WO2017151066A1 - Système et procédé de détermination de qualité de fond de tasse par spectroscopie proche infrarouge - Google Patents

Système et procédé de détermination de qualité de fond de tasse par spectroscopie proche infrarouge Download PDF

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Publication number
WO2017151066A1
WO2017151066A1 PCT/TH2016/000016 TH2016000016W WO2017151066A1 WO 2017151066 A1 WO2017151066 A1 WO 2017151066A1 TH 2016000016 W TH2016000016 W TH 2016000016W WO 2017151066 A1 WO2017151066 A1 WO 2017151066A1
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WO
WIPO (PCT)
Prior art keywords
cup lump
calibration
cup
nir
lump
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Application number
PCT/TH2016/000016
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English (en)
Inventor
Ronnarit RITTIRON
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Premier System Engineering Co., Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Premier System Engineering Co., Ltd filed Critical Premier System Engineering Co., Ltd
Priority to MYPI2017001447A priority Critical patent/MY187657A/en
Priority to PCT/TH2016/000016 priority patent/WO2017151066A1/fr
Publication of WO2017151066A1 publication Critical patent/WO2017151066A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
    • G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light

Definitions

  • the invention relates to a system and a method for determining quality of cup lump, and more particularly, it relates to determination of quality of cup lump by using near infrared spectroscopy.
  • Para rubber is an economic crop for Thailand, especially in the southern, eastern and northeastern parts. This is due to the fact that Para rubber is used as a raw material for processing in several industries, such as rubber threads, tires, gloves, and even the medical supply industry. For commercial trade, Para rubber is available in several types, such as concentrated latex, standard Thai rubber (STR), rubber smoked sheet, raw rubber sheet, crepe rubber, etc. Furthermore, cup lump is one type of rubber that agriculturists in northeastern Thailand prefer to produce because of the lower cost, consumption of water, and labor costs, as well as for quicker sales than rubber sheet. In addition, cup lump can be used as a raw material for STR production.
  • STR standard Thai rubber
  • Cup lump production starts from tapping a rubber tree, then the latex flows into a cup and coagulated latex by adding an acid solution. Cup lump obtained from this process is white in color, but if it is left longer, the moisture content decreases and the color will be darker.
  • the price of cup lump in commercial trade changes in direct relation to the dry rubber content (DRC) and reverse variation to moisture content, meaning that in cup lump with high moisture content, the DRC is low, and the purchase price is also low.
  • the adulteration of vulcanized rubber in cup lump is also an important parameter for trading, because it has an effect on the quality of either cup lump or STR. [0003] The quality of cup lump is determined in a laboratory.
  • the DRC and moisture content are analyzed by drying cup lump in a hot air oven, which is time consuming. Meanwhile, the adulteration of rock, gravel, sand, earth and bark in cup lump is determined by observation with the naked eye by skilled analysts and by using a chemical solution for adulteration of the vulcanized rubber. This traditional method is time, chemical and energy consuming, and also requires skilled analysts.
  • NIR spectroscopy is an interesting and attractive method that is rapid, accurate and reliable. Theoretically, NIR measures the absorbance of constituents-related molecules at specific wavelengths in the NIR region. Therefore, absorbance looks like a fingerprint of the sample. From that reason, NIR is applied to use in many agro-industries, such as measuring starch gelatinization in a feed production system (U.S. Pat. No. 7,907,273 B2) and the determination of quality parameters in pulp and paper and/or the organic content in effluents from pulp and paper production (U.S. Pat. No. 5,842,150 A).
  • NIR NIR-infrared spectroscopy
  • the system comprises a scanning head, an NIR spectrophotometer, a database and a control device.
  • the scanning head comprises a light source, which generates light in the NIR wavelength region, and a detector, which is used to collect, reflected or transmitted light from cup lump.
  • the NIR spectrophotometer includes the type of dispersive (e.g. grating monochromators), whether interferometric or nonthermal, which can generate light within a specific wavelength (e.g. light emitting diodes, laser diodes and lasers) resolving the reflected light and transmitting it into light of a discrete wavelength.
