the preset nutrient content data set according to the reference nutrient content.
Preferably, the analysis module is further configured to preprocess the preset nutrient content data set through a preset principal component analysis model to obtain an intermediate nutrient content data set;
and the analysis module is also used for calculating a reference value of the intermediate nutrient content data set according to a preset reference value calculation rule to obtain a nutrient content reference value.
Preferably, the sampling module is further configured to sample the grain product in the processing process according to a preset interval time to obtain a grain sample;
the sampling module is also used for carrying out element detection on the grain sample to obtain nutrient content data;
the sampling module is further used for screening the nutrient content data according to a preset content interval, and taking the screened nutrient content data as the current nutrient content.
In addition, in order to achieve the above object, the present invention further provides a method for detecting food nutrients based on the above device for detecting food nutrients, wherein the method for detecting food nutrients comprises the following steps:
the sampling module acquires the current nutrient content of the grain product in the processing process;
the analysis module calculates a reference value of a preset nutrient content data set according to a preset reference value calculation rule to obtain a nutrient content reference value;
the analysis module calculates the relative quantity of the current nutrient content according to a preset relative quantity calculation rule and the nutrient content reference value to obtain the total amount of the current relative nutrient;
and the detection module compares the current relative nutrient total amount with the nutrient content reference value and determines a detection result according to a comparison result.
Preferably, the step of calculating the reference value of the preset nutrient content data set by the analysis module according to the preset reference value calculation rule to obtain the reference value of the nutrient content includes:
the analysis module calculates the mean value of the nutrient content in the preset nutrient content data set to obtain the average value of the nutrient content;
the analysis module sequences the nutrient content in the preset nutrient content data set to obtain a nutrient content median;
the analysis module calculates the relative nutrient content corresponding to each nutrient content in the preset nutrient content data set according to the average nutrient content or the median of the nutrient content;
the analysis module obtains a relative nutrient total amount according to the relative nutrient content, and takes the average nutrient content value, the median nutrient content value and the relative nutrient total amount as nutrient content reference values.
In the invention, a grain nutrient detection device is formed by arranging a sampling module, an analysis module and a detection module; the sampling module is used for acquiring the current nutrient content of the grain product in the processing process; the analysis module is used for calculating a reference value of a preset nutrient content data set according to a preset reference value calculation rule to obtain a nutrient content reference value; the analysis module is further used for carrying out relative quantity calculation on the current nutrient content according to a preset relative quantity calculation rule and the nutrient content reference value to obtain the total amount of the current relative nutrient; and the detection module is used for comparing the current relative nutrient total amount with the nutrient content reference value and determining a detection result according to a comparison result. According to the invention, the nutrients of the grain are detected in the production process of the grain product, the reference value is obtained through the preset nutrient content data set, and the detected nutrient content is compared with the reference value, so that the relative content of the nutrients in the production process of the grain product is obtained, the nutrient change process in the processing process is further obtained, and the production adjustment is facilitated.
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FIG. 1 is a block diagram of a first embodiment of a food nutrient detection device according to the present invention;
fig. 2 is a schematic flow chart of a food nutrient detection method according to a first embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
The invention provides a grain nutrient detection device, and referring to fig. 1, fig. 1 is a structural block diagram of a first embodiment of the grain nutrient detection device.
In a first embodiment, the apparatus for detecting nutrients in grain comprises:
and the sampling module 10 is used for acquiring the current nutrient content of the grain product in the processing process.
It should be noted that the grain product may be rice, wheat, corn, or the like, and may also be other varieties, which is not limited in this embodiment. During specific implementation, the current nutrient content is obtained by sampling grain products in the processing process and detecting sample products.
In addition, the content of the nutrient may be carbohydrate, fat, protein, vitamin, trace element, or the like, and in specific implementation, the content of the nutrient may be one or more of the above. The content is expressed by the amount of the nutrient contained per 100g, but other expressions may be used, and the present embodiment is not limited thereto.
