A rice quality detection method

Abstract

The invention discloses a rice quality detection method, and relates to the technical field of rice quality detection. The method is implemented by adopting a data collection and data preprocessing module, a comprehensive evaluation module, a detection adjustment and detection data management module, using an optical instrument to detect the reflectivity and transmittance of a rice sample at different wavelengths, and recording the detected data in a system of a detection device, wherein the different wavelengths specifically include infrared light and ultraviolet light, cleaning and collating the detection data recorded in the detection device system, removing repeated, erroneous and invalid detection data, and collating the measured detection data into a table or a data set in the detection device system, wherein each row represents a wavelength, and each column contains the reflectivity and transmittance values ​​at the wavelength, and according to the feedback analysis result, a targeted adjustment plan is formulated, and optimization of material formula or improvement of optical structure design is considered to obtain the reflectivity and transmittance of rice quality that meets the standard.

Description

Technical Field

[0001] The invention relates to the technical field of rice quality detection, in particular to a rice quality detection method. Background Art

[0002] As one of the staple foods widely consumed worldwide, the quality of rice is directly related to the health and satisfaction of consumers. Therefore, rice quality testing is an important link to ensure the safety and quality of rice. With the development of science and technology, rice testing methods have gradually developed from traditional sensory evaluation and physical testing to more scientific and accurate optical testing, chemical analysis and comprehensive quality assessment.

[0003] Among them, in rice quality inspection, optical inspection technology has attracted much attention due to its non-contact, fast and accurate characteristics. Through optical equipment such as spectrometers and cameras, the basic optical properties of rice, such as color and transparency, can be measured to preliminarily evaluate the quality of rice. These basic optical properties are closely related to the nutritional content and processing accuracy of rice, providing an important basis for comprehensive quality assessment.

[0004] As consumers' requirements for rice quality continue to increase, the requirements for detection accuracy and efficiency are also getting higher and higher. However, existing technologies are still difficult to meet this demand in some aspects, such as limited detection capabilities for minor defects, slow detection speed, and the existing detection dimensions are too single; in addition, although the comprehensive quality evaluation fully reflects the overall quality level of rice, the calculation process involves multiple indicators and complex weighted summation or comprehensive evaluation algorithms, which makes the evaluation process relatively complex and difficult to standardize; finally, after feedback adjustment, although it helps to verify the adjustment effect, its adjustment effect is often affected by many factors, such as the rationality of the adjustment plan and the accuracy of the adjustment equipment. In addition, the feedback adjustment mechanism also needs to be continuously optimized and improved according to actual conditions. Summary of the invention

[0005] The object of the present invention is to provide a rice quality detection method, which solves the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a rice quality detection method, using:

[0007] Implementation of data collection and data preprocessing module, comprehensive evaluation module, detection adjustment and detection data management module;

[0008] The specific implementation process is as follows:

[0009] Data Collection:

[0010] Using an optical instrument to detect the reflectivity and transmittance of the rice sample at different wavelengths, and recording the results in a system of the detection device, wherein the different wavelengths specifically include infrared light and ultraviolet light;

[0011] Data processing:

[0012] Clean and organize the test data recorded in the test equipment system, and remove duplicate, erroneous and invalid test data. Clean and organize the test data recorded in the test equipment system, and remove duplicate, erroneous and invalid test data. Organize the measured test data into a table or data set in the test equipment system, where each row represents a wavelength and each column contains the reflectance and transmittance values ​​at the wavelength;

[0013] Test data management:

[0014] The comprehensive evaluation is realized by the comprehensive evaluation module, and the implementation process of the specific calculation steps of the comprehensive evaluation module includes:

[0015] Basic optical properties unit, comprehensive rice quality assessment unit and adjusted basic optical properties unit;

[0016] First, observe whether the rice grains are full, whether the color is natural and shiny, whether the surface is smooth and uniform, and whether there are impurities and breakage. The above observations can indirectly reflect the processing quality, storage conditions and freshness of the rice;

