EP3298384A1 - Étalonnage d'une unité de mesure proche infrarouge à l'aide d'un spectre proche infrarouge simulé obtenu à partir d'un spectre infrarouge moyen mesuré - Google Patents

Étalonnage d'une unité de mesure proche infrarouge à l'aide d'un spectre proche infrarouge simulé obtenu à partir d'un spectre infrarouge moyen mesuré

Info

Publication number
EP3298384A1
EP3298384A1 EP16744886.9A EP16744886A EP3298384A1 EP 3298384 A1 EP3298384 A1 EP 3298384A1 EP 16744886 A EP16744886 A EP 16744886A EP 3298384 A1 EP3298384 A1 EP 3298384A1
Authority
EP
European Patent Office
Prior art keywords
near infrared
calibration data
measurements
chemical
calibration
Prior art date
Legal status (The legal status 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 status listed.)
Withdrawn
Application number
EP16744886.9A
Other languages
German (de)
English (en)
Inventor
Hermanus Wouter VEDDER
Thomas TERHOEVEN-URSELMANS
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Tree of Knowledge Patents BV
Original Assignee
Tree of Knowledge Patents BV
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 Tree of Knowledge Patents BV filed Critical Tree of Knowledge Patents BV
Publication of EP3298384A1 publication Critical patent/EP3298384A1/fr
Withdrawn legal-status Critical Current

Links

Classifications

    • 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
    • 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
    • G01N21/27—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands using photo-electric detection ; circuits for computing concentration
    • G01N21/274—Calibration, base line adjustment, drift correction

