39 results about "Near infrared reflectance spectroscopy" patented technology

The invention discloses a method for rapid detection and authenticity identification of fatty acid of racy camellia oil by near infrared transmission spectroscopy (NITS). The method comprises the steps of: screening high quality varieties with oil content of 30%-60% from more than 130 camellia seed varieties, wherein in the camellia oil, the content of oleinic acid is 65%-85%, the content of linoleic acid is 5%-20%, the content of palmitic acid is 3%-15%, and the content of stearic acid is 1%-5%; establishing a near infrared transmission spectroscopy (NITS) model of the main fatty acids (oleinic acid, linoleic acid, palmitic acid, stearic acid and total unsaturated fatty acid) with a partial least squares (PLS) method by adopting the Fourier near infrared transmission spectroscopy (NITS), wherein the determination coefficients of the correction models of the oleinic acid, the linoleic acid and the palmitic acid respectively are 0.93446, 0.96538 and 0.88789, and the determination coefficients of cross validation respectively are 0.91987, 0.95755 and 0.84447; further verifying accuracy and reliability of five NIRS (Near Infrared Reflectance Spectroscopy) models by external verification so as to obtain related coefficients of the external verification, which respectively are 0.9424, 0.9682, 0.8862, 0.6834 and 0.7587; and evaluating doped camellia oil by establishing the NIRS model of binary system miscella of the camellia oil. The method is applicable to rapid measurement of the content of main fatty acids of the camellia oil and the doped camellia oil, has the characteristics of simplicity, convenience, rapidness and economy, and is suitable for industrial application.

A method and system for predicting the content level of components in materials based on the response of the materials to near infrared radiation. One embodiment comprises electronically receiving a near infrared reflectance spectrum of a material from a customer, predicting the content level of a component in the material based on the spectrum, and electronically reporting the prediction to the customer. Another embodiment includes the exchange of the customer request and prediction report on a Web site or by electronic mail. Other embodiments include the prediction reports, and uses of the predictions, for example in quality control and toxicity evaluation.

The invention discloses a model for determining content of liquid detergent in hogwash oil by combining LS-SVM (least squares-support vector machine) with siPLS (synergy interval partial least squares) based on a near infrared reflectance spectroscopy. The method comprises the steps of: firstly, carrying out pretreatment on collected oil spectrum by adopting a method of combining multiplicative scatter correction treatment with Karl Norris smooth treatment to remove the effect of an interference factor; then screening 548 spectroscopic data which have large correlation with the content of the liquid detergent in the hogwash oil by utilizing the siPLS method, and building a regression prediction model by utilizing the LS-SVM, wherein the selected regularization parameter C is 34.26, and the core parameter rho2 is 11.84; selecting front 10 main ingredients as input variables by applying a main ingredient analysis method; making out a relevant figure line; providing the judgment result whether the oil is the hogwash oil.

The invention discloses an automatic monitoring system of greenhouse crop growth conditions based on a reflection spectrum, comprises a first screw rod, a second screw rod and a third screw rod, wherein a sliding block with a threaded hole is respectively sleeved on the three screw rods, and the movement of any points in the three-dimensional space can be realized by a stepping motor; and a camera and a reflection probe are arranged on one screw rod, and a near-infrared light source, a spectrometer, an industrial personal computer and a relay are arranged on another screw rod. The monitoring system is capable of automatically adjusting the space position of the reflection probe by combining the reflectance spectrum and image information under the control of a remote computer and calculating a plurality of indexes, such as leaf area index, water content, chlorophyll content, and the like on the basis of the visible / near-infrared reflectance spectrum, thereby analyzing the growth conditions of crops and providing the reference for growth management of the crops. The whole system has simple structure, low cost and high automation level and realizes the aims of fast and dynamically monitoring the growth conditions of the crops in loss-free, all-sided and multi-index forms.

The invention discloses a plastic identification apparatus and a method based on near-infrared spectroscopy analysis. The plastic identification apparatus comprises a light source unit, a sample acquisition unit, a detection unit and a circuit control unit. The light source unit is used for providing a light source; the sample acquisition unit is used for collecting the reflected light of a to-be-identified sample and sending to the detection unit; the detection unit is used for performing light splitting on the reflected light and then transferring to a photoelectric current signal and then sending the photoelectric current signal to the circuit control unit; the circuit control unit comprises DC power supply, an operational amplifier and a computer control terminal; and the operational amplifier is used for receiving the photoelectric current signal and performing amplification, and then sending the amplified photoelectric current signal to the computer control terminal. The method comprises the following steps: training an identification model in advance based on an artificial neural network model, extracting a near-infrared reflectance spectroscopy of the to-be-identified sample according to the identification model, and acquiring the identification result of the to-be-identified sample. The method and the apparatus can accurately and rapidly indentify a plurality of common plastics.