  • NIR hyperspectral imaging which combines conventional digital camera and spectrograph in a single system, is also included.
  • the position of the NIR spectrophotometer mounting depends on each system.
  • the NIR spectrophotometer and light source are mounted on the same side for a reflection system (FIG. 1) and on opposite sides for a transmission system (FIG. 2).
  • the database comprises calibration equations, which are constructed from the relation between the absorbance of the sample in each wavelength and quality parameters of interest, whereas the calibration model is constructed from the relation between the absorbance of the sample in each wavelength and group of cup lump quality.
  • the control device and data processing device may be a computer, microcontroller or other device performing in the same manner. This part uses a control system and analyzes cup lump quality with the aid of calibration equations or a calibration model database based on the NIR absorbance (spectra) of the cup lump.
  • the method comprises the steps of, obtaining the NIR absorbance, also known as NIR spectra, of cup lump, the sample of which shall be truly representative of the cup lump population that is expected to be found in the future, obtaining laboratory testing of the cup lump qualities, such as the dry rubber content (DRC), moisture content, and adulterated cup lump.
  • NIR absorbance also known as NIR spectra
  • DRC dry rubber content
  • moisture content and adulterated cup lump.
  • the calibration equation or calibration model is developed by a software program using regression; either linear regression, such as Multiple Linear Regression (MLR) or Partial Least Squares (PLS) regression, or non-linear regression, such as Artificial Neural Network (ANN) etc.
  • LLR Multiple Linear Regression
  • PLS Partial Least Squares
  • ANN Artificial Neural Network
  • Samples for database construction are separated into two sets.
  • the calibration set is used to develop the calibration equation or calibration model and the validation set is used to validate the accuracy and precision of the developed calibration equation or calibration model.
  • Conducting statistical testing for the measurement of accuracy and precision of constructed database, standard error of prediction (SEP), bias and slope obtained from the validation set are tested as follows: ISO 12099: 2010, which is a guideline for the application of NIR spectrometry for constituent measurement of the sample.
  • the third embodiment of the invention is to provide a method for the measurement of quality parameters of cup lump using the stored database.
  • the database is validated statistically, given the above, and is suitable to be used industrially.
  • the method comprises obtaining NIR absorbance of cup lump, which is measured by an NIR spectrophotometer, then applying appropriate calibration equation or calibration model to the NIR spectrum of cup lump to analyze the quality parameters of interest. Further, the analyzed results are considered reliable when the spectrum conforms to the set of spectra used to derive the calibration equation, wherein the spectrum obtained is useable for as many parameters as calibrations are available.
  • the system according to the second and third embodiments of the invention can be incorporated into a network.
  • a centralized database provides reference calibration equations or models to other processing streams in the network, provided that NIR spectrophotometers are standardized against the NIR spectrophotometers on which the calibration equations were developed, the latter can be used as a master instrument within the network.
  • a network of systems according to the invention is particularly advantageous in measuring the parameter of interest in cup lump processing. Cup lump quality measurement in the purchasing process may be part of the network system. The network is convenient for industrial operations, because the data in the master instrument can be exchanged and accessed from all slave instruments. [0011] It is another object of the present invention to provide a system for the measurement of the quality parameters of cup lump, wherein the system comprises a scanning head, an NIR spectrophotometer, a database and a control device.
  • the calibration equation or calibration model is developed by a software program using regression; either linear regression, such as Multiple Linear Regression (MLR) or Partial Least Squares (PLS) regression, or non-linear regression, such as Artificial Neural Network (ANN) etc.
  • LLR Multiple Linear Regression
  • PLS Partial Least Squares
  • ANN Artificial Neural Network
  • the spectrum is measured over or partially the range of 700 to 2,500 nm.
  • FIG. 1 illustrates a schematic representation of a reflection system of the invention
  • FIG. 2 illustrates a schematic representation of a transmission system of the invention.