[0017] Next, by using optical instruments to measure the optical properties of rice, including the reflectivity of different light wavelengths, the quality of rice can be evaluated under dual optical observation, and the difference in the optical properties of rice can be obtained through evaluation;

[0018] Then, by inspecting the appearance of the rice and the difference in its optical properties, combined with the transmittance at another different wavelength of light, the overall quality of the rice can be comprehensively evaluated, ensuring that multiple quality indicators of the rice are comprehensively considered and a comprehensive quality evaluation result is given;

[0019] And, based on the results of the comprehensive quality assessment, feedback adjustments are made to the evaluation results of the differences in the optical properties of the rice under optical observation, so as to obtain a test evaluation result that more accurately reflects the current status of the rice;

[0020] Afterwards, the detection and evaluation result of the current state of the rice is compared with the result of the reference quality evaluation to obtain an adjustment factor of the optical property difference after the change. The adjustment factor of the optical property difference after the change replaces the optical property difference obtained by the evaluation under the double optical observation, thereby determining the adjustment direction and degree of the rice quality;

[0021] Detection Adjustment:

[0022] According to the feedback analysis results, formulate targeted adjustment plans, consider optimizing material formulations or improving optical structure design to obtain reflectivity and transmittance that meet rice quality standards;

[0023] Data upload:

[0024] After the test data is sorted, it is uploaded to the rice quality testing equipment system.

[0025] Optionally, the calculation process of the basic optical property unit is as follows:

[0026]

[0027] FC = HB-ZB;

[0028] FH=HB+ZB;

[0029] in:

[0030] MC is the optical property difference index, which reflects the difference in optical properties of rice at different wavelengths;

[0031] HB is the reflectivity index of the first infrared wavelength, that is, the reflectivity detected by the first infrared wavelength. HB reflects the composition of rice, including the proportion of starch and protein, as well as the surface state;

[0032] ZB is the UV wavelength reflectivity index, which is the reflectivity of the UV light wavelength;

[0033] FC is the wavelength difference value, FC reflects the difference between different wavelengths;

[0034] FH is the wavelength normalization value, which reflects the normalization of differences between different wavelengths.

[0035] Optionally, the calculation process of the rice comprehensive quality assessment unit is as follows:

[0036]

[0037] MY=MC*(1-HT);

[0038] in:

[0039] MZ is the comprehensive quality assessment index;

[0040] MC is the optical property difference index;

[0041] HT is the transmittance index of the second infrared wavelength, that is, the transmittance detected by the second infrared wavelength. HT reflects the level of impurities or moisture content inside the rice;

[0042] MY is the comprehensive quality impact index, which reflects the impact of internal impurities and moisture content of rice on quality.

[0043] Optionally, the calculation process of the adjusted basic optical property unit is as follows:

[0044] MC new =MC*(1+β*CTZ)

[0045]

[0046] in:

[0047] MC new is the new optical property difference index after the replacement;

[0048] MC is the optical property difference index;

[0049] MZ is the comprehensive quality assessment index;

[0050] β is the adjustment coefficient, which is used to control the adjustment amplitude of MZ to MC;

[0051] MPZ is the reference quality assessment index;

[0052] CTZ is the difference unified modulation index, which is used to normalize the difference amplitude between MZ and MPZ.

[0053] Optionally, the calculation steps of the adjusted basic optical property unit under the influence of further feedback to the basic optical property unit are as follows:

[0054] S1. First, MC is adjusted by the value of MZ to reflect the feedback of the rice comprehensive quality assessment unit to the basic optical property unit, and this adjustment process is achieved by a multiplication factor based on the difference between MZ and MPZ.

[0055] Specifically, the multiplication factor based on the difference between MZ and MPZ is: For the sake of convenience, the multiplication factor will be replaced by CFY in the following calculation steps.