The invention relates to a quality monitoring method of the preparation process of condensed pills of cyperus and amomum stomach nourishing pills. According to the quality monitoring method of the preparation process of the condensed pills of the cyperus and amomum stomach nourishing pills, the problem of rapid quality detection of the condensed pills of the cyperus and amomum stomach nourishing pills in the process of online production is effectively solved; samples with different water extraction time and concentration time are scanned by a near-infrared spectrometer to obtain original spectral data of the samples; the collected content of hesperidin and magnolol in corrected samples is determined by a high performance liquid chromatography (HPLC); a calibration set and a validation setare selected through the content of indexity components; the spectral data is subjected to pre-processing and spectral area selection; the content measured by the HPLC is taken as a reference value, acorrected sample set characteristic spectrum and the reference value are combined by the partial least squares to establish a multivariate calibration model of a near infrared reflectance spectroscopy (NIRS), and the model is verified; the NIRS is input the calibration model, and a NIRS predicted value and the HPLC reference value are analyzed; and the predicted value of the validation sample setis compared with the content of the hesperidin and the magnolol measured by the HPLC, the calibration model is monitored, and whether the validation sample set is a foul territory point or not is measured.

The invention discloses a method for measuring lignin of a reconstituted tobacco by a paper-making process by virtue of a near infrared reflectance spectroscopy technique. The method comprises the following steps: (1) collecting and preparing a representative sample; (2) collecting an original spectrum; (3) selecting a correcting sample set and a verifying sample set; (4) measuring a reference value of the sample; (5) carrying out pretreatment on spectrum; (6) establishing a PLC model; (7) verifying the model; and (8) measuring the lignin. The method disclosed by the invention is simple, feasible and fast. By adopting a near infrared spectrum nondestructive detection technology, not only can the analytical efficiency be enhanced and the cost be lowered, but also the method has obvious practicality for accurately measuring the lignin of the reconstituted tobacco, improving the detection efficiency and objectively reflecting the product quality. The method disclosed by the invention has the advantages of high detection speed, no pollution, greenness and environmental protection, high accuracy, good repeatability and the like, and is suitable for on-site analysis and fast detection of the lignin as well as online monitoring of fluctuation of product quality.

The invention discloses a method for measuring hot water solvends of a reconstituted tobacco by a paper-making process by virtue of a near infrared reflectance spectroscopy technique. The method comprises the following steps: (1) collecting and preparing a representative sample; (2) collecting an original spectrum; (3) selecting a correcting sample set and a verifying sample set; (4) measuring a reference value of the sample; (5) carrying out pretreatment on spectrum; (6) establishing a PLC model; (7) verifying the model; and (8) measuring the hot water solvends. The method disclosed by the invention is simple, feasible and fast. By adopting a near infrared spectrum nondestructive detection technology, not only can the analytical efficiency be enhanced and the cost be lowered, but also the method has obvious practicality for accurately measuring the hot water solvends of the reconstituted tobacco, improving the detection efficiency and objectively reflecting the product quality. The method disclosed by the invention has the advantages of high detection speed, no pollution, greenness and environmental protection, high accuracy, good repeatability and the like, and is suitable for on-site analysis and fast detection of the hot water solvends as well as online monitoring of fluctuation of product quality.

The invention discloses a method for predicting potential photosynthetic capacity of plants based on characteristic wavelengths. The method comprises the following steps: setting culture environmentswith the same temperature, humidity and CO2 concentration under six illumination gradients, randomly selecting plant leaves as experimental samples when plants under different illumination treatmentsare different, and respectively measuring dark fluorescence parameters and visible-near infrared reflection spectra of the plant leaves as sample data; rejecting abnormal samples by adopting a Monte Carlo method, and randomly dividing a training set and a test set according to a ratio of 4: 1; extracting characteristic wavelengths by adopting a correlation coefficient method and a continuous projection method; establishing a plant potential maximum photosynthetic capability prediction model by taking the reflection spectrum corresponding to the characteristic wavelength as an input and takingthe plant potential maximum photosynthetic capability as an output and utilizing a radial basis function neural network optimized by a genetic algorithm. The potential maximum photosynthetic capacityof the plant is predicted, and a theoretical basis is provided for rapid, lossless and low-cost monitoring of the potential maximum photosynthetic capacity of the plant.

