CHNSpec Technology （Zhejiang）Co.,Ltd Company News

In the milk industry, the color of milk is an important quality indicator, which reflects the composition, freshness and processing of milk, and is of great significance for evaluating the quality and safety of milk. For example, excessive heat treatment or oxidation may lead to yellow milk color, which is usually undesirable, so strict quality control of milk color is required to ensure that it complies with relevant standards and regulations, while traditional color evaluation methods may be affected by human factors, ambient light or observer subjectivity, leading to large deviations in evaluation. However, the desktop spectrophotometer can accurately quantify the color difference by measuring the spectral distribution of the reflection or transmission of the sample and converting it into objective color parameters, such as Lab values. This paper introduces a method of measuring the color difference of milk by using a desktop spectrophotometer.   The working principle of desktop spectrophotometer A desktop spectrophotometer is an instrument that evaluates the color of an object by measuring the reflected or transmitted light of the color. It splits the light reflected by the object into different wavelengths of monochromatic light and measures the intensity of light at each wavelength. By measuring the color of the object and the target color, the desktop spectrophotometer can calculate the color difference between the two, and then judge the quality of milk.   Measurement procedure 一、Prepare materials (1) Color spectrum desktop spectrophotometer CS-821N (2) Standard milk sample (3) Milk sample to be tested (4) Colorimetric dishes Among them, the desktop spectrophotometer CS-821N is the main instrument used to measure the color of milk, and the circular colorimetric dish is the instrument used to hold milk samples.   二、Sample preparation (1) Pour the milk into the cupola (make sure that the milk is poured into more than 3/4 of the cupola volume)   三、Sample measurement (1) Turn on the desktop spectrophotometer CS-821N (2) Set parameters: Select reflection measurement mode, D65 light source, 10° observer Angle, etc (3) Perform black and white calibration in reflection measurement mode (4) Erect CS-821N so that the test port is measured upward (5) Place the colorimetric dish poured into the standard milk on the test port to ensure that it completely covers the test port (6) Press the measurement key and wait for the instrument to complete the measurement and display the result   (7) Record the measurement results (8) Clean the comparator and instrument to prepare for the next measurement   四、Result analysis This experiment can evaluate the color difference of the sample to be tested by comparing the color difference between the sample to be tested and the standard sample. This approach can help milk producers ensure product quality and improve the consumer experience. At the same time, in the new product development stage, color adjustment and optimization is a key step. By using benchtop spectrophotometers, researchers can precisely measure and adjust the color of new products to meet market and consumer expectations.  

一、 Introduction It is an important work to test ore whiteness classification in open pit mine, which has a decisive influence on the effective utilization and fine processing of mineral resources. Traditional detection methods mainly rely on manual operation, which is not only inefficient, but also susceptible to subjective factors. Therefore, it is very important to adopt advanced detection technology to improve the accuracy and efficiency of ore whiteness classification detection. This paper introduces the application of color spectrum hyperspectral camera in the detection of whiteness classification of ores in open pit mines.   二、Background The customer needs to test the whiteness of mine ore in a large area, but the detection efficiency by manual or hand-held whiteness meter is low, and a more efficient detection method is urgently needed. A 400-1000nm hyperspectral camera was used for this classification detection, and FS13, a product of Color Spectrum Technology (Zhejiang) Co., LTD., was used for related research. The spectral range is 400-1000nm, the wavelength resolution is better than 2.5nm, and up to 1200 spectral channels can be reached. The acquisition speed can reach 128FPS in the full spectrum, and the maximum after band selection is 3300Hz (support multi-region band selection).     三、 Laboratory testing The reflectance of calcium carbonate with different whiteness at 400-1000nm was obtained after the four ores were placed on the transmission platform and tested with FS-13.     It can be seen from Figure 4 that the primary whiteness and secondary whiteness are similar. According to the overall waveform, the primary and secondary whiteness can be classified into one category, and the tertiary and quaternary distinctions are obvious. The four-stage whiteness slope is high, the three-stage whiteness slope is low, and the overall difference with the first-stage and second-stage is large, and it is easy to distinguish.   四、On-site detection Shooting time: 15:00, November 07, 2023   Figure 5   Figure 5 shows the hyperspectral camera FS-23 set up on site and the bench for detection.   Figure 6   Technicians selected a piece of calcium carbonate with second-grade whiteness in FIG. 6 and photographed it about 50m away. After modeling, the band curve was calibrated to invert the ore in the figure.   Figure 7   FIG. 7 shows the field shooting map of secondary calcium carbonate calibration at 20m and the inversion effect map.   