And the analysis module 20 is configured to perform reference value calculation on the preset nutrient content data set according to a preset reference value calculation rule to obtain a nutrient content reference value.
It should be noted that the preset nutrient content data set is a reference nutrient content obtained by detecting historically produced food products in advance, and can be expressed as
Figure BDA0002592140640000051
Wherein j =1,2, \8230;, n; k =1,2, \ 8230;, p,
Figure BDA0002592140640000052
indicating the content of the jth nutrient in the kth sample.
It should be noted that the reference value of the nutrient content may be an average value or a median. In this embodiment, the analysis module 20 is further configured to perform a mean calculation on the nutrient contents in the preset nutrient content data set to obtain a mean nutrient content value. Specifically, the content U of the jth nutrient can be calculated by the following formula j
Figure BDA0002592140640000053
The analysis module 20 is further configured to sort the nutrient contents in the preset nutrient content data set to obtain a nutrient content median. Specifically, the content of each nutrient is sorted in an ascending order (or a descending order), and the median D of the j-th nutrient is obtained j
The analysis module 20 is further configured to calculate, according to the average nutrient content value or the median nutrient content value, a relative nutrient content corresponding to each nutrient content in the preset nutrient content data set.
When specifically realized, the content is U j As a basis, the first relative nutrient content of each nutrient content in the preset nutrient content data set is measured. Specifically, the first relative nutrient content was calculated by the following formula
Figure BDA0002592140640000056
Figure BDA0002592140640000055
At the same time, when specifically realized, as the content D j As a basis, the second relative nutrient content of each nutrient content in the preset nutrient content dataset is measured. Specifically, the second relative nutrient content was calculated by the following formula
Figure BDA0002592140640000067
Figure BDA0002592140640000062
The analysis module 20 is further configured to obtain a total relative nutrient amount according to the relative nutrient content, and use the average nutrient content value, the median nutrient content value, and the total relative nutrient amount as a nutrient content reference value.
It should be noted that, in order to compare different nutrients respectively, the first mean value F of the first relative nutrient content of the jth nutrient needs to be calculated by the following formula according to the mean value of each type of nutrient j :
Figure BDA0002592140640000063
Meanwhile, a second average G of the second relative nutrient content of the jth nutrient is calculated by the following formula j :
Figure BDA0002592140640000064
It should be noted that the first average value F j Is the average value of each nutrient in the grain product obtained on the basis of the average value, and the second average value G j Refers to each of the grain products obtained based on the medianThe average nutrient value, in order to make a thorough comparison of the food products, requires the calculation of the total nutrient content of the food products.
In a specific implementation, the first relative nutrient total S corresponding to the first average value can be calculated by the following formula:
Figure BDA0002592140640000065
calculating a second relative nutrient total T corresponding to the second mean value by:
Figure BDA0002592140640000066
the total relative nutrient total amount ST of the grain product can be obtained by obtaining the relative nutrient total amount under the two levels through the calculation. Where ST = max { S, T } (8).
It should be noted that the total relative nutrient total amount refers to a total content value of nutrients in a food product, and since the preset nutrient content data set is sampling data of historically produced food products, the total relative nutrient total amount reflects the nutrient content of the food product in the historical production process. The calculation process is explained by a single grain product, and the nutrient content of various grain products can be calculated simultaneously in specific implementation.
The analysis module 20 is further configured to perform relative quantity calculation on the current nutrient content according to the preset relative quantity calculation rule and the nutrient content reference value, so as to obtain a current relative nutrient total amount.
It should be noted that, in order to take into account the current production state, the current nutrient content needs to be calculated, which can be expressed as Z j J =1,2, \ 8230;, n. Wherein Z j The content of nutrients in jth grain products is detected, so that multiple times of sampling and detection are needed when the content of the nutrients is detected in order to avoid accidental errors during sampling.
In this embodiment, the analysis module 20 is further configured to calculate the current nutrient content according to the average nutrient content or the median nutrient content to obtain the current relative nutrient content.