[0056] In addition, it is worth mentioning that MC is the optical property difference index. new is the new optical property difference index after the replacement, MZ is the comprehensive quality evaluation index, and MPZ is the reference quality evaluation index;

[0057] S2. When MZ>MPZ, the result value of CFY is greater than 1, MC new will increase, indicating that MC is positively adjusted due to the better evaluation results of MZ;

[0058] S3. When MZ < MPZ, the result value of CFY is less than 1 but greater than 0, and MC new will decrease, indicating that MC is negatively adjusted due to the poor evaluation result of MZ.

[0059] S4. When MZ = MPZ, the result value of CFY is 1, and MC new = MC. The evaluation result of MC is moderate and remains unchanged.

[0060] Optionally, the data collection and data preprocessing module includes:

[0061] a data collection unit, a data cleaning unit, and a data sorting unit;

[0062] The data collection unit collects the detection data of rice from an optical instrument, and the detection data covers the reflectance and transmittance of infrared light and ultraviolet light.

[0063] Optionally, the data sorting unit centrally sorts the detection data processed by the data cleaning unit and marks and estimates the missing detection data.

[0064] Optionally, the device used by the data collection unit is a spectrometer.

[0065] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0066] First, the rice quality detection method of the present invention combines the characteristic differences under two optical reflectivities and the transmittance at a third wavelength, and can construct a more comprehensive rice quality evaluation model. This multi-dimensional evaluation method can capture more subtle quality changes, thereby improving the detection accuracy. And by performing feedback adjustment on the optical characteristic differences, the detection model can be continuously optimized to reduce errors and biases. This dynamic adjustment process makes the detection results more accurate and reliable.

[0067] Second, the feedback adjustment mechanism requires the detection model to have the ability of self-optimization and learning, which promotes the continuous innovation and development of related technologies. For example, by introducing machine learning algorithms, the automatic optimization and iterative update of the detection model can be realized. The comprehensive quality evaluation method based on multi-dimensional optical characteristic differences and transmittance helps to establish a more unified and standardized evaluation system. This helps to improve the comparability and credibility of rice quality detection, and provides strong support for the fair competition in the rice market and the protection of consumers' rights and interests.

[0068] Detection methods based on optical properties are usually non-destructive and do not cause physical or chemical damage to rice. This helps maintain the integrity and nutritional value of rice. Combining multiple optical detection data for comprehensive quality assessment and continuously optimizing the detection model under the feedback adjustment mechanism can achieve efficient and rapid rice quality detection. This helps meet the quality detection needs in large-scale production and circulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 is a flow chart of the rice quality detection method;

[0070] Figure 2 It is a structural schematic diagram of the data collection and preprocessing module of the present invention;

[0071] Figure 3 It is a structural schematic diagram of the comprehensive evaluation module of the present invention. DETAILED DESCRIPTION

[0072] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0073] The rice quality detection method is different from the existing rice quality detection method. The existing rice quality detection method has limited detection capabilities for minor defects, slow detection speed, and too single detection dimension, resulting in the evaluation results of rice detection being too limited and single, and cannot comprehensively and completely detect the comprehensive quality of rice. In addition, the sampling destructive detection using manual or machine intervention not only makes the detection results less objective and comprehensive, but also causes physical or chemical damage to the rice, which is not conducive to maintaining the integrity and nutritional value of the rice. The algorithm unit can significantly improve the accuracy of the detection data through optical intelligent comprehensive evaluation and processing technology, and can continuously optimize the detection model and reduce errors and deviations in conjunction with feedback adjustment. This dynamic adjustment process makes the detection results more accurate and reliable, which helps to improve the comparability and credibility of rice quality detection.