Figure 8   FIG. 8 shows the field shooting map of primary calcium carbonate calibration at 20m and the inversion effect map.   Figure 9   FIG. 9 shows the field shooting map of primary calcium carbonate calibration at 50m and the inversion effect map.   Figure 10   As shown in Figure 10, after the parameter value (similarity threshold value) is adjusted from 0.993 to 0.99 at 50m, the proportion of primary calcium carbonate in similar bands after reverse selection is greatly increased.   Figure 11   Figure 12   In FIG. 11 and FIG. 12, an adjustment threshold with whiteness of secondary calcium carbonate is selected 50m away for inversion effect.   五、Conclusion 1. Laboratory testing The 400-1000nm hyperspectral camera FS-13+ platform can be used to detect the whiteness classification of calcium carbonate, which is completely feasible in terms of identification feasibility. At the same time, it is found that the reflectance difference between primary whiteness and secondary whiteness is very small, and only two small differences are found, as shown in the following figure:     2. On-site inspection The portable hyperspectral camera FS-23 can be used to shoot the field situation and invert the specific position, mainly inverting the primary and secondary calcium carbonate. When the model threshold is adjusted, the accuracy is gradually improved, so the primary and secondary whiteness of this area can be inverted to the general area. The disadvantage is that only a single model is used, and the accuracy still has great room for improvement.   3. Uav hyperspectral detection If it is necessary to detect the whiteness level of calcium carbonate in a large area and efficiently in the future, the UAV-based hyperspectral measurement system can be used for detection. The UAV-based hyperspectral measurement system has the characteristics of high efficiency and low power consumption, and can provide high stability spectral image acquisition.     The application of color spectrum hyperspectral camera in the whiteness classification of ores in open pit has achieved some success. Through the acquisition and analysis of the hyperspectral data of color spectrum, the accurate detection of ore whiteness is realized, the accuracy and efficiency of detection are improved, and the error of manual operation is reduced. It is believed that in the future, with the further development of technology, color spectrum hyperspectral cameras will also play a greater role in the field of whiteness classification detection of open-pit ores, and provide more powerful technical support for the effective use of mineral resources and fine processing.

一、 Background   In the face of challenges such as food shortages, population growth and climate change, increasing crop yields is an urgent need. Crop phenotype analysis provides valuable information for improving yield by deeply understanding the relationship between crop growth and environment.   二、Problems with traditional methods: The traditional vehicle-mounted platform has some problems in sample testing and crop character parameter determination, such as time and effort, limited space coverage, etc., which limits the development of crop science research.   三、the application of UAV hyperspectral remote sensing in the field of agriculture Color Spectrum Technology's unmanned Hyperspectral Measurement System (FS-60) provides an efficient and accurate solution for crop phenotyping.   Here are the key features and applications of the technology: 1. Uav Hyperspectral Measurement System (FS-60) : FS-60 of color spectrum technology is a high-throughput near-earth remote sensing phenotype platform, which has high flexibility, low cost and wide spatial coverage, and becomes an effective way to obtain field phenotype information.   2. System composition and characteristics: Dji M350RTK is adopted as the flight bearing platform. Ultra-high-speed spectral scanning imaging devices with high signal-to-noise ratio provide highly stable spectral image acquisition.   Self-developed high-efficiency and low-power image processing algorithm, which prolongs the flight time of the whole machine and reduces the power consumption of the system. Operating wavelength range of 400 to 1000nm with high spectral and spatial resolution, high sensitivity and high signal-to-noise ratio.     3. Application scenario The system can measure the spectral image information of plants, water bodies, soil and other ground objects in real time, which is widely used in precision agriculture, crop growth and yield assessment, forest pest monitoring and fire prevention monitoring, coastline and Marine environment monitoring, lake and watershed environmental monitoring and other fields.   4. Crop phenotype analysis The normalized vegetation index (NDVI) and plant Aging Reflex index (PSRI) can be evaluated by collecting spectral data of wheat at different periods. These indicators can be used to judge crop nitrogen requirements, guide fertilizer application and determine harvest time.   四、Value and application Prospect: Uav hyperspectral measurement system has high value and broad application prospect in agricultural production. Its high spectral resolution helps to detect pests and diseases early and monitor their evolution on crops, providing strong support for the protection and prediction of crop growth. Through the use of color spectrum technology UAV hyperspectral measurement system, agricultural researchers can be more comprehensive, more in-depth understanding of crop growth conditions, providing powerful tools and data support for scientific decision-making in agricultural production.