It will be appreciated that for comparison with a reference value for nutrient content, a corresponding comparison parameter needs to be obtained. Specifically, the current relative nutrient content is obtained by the following formula;
Figure BDA0002592140640000071
Figure BDA0002592140640000072
wherein, X j Is the first current relative nutrient content, Y, based on the mean nutrient content j Is the second current relative nutrient content on a median nutrient content basis.
The analysis module 20 is further configured to obtain a current relative nutrient total amount according to the current relative nutrient content.
And obtaining the corresponding current relative nutrient total amount according to the first current relative nutrient content and the second current relative nutrient content. Specifically, the current relative total nutrient is obtained by the following formula:
Figure BDA0002592140640000073
Figure BDA0002592140640000074
wherein SZ is a first current relative nutrient total obtained on a nutrient content average basis, and TZ is a second current relative nutrient total obtained on a nutrient content median basis. Likewise, the current relative nutrient total at both levels is obtained, from which the individual relative nutrient total STZ of the currently tested food product can be determined. Where STZ = max { SZ, TZ } (13).
And the detection module 30 is configured to compare the current relative nutrient total amount with the nutrient content reference value, and determine a detection result according to a comparison result.
It should be noted that the test result usually includes pass and fail, and the test result is determined according to the comparison result of the current relative nutrient total amount and the nutrient content reference value and with reference to the preset condition.
Specifically, the detection module 30 is further configured to make a difference between the current total relative nutrient amount and the total relative nutrient amount to obtain a content difference value.
It should be noted that the current relative total nutrient amount may be the first current relative total nutrient amount and the second current relative total nutrient amount in the above process, or may be the individual relative total nutrient amount. Also the relative total nutrient amount may be the first relative total nutrient amount and the second relative total nutrient amount, or the total relative total nutrient amount.
The detection module 30 is further configured to compare the content difference with a preset threshold, and determine that the detection result is qualified when the content difference is smaller than the preset threshold.
It should be noted that, according to the user requirement, the preset threshold may be freely set. For example, the content difference is STZ-ST, i.e. the relative total nutrient content of the individual corresponding to the current nutrient content is compared to the total relative total nutrient content corresponding to the preset nutrient content data set. When the content difference is larger than zero, the nutrient content in the current production process exceeds the nutrient content in the historical production, and the detection result can be judged to be qualified. When the content difference is less than zero, the nutrient content in the current production process is lower than that in the historical production, and the detection result can be judged to be unqualified.
In the first embodiment, a grain nutrient detection device is formed by arranging a sampling module, an analysis module and a detection module; the sampling module is used for acquiring the current nutrient content of the grain product in the processing process; the analysis module is used for calculating a reference value of a preset nutrient content data set according to a preset reference value calculation rule to obtain a nutrient content reference value; the analysis module is further used for carrying out relative quantity calculation on the current nutrient content according to a preset relative quantity calculation rule and the nutrient content reference value to obtain the total amount of the current relative nutrient; and the detection module is used for comparing the current relative nutrient total amount with the nutrient content reference value and determining a detection result according to a comparison result. The embodiment detects the nutrients of the grains in the production process of the grain products, acquires the reference value through the preset nutrient content data set, compares the detected nutrient content with the reference value, and accordingly acquires the relative content of the nutrients in the production process of the current grain products, and further acquires the nutrient change process of the processing process, thereby being beneficial to production adjustment.
With continued reference to fig. 1, a second embodiment of the food nutrient detection apparatus of the present invention is provided.
In a second embodiment, the sampling module 10 is further configured to obtain an initial nutrient content of the grain before processing, and generate the preset nutrient content data set according to the initial nutrient content.
It should be noted that, during the grain production process, the loss of nutrients is absolute, and in order to ensure the content of nutrients in the production process, the loss of nutrients needs to be controlled. Generating a preset nutrient content data set according to the initial nutrient content of the grain before processing, wherein the comparison result output by the detection module 30 is the retention proportion of the nutrient content in the production process, and the retention proportion is unqualified when the retention proportion is smaller than the preset proportion; and when the retention ratio is larger than the preset ratio, the product is qualified.