[0074] For examples, see Figures 1 to 3 ,This implementation provides a rice quality detection method which is implemented by a data collection and data preprocessing module, a comprehensive evaluation module, a detection adjustment and detection data management module;

[0075] The specific steps are as follows:

[0076] Data collection: Use optical instruments to test the reflectivity and transmittance of rice samples at different wavelengths, including infrared light and ultraviolet light, and record them in the system of the testing equipment;

[0077] Data processing: cleaning and arranging the test data recorded in the test equipment system, and removing duplicate, erroneous and invalid test data; cleaning and arranging the test data recorded in the test equipment system, and removing duplicate, erroneous and invalid test data; arranging the measured test data into a table or data set in the test equipment system, where each row represents a wavelength, and each column contains the reflectance and transmittance values ​​at that wavelength;

[0078] Test data management: achieved through comprehensive evaluation calculated by the comprehensive evaluation module;

[0079] The implementation process of the specific calculation steps of the comprehensive evaluation module includes:

[0080] Basic optical properties unit, comprehensive rice quality assessment unit and adjusted basic optical properties unit;

[0081] First, observe whether the rice grains are full, whether the color is natural and shiny, whether the surface is smooth and uniform, and whether there are impurities and breakage. The above observations can indirectly reflect the processing quality, storage conditions and freshness of the rice;

[0082] Next, by using optical instruments to measure the optical properties of rice, including the reflectivity of different light wavelengths, the quality of rice can be evaluated under dual optical observation, and the difference in the optical properties of rice can be obtained through evaluation;

[0083] Then, by inspecting the appearance of the rice and the difference in its optical properties, combined with the transmittance at another different wavelength of light, the overall quality of the rice can be comprehensively evaluated, ensuring that multiple quality indicators of the rice are comprehensively considered and a comprehensive quality evaluation result is given;

[0084] And, based on the results of the comprehensive quality assessment, feedback adjustments are made to the evaluation results of the differences in the optical properties of the rice under optical observation, so as to obtain a test evaluation result that more accurately reflects the current status of the rice;

[0085] Afterwards, the detection and evaluation result of the current state of the rice is compared with the result of the reference quality evaluation to obtain an adjustment factor of the optical property difference after the change. The adjustment factor of the optical property difference after the change replaces the optical property difference obtained by the evaluation under the double optical observation, thereby determining the adjustment direction and degree of the rice quality;

[0086] Detection Adjustment:

[0087] According to the feedback analysis results, formulate targeted adjustment plans, consider optimizing material formulations or improving optical structure design to obtain reflectivity and transmittance that meet rice quality standards;

[0088] Data upload:

[0089] After the test data is sorted, it is uploaded to the rice quality testing equipment system.

[0090] In this embodiment, the system uses the cooperation of three algorithm units to capture more subtle quality changes of multi-dimensional rice and dynamically adjust according to the changes to ensure that the detection results are more accurate and reliable. new The three calculation results can form a multi-dimensional, comprehensive and detailed rice quality detection method. The system method can evaluate the difference in optical properties, comprehensive quality evaluation, and whether the new optical property differences after the replacement need to be adjusted. At the same time, the comprehensive quality evaluation method based on multi-dimensional optical property differences and transmittance can help to establish a more unified and standardized evaluation system. This helps to improve the comparability and credibility of rice quality detection, and provide strong support for fair competition in the rice market and the protection of consumer rights. MC is the optical property difference index, which is used to quantify the difference in optical properties of rice at different wavelengths, and through the measured optical property difference index, to verify whether the quality of rice meets the standard through the reflectivity of different wavelengths. MZ is the comprehensive quality evaluation index, which combines the optical property difference index and the second infrared wavelength transmittance to evaluate the comprehensive evaluation of rice quality, and can obtain a more comprehensive and multi-dimensional quality evaluation. This comprehensive evaluation of multiple test data can more accurately reflect the true quality status of rice, and the comprehensive evaluation combined with multiple test data can verify and complement each other, thereby reducing the overall evaluation deviation caused by the error of a single test data, MC new In order to update the new optical characteristic difference index, the detection model can be continuously optimized and the error and deviation can be reduced by feedback adjustment of the optical characteristic difference. This dynamic adjustment process makes the detection and evaluation results more accurate and reliable, and MC new The calculation results can also iteratively affect MC, making the three algorithms of this system have a high correlation and entanglement, so that the overall algorithm system can be automatically iterated and optimized according to the actual situation to be closer to reality.