一、Introduction A Haze meter is an instrument widely used in industrial production and laboratory research to measure the Haze and transmittance of transparent or translucent materials. The GB/T 2410-2008 standard provides detailed specifications for the design, performance and testing of such instruments. In this article, we will introduce three different models of fog meters that meet this standard.   二、Haze meter model introduction   1. Color Haze meter CS-700   Wavelength range: 400-700nm Meets the ASTM&ISO double standard Lighting source: halogen tungsten lamp Has the industry's comprehensive measurement function: fog, spectral transmittance, total transmittance, transmission chroma Lab value, yellowness, whiteness, Gardner, platinum cobalt color and other dozens of color parameters Provide A, C, D65 kinds of measurement light source selection, provide 24 kinds of measurement light source for color measurement can achieve compensation measurement of transmittance, providing more accurate transmittance test results Provides powerful fog, color, transmittance measurement and analysis software, which can be operated on the computer and print test reports 7 inch Android operating system, touch screen touch, to achieve more convenient operation, more smooth experience Open sample compartment, you can free the limit of sample size, you can make horizontal or vertical measurements according to different samples. Provide a wealth of fixture accessories to meet the measurement needs of different forms of sheet and liquid samples   2. Haze meter TH-100 Vertical optical path design, can facilitate the sample directly placed measurement, no extra fixture Meet the ASTM&ISO double standard haze transmittance measurement Lighting source: LED lamp Has an open measuring area that can be used to measure samples of any size Unique signal processing technology to ensure that the measurement results are not interfered by external ambient light No need to warm up, the test time is only 1.5 seconds   3. Hand Haze meter DH-12 Small size, portable Lighting source: LED lamp Lithium battery powered, mobile measurement Support a variety of caliber switching, magnetic replacement is more convenient Support the connection of mobile phone small programs to achieve data cloud storage Support the connection of computer QC software, export professional data reports   三、Conclusion All three fog gauges comply with GB/T 2410-2008 and offer unique advantages in terms of detection range, ease of operation, and customization options. In the selection of the appropriate fog timing, users can consider these characteristics according to the specific needs and application scenarios to ensure the accuracy and stability of the measurement. If you need to know more about color spectrum fog meter products, please visit the official website of Color Spectrum Technology.