Definitions

  • the invention relates to a method for calibrating an near infrared measurement unit for characterizing a physical, chemical and/or biological parameter of a mineral and/or organic sample, comprising the steps of providing a multiple number of near infrared calibration data of a mineral and/or organic sample class, and feeding a calibration model of near infrared measurements with the multiple number of near infrared calibration data.
  • Near infrared measurement units are known for performing measurements on agricultural samples so that values of physical, chemical and/or biological parameters can be determined in a manner that is faster than conventional wet chemical analysis methods.
  • mid infrared measurement units are known for the same purpose.
  • mid infrared measurement procedures are generally significantly more expensive since pre-treatments have to be carried out on the samples to be measured, such as drying and grinding.
  • less calibration measurements are required for providing relatively accurate results.
  • the invention is at least partially based on the insight that, advantageously, a conversion model for converting a mid infrared spectrum into near infrared calibration spectrum can be used.
  • the invention also relates to a near infrared measurement unit. Further, the invention relates to a computer program product.
  • a computer program product may comprise a set of computer executable instructions stored on a data carrier, such as a flash memory, a CD or a DVD. The set of computer executable instructions, which allow a
  • programmable computer to carry out the method as defined above may also be available for downloading from a remote server, for example via the Internet, e.g. as an app.
  • Fig. 1 shows a diagram of near infrared spectra measurements
  • Fig. 2 shows a diagram of mid infrared spectra measurements
  • Fig. 3 shows a schematic view of a near infrared measurement unit
  • Fig. 4 shows a calibration diagram for calibrating a near infrared measurement unit according to the invention
  • Fig. 5 shows a flow chart of an embodiment of a method according to the invention.
  • Figure 1 shows a diagram 1 of four near infrared spectra measurements, also known as NIR spectra measurements, depicting a respective absorption curve 2, 3, 4, 5 with an absorption value A as a function of a wavenumber k that is reciprocal to the wavelength ⁇ .
  • Each absorption curve 2, 3, 4, 5 corresponds to a specific soil sample measured by a near infrared measurement unit that is arranged for characterizing a physical, chemical and/or biological parameter of the soil sample.
  • the curves 2, 3, 4, 5 have a profile including peaks and valleys indicative of said physical, chemical and/or biological parameters.
  • the profile is a
  • each class of molecules generates a unique spectral response characteristic wherein the amplitude depends on the amount of molecules of the respective class of molecules.
  • numerical values for the physical, chemical and/or biological parameters can be determined.
  • characterized can e.g. be a dry substance content, a nitrogen content, a sulfur content and/or pH value.
  • Figure 2 shows a similar diagram 11, however related to mid infrared spectra measurements, also known as MIR spectra measurements. Again, four absorption curves 12, 13, 14, 15 are depicted with an absorption value A as a function of a wavenumber k that is reciprocal to the
  • the near infrared spectra ranges between circa 8000 and circa 4000 cm 1
  • the mid infrared spectra ranges between circa 4000 and circa 500 cm 1 .
  • the near infrared spectra and the mid infrared spectra range can be slightly different.
  • mid infrared spectra curves 12, 13, 14, 15 include more variations than near infrared spectra curves 2, 3, 4, 5, so that generally more information about physical, chemical and/or biological parameters can be retrieved from a mid infrared spectra curve than from a near infrared spectra curve, measured from the same soil sample.
  • a near infrared spectra curve is smoother so that parameters information is more filtered in the superposition of spectral responses generated by the molecules of distinct particles classes. The near infrared spectra curve is less specific.
  • a near infrared spectra curve can be measured relatively simple using relatively cheap components and processes, without performing elaborate pre-treatment processes. Also, a near infrared spectra curve may provide accurate results if the near infrared measurement unit has been calibrated with relatively many calibration data.
  • Figure 3 shows a schematic view of a near infrared measurement unit 20, comprising a near infrared sensor 21 and a processing unit 22.
  • the near infrared sensor 21 is arranged for performing an infrared sensor measurement on a mineral and/or organic sample 26 and for transmitting the measurement data to the processing unit 22, in the shown embodiment via a wired transmission channel 25.
  • the processing unit 22 includes a processor 23 and a memory 24 for retrieving a numerical value of said physical, chemical and/or biological parameter of the sample 26, based on the near infrared sensor measurement.
  • the near infrared sensor 21 is a handheld device to facilitate easy sample measurements.
  • a mid infrared measurement has, from a conceptual point of view, a similar system setup, but has in practice normally another implementation structure, e.g. due to required pre-treatment process steps.
  • the near infrared measurement unit is calibrated by the steps of providing a multiple number of near infrared calibration data of a mineral and/or organic sample class and feeding a calibration model of near infrared measurements with the multiple number of near infrared calibration data.
  • calibrating the near infrared measurement unit with known calibration data actual near infrared measurements can be interrelated using the calibration model so that accurate measurement results can be obtained, depending on density and distribution of calibration data.
  • At least a subset of the near infrared calibration data is based on mid infrared measurements.
  • Figure 4 shows a calibration diagram for calibrating a near infrared measurement unit according to the invention.
  • the calibration data for both a mid infrared measurement unit and a near infrared measurement unit are represented on a one -dimensional line, though keeping in mind that the calibration is multi-dimensional, due to a multiple number of physical, chemical and/or biological parameters that can be characterized by the near infrared measurement.
  • a near infrared measurement unit 20 is calibrated using measurements of a mid infrared measurement unit.
  • the mid infrared measurement unit is calibrated using a multiple number of wet chemical calibration measurements Wl, W2, W3 on a first set of common NIR/MIR calibration samples.
  • the wet chemical calibration measurement are fed into a calibration model of mid infrared
  • the mid infrared measurement unit is ready for use and performs a multiple number of real measurements Ml, M2, M3, M4 on a second set of NIR calibration samples, for providing a set of virtual near infrared calibration data.
  • various types of mid infrared measurements can be used for generating the virtual near infared calibration data, including mid infrared measurements on remote samples that have been obtained for other purposes, e.g. for analyzing specific samples in the field.
  • the mid infrared measurements on the field samples serve both as a source for analyzing local samples and as a NIR calibration sample for calibration a near infrared measurement device that has not performed measurements on said field sample.