[0091] See also Figures 1 to 3 , the calculation process of the basic optical property unit is as follows:

[0092]

[0093] FC = HB-ZB;

[0094] FH=HB+ZB;

[0095] in:

[0096] MC is the optical property difference index, which reflects the difference in optical properties of rice at different wavelengths;

[0097] HB is the reflectivity index of the first infrared wavelength, that is, the reflectivity detected by the first infrared wavelength. HB reflects the composition of rice, including the proportion of starch and protein, as well as the surface state;

[0098] ZB is the UV wavelength reflectivity index, which is the reflectivity of the UV light wavelength;

[0099] FC is the wavelength difference value, FC reflects the difference between different wavelengths;

[0100] FH is the wavelength normalization value, which reflects the normalization of differences between different wavelengths.

[0101] In the present embodiment: first, HB in the algorithm unit is the first infrared wavelength reflectivity index, ZB is the ultraviolet wavelength reflectivity index, and the reflectivity embodied in the algorithm refers to the ratio of the first infrared wavelength and the ultraviolet wavelength reflected by the rice surface, and after calculation, the optical property difference index MC reflecting the rice sample at different wavelengths can be obtained;

[0102] This algorithm unit combines the calculation of different optical reflectances to evaluate the surface characteristics and internal structure of rice from multiple angles. For example, one method may focus on the color uniformity and glossiness of rice, while another method may pay more attention to the tiny textures and details on the surface of rice. This multi-angle evaluation can reduce the possibility of misjudgment and missed judgment; and the results obtained by calculating the two different optical reflectances can verify each other and improve the reliability of the test results. If the results obtained by the two methods are consistent or similar, the confidence in the rice quality assessment can be enhanced; if there are differences, the reasons can be further analyzed to improve the accuracy of the test, thereby providing a cross-validation effect for the test data.

[0103] Some optical reflectance calculation methods may be able to more deeply detect the internal quality of rice, such as moisture content and protein content. This information is important for evaluating the nutritional value and storage stability of rice, while different optical reflectance calculation methods may have different sensitivities to surface defects of rice. One method may be more likely to detect color anomalies or spots, while another method may be better at detecting surface cracks or scratches. This complementarity makes the inspection more comprehensive and helps reduce the flow of substandard rice into the market.

[0104] See also Figures 1 to 3, the calculation process of the rice comprehensive quality assessment unit is as follows:

[0105]

[0106] MY=MC*(1-HT);

[0107] in:

[0108] MZ is the comprehensive quality assessment index;

[0109] MC is the optical property difference index;

[0110] HT is the transmittance index of the second infrared wavelength, that is, the transmittance detected by the second infrared wavelength. HT reflects the level of impurities or moisture content inside the rice;

[0111] MY is the comprehensive quality impact index, which reflects the impact of internal impurities and moisture content of rice on quality.

[0112] In this embodiment, firstly, the optical property difference index MC is calculated by referencing the basic optical property unit, and the second infrared light wavelength transmittance index HT is added to the calculation, which further considers the light absorption capacity of the internal structure of rice, thereby more comprehensively detecting and evaluating the quality of rice.

[0113] This algorithm unit combines the characteristic differences under two different optical reflectances and the transmittance under a third optical wavelength to obtain more comprehensive and multi-dimensional quality information. This comprehensive evaluation of multiple test data can more accurately reflect the true quality status of rice. Since a single optical characteristic or transmittance may be affected by multiple factors, a comprehensive evaluation based on multiple test data can verify and complement each other, thereby reducing the overall evaluation deviation caused by errors in a single test data.

[0114] Optical reflectivity mainly reflects the optical properties of the rice surface, such as color and glossiness, while transmittance can provide more information about the internal structure of rice, such as moisture content and chemical composition. Combining the two can achieve a comprehensive evaluation of the internal and external quality of rice. Different optical properties and transmittances may have different sensitivities to surface and internal defects of rice. Through comprehensive evaluation, cracks and scratches on the surface of rice and insect and mildew defects inside can be detected more accurately.

