Method for judging flavor of fruit and vegetable juice and fruit and vegetable powder based on color detection

Abstract

The invention relates to the technical field of fruit and vegetable juice and fruit and vegetable powder production, in particular to a method for judging the flavor of fruit and vegetable juice and fruit and vegetable powder based on color detection, which comprises the following steps: S1, sample preparation: collecting samples from production lines or finished products of fruit and vegetable juice and fruit and vegetable powder with different batches and different flavors; s2, storing the collected sample in an environment at the temperature of 4-10 DEG C; s3, directly detecting the fruit and vegetable juice, and diluting the concentrated fruit and vegetable juice in a proportion of 1-10% for later use; s4, a visible spectrophotometer is used, the detection wavelength detection range is selected and set to be 360-1000 nm, a light source is a tungsten halogen lamp, the precision can be selected from + / -0.5 nm to + / -2 nm, and color detection equipment and parameters are set; the accurate and objective flavor evaluation is beneficial to ensuring the consistency of the product quality and ensuring the reliability and repeatability of the flavor evaluation result, the complicated chemical pretreatment step is not needed, the expenditure is remarkably saved, and the method can also be used in the research and development stage of new products.

Description

Technical Field

[0001] The invention relates to the technical field of fruit and vegetable juice and fruit and vegetable powder production, and in particular to a method for judging the flavor of fruit and vegetable juice and fruit and vegetable powder based on color detection. Background Art

[0002] In the production and quality control of fruit and vegetable juice and fruit and vegetable powder, flavor is a key indicator, which directly affects consumer acceptance and the market competitiveness of the product. At present, the methods for evaluating the flavor of concentrated fruit and vegetable juice and fruit and vegetable powder have many limitations.

[0003] There are several main methods for evaluating the flavor of fruit and vegetable juice and fruit and vegetable powder: First, traditional manual sensory evaluation, in which professional tasters identify flavors based on their own taste and smell. For example, tasters will first smell the flavor to evaluate whether there are abnormal flavors such as fruity or fermented, and then taste it to determine flavor characteristics such as sourness, sweetness, and bitterness. However, this method is highly subjective, and different tasters have different sensory sensitivities and evaluation standards. The same batch of products may produce different evaluation results, and factors such as the tasters' physical condition and emotional state will affect the accuracy of the evaluation. At the same time, manual evaluation is inefficient and is not suitable for rapid testing in large-scale production.

[0004] There are also chemical analysis methods, such as gas chromatography-mass spectrometry (GC-MS) technology, to detect volatile flavor components in fruit juice. After complex sample pretreatment, including extraction, concentration and purification, the sample is injected into the GC-MS instrument to analyze the types and contents of various flavor substances. However, this method requires professionals to operate precise and expensive instruments, which is costly and complicated to operate. It can only analyze a limited number of known flavor substances, and may not be able to effectively detect some trace or unknown flavor-related components. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides an accurate and objective flavor evaluation, which helps to ensure the consistency of product quality, ensure the reliability and repeatability of flavor evaluation results, and does not require complicated chemical pretreatment steps, thereby significantly saving costs. The present invention can also be used in the method of judging the flavor of fruit and vegetable juice and fruit and vegetable powder based on color detection in the new product development stage.