  • FIG. 1 and FIG. 2 A method and a system 100 for quality measurement of cup lump sample 102 using NIR spectroscopy is described in FIG. 1 and FIG. 2.
  • the system 100 comprises a scanning head 104, an NIR spectrophotometer 106, a database 108 and a control device 110.
  • the scanning head of the NIR spectrophotometer in the reflection and transmission system is mounted adjacent to the sample as shown in Fig. 1 and Fig. 2, respectively.
  • the scanning head 104 of the NIR spectrophotometer 106 is mounted adjacent to the cup lump sample 102 to receive the reflected lights 112 from the sample 102 after part of the light 114 in the NIR wavelength region from the light source 116 is being reflected from the cup lum 102.
  • a detector 111 which is used to collect, reflected light 112 from cup lump 102. An average spectrum is produced for each sample scan.
  • the cup lump qualities such as dry rubber content (%), moisture content (%) and adulterated cup lump, are determined by the standard analytical method which is actually used in the factory.
  • a calibration equation is developed and stored in a database 108, such as the equation for the determination of dry rubber content (DRC), equation for the determination of moisture content, and model for classification of adulterated cup lump 102.
  • a database 108 is developed from the relation between the NIR spectra obtained by the spectrophotometer 106 and the quality parameters obtained from the standard method by using a control device and data processing unit 110 such as a CPU, a computer or a microcontroller, with the aid of chemometrics.
  • the near infrared spectrophotometer 106 further includes types of dispersives (e.g. grating monochromators), interferometric or non-thermal) which, generates light within a specific wavelength (e.g.
  • the processor 110 such as the computer, the microcontroller or the other similar device measures the parameter by application of the calibration equation or calibration model to the obtained spectrum for a sample 102.
  • the calibration equation database 108 created for each parameter must collect characteristic features of the spectra associated with the parameter of interest. After that, this database will be stored in order to be further utilized for routine analysis.
  • the scanning head 104 of the NIR spectrophotometer 106 is mounted adjacent to the cup lump sample 102 to receive the transmitted lights 118 from the sample 102 after a part of the light 114 in the NIR wavelength region from the light source 116 is being absorbed by the sample 102 and another part of the light 118 is transmitted through the cup lump 102.
  • Light 114 is resolved into a light of discrete wavelength using various methods, including dispersive (e.g. grating monochromators), interferometric or non-thermal, which can generate light within a specific wavelength (e.g. light emitting diodes, laser diodes and lasers) over or partial wavelength region of 700-2,500 nm. An average spectrum is produced for each sample scan.
  • the cup lump qualities are determined by using the similar method as described in the FIG. 1. Further analysis of the spectrum data associated with the parameter of interest by the use of control device and data processing unit 110 such as a CPU, a computer or a microcontroller, with the aid of chemometrics, such as Multiple Linear Regression (MLR(, Partial Least Square regression (PLS), Artificial Neural Network (ANN) or discriminant model development by Partial Least Square Discriminant analysis (PLSD A) or Principal Component Analysis (PCA), etc.
  • MLR Multiple Linear Regression
  • PLS Partial Least Square regression
  • ANN Artificial Neural Network
  • PLSD A Partial Least Square Discriminant analysis
  • PCA Principal Component Analysis
  • the system 100 can be incorporated into a network having a centralized database, which provides reference calibration equations or models to other processing streams in the network, provided that NIR spectrophotometers 106 are standardized against the NIR spectrophotometers 106 on which the calibration equations were developed.
  • Cup lump quality measurement in the purchasing process may be part of the network system.
  • the computer system, the processor, the server or the like 110 associated With the Centralized database acts as a master instrument within the network. The data in the master instrument can be exchanged and accessed from all slave instruments that are associated with the sample for analysis of the spectrum data and is particularly advantageous in measuring the parameter of interest in cup lump 102 processing.
  • the system 100 comprises a scanning head 104, an NIR spectrophotometer 106, a database 108 and a control device 110.
  • the scanning head 104 comprises a light source 116, which generates light 114 in the NIR wavelength region, and a detector 111, which is used to collect, reflected 112 or transmitted light 118 from cup lump 102.