In packaging printing, color management is crucial in packaging printing. It helps maintain brand image, attract consumers, control quality, ensure color accuracy, improve production efficiency, and coordinate all aspects of the supply chain. Color management work must not be without the use of color difference meter, that color difference meter in packaging and printing can play what role?   1. Color measurement and analysis: DS-220 color difference meter can accurately measure the color of packaging printed matter and provide numerical representation of color. It is capable of analyzing the Lab* value, RGB value, or other parameters of the color space to help determine the accurate characteristics of the color.   2. Color comparison and matching: By comparing the measured color with the standard color, the DS-220 color difference meter can assess how well the print matches the intended color. It can provide a color difference value (Delta E), indicating the degree of color difference, to help determine whether the quality standard is met.   3. Quality control: In the process of packaging printing, DS-200 color difference meter can monitor the consistency of color in real time. It can detect the color difference between prints produced in different batches, different presses or different times to ensure the color quality of the product is stable.   4. Color adjustment and calibration: According to the color data provided by the color difference meter, the operator can adjust and calibrate the color. It can help optimize factors such as ink ratio, printing pressure, paper selection in the printing process to achieve more accurate color reproduction.   5. Supply chain color management: In the packaging and printing supply chain, different suppliers may be involved in materials, printing and processing. The DS-220 colorimeter ensures color consistency across all links, reducing color issues due to supply chain differences.   6. Quick decision and communication: The color difference meter provides objective color data and measurement results, which can help decision makers make quick judgments about color quality. It also facilitates effective communication with customers, designers and suppliers, ensuring that color requirements are accurately understood and met.   When using the DS-220 color difference meter for color measurement, in addition to seeing whether there is a color difference between the measured color and the standard color, it can also provide guidance on color bias, which is very useful to help customers better color mixing. The color deviation guide in the measurement results of the DS-220 color difference meter (as shown in the figure below) means that the instrument can indicate the direction of the difference in color parameters between the measured color and the standard color. Through the measurement of the DS-220 color difference meter, customers can obtain specific information about color bias, such as red, green, yellow, etc. This color bias guide is very helpful for customers in the color mixing process. It can help customers more accurately understand the gap between the color they are using and the target color, and the direction of adjustments that need to be made. Customers can adjust the amount of pigments, dyes or other toning materials according to the guidance provided by the DS-220 color difference meter to achieve more accurate color matching.   In summary, the color bias guidelines in the results of the DS-220 color difference meter provide customers with valuable information to help them better understand the color differences and adjust the color accordingly to achieve the desired color goals.  

As an advanced spectral imaging technology, hyperspectral camera has shown wide application potential in the field of industrial sorting. It can obtain the high-resolution spectral information of objects, and through the analysis and processing of these spectral data, it can realize the rapid and accurate sorting of different materials. The following will introduce several application cases of hyperspectral cameras in industrial sorting.   Case 1: Pest monitoring As an advanced monitoring technology, hyperspectral camera can realize rapid and accurate monitoring of pests and diseases by obtaining spectral information of crops. It has the advantages of lossless, real-time, fast, high precision and so on. When using hyperspectral camera for pest monitoring, just point the camera at the crop to quickly obtain spectral information of the crop. These spectral information can reflect the health status of the crop, and through the analysis of this information, it can accurately determine whether the crop is affected by pests and diseases. Hyperspectral cameras can not only monitor the occurrence of diseases and pests, but also monitor the development trend of diseases and pests in real time, and provide timely early warning and control measures for agricultural production. At the same time, the hyperspectral camera can also realize the monitoring of large areas of crops, improve the monitoring efficiency and accuracy.     