[0006] The method for judging the flavor of fruit and vegetable juice and fruit and vegetable powder based on color detection of the present invention comprises the following steps: S1. Sample preparation: Collect samples from different batches and flavors of fruit and vegetable juices, fruit and vegetable powder production lines or finished products. For each batch of samples, ensure that the collection process complies with standardized operations to avoid contamination of samples by external factors. The collection volume must meet the needs of subsequent testing and analysis. The collection volume of each sample is 50-100g; S2. Store the collected samples in an environment with a temperature of 4-10°C to maintain the stability of the samples and prevent unnecessary changes in flavor and color before testing; S3. For the original fruit and vegetable juice, it is directly used for testing. For the concentrated fruit and vegetable juice, it is diluted by 1-10% for standby use. For the fruit and vegetable juice and fruit and vegetable powder products containing a certain amount of pulp, it is diluted by a fixed ratio of 1-10% or dissolved without dilution and filtered; S4. Use a visible light spectrophotometer, select the detection wavelength and detection range to be set at 360-1000nm, the light source is a tungsten halogen lamp, the accuracy can be selected to be ±0.5nm-±2nm, and perform color detection equipment and parameter settings; S5. Place the sample in a standard transparent measuring cuvette with an optical path of 1-5 cm. For spectrum analyzer measurement, ensure that the sample fills the cuvette without bubbles. Measure the absorbance value of each sample in the wavelength range of 400-680 nm, record the absorbance data at different wavelengths, and perform color measurement. S6. Collect a large number of fruit and vegetable juice and fruit and vegetable powder samples with different flavors and known qualified flavor quality, with the number of samples not less than 100, covering the flavors of concentrated red date juice, concentrated hawthorn, and red date powder, measure the color parameters of these samples and establish a database, and train and establish a flavor evaluation model; S7. When testing fruit and vegetable juice or fruit and vegetable powder samples of unknown flavor, input the color measurement data into the trained flavor evaluation model, and the model outputs the corresponding flavor result. The confidence level of the evaluation result is required to reach 70%-90% or more. If the confidence level is lower than this range, it is necessary to re-measure or further analyze the sample. The relationship between color and flavor: Deeply explore the intrinsic relationship between the color and flavor of fruit and vegetable juices and fruit and vegetable powders, and establish an evaluation method based on this, breaking through the limitations of traditional methods that only evaluate flavor from the perspective of taste, smell or a single chemical substance; Selection and calibration of testing equipment: Select a commonly used visible light spectrophotometer in the laboratory and calibrate it to ensure accuracy in measuring color-related parameters, which is a prerequisite for obtaining reliable data; Establishment of flavor evaluation model: Collect a large amount of data of different flavor samples, use support vector machines and neural networks, and establish models with reasonable parameter ranges, accurately map color parameters to flavor categories, and make the model highly accurate and generalizable. At the same time, reasonably divide the ratio of training data and test data to ensure model quality; Determination of parameter range: Appropriate ranges were determined in terms of sample collection volume, storage temperature, precision parameters of measuring equipment, cuvette optical path length and model training-related parameters, as well as confidence in evaluation results. These ranges, which were summarized through multiple experiments, can ensure the stable and effective operation of the entire invention scheme and achieve reliable evaluation of the flavor of fruit and vegetable juice and fruit and vegetable powder.

[0007] Preferably, in S6, the flavor evaluation model is trained and established by using a support vector machine algorithm, the kernel function selects the radial basis function, the parameter C has a value range of 0.1-10, the value range of γ has a value range of 0.01-1, or a neural network algorithm, the number of hidden layer nodes is 5-20, the color parameter is used as input, the flavor category is used as output, the evaluation model is trained, the ratio of training data to test data is 7:3-8:2, and the model parameters are optimized by methods such as cross-validation to ensure the accuracy and generalization ability of the model.

[0008] Preferably, S5 also includes preparations before calibration, first ensuring that the instrument is fault-free and in normal working condition, preheating the instrument for more than 30 minutes before use, and calibrating it in an environment with a temperature of 20°C-25°C, a relative humidity of no more than 85%RH, and a dust-free, vibration-free, and electromagnetic interference-free environment, and then preparing the cuvette and reference material that meet the requirements.

[0009] Preferably, in S5, to ensure that the instrument enters the correct test state, zero calibration, absorbance calibration, linear calibration and repeatability calibration are performed after the instrument changes the test wavelength and tests for a period of time.

[0010] Preferably, the absorbance calibration uses distilled water as the calibration standard substance, which is prepared according to the requirements of the operating manual, and its absorbance value is measured and compared with the standard value, and the error is calculated. If it exceeds the range, adjustment or maintenance is required.

[0011] Preferably, the zero calibration is performed by measuring the photocell against a blank solution and adjusting the photocell to zero according to the absorbance value obtained.

[0012] Preferably, the linear calibration is performed using a series of standard substances of known concentrations, measuring standard samples of different concentrations and drawing a standard curve, and calibrating the relationship between absorbance value and concentration value.