  • the NIR spectrophotometer 106 includes the type of dispersive (e.g. grating monochromators), whether interferometric or non-thermal, which can generate light 114 within a specific wavelength (e.g.
  • the position of the NIR spectrophotometer 106 mounting depends on each system.
  • the NIR spectrophotometer 106 and light source 116 are mounted on the same side for a reflection system (FIG. 1) and on opposite sides for a transmission system (FIG. 2).
  • the database 108 comprises calibration equations, which are constructed from the relation between the absorbance of the sample in each wavelength and quality parameters of interest, whereas the calibration model is constructed from the relation between the absorbance of the sample in each wavelength and group of cup lump quality.
  • the control device and data processing device 110 may be a computer, microcontroller or other device performing in the same manner. This part uses a control system 110 and analyzes cup lump quality with the aid of calibration equations or a calibration model database based on the NIR absorbance (spectra) of cup lump 102.
  • the method comprises the steps of, obtaining the NIR absorbance, also known as NIR spectra, of cup lump 102, the sample of which shall be truly representative of the cup lump population that is expected to be found in the future, obtaining laboratory testing of the cup lump qualities, such as the DRC, moisture content, and adulterated cup lump 102. These qualities can be analyzed by a standard analytical method or another reliable method that is accepted by industries.
  • the calibration equation or calibration model is developed by a software program using regression; either linear regression, such as Multiple Linear Regression (MLR) or Partial Least Squares (PLS) regression, or non-linear regression, such as Artificial Neural Network (ANN) etc.
  • LLR Multiple Linear Regression
  • PLS Partial Least Squares
  • ANN Artificial Neural Network
  • Samples for database construction are separated into two sets.
  • the calibration set is used to develop the calibration equation or calibration model and the validation set is used to validate the accuracy arid precision of the developed calibration equation or calibration model.
  • Conducting statistical testing for the measurement of accuracy and precision of constructed database, standard error of prediction (SEP), bias and slope obtained from the validation set are tested as follows: ISO12099: 2010, which is a guideline for the application of NIR spectrometry for constituent measurement of the sample.
  • the databasel08 is validated statistically, given the above, and is suitable to be used industrially.
  • the method comprises obtaining NIR absorbance of cup lump 102, which is measured by an NIR spectrophotometer 106, then applying appropriate calibration equation or calibration model to the NIR spectrum of cup lump 102 so as to analyze and quantify the presence of the quality parameters of interest, and then statistically validating the spectrum obtained as being represented by the calibration equation or calibration model. Further the analyzed results are considered reliable when the spectrum conforms to the set of spectra used to derive the calibration equation, wherein the spectrum obtained is useable for as many parameters as calibrations are available.
  • the system 100 according to the second and third aspects of the invention can be incorporated into a network (not shown).
  • a network a centralized database provides reference calibration equations or models to other processing streams in the network, provided that NIR spectrophotometers are standardized against the NIR spectrophotometers on which the calibration equations were developed, the latter can be used as a master instrument within the network.
  • a network of systems according to the invention is particularly advantageous in measuring the parameter of interest in cup lump processing. Cup lump quality measurement in the purchasing process may be part of the network system.
  • the network is convenient for industrial operations, because the data in the master instrument can be exchanged and accessed from all slave instruments.
  • Another aspect of the invention is to provide a system 100 for the measurement of the quality parameters of cup lump 102 , wherein the system 100 comprises a scanning head 104, an NIR spectrophotometer 106, a detector 111, a database 108 and a control- device 110.
  • Still another aspect of the invention is to provide a method for the development of a calibration equation database, wherein the calibration equations are constructed from the relation between the absorbance of the sample in each wavelength and quality parameters of interest.
  • the calibration equation or calibration model is developed by a software program using regression; either linear regression, such as Multiple Linear Regression (MLR) or Partial Least Squares (PLS) regression, or non-linear regression, such as Artificial Neural Network (ANN) etc.