[0115] Combining multiple optical detection data for comprehensive quality assessment requires advanced detection technology and data processing methods. This demand has promoted the continuous integration and innovation of related technologies, providing new impetus for the development of rice quality detection technology. And by establishing a comprehensive quality assessment system based on multiple optical detection data, the standardization process of rice quality detection can be promoted. The standardized assessment system helps to improve the reliability and comparability of test results, and provides strong support for fair competition in the rice market and the protection of consumers' rights and interests.

[0116] See also Figures 1 to 3 , the calculation process of the adjusted basic optical characteristic unit is as follows: MC new =

[0117] MC*(1+β*CTZ)

[0118]

[0119] in:

[0120] MC new is the new optical property difference index after the replacement;

[0121] MC is the optical property difference index;

[0122] MZ is the comprehensive quality assessment index;

[0123] β is the adjustment coefficient, which is used to control the adjustment amplitude of MZ to MC;

[0124] MPZ is the reference quality assessment index;

[0125] CTZ is the difference unified modulation index, which is used to normalize the difference amplitude between MZ and MPZ.

[0126] In this embodiment, the algorithm unit first MC new is the new optical characteristic difference index after the replacement, MC is the optical characteristic difference index, and the new optical characteristic difference index MC after the replacement new It is an iterative optimization of the optical characteristic difference index MC, which takes into account the influence of the comprehensive quality evaluation index MZ on the optical characteristic difference index MC. When the comprehensive quality evaluation index MZ deviates from the middle value, assuming that 0.5 is the medium quality level, the adjustment amplitude is proportional to the deviation degree of the first infrared light wavelength reflectivity index HB, thereby realizing the correlation and feedback between quality evaluation and basic characteristics;

[0127] This algorithm unit combines the characteristic differences under two optical reflectivities and the transmittance at a third wavelength to construct a more comprehensive rice quality evaluation model. This multi-dimensional evaluation method can capture more subtle quality changes, thereby improving the detection accuracy. By making feedback adjustments to the optical characteristic differences, the detection model can be continuously optimized to reduce errors and biases. This dynamic adjustment process makes the detection results more accurate and reliable. The comprehensive quality evaluation method based on multi-dimensional optical characteristic differences and transmittance helps to establish a more unified and standardized evaluation system. This helps to enhance the comparability and credibility of rice quality detection, providing strong support for the fair competition in the rice market and the protection of consumers' rights and interests.

[0128] It should be noted that the rice detection method based on optical characteristics is usually non-destructive and will not cause physical or chemical damage to the rice. This helps to maintain the integrity and nutritional value of the rice.

[0129] Please refer to Figures 1 to 3 , after adjustment, the calculation steps of the basic optical characteristic unit based on the further feedback influence on the basic optical characteristic unit are as follows:

[0130] S1. First, adjust MC through the value of MZ to reflect the feedback of the rice comprehensive quality evaluation unit on the basic optical characteristic unit. This adjustment process is achieved through a multiplication factor, which is based on the difference between MZ and MPZ.

[0131] Specifically, the multiplication factor based on the difference between MZ and MPZ is: For the convenience of explanation, this multiplication factor will be replaced by CFY in the following calculation steps.

[0132] In addition, it should be noted that MC is the optical characteristic difference index, MC new is the new optical characteristic difference index after iteration, MZ is the comprehensive quality evaluation index, and MPZ is the reference quality evaluation index;

[0133] S2. When MZ > MPZ, the result value of CFY is greater than 1, and MC new will increase, indicating that MC is positively adjusted because the evaluation result of MZ is good.

[0134] S3. When MZ < MPZ, the result value of CFY is less than 1 but greater than 0, and MC new will decrease, indicating that MC is negatively adjusted because the evaluation result of MZ is poor.

[0135] S4. When MZ = MPZ, the result value of CFY is 1, and MC new = MC, and the evaluation result of MC is moderate and remains unchanged.