Case 2: Mine exploration During the exploration, a hyperspectral camera was used for geological analysis. By hyperspectral imaging of the rock and soil in the mining area, the camera captures a wealth of spectral information. This information helped geologists accurately identify different types of mineral deposits, including copper and iron. In addition, the hyperspectral camera was able to detect subtle changes in the veins, providing important clues for further exploration work. In practice, hyperspectral cameras not only improve the efficiency and accuracy of exploration, but also reduce costs and risks. Compared to traditional exploration methods, it can acquire large amounts of data more quickly and can monitor multiple areas in a shorter period of time. This enables mines to better plan mining operations, improve resource utilization, and achieve sustainable development.   This case demonstrates the practical application and remarkable results of hyperspectral cameras in mine exploration. It provides strong support for the scientific decision-making and resource management of the mine, and helps to improve the success rate and economic benefit of exploration.   Case 3: Plastic waste sorting With the widespread use of plastic products, the sorting and recycling of plastic waste becomes more and more important. Hyperspectral cameras can be used for sorting plastic waste, sorting and recycling different types of plastic. The spectral characteristics of plastics are related to their material and composition, for example, polyethylene (PE), polypropylene (PP) and polyvinyl chloride (PVC) and other plastics have different spectral characteristics. Through the detection of the hyperspectral camera, different types of plastic waste can be distinguished to achieve accurate sorting and recycling. In the plastic waste sorting process, the hyperspectral camera can quickly obtain the spectral image of the waste, and identify the type of plastic through algorithmic analysis. This helps to improve the efficiency and quality of plastic recycling, reduce environmental pollution, and promote sustainable development.   Case 4: River water quality monitoring Hyperspectral camera plays an important role in river water quality monitoring. It can obtain spectral information of water quickly and accurately, so as to analyze water quality parameters.   Through the images taken by the hyperspectral camera, the content of organic matter and inorganic matter in the water can be detected, as well as dissolved oxygen, turbidity and other indicators. This provides a reliable basis for assessing river water quality. For example, in a river monitoring project, the hyperspectral camera successfully identified pollutants in the water body and accurately judged their distribution. This will help take timely treatment measures to ensure the ecological health of water bodies.   Hyperspectral cameras have the advantage of non-contact monitoring, which can realize large-scale, real-time water quality monitoring. It provides strong technical support for river management and environmental protection.   To sum up, the application cases of hyperspectral cameras in the field of industrial sorting are diverse. It provides an efficient and accurate method for sorting agricultural products, minerals, plastics, textiles and chemical materials. By utilizing the technical advantages of hyperspectral cameras, industrial enterprises can improve production efficiency, reduce costs, improve product quality, and achieve rational use of resources and environmental protection. With the continuous development and innovation of technology, the application prospect of hyperspectral cameras in the field of industrial sorting will be broader, bringing new opportunities and challenges to the development of industrial automation and intelligence.

  Device name Model number Configuration details Remark Imaging hyperspectral camera FS-23 Spectral range: 400-1000nm; Spectral resolution: 2.5nm   Auxiliary equipment Dedicated tripod       1. Experimental content A 400-1000nm hyperspectral camera was used to study the phenotype of tea plants   The experimental measurement process is shown in the figure below:     2. Experimental results In the process of tea growth, the spectral characteristics of the light and backlight sides are very obvious, including the analysis of NDVI index, anthocyanins (1/R(550))-(1/R(700))... Through spectral analysis, further analysis, whether it is necessary to water, fertilize and so on.     3. Conclusion Through the test of hyperspectral camera, the spectral characteristics are obvious, which plays a certain scientific basis for the study of tea growth, disease and pest stress, water and fertilizer deficiency.    

Introduction   Spectral reflectance is an index of the wavelength distribution of the reflected sunlight of an object, which is affected by the spectral absorption characteristics of the object itself, the surface structure, the degree of smoothness and the ambient light conditions. Hyperspectral imaging technology, as an advanced detection method, uses dispersive elements (such as grating or prism) to divide the incident light, and imagines the object on the detector through the imaging system, so as to realize the high-precision analysis of the object.   In this report, we will introduce the principle of hyperspectral imaging technology in detail, and verify the application effect of this technology in detecting the presence of acid solution on gauze through experimental tests. During the experiment, we will use the hyperspectral camera to detect the spectral reflectance of the gauze coated with acid solution and the blank control gauze, and analyze the experimental results. It is hoped that this report can provide useful reference for the research and application in related fields.   