[0013] Preferably, the repeatability calibration uses the same standard sample for multiple measurements, and compares the absorbance value differences, which are within an acceptable range, thereby ensuring the accuracy of the measurement results.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. Accurate and objective flavor evaluation The present invention is based on the intrinsic relationship between the color and flavor of fruit and vegetable juice and fruit and vegetable powder, and uses scientific detection methods and advanced machine learning models to overcome the subjective problem of manual tasting. Compared with traditional manual sensory evaluation, the results are more objective and accurate, providing a reliable basis for the evaluation of the flavor of fruit and vegetable juice and fruit and vegetable powder, and helping to ensure the consistency of product quality. 2. Efficient testing process The detection process mainly focuses on the acquisition of color parameters, without the need for complex chemical pre-treatment steps. Compared with chemical analysis methods, it greatly improves the detection speed and can meet the needs of rapid quality control in large-scale production of fruit and vegetable juice and fruit and vegetable powder. This not only shortens the detection time, but also can promptly feedback problems on the production line, effectively improving production efficiency. 3. Significant cost-effectiveness The present invention does not require the use of expensive chemical analysis instruments such as gas chromatography, mass spectrometry and a large number of chemical reagents, while reducing the dependence on professional chemical analysts, greatly reducing the detection cost, especially for enterprises that produce fruit and vegetable juice and fruit and vegetable powder on a long-term large scale, it can significantly save expenses while ensuring the flavor quality detection; 4. Stable and reliable performance Through a large number of R&D experiments, the parameter range of each link was determined, including sample collection, equipment calibration, and model training. This allows the invention to work stably when facing different batches and varieties of fruit and vegetable juices and fruit and vegetable powders, ensuring the reliability and repeatability of flavor evaluation results. 5. In addition to playing a role in the quality control link in the production process of fruit and vegetable juice and fruit and vegetable powder, the present invention can also be used in the new product development stage. In the new product development, researchers can use the present invention to quickly detect the flavor changes of fruit and vegetable juice and fruit and vegetable powder under different formulas or processes. Since color can reflect flavor, by detecting color and using the model to evaluate flavor, researchers can quickly screen out formulas and process directions that meet the expected flavor. This method can guide the research and development process more efficiently, reduce the number of unnecessary experiments, and speed up the development of new products. At the same time, this color-based flavor evaluation method can help discover some new flavor combination possibilities, because there may be flavors corresponding to certain colors that have not been fully explored in traditional research and development methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of judging the flavor intensity of the concentrated jujube juice according to the absorbance of the present invention. DETAILED DESCRIPTION

[0016] In order to facilitate understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. The present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive. Example 1