[0136] In this embodiment, the algorithm unit uses the reference quality evaluation index MPZ as the detection reference of rice quality, and compares and evaluates it with the comprehensive quality evaluation index MZ. According to the evaluation results of different comparisons, the new optical property difference index MC after the replacement can be obtained. new , comprehensive evaluation results of rice quality testing.

[0137] This algorithm unit calculates the optical characteristic difference index MC based on two different optical reflectivities, and combines the transmittance at the third optical wavelength to perform a comprehensive quality evaluation index MZ, and then evaluates the new optical characteristic difference index MC after the replacement. new Feedback adjustment has a significant effect on rice quality detection. This method not only improves the precision and accuracy of detection, but also enhances the comprehensiveness of detection, promotes technological innovation and standardization, and improves market trust and consumer satisfaction. In practical applications, this method also has the advantages of non-destructiveness and high efficiency.

[0138] In the specific implementation process, the image of rice quality detection can also be reflected by drawing a curve graph, in which the reflectivity curve graph uses wavelength as the horizontal axis and reflectivity as the vertical axis, and draws a curve of reflectivity changing with wavelength. This curve will show the reflection characteristics of rice samples at different wavelengths; the transmittance curve graph also uses wavelength as the horizontal axis, but the vertical axis is transmittance, and draws a curve of transmittance changing with wavelength. This curve will show the transmission characteristics of rice samples at different wavelengths. Finally, by analyzing the curve graph and observing these two curves, you can find the changes in the optical properties of rice samples at different wavelengths. For example, a higher reflectivity at certain wavelengths may mean that the wavelength is effectively reflected by the sample surface; while a wavelength with a lower transmittance may correspond to a strong absorption or scattering inside the sample.

[0139] For example 2, please refer to Figures 1 to 3 ,The data collection and data preprocessing modules include: a data collection unit, a data cleaning unit, and a data ,collation unit;

[0140] The data collection unit collects rice detection data from an optical instrument, and the detection data covers the reflectivity and transmittance of infrared light and ultraviolet light.

[0141] The data sorting unit centrally sorts the detection data cleaned by the data cleaning unit and marks and estimates the missing detection data.

[0142] The equipment used in the data collection unit is a spectrometer.

[0143] In this embodiment, the spectrometer can measure the reflectivity and transmittance characteristics of different lights collected at different wavelengths through the data collection unit, the data cleaning unit and the data sorting unit. The spectrometer usually includes a light source, a spectroscopic system, a detector and a data processing system function.

[0144] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A rice quality detection method, characterized in that, The steps include: Data collection, using optical instruments to detect the reflectivity and transmittance of rice samples at different wavelengths and record them in the system of the detection equipment. The different wavelengths specifically include infrared light and ultraviolet light; Data processing, arranging the test data recorded in the test equipment system into tables and data sets, where each row represents a wavelength and each column contains the reflectance and transmittance values ​​at that wavelength; Test data management, through the comprehensive evaluation module to obtain the optical characteristic difference index MC, the comprehensive quality evaluation index MZ, and the new optical characteristic difference index after the replacement ; Detection and adjustment: According to the output results of the comprehensive evaluation module, an adjustment plan is formulated to obtain the reflectance and transmittance of rice that meet the quality standards; Data upload: After the test data is sorted, it is uploaded to the system of rice quality testing equipment; The comprehensive assessment module includes: Basic optical properties unit, comprehensive rice quality assessment unit and adjusted basic optical properties unit; The calculation process of the basic optical property unit is as follows: ； ； ； in: MC is the optical property difference index, which reflects the difference in optical properties of rice at different wavelengths; HB is the reflectivity index of the first infrared wavelength, that is, the reflectivity detected by the first infrared wavelength. HB reflects the composition of rice, including the proportion of starch and protein, as well as the surface state; ZB is the UV wavelength reflectivity index, which is the reflectivity of the UV light wavelength; FC is the wavelength difference value, FC reflects the difference between different wavelengths; FH is the wavelength normalized value, and FH reflects the normalization of the differences between different wavelengths; The calculation process of the rice comprehensive quality assessment unit is as follows: ； ； in: MZ is the comprehensive quality assessment index; MC is the optical property difference index; HT is the transmittance index of the second infrared wavelength, that is, the transmittance detected by the second infrared wavelength. HT reflects the level of impurities or moisture content inside the rice; MY is the comprehensive quality impact index, which reflects the impact of internal impurities and moisture content of rice on quality; The calculation process of the adjusted basic optical property unit is as follows: ； ； in: is the new optical property difference index after the replacement; MC is the optical property difference index; MZ is the comprehensive quality assessment index; β is the adjustment coefficient, which is used to control the adjustment amplitude of MZ to MC; MPZ is the reference quality assessment index; CTZ is the difference unified modulation index, which is used to normalize the difference amplitude between MZ and MPZ.