1. Spectral reflectance Spectral reflectance refers to the wavelength distribution of sunlight reflected by an object, which is related to the spectral absorption characteristics of the object, the surface structure of the object, the smoothness of the object and the environmental lighting conditions.   2. Hyperspectral imaging principle Dispersive hyperspectral camera - Grating Dispersive type: The use of dispersive elements (grating or prism) to light, and then through the imaging system image on the detector. The above picture shows the specific principle of a raster dispersive hyperspectral camera.   If we want to measure the hyperspectral data of each point of the leaf in the figure, the incident light is reflected on the grating plane, the incident light of this point is decomposed into the energy distribution at different wavelengths, and then the energy at different wavelengths is measured by multiple sensor pixels. What this picture shows is that you need a reflection grating or a transmission grating to split the light.   The advantage of this approach is that you can deal with all the points on a line at once. The energy at each point at a different wavelength can then be measured once. Therefore, most raster type hyperspectral cameras are designed as line scanning cameras. Get spectral data for all wavelengths at each point on a line at a time. Since the spectral data at different wavelengths of each point are obtained at the same time, the spectral data at different wavelengths of this point can be calculated simultaneously. This is a very important feature of the raster type. Raster hyperspectral cameras are particularly suitable for color measurement, fruit classification and quality, sugar content detection, and plastic classification in plastic waste recycling, because these applications require simultaneous computation of different wavelength data at each point in order to calculate the results we want.   3. Experimental testing   3.1 Experimental purpose Test the fabric for acid solution.   3.2 List of experimental test instruments Device name Model number Configuration details remark Hyperspectral camera FS-17 Spectral range: 900-1700nm; Spectral resolution: 8nm   Test bench FS-826 Measuring platform 10*15cm   Material reagent: hypochlorous acid solution, gauze   3.3 Experimental content Hypochlorous acid was applied to one of the two pieces of gauze and marked, and the other was used as a blank control. The spectral reflectance of acid-free and acid-free regions on the gauze was measured.   The experimental measurement process of whether the gauze contains acid is shown in the figure below：   3.4 Experimental Results Through 900-1700nm near-infrared spectral image can be directly observed whether there is an acid solution on the surface of the object   4. Conclusion Through the above two sets of sampling test results, 900-1700nm can feedback whether there is an acid solution, and can detect whether there is an acid solution on the cloth through near-infrared spectroscopy.  

When choosing a measuring instrument suitable for PVC silicone color matching, the following key factors need to be considered: 1. Accuracy and accuracy: The accuracy and accuracy of the measuring instrument are very important for color matching. Choose an instrument that provides accurate color measurement data to ensure accurate evaluation of color differences and match.   2. Spectral resolution: Higher spectral resolution can more accurately analyze the spectral characteristics of colors, helping to identify and distinguish subtle color differences.   3. Measurement mode: Common measurement modes include reflection and transmission. According to the sample characteristics of PVC silica gel, the appropriate measurement mode is selected to obtain accurate color data.   4. Compatibility and scalability: Make sure the measuring instrument is compatible with your existing workflows and software systems, and is scalable for integration with other devices or software.   5. Brand and reputation: Choose well-known brands and reputable measuring instrument suppliers, who are usually able to provide reliable products and technical support.   6. User friendliness: Simple operation and easy to use measuring instruments can improve work efficiency and reduce the possibility of misoperation.   7. Price and budget: Consider the price of the measuring instrument, and choose the right equipment according to the budget. At the same time, it is necessary to balance the relationship between price and performance.   Before choosing a measuring instrument, it is best to understand the characteristics of different brands and models, and refer to the evaluation and experience of other users. In addition, it is also important to communicate with suppliers to understand their product advantages and after-sales service. If possible, try out or rent some instruments for actual testing to determine the best measuring instrument for your needs. Color spectrum technology is the leading domestic color detection equipment manufacturer, product performance is excellent, price is generous, if you want to know more information, you can go to the color spectrum technology website to consult the corresponding technical personnel contact.