In a second embodiment, the sampling module 10 is further configured to obtain a reference nutrient content of the processed grain, and generate the preset nutrient content data set according to the reference nutrient content.
It should be noted that the processed grain refers to a grain product which is qualified after processing, and in order to ensure that the loss rate of nutrients in the grain production process cannot be too high. Therefore, the preset nutrient content data set is generated according to the reference nutrient content of the processed grain, so that a producer can determine the difference between the current nutrient content and the standard value according to the comparison result output by the detection module 30, and if the difference is greater than the preset value, the loss rate is too high, and the processing is unqualified; otherwise, the product is qualified.
Generally, the processing of grain products involves a plurality of processes and devices, and grain products in any processing link can be sampled during specific implementation. Specifically, the sampling module 10 is further configured to sample a grain product in a processing process according to a preset interval time to obtain a grain sample; the sampling module 10 is further configured to perform element detection on the grain sample to obtain nutrient content data; the sampling module 10 is further configured to screen the nutrient content data according to a preset content interval, and use the screened nutrient content data as the current nutrient content.
It will be appreciated that repeated sampling of the food product is required in order to reduce accidental errors in sampling. The preset interval time may be 1 minute or 2 minutes. Meanwhile, in order to ensure the reasonability of data, the acquired data needs to be screened, a reasonable interval can be determined according to the nutrient content data of the current grain sample in the preset content interval, and obvious error data is eliminated.
In a second embodiment, the analysis module 20 is further configured to pre-process the preset nutrient content data set through a preset principal component analysis model to obtain an intermediate nutrient content data set; the analysis module 20 is further configured to perform reference value calculation on the intermediate nutrient content data set according to a preset reference value calculation rule to obtain a nutrient content reference value.
It can be understood that, since the preset nutrient content data set may have error data, in order to ensure the reasonability of the data, the sampled data needs to be reasonably preprocessed, and the main nutrient components of the grain are obtained by applying a principal component analysis method. The predetermined principal component analysis model may be created by a predetermined Principal Component Analysis (PCA) algorithm.
In the second embodiment, a plurality of preset nutrient content data sets are arranged, and production personnel can call corresponding data sets as comparison standards according to production index control requirements, so that the nutrient loss rate in the grain production process can be monitored more comprehensively. Meanwhile, collected nutrient content data are preprocessed, the reasonability of the quantity is guaranteed, and the accuracy of a detection result is improved.
In addition, referring to fig. 2, an embodiment of the present invention further provides a method for detecting a grain nutrient, where the method for detecting a grain nutrient includes the following steps:
step S10: the sampling module acquires the current nutrient content of the grain product in the processing process.
It should be noted that the grain product may be rice, wheat, corn, or the like, and may also be other varieties, which is not limited in this embodiment. During specific implementation, the current nutrient content is obtained by sampling grain products in the processing process and detecting sample products.
The nutrient content may be carbohydrate, fat, protein, vitamin, trace element, or the like, and in specific implementation, the nutrient detection object may be one or more of the above. The content is expressed by the amount of the nutrient contained per 100g, but other expressions may be used, and the present embodiment is not limited thereto.
Step S20: and the analysis module calculates a reference value of the preset nutrient content data set according to a preset reference value calculation rule to obtain a nutrient content reference value.
It should be noted that the preset nutrient content data set is a reference nutrient content obtained by detecting the historical grain products in advance, and can be expressed as
Figure BDA0002592140640000101
Wherein the content of the first and second substances,j=1,2,…,n;k=1,2,…,p,
Figure BDA0002592140640000102
indicating the content of the jth nutrient in the kth sample.