[0017] like Figure 1 As shown, the method for judging the flavor of fruit and vegetable juice and fruit and vegetable powder based on color detection of the present invention comprises the following steps: S1. Sample preparation: Collect samples from different batches and flavors of fruit and vegetable juices, fruit and vegetable powder production lines or finished products. For each batch of samples, ensure that the collection process complies with standardized operations to avoid contamination of samples by external factors. The collection volume must meet the needs of subsequent testing and analysis. The collection volume of each sample is 50-100g; S2. Store the collected samples in an environment with a temperature of 4-10°C to maintain the stability of the samples and prevent unnecessary changes in flavor and color before testing; S3. For the original fruit and vegetable juice, it is directly used for testing. For the concentrated fruit and vegetable juice, it is diluted by 1-10% for standby use. For the fruit and vegetable juice and fruit and vegetable powder products containing a certain amount of pulp, it is diluted by a fixed ratio of 1-10% or dissolved without dilution and filtered; S4. Use a visible light spectrophotometer, select the detection wavelength and detection range to be set at 360-1000nm, the light source is a tungsten halogen lamp, the accuracy can be selected to be ±0.5nm-±2nm, and perform color detection equipment and parameter settings; S5. Place the sample in a standard transparent measuring cuvette with an optical path of 1-5 cm. For spectrum analyzer measurement, ensure that the sample fills the cuvette without bubbles. Measure the absorbance value of each sample in the wavelength range of 400-680 nm, record the absorbance data at different wavelengths, and perform color measurement. S6. Collect a large number of fruit and vegetable juice and fruit and vegetable powder samples with different flavors and known qualified flavor quality, with the number of samples not less than 100, covering the flavors of concentrated red date juice, concentrated hawthorn, and red date powder, measure the color parameters of these samples and establish a database, and train and establish a flavor evaluation model; S7. When testing fruit and vegetable juice or fruit and vegetable powder samples of unknown flavor, input the color measurement data into the trained flavor evaluation model, and the model outputs the corresponding flavor result. The confidence level of the evaluation result is required to reach 70%-90% or more. If the confidence level is lower than this range, it is necessary to re-measure or further analyze the sample. The relationship between color and flavor: Deeply explore the intrinsic relationship between the color and flavor of fruit and vegetable juices and fruit and vegetable powders, and establish an evaluation method based on this, breaking through the limitations of traditional methods that only evaluate flavor from the perspective of taste, smell or a single chemical substance; Selection and calibration of testing equipment: Select a commonly used visible light spectrophotometer in the laboratory and calibrate it to ensure accuracy in measuring color-related parameters, which is a prerequisite for obtaining reliable data; Establishment of flavor evaluation model: Collect a large amount of data of different flavor samples, use support vector machines and neural networks, and establish models with reasonable parameter ranges, accurately map color parameters to flavor categories, and make the model highly accurate and generalizable. At the same time, reasonably divide the ratio of training data and test data to ensure model quality; Determination of parameter range: Appropriate ranges were determined in terms of sample collection volume, storage temperature, precision parameters of measuring equipment, cuvette optical path length, model training related parameters, and confidence level of evaluation results. These ranges summarized through multiple experiments can ensure the stable and effective operation of the entire invention scheme and achieve reliable evaluation of the flavor of fruit and vegetable juice and fruit and vegetable powder; In the S6, the flavor evaluation model is trained and established by using a support vector machine algorithm, the kernel function selects a radial basis function, the parameter C has a value range of 0.1-10, the value range of γ has a value range of 0.01-1, or a neural network algorithm, the number of hidden layer nodes is 5-20, the color parameter is used as input, the flavor category is used as output, and the evaluation model is trained, the ratio of training data to test data is 7:3-8:2, and the model parameters are optimized by methods such as cross-validation to ensure the accuracy and generalization ability of the model; The S5 also includes preparations before calibration, first ensuring that the instrument is fault-free and in normal working condition, preheating the instrument for more than 30 minutes before use, and calibrating in an environment with a temperature of 20°C-25°C, a relative humidity of no more than 85%RH, and no dust, vibration, or electromagnetic interference, and then preparing a cuvette and reference material that meet the requirements; In S5, in order to ensure that the instrument enters the correct test state, zero calibration, absorbance calibration, linear calibration and repeatability calibration are performed after the instrument changes the test wavelength and tests for a period of time; The absorbance calibration uses distilled water as the calibration standard substance, which is prepared according to the requirements of the operation manual, and its absorbance value is measured and compared with the standard value, and the error is calculated. If it exceeds the range, it needs to be adjusted or repaired; The zero calibration is to measure the photocell against a blank solution and adjust the zero value according to the absorbance value obtained; The linear calibration is performed using a series of standard substances of known concentrations, measuring standard samples of different concentrations and drawing a standard curve, and calibrating the relationship between absorbance value and concentration value; The repeatability calibration uses the same standard sample for multiple measurements and compares the absorbance value differences, which are within an acceptable range, thereby ensuring the accuracy of the measurement results; In this embodiment, 1. the intrinsic relationship between the color and flavor of fruit and vegetable juice and fruit and vegetable powder is deeply explored, and an evaluation method is established based on this, which breaks through the limitation of traditional methods that evaluate flavor only from the perspective of taste, smell or a single chemical substance; 2. Choose a commonly used visible light spectrophotometer in the laboratory and calibrate it to ensure the accuracy of measuring color-related parameters, which is the prerequisite for obtaining reliable data; 3. Collect a large amount of data on different flavor samples, use support vector machines and neural networks, and establish a model with a reasonable parameter range to accurately map color parameters to flavor categories, so that the model has high accuracy and generalization ability. At the same time, reasonably divide the ratio of training data and test data to ensure model quality; 4. Appropriate ranges have been determined in terms of sample collection volume, storage temperature, precision parameters of measuring equipment, cuvette optical path length and model training-related parameters, as well as confidence in evaluation results. These ranges, which have been summarized through multiple experiments, can ensure the stable and effective operation of the entire invention scheme and achieve reliable evaluation of the flavor of fruit and vegetable juice and fruit and vegetable powder. Example 2