  • the calibration model is constructed from the relation between the absorbance of the sample in each wavelength and group of cup lump quality. Further the calibration set is used to develop the calibration equation or calibration model and the validation set is used to validate the accuracy and precision of the developed calibration equation or calibration model.
  • Further another aspect of the invention is to provide a method for the measurement of quality parameters of cup lump 102 using the stored database 108, wherein the method comprises obtaining NIR absorbance of cup lump 102, which is measured by an NIR spectrophotometer 106, then applying appropriate calibration equation or calibration model to the NIR spectrum of cup lump 102 so as to analyze the quality parameters of interest.
  • Another aspect of the invention is to provide a system measuring the parameter of interest in cup lump 102 by developing a calibration equation database 108 and measurement of quality parameters of cup lump 102 using the stored database 108 can be incorporated into a network, wherein a centralized database provides reference calibration equations or models to other processing streams in the network.
  • Another aspect of the present invention is to provide a system 100 for offline and online measurement of a parameter in cup lump 102, wherein the system 100 comprises, a scanning head 104 mounted adjacent to a continuous stream of cup lump 102, the scanning head 104 comprising a light source 116 and reflected 112 or transmitted light 118 gathering and detector 111; a near infrared spectrophotometer 106 which includes types of dispersives (e.g. grating monochromators), interferometric or non-thermal, which can generate light within a specific wavelength (e.g.
  • dispersives e.g. grating monochromators
  • interferometric or non-thermal which can generate light within a specific wavelength
  • a database 108 containing a reference calibration equation linking absorption characteristics by wavelength and quantified presence of the parameter of interest a database 108 containing a reference calibration model linking absorption characteristics by wavelength and qualities of cup lumps 102
  • a processor 110 such as a computer, microcontroller or other device, performing in the same manner for measuring the parameter by application of the calibration equation or calibration model to the obtained spectrum for a sample 102.
  • Another aspect of the present invention is to provide a method of offline and online measurement of a parameter in cup lump 102, wherein spectrum used is a single spectrum or the average of the plurality of the obtained spectra which is obtained from the reflectance or transmittance measurement. The spectrum is measured over or partially the range of 700 to 2,500 run.
  • Another aspect of the present invention is to provide a method of offline and online measurement of a parameter in cup lump 102, wherein the scanning head 104 is remote from said spectrophotometer 106 and is linked thereto by a fiber optics cable (not shown).
  • a scanning head 104 of the NIR spectrophotometer 106 in the reflection and transmission system is mounted adjacent to a cup lump sample 102 as shown in FIG. 1 and FIG. 2, respectively.
  • Light 114 obtained from the light source 116 in the NIR wavelength region illuminates the sample 102, and part of the light 114 is absorbed within the sample 102, while part of the light is reflected 112 (or transmitted 118) and consigned into the NIR spectrophotometer 106.
  • Light 114 is resolved into a light of discrete wavelength using various methods, including dispersive (e.g. grating monochromators), interferometric or non-thermal, which can generate light within a specific wavelength (e.g.
  • the cup lump 102 qualities such as dry rubber content (%), moisture content (%) and adulterated cup lump 102, are determined by the standard analytical method which is actually used in the factory.
  • the calibration equation is developed and stored in a database 108, such as the equation for the determination of DRC, equation for the determination of moisture content, and the model for classification of adulterated cup lump 102.
  • This database 108 is developed from the relation between the NIR absorbance (or NIR spectra) obtained from this invention and the quality parameters obtained from the standard method.
  • This step is achieved using a control device and data processing unit 110 such as a CPU, a computer or a microcontroller, with the aid of chemometrics, such as Multiple Linear Regression(MLR(, Partial Least Square regression (PLS), Artificial Neural Network( ANN) or discriminant model development by Partial Least Square Discriminant analysis (PLSDA) or Principal Component Analysis (PCA), etc.
  • chemometrics such as Multiple Linear Regression(MLR(, Partial Least Square regression (PLS), Artificial Neural Network( ANN) or discriminant model development by Partial Least Square Discriminant analysis (PLSDA) or Principal Component Analysis (PCA), etc.