Hyperspectral imaging technology is a cutting-edge technology that combines imaging technology and spectrum technology, and its principle is mainly based on the spectral absorption and reflection characteristics of objects. When light hits the surface of an object, light waves of different wavelengths are absorbed or reflected by the object, forming specific spectral features. Hyperspectral imaging system can obtain spectral information of objects in different bands by continuously measuring the spectrum of multiple bands. These spectral data are further used to reveal the detailed information of the chemical composition and physical characteristics of the object through spectral demixing and feature extraction.   一. Overview of hyperspectral imaging technology Hyperspectral imaging is an advanced method that combines imaging and spectroscopy. It performs spectral analysis and imaging in near-infrared, infrared and visible wavelengths. By obtaining spectral information of objects in different bands, hyperspectral imaging technology can quickly identify and quantitatively analyze objects. This technique has the advantages of high spatial resolution, high spectral resolution and high sensitivity. 二.the research status of hyperspectral imaging in the field of cultural relics In recent years, in the field of cultural relics, hyperspectral imaging technology can detect the damage, weathering or corrosion of cultural relics, and provide strong support for the protection and restoration of cultural relics. At the same time, the technology can also reveal hidden information in cultural relics, such as colors and patterns in ancient murals and painting and calligraphy relics, helping researchers gain a deeper understanding of history and culture. In June 2015, researchers successfully authenticated the authenticity of Thangka using hyperspectral technology, which was broadcast in the documentary "The Adventures of Thangka" by Beijing TV Station. In the third episode of the documentary "I repair cultural Relics in the Forbidden City" broadcast by CCTV-9 in January 2016, it was mentioned that researchers of the Chinese Academy of Sciences used hyperspectral remote sensing technology to provide important technical support for the restoration of calligraphy and painting cultural relics in the Forbidden City.   三. Experimental instruments and data 1. Use instrument: Color spectrum FS-IQ Hyperspectral camera 2. Use light source: halogen light source 3. Shooting effect False color pictures at different wavelengths 4. The software can be used to observe the tiny details and changes on the surface of cultural relics in detail, and can be used for visual enhancement, hidden information mining, protection monitoring, pigment analysis, etc., which helps researchers to identify the characteristics of cultural relics more accurately.   四.the advantages of hyperspectral imaging in cultural relics detection First of all, hyperspectral imaging technology is non-invasive and non-destructive. This characteristic allows it to be scanned and analyzed without touching the artifacts, minimizing the risk of damage to the artifacts. Through the non-contact detection method, hyperspectral imaging can ensure the safety and integrity of cultural relics, avoiding any form of damage during the detection process. Secondly, hyperspectral imaging technology can provide rich spectral information. By capturing the reflection and scattering of light waves of different wavelengths on the surface of cultural relics, hyperspectral imaging can obtain detailed information such as material composition, structure and color of the surface of cultural relics. This information helps researchers to have a deeper understanding of the material, production process and historical background of cultural relics, and provides an important reference for the identification and protection of cultural relics.   In addition, hyperspectral imaging technology has the characteristics of high spatial resolution and high spectral resolution. This means it is able to pick up minute details and changes on the surface of artifacts and accurately distinguish spectral differences between different substances. This helps researchers to more accurately identify the characteristics of cultural relics, discover potential damage and diseases, and provide a scientific basis for the restoration and protection of cultural relics. Finally, hyperspectral imaging technology also has fast and efficient detection capabilities. Through high-speed scanning and data processing, hyperspectral imaging can obtain a large amount of cultural relic information in a short time, which greatly improves the detection efficiency. This allows researchers to understand the condition of cultural relics more quickly, and take corresponding protection measures in time to avoid further damage to cultural relics.   To sum up, hyperspectral imaging has significant advantages in the detection of cultural relics, including non-invasive and non-destructive, rich spectral information, high spatial resolution and high spectral resolution, and fast and efficient detection capabilities. These advantages make hyperspectral imaging an important tool in the field of cultural relics detection, which provides strong support for the protection and research of cultural relics.

In this study, a 400-1000nm hyperspectral camera can be used, and the products of Hangzhou Color Spectrum Technology Co., LTD FS13 conducts related research. The spectral range is 400-1000nm, and the wavelength resolution is better than 2.5nm, up to 1200 Two spectral channels. Acquisition speed up to 128FPS in the full spectrum, up to 3300Hz after band selection (multi-zone support Domain band selection). The quality of beef is usually graded according to its marbling, physiological ripeness, muscle color and fat color. Among them, the richness of marbling is the most important evaluation index. With the development of computer and image processing technology, machine vision has been widely studied and applied in beef marbling image segmentation, feature extraction and automatic grade determination. In the automatic determination of beef marbling grade by using machine vision technology, accurate segmentation of marbling is the basis of automatic determination of beef grade. Although a large number of beef image algorithms have been proposed, the problem of inaccurate segmentation of marbling still exists due to the light source, water reflection on the sample surface and other reasons. At present, hyperspectral image technology has been used in many research fields, and there have been extensive research reports in the detection of agricultural products, but the research of beef marbling segmentation by hyperspectral image and spectral information technology has not been reported. In this paper, by mining and analyzing the spectral information of fat and muscle in beef hyperspectral images, the optimal band image suitable for beef marbling segmentation was extracted, and then the marbling segmentation was carried out by Otsu automatic threshold method, and the segmentation accuracy was compared and analyzed. In different bands, the spectral reflection intensity of fat region and muscle region in beef hyperspectral images is obviously different. The ratio of spectral reflection intensity between fat region and muscle region is mainly concentrated in the band of 465 ~ 580 nm. At the wavelength of 534 nm, the ratio of spectral reflection intensity between the fat region and the muscle region has the maximum value. The same image processing method was used for marbling segmentation of beef color original image and 534nm feature wavelength image. The marbling segmentation accuracy η=0.928 for feature wavelength image is closer to 1 than the original image, and the mean square error is also smaller. Therefore, compared with the original image, marbling segmentation of beef characteristic wavelength image can obtain higher segmentation accuracy.