The invention discloses a soil heavy metal visible and near infrared reflection spectrum feature diagnosing method, comprising first selecting to measure a visible-near infrared reflection spectrum of a heavy metal compound; associating the heavy metal reflection spectrum with an external electron configuration of a heavy metal element; observing a reflection spectrum feature of the heavy metal compound; using a crystal field theory for analyzing wave band positions and reasons occurring at the feature reflection peak of the heavy metal; adding heavy metal compounds at different concentration gradients in a soil sample, and studying influences of the heavy metals with different types and different concentrations on the soil reflection spectrum; performing different spectra pretreatments on the sample reflection spectrum; researching linear correlation between the heavy metal concentration and soil reflection spectrum and position and potential theory for the occurrence of the obviously associated (p is smaller than 0.05) wave band. The studying method provides theoretical basis and experimental reference for qualitative and quantitive reflection spectrum analysis of soil heavy metal.

The invention discloses a method for measuring cellulose of a reconstituted tobacco by virtue of a near infrared reflectance spectroscopy technique. The method comprises the following steps: (1) collecting and preparing a representative sample; (2) collecting an original spectrum; (3) selecting a correcting sample set and a verifying sample set; (4) measuring a reference value of the sample; (5) carrying out pretreatment on spectrum; (6) establishing a PLC model; (7) verifying the model; and (8) measuring cellulose. The method disclosed by the invention is simple, feasible and fast. By adopting a near infrared spectrum nondestructive detection technology, not only can the analytical efficiency be enhanced and the cost be lowered, but the method also has obvious practicality for accurately measuring the cellulose of the reconstituted tobacco, improving the detection efficiency and objectively reflecting the product quality. The method disclosed by the invention has the advantages of high detection speed, no pollution, greenness and environmental protection, high accuracy, good repeatability and the like, and is suitable for on-site analysis and fast detection of the cellulose of a reconstituted tobacco product as well as online monitoring of fluctuation of product quality.

The invention belongs to the technical field of chlorite mineral identification and discloses a chlorite mineral species identification method based on near infrared reflectance spectroscopy. The method comprises the following steps: acquiring a near infrared reflection spectrum of a field chlorite mineral species through nondestructive surface measurement; performing smooth denoising processing on spectrum data, and determining a characteristic absorption peak by adopting Gaussian-Lorentzian function fitting; performing spectral curve smoothing data preprocessing on the near infrared reflection spectrum data in a data processing terminal, and performing peak-differentiating and imitating on the characteristic absorption peak of the curve subjected to a spectrum data smoothing link; and according to a linear statistical relationship between a position of the characteristic absorption peak and content of iron in chlorite, rapidly identifying the subspecies type of a chlorite mineral according to the position of the characteristic absorption peak. The method disclosed by the invention can enable field staff to obtain subspecies information of the chlorite mineral in an alteration zone in real time, shortens time required by laboratory rock and mineral identification, eliminates a sample preparation step, is time-saving and labor-saving and also saves fund.

The invention discloses a method for detecting the content of soluble solids in strawberries based on the near-infrared reflectance spectroscopy. The method includes the steps of firstly, conducting near-infrared spectrum scanning on a strawberry standard product with the known content of soluble solids; secondly, preprocessing an obtained calibration set sample spectrum; thirdly, conducting main component analysis, and extracting characteristic information data; fourthly, establishing a calibration model; fifthly, measuring the straw sample with the unknown content of soluble solids, wherein the obtained characteristic information data is input to the calibration model in the fourth step to obtain the content of soluble solids in the to-be-measured strawberry sample. The method has the advantages of being high in analysis speed, high in analysis efficiency, free of chemical reagents, low in analysis cost, free of pollution to the environment and the like, and can provide reliable basis for the analysis of the strawberry quality and the control over the strawberry quality and product quality.

The invention discloses a novel method for rapidly detecting total sulfur in coal samples. The method comprises the following steps: S1. collecting and preparing a plurality of coal samples, and measuring the content of total sulfur in each sample by a conventional method; S2. scanning the coal samples with an NIRS (near infrared reflectance spectroscopy) analyzer, and collecting the spectral data and curves of the coal samples; S3. processing the spectral data of the samples, obtained in the S2, obtaining calibration equations of total sulfur through regression calculation, correcting and verifying the calibration equations of total sulphur, and building detection models; S4. directly filling a sample injector of the NIR instrument with the coal samples to be detected in sequence, starting a scan key, automatically recording and storing the spectra of the samples by the NIR instrument, determining the types of the attributive spectrograms of the samples, selecting corresponding detection models, and obtaining detection results. The method provided by the invention has the beneficial effects that the accuracy of the method meets the requirements of the reproducibility tolerance of current standard methods; the method is quite easy, convenient and rapid to operate, and scan detection of one sample can be completed in about 50 seconds, including data output; sample weighing and addition of any chemical reagent are not needed in the whole detection operation process, so that the method has the characteristics of high speed, convenience and no pollution.