It should be noted that the reference value of the nutrient content may be an average value or a median. In this embodiment, the step S20 specifically includes: the analysis module carries out mean calculation on the nutrient content in the preset nutrient content data set to obtain a nutrient content mean value; the analysis module sorts the nutrient content in the preset nutrient content data set to obtain a nutrient content median; the analysis module calculates the relative nutrient content corresponding to each nutrient content in the preset nutrient content data set according to the average nutrient content or the median of the nutrient content; and the analysis module obtains the total relative nutrient content according to the relative nutrient content, and takes the average nutrient content value, the median nutrient content value and the total relative nutrient content as nutrient content reference values.
Specifically, the content U of the jth nutrient can be calculated by the following formula j
Figure BDA0002592140640000111
Specifically, the content of each nutrient is sorted in an ascending order (or a descending order), and the median D of the j-th nutrient is obtained j
When specifically implemented, in the amount of U j As a basis, the first relative nutrient content of each nutrient content in the preset nutrient content data set is measured. Specifically, the first relative nutrient content was calculated by the following formula
Figure BDA0002592140640000118
Figure BDA0002592140640000113
At the same time, when specifically realized, as the content D j As a basis, the second relative nutrient content of each nutrient content in the preset nutrient content data set is measured. Specifically, the second relative nutrient content was calculated by the following formula
Figure BDA0002592140640000119
Figure BDA0002592140640000115
It should be noted that, in order to compare different nutrients respectively, the first mean value F of the first relative nutrient content of the jth nutrient needs to be calculated by the following formula according to the mean value of each type of nutrient j :
Figure BDA0002592140640000116
Meanwhile, a second mean value G of a second relative nutrient content of the jth nutrient is calculated by the following formula j :
Figure BDA0002592140640000117
It should be noted that the first average value F j Is the average value of each nutrient in the grain product obtained on the basis of the average value, the second average value G j The average value of each nutrient in the grain product obtained on the basis of the median is used as a basis, and the total amount of the nutrient in the grain product needs to be calculated in order to comprehensively compare the grain product.
In a specific implementation, the first relative nutrient total S corresponding to the first average value can be calculated by the following formula:
Figure BDA0002592140640000121
calculating a second relative total nutrient T corresponding to the second average value by the following formula:
Figure BDA0002592140640000122
the total relative nutrient total amount ST of the grain product can be obtained by obtaining the relative nutrient total amount under the two levels through the calculation. Where ST = max { S, T } (8).
It should be noted that the total relative nutrient total amount refers to a total content value of nutrients in a food product, and since the preset nutrient content data set is sampling data of historically produced food products, the total relative nutrient total amount reflects the nutrient content of the food product in the historical production process. The calculation process is explained by a single grain product, and the nutrient content of various grain products can be calculated simultaneously in specific implementation.
Step S30: and the analysis module calculates the relative quantity of the current nutrient content according to a preset relative quantity calculation rule and the nutrient content reference value to obtain the total amount of the current relative nutrient.
It should be noted that in order to take into account the current production state, the current nutrient content needs to be calculated, which can be expressed as Z j J =1,2, \8230;, n. Wherein Z j The content of nutrients in jth grain products is detected, so that multiple times of sampling and detection are needed when the content of the nutrients is detected in order to avoid accidental errors during sampling.
It will be appreciated that for comparison with the nutrient content reference, a corresponding comparison parameter needs to be obtained. Specifically, the current relative nutrient content is obtained through the following formula;
Figure BDA0002592140640000123
Figure BDA0002592140640000124
wherein X j A first current relative nutrient content, Y, based on the mean nutrient content j The second current relative nutrient content is obtained on a median basis of nutrient content.
And obtaining the corresponding current relative nutrient total amount according to the first current relative nutrient content and the second current relative nutrient content. Specifically, the current relative total nutrient is obtained by the following formula:
Figure BDA0002592140640000125
Figure BDA0002592140640000126
wherein SZ is a first current relative nutrient total obtained on the basis of the mean nutrient content, and TZ is a second current relative nutrient total obtained on the basis of the median nutrient content. Likewise, the current relative nutrient total at both levels is obtained, from which the individual relative nutrient total STZ of the currently tested food product can be determined. Where STZ = max { SZ, TZ } (13).