In this study, a 900-1700nm hyperspectral camera was applied, and FS-15, the product of Hangzhou Color Spectrum Technology Co., LTD., could be used for related research. Short-wave near-infrared hyperspectral camera, the acquisition speed of the full spectrum up to 200FPS, is widely used in the composition identification, substance identification, machine vision, agricultural product quality, screen detection and other fields. Maple scoop is the initial processing product of medicinal Dendrobium. The production process is to cut off some of the roots of the fresh stem of Dendrobium, heat it while twisting it into a spiral shape or spring shape, and dry it into a concave. Maple bucket is a famous tonic in our country, mainly including tin maple bucket and purple maple bucket and other types. Among them, tin maple bucket with its good Yin and blood, throat protection effect, has become a kind of high-end health tonic, in East China, South China, especially in Hong Kong, Taiwan, foreign countries in Japan, Southeast Asia, is generally considered to be a high-grade health care products, the market demand is large. Dendrobium officinale is the only source of processing dendrobium officinale collected in China's pharmacopeia, the wild resources are very limited, although there is a certain scale of cultivation, but can not meet the current market demand, so the price is expensive, but also caused a lot of other dendrobium processing of Dendrobium officinale confused products. Such as dendrobium hairpin, dendrobium dentate (commonly known as purple skin Dendrobium) and other raw materials processing of the so-called "iron maple bucket". The medicinal value of Dendrobium officinale from different sources is very different, which seriously affects the stability of commodity quality, but also damages the rights of consumers, so it is very meaningful to establish an effective identification method for Dendrobium officinale. In addition, the price and medicinal value of Dendrobium officinale of different origin vary greatly. In the face of such a chaotic market, it is very necessary to study a rapid identification technology for Dendrobium officinale origin. In this paper, the identification of three easily confused Dendrobium species was studied by using a miniature near infrared spectrometer, and an Internet of Things identification system for Dendrobium was constructed. (1) This study investigated the influence of different sample sizes on NIR spectra and the establishment and evaluation of SIMCA models of different sample sizes. The results showed that with the increase of sample size, the larger the sample reflectance spectrum (log1/R), the higher the absorption intensity, and the NIR absorption intensity was positively correlated with the sample particle size. The model established by 80-eye spectrum is better than the model established by 40-eye and 60-eye spectrum. (2) The near infrared diffuse reflectance spectra of intact and crushed maple bucket samples were quickly identified by SIMCA modeling. The results showed that after different pretreatment methods: The best preprocessing method for the complete sample spectrum is NAS plus S-G smoothing plus 1 order S-G derivative, and the best preprocessing method for the crushed sample spectrum is S-G smoothing plus 1 order S-G derivative plus mean centralization. The correct recognition rate and rejection rate of the models established for both the complete sample and the crushed sample are 100%, and the prediction stability and accuracy are high. Can realize the rapid identification of three kinds of maple bucket, more suitable for practical application. (3) Using the best model built by the spectra of Fengdou complete samples and crushed samples to identify other samples, the results show that the rejection rate of all models is 100%, and the reliability of the model is good.