[0018] Based on the embodiments, the method of judging the flavor of fruit and vegetable juice and fruit and vegetable powder based on color detection of the present invention is as follows: S1. Sample collection and preparation: A batch of concentrated jujube juice samples were collected from a fruit and vegetable juice and fruit and vegetable powder production factory. A total of 200 samples were collected, and the collection volume of each sample was 50g. After collection, the samples were immediately stored in a refrigerated environment at 6℃. At the same time, 50 samples of concentrated hawthorn juice and red jujube powder were collected for model training and verification. S2. Color detection: Use a visible light spectrophotometer with a wavelength detection range of 380-780nm and an accuracy of ±2nm. Before measurement, calibrate the visible light spectrophotometer with a standard cuvette of 1cm and distilled water. Dilute the concentrated jujube juice sample at a ratio of 5% and place it in a transparent cuvette with an optical path of 1cm to ensure that there are no bubbles. Use a visible light spectrophotometer to measure the absorbance values ​​of the sample at wavelengths of 420nm, 510nm, 610nm and 660nm. Repeat the measurement twice for each sample and take the average value. S3. Establishing flavor evaluation model: The previously collected data of 200 different batches of concentrated jujube juice and red jujube powder samples with known qualified flavor quality were used to establish a database and model. The color measurement data of the concentrated jujube juice samples collected were input into the trained flavor evaluation model. The model outputs the flavor grade of the corresponding sample accurately with a confidence level of 85%, indicating that the evaluation result is reliable. If the confidence level is lower than this range, the sample needs to be re-measured or further analyzed. The flavor evaluation model is trained and established by using a support vector machine algorithm, with the radial basis function selected as the kernel function, the parameter C in the range of 0.1-10, the γ in the range of 0.01-1, or a neural network algorithm with 5-20 hidden nodes, using the color parameter as input and the flavor category as output, training an evaluation model, with the ratio of training data to test data being 7:3-8:2, and optimizing the model parameters by cross-validation and other methods to ensure the accuracy and generalization ability of the model; In this embodiment, 1. Accuracy In this example, the confidence level of the model in accurately evaluating the concentrated jujube juice was 85%, which shows its advantage of being more objective and accurate than manual tasting. Even though different people have different understandings and perceptions of the flavor intensity of jujubes, this method is not affected by these subjective factors based on color data and model evaluation. 2. Efficiency The entire process from sample collection to flavor evaluation results takes less than an hour, which greatly improves the detection efficiency compared to the complex process of chemical analysis methods that may take several days. For rapid quality control on the production line, product batches with abnormal flavors can be discovered in a timely manner. 3. Cost Only a single visible light spectrophotometer is needed, and the equipment cost is relatively low. Unlike chemical analysis, there is no need to use expensive instruments and a large amount of chemical reagents, which reduces the cost. In addition, the operation is simple, and ordinary technicians can complete the detection process after simple training; 4. Stability In the subsequent detection of concentrated hawthorn juice, red date powder and other fruit and vegetable juices and fruit and vegetable powders, the model also showed stable evaluation capabilities, indicating that the present invention can work reliably in the detection of fruit and vegetable juices and fruit and vegetable powders of different flavor types, ensuring the stability of quality control in the production process.

[0019] The main functions achieved by the present invention are: 1. Overcome the problems of strong subjectivity, low efficiency and susceptibility to individual factors in traditional manual tasting methods, reduce the flavor evaluation errors caused by human differences, and ensure the consistency and reliability of flavor evaluation; 2. Data records can be established while evaluating, which can enhance the retrospective and reproducible nature of the evaluation and avoid deviations in evaluation results due to personnel changes and time alternations; 3. Solve the limitations of chemical analysis methods, such as high cost, complex operation, and inability to fully detect flavors, and avoid complex sample pretreatment processes and reliance on expensive instruments; 4. Make full use of the intrinsic relationship between the color and flavor of fruit and vegetable juices and powders. By testing the color, a relatively easy-to-obtain physical characteristic, the flavor of fruit and vegetable juices and powders can be quickly evaluated to meet the needs of rapid testing in the quality control link during the production of fruit and vegetable juices and powders. At the same time, it helps optimize the formula and process during the product development stage to ensure the stability and improvement of the product flavor quality.