The invention discloses a method for measuring the content of a manganese element in cotton seed meal. Different types of cotton seed meal samples planted in different regions are prepared, spectra of the cotton seed meal samples are acquired by a near infrared reflectance spectrograph, a PLS model is constructed through full cross validation in the full spectrum range, and then the PLS model is analyzed with 12 preprocessing methods; a processing method corresponding to the prediction related coefficient R<2> maximum and the RMSE (root-mean-square error) minimum are taken as the optimal preprocessing method, and an NIRS (near infrared reflectance spectroscopy) correction model is established with the optimal preprocessing method; the to-be-measured cotton seed meal is detected with the NIRS correction model constructed in the previous steps, and the content of the manganese element is obtained. A spectrum chart of the cotton seed meal is acquired by the aid of the FOSS5000 near infrared reflectance spectrograph, the measurement accuracy is high, and the method is quick, convenient and efficient and has great significance in cultivation of new cotton varieties and promotion of processing and utilization of cotton by-products.

A method for identifying a stain on a textile (10), the method comprising the steps of: performing near-infrared reflectance spectroscopy to obtain spectral data from the stain over a range of wavelengths ranging from a shortest wavelength to a longest wavelength, the shortest wavelength having a value of 1595 nm or longer; accessing reference spectral data (33) of known stains; and comparing the spectral data of the stain to the reference spectral data of known stains to identify the stain.

The invention relates to a split pork carcass fat and lean thickness nondestructive measurement system based on near-infrared light.The system comprises a near-infrared emission light source, a near-infrared reflection spectrum acquisition instrument, an emitted and reflected light conduction module, a probe, a pork carcass clamping device, a displacement detection device and a controller module; emitted light emitted by the near-infrared emission light source and reflected light of the near-infrared reflection spectrum acquisition instrument are subjected to conduction through optical fibers of the emitted and reflected light conduction module; the optical fibers are encapsulated inside the probe; the pork carcass clamping device is used for positioning and clamping a split pork carcass which is on the slaughtering production line and is in a moving state; the controller is used for processing a spectrum signal output by the near-infrared reflection spectrum acquisition instrument and a signal output by the displacement detection device, and non-contact and nondestructive measurement with line is conducted on fat and lean thickness of live pigs on the production line.The split pork carcass fat and lean thickness nondestructive measurement system based on the near-infrared light has the advantages of being low in power consumption, long in service life, easy to operate and the like.

The invention discloses a method for rapidly analyzing the occurrence state of rare earth by using visible light-near infrared reflectance spectroscopy, which comprises the following steps: (1) drying a weathering crust sample, putting the weathering crust sample into a vessel, and flattening the surface; (2) carrying out reflection spectrum measurement on the sample in the vessel by using a visible light-near infrared reflection spectrometer, wherein the spectrum range is set to be 350-2500nm; measuring the powder sample for a plurality of times from different directions at an interval of 90 degrees, measuring the rock block sample for a plurality of times from different directions at an interval of 30 degrees, and recording original spectral data; and (3) processing the obtained original spectrum data, carrying out peak shape fitting on 800nm absorption band characteristics, obtaining the position and relative intensity information of an absorption band, and judging the occurrence state of the rare earth element. The method provided by the invention can meet the requirement of weathering crust ion adsorption type rare earth deposit prospecting exploration work on rapid sample analysis.

The invention relates to a split pork carcass fat and lean thickness nondestructive measurement system based on near-infrared light.The system comprises a near-infrared emission light source, a near-infrared reflection spectrum acquisition instrument, an emitted and reflected light conduction module, a probe, a pork carcass clamping device, a displacement detection device and a controller module; emitted light emitted by the near-infrared emission light source and reflected light of the near-infrared reflection spectrum acquisition instrument are subjected to conduction through optical fibers of the emitted and reflected light conduction module; the optical fibers are encapsulated inside the probe; the pork carcass clamping device is used for positioning and clamping a split pork carcass which is on the slaughtering production line and is in a moving state; the controller is used for processing a spectrum signal output by the near-infrared reflection spectrum acquisition instrument and a signal output by the displacement detection device, and non-contact and nondestructive measurement with line is conducted on fat and lean thickness of live pigs on the production line.The split pork carcass fat and lean thickness nondestructive measurement system based on the near-infrared light has the advantages of being low in power consumption, long in service life, easy to operate and the like.