Step S40: and the detection module compares the current relative nutrient total amount with the nutrient content reference value and determines a detection result according to a comparison result.
It should be noted that the test result usually includes pass and fail, and the test result is determined according to the comparison result between the current relative total nutrient content and the reference value of the nutrient content by referring to a preset condition.
It should be noted that the current relative total nutrient amount may be the first current relative total nutrient amount and the second current relative total nutrient amount in the above process, or may be the individual relative total nutrient amount. Also the relative total nutrient amount may be the first relative total nutrient amount and the second relative total nutrient amount, or the total relative total nutrient amount.
It should be noted that, according to the user requirement, the preset threshold may be freely set. For example, the content difference is STZ-ST, i.e. the relative total nutrient content of the individual corresponding to the current nutrient content is compared with the total relative total nutrient content corresponding to the preset nutrient content data set. When the content difference is larger than zero, the nutrient content in the current production process exceeds the nutrient content in the historical production process, and the detection result can be judged to be qualified. When the content difference is less than zero, the nutrient content in the current production process is lower than the nutrient content in the historical production process, and the detection result can be judged to be unqualified.
In the embodiment, the current nutrient content of the grain product in the processing process is obtained through the sampling module; the analysis module calculates a reference value of a preset nutrient content data set according to a preset reference value calculation rule to obtain a nutrient content reference value; the analysis module calculates the relative quantity of the current nutrient content according to a preset relative quantity calculation rule and the nutrient content reference value to obtain the total amount of the current relative nutrient; and the detection module compares the current relative nutrient total amount with the nutrient content reference value and determines a detection result according to a comparison result. The embodiment detects the nutrients of the grains in the production process of the grain products, acquires the reference value through the preset nutrient content data set, compares the detected nutrient content with the reference value, and accordingly acquires the relative content of the nutrients in the production process of the current grain products, and further acquires the nutrient change process of the processing process, thereby being beneficial to production adjustment.
Other embodiments or specific implementation manners of the grain nutrient detection method of the present invention may refer to the above embodiments of the apparatus, and are not described herein again.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrases "comprising one of 8230; \8230;" 8230; "does not exclude the presence of additional like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order, but rather the words first, second, third, etc. are to be interpreted as names.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention or portions thereof that contribute to the prior art may be embodied in the form of a software product, where the computer software product is stored in a storage medium (e.g., a Read Only Memory (ROM)/Random Access Memory (RAM), a magnetic disk, an optical disk), and includes several instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims (6)

1. The utility model provides a grain nutrient detection device which characterized in that, grain nutrient detection device includes:
a sampling module for obtaining the current nutrient content of the grain product in the processing process, wherein the current nutrient content is expressed as Z j J =1,2, \8230n, where Z j The content of jth nutrient in the detected grain product is detected;
the analysis module is used for calculating a reference value of a preset nutrient content data set according to a preset reference value calculation rule to obtain a nutrient content reference value, wherein the preset nutrient content data set is a reference nutrient content obtained by detecting historical produced grain products in advance and is represented as follows:
Figure FDA0003858489160000011
wherein j =1,2, \8230, n; k =1,2, \8230;, p,
Figure FDA0003858489160000012
representing the content of the jth nutrient in the kth sample, wherein the nutrient content reference value is an average value or a median;
the analysis module is further used for carrying out mean value calculation on the nutrient content in the preset nutrient content data set to obtain a nutrient content average value and the content U of the jth nutrient j Calculated according to the following formula:
Figure FDA0003858489160000013
the analysis module is further used for sequencing the nutrient contents in the preset nutrient content data set to obtain a nutrient content median, and the median of the jth nutrient is represented as D j The nutrient contents are sorted in an ascending order or a descending order;