2. A rice quality detection method according to claim 1, characterized in that, The specific evaluation steps of the comprehensive evaluation module include: First, observe whether the rice grains are full, whether the color is natural and shiny, whether the surface is smooth and uniform, and whether there are impurities and breakage. The above observations can reflect the processing quality, storage conditions and freshness of the rice; Next, by using optical instruments to measure the optical properties of rice, including the reflectivity of different light wavelengths, the quality of rice can be evaluated under dual optical observation, and the difference in the optical properties of rice can be obtained through evaluation; Then, by inspecting the appearance of the rice and the difference in its optical properties, combined with the transmittance at another different wavelength of light, the overall quality of the rice can be comprehensively evaluated, ensuring that multiple quality indicators of the rice are comprehensively considered and a comprehensive quality evaluation result is given; And, based on the results of the comprehensive quality assessment, feedback adjustments are made to the evaluation results of the differences in the optical properties of the rice under optical observation, so as to obtain a test evaluation result that more accurately reflects the current status of the rice; Afterwards, the detection and evaluation results of the current state of the rice are compared with the results of the reference quality evaluation to obtain the adjustment factor of the new optical property difference after the change. The adjustment factor of the new optical property difference after the change replaces the optical property difference obtained by the evaluation under double optical observation, thereby determining the adjustment direction and degree of rice quality.

3. A rice quality detection method according to claim 1, characterized in that: The process in which the adjusted basic optical property unit further affects the basic optical property unit is as follows: S1. First, the optical property difference index MC is adjusted by the comprehensive quality assessment index MZ to reflect the influence of the rice comprehensive quality assessment unit on the basic optical property unit. This adjustment process is carried out through a multiplication factor based on the difference between the comprehensive quality assessment index MZ and the reference quality assessment index MPZ. Specifically, the multiplication factor based on the difference between the comprehensive quality assessment index MZ and the reference quality assessment index MPZ is: , for the sake of convenience, the multiplication factor will be replaced by CFY in the following calculation steps. In addition, MC is the optical property difference index, is the new optical property difference index after the replacement, MZ is the comprehensive quality evaluation index, and MPZ is the reference quality evaluation index; S2. When MZ>MPZ, the result value of CFY is greater than 1. will increase, indicating that MC is positively adjusted due to the better evaluation results of MZ; S3. When MZ<MPZ, the result value of CFY is less than 1 but greater than 0. will decrease, indicating that MC is negatively adjusted due to the poor evaluation results of MZ; S4. When MZ=MPZ, the result value of CFY is 1. =MC, the evaluation result of MC is moderate and remains unchanged.

4. A rice quality detection method according to claim 1, characterized in that: The data collection and data preprocessing module includes: Data collection unit, data cleaning unit, data sorting unit; The data collection unit is detection data of rice collected from an optical instrument, and the detection data covers the reflectivity and transmittance of infrared light and ultraviolet light.

5. A rice quality detection method according to claim 4, characterized in that: The data sorting unit centrally sorts the detection data cleaned by the data cleaning unit and marks and estimates the missing detection data.

6. A rice quality detection method according to claim 5, characterized in that: The equipment used in the data collection unit is a spectrometer.

Images