[0020] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for judging the flavor of fruit and vegetable juice and fruit and vegetable powder based on color detection, characterized in that: The following steps are involved: S1. Sample preparation: collect samples from different batches and flavors of fruit and vegetable juice, fruit and vegetable powder production lines or finished products; S2. Store the collected samples in an environment with a temperature of 4-10°C; S3. For the original fruit and vegetable juice, it is directly used for testing. For the concentrated fruit and vegetable juice, it is diluted by 1-10% for standby use. For the fruit and vegetable juice and fruit and vegetable powder products containing a certain amount of pulp, it is diluted by a fixed ratio of 1-10% or dissolved without dilution and filtered; S4. Use a visible light spectrophotometer, select the detection wavelength and detection range to be set at 360-1000nm, the light source is a tungsten halogen lamp, the accuracy can be selected to be ±0.5nm-±2nm, and perform color detection equipment and parameter settings; S5. Place the sample in a standard transparent measuring cuvette with an optical path of 1-5 cm. For spectrum analyzer measurement, ensure that the sample fills the cuvette without bubbles. Measure the absorbance value of each sample in the wavelength range of 400-680 nm, record the absorbance data at different wavelengths, and perform color measurement. S6. Collect a large number of fruit and vegetable juice and fruit and vegetable powder samples with different flavors and known flavor quality, with the number of samples being no less than 100, measure the color parameters of these samples and establish a database, and train and establish a flavor evaluation model; S7. When testing fruit and vegetable juice or fruit and vegetable powder samples of unknown flavor, input the color measurement data into the trained flavor evaluation model. The model outputs the corresponding flavor results. The confidence level of the evaluation results is required to reach 70%-90% or above. If the confidence level is lower than this range, the samples need to be remeasured or further analyzed.

2. The method for judging the flavor of fruit and vegetable juice and fruit and vegetable powder based on color detection according to claim 1, characterized in that: In S6, the flavor evaluation model is trained and established using a support vector machine algorithm, the kernel function selects the radial basis function, the parameter C has a value range of 0.1-10, the value range of γ has a value range of 0.01-1, or a neural network algorithm, the number of hidden layer nodes is 5-20, the color parameter is used as input, and the flavor category is used as output, and the evaluation model is trained, the ratio of training data to test data is 7:3-8:2, and the model parameters are optimized by methods such as cross-validation to ensure the accuracy and generalization ability of the model.

3. The method for judging the flavor of fruit and vegetable juice or fruit and vegetable powder based on color detection according to claim 1, characterized in that: The S5 also includes preparations before calibration. First, ensure that the instrument is fault-free and in normal working condition. Preheat the instrument for more than 30 minutes before use. Calibrate in an environment with a temperature of 20°C-25°C, a relative humidity of no more than 85%RH, and no dust, vibration, or electromagnetic interference. Then prepare the cuvette and reference material that meet the requirements.

4. The method for judging the flavor of fruit and vegetable juice and fruit and vegetable powder based on color detection according to claim 1, characterized in that: In S5, to ensure that the instrument enters the correct test state, zero calibration, absorbance calibration, linear calibration and repeatability calibration are performed after the instrument changes the test wavelength and tests for a period of time.

5. The method for judging the flavor of fruit and vegetable juice and fruit and vegetable powder based on color detection according to claim 4, characterized in that: The absorbance calibration uses distilled water as the calibration standard substance, which is prepared according to the requirements of the operating manual. Its absorbance value is measured and compared with the standard value, and the error is calculated. If it exceeds the range, adjustment or maintenance is required.

6. The method for judging the flavor of fruit and vegetable juice or fruit and vegetable powder based on color detection according to claim 4, characterized in that: The zero calibration is performed by measuring the photocell against a blank solution and adjusting the photocell to zero based on the absorbance value obtained.

7. The method for judging the flavor of fruit and vegetable juice or fruit and vegetable powder based on color detection according to claim 4, characterized in that: The linear calibration is performed using a series of standard substances with known concentrations, measuring standard samples of different concentrations and drawing a standard curve, and calibrating the relationship between absorbance value and concentration value.

8. The method for judging the flavor of fruit and vegetable juice or fruit and vegetable powder based on color detection according to claim 4, characterized in that: The repeatability calibration uses the same standard sample for multiple measurements, and compares the absorbance value differences. The differences are within an acceptable range, thereby ensuring the accuracy of the measurement results.

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