the analysis module is further used for carrying out relative quantity calculation on the current nutrient content according to a preset relative quantity calculation rule and the nutrient content reference value to obtain the total amount of the current relative nutrient;
the analysis module is further configured to calculate a relative nutrient content corresponding to each nutrient content in the preset nutrient content data set according to the average nutrient content or the median nutrient content, where the relative nutrient content is calculated according to the following formula:
Figure FDA0003858489160000014
Figure FDA0003858489160000015
wherein the content of the first and second substances,
Figure FDA0003858489160000021
is in an amount of U j Calculating the first relative nutrient content on the basis,
Figure FDA0003858489160000022
is in an amount D j Calculating the second relative nutrient content on the basis;
the analysis module is further used for obtaining a relative total nutrient amount according to the relative nutrient content, and the relative total nutrient amount is calculated according to the following formula:
Figure FDA0003858489160000023
Figure FDA0003858489160000024
Figure FDA0003858489160000025
Figure FDA0003858489160000026
wherein, F j Is a first mean value of a first relative nutrient content of the jth nutrient, G j Is a second average of a second relative nutrient content of the jth nutrient, S is a first relative nutrient total amount, and T is a second relative nutrient total amount;
the analysis module is further configured to obtain a total relative nutrient total ST of the food product, wherein ST = max { S, T };
the analysis module is further configured to calculate the current nutrient content according to the average nutrient content or the median nutrient content to obtain a current relative nutrient content, where the current relative nutrient content is obtained according to the following formula:
Figure FDA0003858489160000027
Figure FDA0003858489160000028
wherein X j The first current relative nutrient content, Y, being the average of the nutrient contents j Obtaining a second current relative nutrient content with a median of nutrient contents, wherein Zj refers to the content of the jth current nutrient in the detected grain product;
the analysis module is further configured to obtain a current relative nutrient total amount according to the current relative nutrient content, where the current relative nutrient total amount is:
Figure FDA0003858489160000029
Figure FDA0003858489160000031
wherein SZ is a first current relative nutrient total obtained on a nutrient content mean basis, and TZ is a second current relative nutrient total obtained on a nutrient content median basis;
the analysis module is further used for determining the total individual relative nutrient amount STZ of the currently detected grain product, wherein STZ = max { SZ, TZ };
the detection module is used for subtracting the current relative nutrient total amount and the relative nutrient total amount to obtain a content difference value, wherein the current relative nutrient total amount is the first current relative nutrient content, the second current relative nutrient content or the individual relative nutrient total amount, and the relative nutrient total amount is the first relative nutrient total amount, the second relative nutrient total amount or the overall relative nutrient total amount;
the detection module is further configured to compare the content difference value with a preset threshold value, and determine that the detection result is qualified when the content difference value is smaller than the preset threshold value.
2. The grain nutrient detection device of claim 1, wherein the sampling module is further configured to obtain an initial nutrient content of the grain before processing, and to generate the preset nutrient content data set according to the initial nutrient content.
3. The food nutrient detection device of claim 1, wherein the sampling module is further configured to obtain a reference nutrient content of the processed food, and generate the preset nutrient content data set according to the reference nutrient content.
4. The apparatus according to claim 1, wherein the analysis module is further configured to preprocess the data set of predetermined nutrient content through a predetermined principal component analysis model to obtain an intermediate data set of nutrient content;
and the analysis module is also used for calculating a reference value of the intermediate nutrient content data set according to a preset reference value calculation rule to obtain a nutrient content reference value.
5. The grain nutrient detection device of claim 1, wherein the sampling module is further configured to sample a grain product in a processing process at preset intervals to obtain a grain sample;
the sampling module is also used for carrying out element detection on the grain sample to obtain nutrient content data;
the sampling module is further used for screening the nutrient content data according to a preset content interval, and taking the screened nutrient content data as the current nutrient content.