The invention discloses a seed vigor determining method and system based on NIRS and a storage medium. The method comprises the following steps: obtaining an index component measured value according to sample seeds and original near infrared transmitted spectra of the sample seeds; pre-processing the original near infrared transmitted spectra of the sample seeds, including detrending and mean centralizing; determining a modeling method according to the index component measured value; constructing a PLSR model according to the pre-processed result based on the determined modeling method; and determining the seed vigor through the PLSR model. The PLSR model capable of predicting the seed vigor is established based on near-infrared reflectance spectroscopy, so that the seed vigor predicting speed is accelerated greatly and the seed vigor predicting accuracy is improved. In addition, a lot of detection equipment is not used, so that the cost is lowered. The method and system can be widelyapplied to the technical field of infrared analysis.

The invention discloses a mahogany furniture identification system based on NIRS (near infrared reflectance spectroscopy) and 3D visualization technologies. The mahogany furniture identification system comprises a mahogany furniture sale display platform, an internet, a cloud database, a foreground user system and an administrator system, wherein the mahogany furniture sale display platform is in bidirectional signal connection with the foreground user system and the administrator system through the internet; the foreground user system comprises a first microprocessor, a mahogany culture module, a user registration module, a 3D display module, an online sales module, an after-sales service module, a mahogany furniture identification module and a first signal transceiver, and the first microprocessor is in bidirectional connection with the mahogany furniture identification module and the first signal transceiver. The NIRS technology and the 3D visualization technology are combined and applied to the mahogany furniture sale display platform, so that the real reliability of the platform is improved, the market development demand is greatly met, and the situation of sales slump of mahogany furniture on e-commerce platforms is well relieved.

The invention discloses a method for recognizing the walking intention based on brain hemoglobin information. The method for recognizing the walking intention based on the brain hemoglobin informationcomprises the steps that (1) cerebral cortex hemoglobin concentration signals are obtained, specifically, the cerebral cortex hemoglobin concentration signals are obtained in the mode that a testingexperiment is conducted by applying a near infrared reflectance spectroscopy (NIRS) brain imaging technology, and a subject completes the corresponding walking task in a fixed area; and (2) through aband-pass filtering technology, the cerebral cortex hemoglobin concentration signals recorded in the experiment are subjected to data pre-processing, and the cerebral cortex hemoglobin concentration signals with multiple frequency bands are extracted. The method has the beneficial effects that the NIRS brain imaging technology is applied for the testing experiment, and the method is easy and convenient to operate and has the portable advantage.

The invention discloses NIRS technology based muscle oxygenation detection equipment, which comprises an electrode, a light source, a proximal receiving end, a distal receiving end, a temperature sensor, a microprocessor, and a power supply. The provided NIRS based muscle oxygenation detection equipment has the characteristics of small volume, simple control and stable performance.

The present invention discloses a three-dimensional multispectral insect distinguishing device and an identifying method thereof. The three-dimensional multispectral insect distinguishing device includes: a handheld probe, which is provided with a first camera, a second camera, a first video interface, a second video interface, a white-light source, an LED light, a first switch, a control module, and a battery; and dual-channel video glasses. The three-dimensional multispectral insect distinguishing device further includes a processing apparatus used obtain a disparity spectrum between the insect and a near infrared reflectivity spectrum of the visible light of the background object according to the insect and the near infrared reflectivity spectrum of the visible light of the background object, to get the wavelength of a preset scope of the peak value of the disparity spectrum. Upon inspection, the tested object is illuminated by the ray of light within the maximum disparity spectrum scope output by the LED light, to enhance the contrast between the insect and the background, which greatly improves the positive rate of the insect. In addition, a three-dimensional image is generated by the dual-channel video glasses, which may reduce confusion between planar plaque or cavity and three-dimensional objects, thereby further increasing the positive rate of the insect.

The invention discloses a waste plastic spectrum identification method based on an XGBoost model. The method comprises the following steps: acquiring near-infrared reflectivity spectrum data of various plastics by using a near-infrared spectrometer; pCA analysis is carried out on the original spectral data, and the data dimension is reduced; an XGBoost algorithm is used to establish a waste plastic algorithm identification model; optimizing the performance of the recognition model by adopting grid search and K-fold cross validation, and finally establishing the recognition model; and based on the trained identification model, extracting the near infrared spectrum of the to-be-identified plastic sample, and identifying the near infrared reflection spectrum of the to-be-identified plastic sample according to the identification model to obtain an identification result of the to-be-identified plastic sample. According to the method, the data processing time is shortened, meanwhile, the accuracy of identifying various common plastics is improved, and application in actual production is facilitated.