  • MLR Multiple Linear Regression
  • PLS Partial Least Square regression
  • ANN Artificial Neural Network
  • PLSDA Partial Least Square Discriminant analysis
  • PCA Principal Component Analysis
  • the calibration equations developed from the calibration set are stored in the database 108 and are used to predict the quality parameters of cup lump 102 in the validation set.
  • the NIR spectra of the sample in the validation set which is measured by the NIR spectrophotometer 106 is processed in the stored database 108. This will verify the accuracy of the developed calibration equations based on statistics.
  • the results of the database 108 development and verification are shown in terms of correlation coefficient (R(, standard error of calibration (SEC(, standard error of prediction (SEP(, and bias (Table 2). This example showed that NIR spectroscopy is accurate and has a high potential to actually be used in either laboratory or industrial uses.

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  • Health & Medical Sciences (AREA)
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Abstract

L'invention concerne un système et un procédé de mesure de qualité de fond de tasse par spectroscopie proche infrarouge (NIR). Le système comprend une tête de balayage (104) montée à proximité d'un échantillon de fond de tasse (102), la tête de balayage (104) comprenant une source de lumière (116), et un spectrophotomètre proche infrarouge (106), qui comprend des types d'éléments dispersifs (par exemple, des monochromateurs à réseau de diffraction) soit interférométriques soit non thermiques, qui peuvent générer une lumière dans une longueur d'onde spécifique (par exemple, des diodes électroluminescentes, des diodes laser et des lasers) ainsi qu'une imagerie hyperspectrale NIR pour résoudre la lumière réfléchie et la transmettre en une lumière d'une longueur d'onde unique; une base de données contenant des équations d'étalonnage construites à partir des relations entre l'absorbance et les qualités de fonds de tasse; un équipement de commande et un traitement de données qui peuvent être soit un ordinateur soit des microcontrôleurs soit d'autres dispositifs fonctionnant de la même manière. L'équipement de commande et le traitement de données sont utilisés pour commander le système et mesurer les qualités de fond de tasse par application d'équations d'étalonnage. L'invention concerne également un procédé de mesure en ligne et hors ligne des qualités de fond de tasse par d'une spectroscopie NIR et un système de réseau, comme mentionné ci-dessus. Le système et le procédé sont particulièrement adaptés pour mesurer des qualités d'intérêt de fond de tasse.
PCT/TH2016/000016 2016-03-01 2016-03-01 Système et procédé de détermination de qualité de fond de tasse par spectroscopie proche infrarouge WO2017151066A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
MYPI2017001447A MY187657A (en) 2016-03-01 2016-03-01 System and method for quality determination of cup lump by near infrared spectroscopy
PCT/TH2016/000016 WO2017151066A1 (fr) 2016-03-01 2016-03-01 Système et procédé de détermination de qualité de fond de tasse par spectroscopie proche infrarouge

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PCT/TH2016/000016 WO2017151066A1 (fr) 2016-03-01 2016-03-01 Système et procédé de détermination de qualité de fond de tasse par spectroscopie proche infrarouge

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6630672B1 (en) * 1997-12-23 2003-10-07 Bureau Of Sugar Experiment Stations On-line measuring system and method
CN102374976A (zh) * 2011-10-21 2012-03-14 中国兵器工业集团第五三研究所 检测复合橡胶中丁苯橡胶含量的关联模型
CN103411916A (zh) * 2013-07-29 2013-11-27 中国热带农业科学院分析测试中心 一种利用近红外光谱即时测定干胶含量的方法

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6630672B1 (en) * 1997-12-23 2003-10-07 Bureau Of Sugar Experiment Stations On-line measuring system and method
CN102374976A (zh) * 2011-10-21 2012-03-14 中国兵器工业集团第五三研究所 检测复合橡胶中丁苯橡胶含量的关联模型
CN103411916A (zh) * 2013-07-29 2013-11-27 中国热带农业科学院分析测试中心 一种利用近红外光谱即时测定干胶含量的方法

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