6. A grain nutrient detection method based on the grain nutrient detection device of any one of claims 1 to 5, characterized by comprising the following steps:
the sampling module acquires the current nutrient content of the grain product in the processing process, and the current nutrient content is expressed as Z j J =1,2, \ 8230;, n, wherein Z j The content of jth nutrient in the detected grain product is detected;
the analysis module calculates a reference value of a preset nutrient content data set according to a preset reference value calculation rule to obtain a nutrient content reference value, wherein the preset nutrient content data set is a reference nutrient content obtained by detecting historically produced grain products in advance and is represented as follows:
Figure FDA0003858489160000041
wherein j =1,2, \8230, n; k =1,2, \ 8230;, p,
Figure FDA0003858489160000042
representing the content of the jth nutrient in the kth sample, wherein the nutrient content reference value is an average value or a median;
the analysis module calculates a reference value of a preset nutrient content data set according to a preset reference value calculation rule to obtain a nutrient content reference value, and the method specifically comprises the following steps:
the analysis module carries out mean value calculation on the nutrient content in the preset nutrient content data set to obtain the average value of the nutrient content and the content U of the jth nutrient j Calculated according to the following formula:
Figure FDA0003858489160000043
the analysis module sequences the nutrient contents in the preset nutrient content data set to obtain a nutrient content median, wherein the median of the jth nutrient is represented as D j The nutrient contents are sorted in an ascending order or a descending order;
the analysis module calculates the relative quantity of the current nutrient content according to a preset relative quantity calculation rule and the nutrient content reference value to obtain the total amount of the current relative nutrient;
the analysis module calculates the relative nutrient content corresponding to each nutrient content in the preset nutrient content data set according to the average nutrient content or the median of the nutrient content, and the relative nutrient content is calculated according to the following formula:
Figure FDA0003858489160000051
Figure FDA0003858489160000052
wherein, the first and the second end of the pipe are connected with each other,
Figure FDA0003858489160000053
is in an amount of U j Calculating the first relative nutrient content on the basis,
Figure FDA0003858489160000054
is in an amount D j Calculating the second relative nutrient content on the basis;
the analysis module obtains the total amount of relative nutrients according to the content of the relative nutrients, and the total amount of the relative nutrients is calculated according to the following formula:
Figure FDA0003858489160000055
Figure FDA0003858489160000056
Figure FDA0003858489160000057
Figure FDA0003858489160000058
wherein, F j Is a first mean value of a first relative nutrient content of a jth nutrient, G j Is a second average of a second relative nutrient content of the jth nutrient, S is a first relative nutrient total amount, and T is a second relative nutrient total amount;
the analysis module is further configured to obtain a total relative nutrient total ST of the food product, wherein ST = max { S, T };
the analysis module calculates the relative quantity of the current nutrient content according to a preset relative quantity calculation rule and the nutrient content reference value to obtain the total amount of the current relative nutrient, and the method specifically comprises the following steps:
the analysis module calculates the current nutrient content according to the average nutrient content value or the median nutrient content value to obtain the current relative nutrient content, and the current relative nutrient content is obtained according to the following formula:
Figure FDA0003858489160000059
Figure FDA00038584891600000510
wherein, X j A first current relative nutrient content, Y, obtained as an average of the nutrient contents j Obtaining a second current relative nutrient content with a median of nutrient contents, wherein Zj refers to the content of the jth current nutrient in the detected grain product;
the analysis module obtains a current relative nutrient total amount according to the current relative nutrient content, wherein the current relative nutrient total amount is as follows:
Figure FDA0003858489160000061
Figure FDA0003858489160000062
wherein SZ is a first current relative nutrient total obtained on a nutrient content mean basis, and TZ is a second current relative nutrient total obtained on a nutrient content median basis;
the analysis module determines the total amount of individual relative nutrients STZ of the currently detected grain product, wherein STZ = max { SZ, TZ };
the detection module performs difference on the current relative nutrient total amount and the relative nutrient total amount to obtain a content difference value, wherein the current relative nutrient total amount is the first current relative nutrient content, the second current relative nutrient content or the individual relative nutrient total amount, and the relative nutrient total amount is the first relative nutrient total amount, the second relative nutrient total amount or the overall relative nutrient total amount;
and the detection module compares the content difference value with a preset threshold value, and judges that the detection result is qualified when the content difference value is smaller than the preset threshold value.
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