  • M4 are converted into near infrared calibration data C l, C2, C3, C4, using a conversion model.
  • the converted near infrared calibration data include mid infrared spectra measurements that have been converted into the near infrared spectrum, obtaining simulated near infrared spectrum measurements on the NIR calibration samples that have not been measured by the near infrared measurement unit to be calibrated.
  • a simulated near infrared spectrum measurement is a simulation of a near infrared spectrum measurement on a calibration sample that has been used for providing the mid infrared measurements, the calibration sample being a sample from the above-mentioned second set of NIR calibration samples.
  • the near infrared measurement unit 20 is calibrated using the wet chemical calibration measurements Wl, W2, W3 and the near infrared calibration data C l, C2, C3, C4 based on the mid infrared measurements Ml, M2, M3, M4.
  • the calibration is performed using a first set of near infrared calibration data and a second set of near infrared calibration data.
  • the first set of near infrared calibration data is based on the first set of common NIR/MIR calibration samples that have also been used for calibrating the mid infrared measurement unit.
  • the second set of near infrared calibration data C l, C2, C3, C4 is a set of virtual near infrared calibration data and is based on mid infrared measurements performed on the second set of NIR calibration samples, the mid infrared measurements Ml, M2, M3, M4 having been converted into near infrared calibration data C l, C2, C3, C4.
  • the set of virtual near infrared calibration data C l, C2, C3, C4 include virtual near infrared spectra resulting from the conversion of mid infrared spectra measurements into near infrared calibration data.
  • the number of virtual near infrared calibration data, based on mid infrared measurements, corresponding to the second set of calibration samples, may exceed the number of wet chemical calibration measurements, corresponding to the first set of calibration samples, thereby saving time- consuming, elaborate and expensive wet chemical calibration
  • the near infrared calibration data correspond to at least one mid infrared measurement, including virtual near infrared calibration data based on at least one mid infrared spectra measurement.
  • the near infrared calibration data preferably also includes a value of a physical, chemical and/or biological parameter determined in the corresponding mid infrared measurement.
  • Mineral and/or organic samples classes may e.g. include soil, plant, food and/or manure, e.g. in the context of agricultural sample analysis.
  • the sample classes may not be restricted to mineral and/or organic materials, then potentially also including food material, chemistry, petro-chemistry including plastic material, oil and/or gas, pharmaceutical substances and biomaterial, e.g. in health care applications.
  • the conversion model for converting a mid infrared measurement into a near infrared calibration data is preferably based on empirical information.
  • the conversion model may include a computation model based on theoretic molecule models.
  • a subset of the near infrared calibration data is based on mid infrared measurements, viz. the second set of near infrared calibration data, also referred to as the set of virtual near infrared calibration data that has been obtained after conversion from mid infrared measurements Ml, M2, M3, M4.
  • calibration data is based on mid infrared measurements. Then, no wet chemical calibration data are used for calibrating the near infrared measurement unit.
  • Figure 5 shows a flow chart of an embodiment of a method according to the invention.
  • the method is used for calibrating an near infrared measurement unit for characterizing a physical, chemical and/or biological parameter of a mineral and/or organic sample.
  • the method comprises a step of providing 110 a multiple number of near infrared calibration data of a mineral and/or organic sample class, and a step of feeding 120 a calibration model of near infrared measurements with the multiple number of near infrared calibration data.
  • at least a subset of the near infrared calibration data is based on mid infrared measurements.
  • the near infrared measurement unit is calibrated including a step of converting a multiple number of mid infrared measurements into near infrared calibration data, using a conversion model.
  • the near infrared calibration data are fed into the calibration model of near infrared measurements.
  • values of physical, chemical and/or biological parameters determined in the corresponding mid infrared measurements also called “predictions” are fed into the near infrared calibration model.
  • These parameter values may relate to a single physical, chemical and/or biological parameter or to an entire range of physical, chemical and/or biological parameters.
  • the calibration data include both the converted mid infrared spectra measurements and the above- mentioned predictions associated with said mid infrared spectra
  • a near infrared measurement of a sample obtained from a near infrared measurement unit can be converted into a conditioned near infrared measurement spectrum wherein weather and/or structure influences have been reduced or entirely compensated.
  • Weather influences may relate to a moisture, temperature and/or electrical conductivity parameter of the sample.
  • Structure influences may relate to sample presentation, aggregation and compaction influences.
  • the conditioned measurement spectrum can be used for determining values of a physical, chemical and/or biological parameter of the sample in an even more accurate way, relating to the near infrared calibration model.
  • conversion into a conditioned near infrared measurement spectrum can be performed using a conditioning converting model, e.g. based on empirical data.
  • the conditioning converting model determines at least one weather and/or structure parameter from the near infrared measurement itself.
  • additional weather and/or structure measurements are added as additional input data to the conditioning converting model for converting a particular near infrared measurement.
  • the method of calibrating a near infrared measurement unit can be facilitated using dedicated hardware structures, such as computer servers. Otherwise, the method can also at least partially be performed using a computer program product comprising instructions for causing a processor of a computer system or a control unit to perform a process including at least one of the method steps defined above.
  • All (sub)steps can in principle be performed on a single processor. However, it is noted that at least one step can be performed on a separate processor.
  • a processor can be loaded with a specific software module. Dedicated software modules can be provided, e.g. from the Internet.
  • the method for calibrating a near infrared measurement unit can not only be used for characterizing a physical, chemical and/or biological parameter of a mineral and/or organic sample, but also for characterizing a physical, chemical and/or biological parameter of another sample type, such as a sample including food material, chemical, petro-chemical material including plastic material, oil and/or gas, pharmaceutical substances and/or biomaterial.

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  • Physics & Mathematics (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Engineering & Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Theoretical Computer Science (AREA)
  • Investigating Or Analysing Materials By Optical Means (AREA)

Abstract

L'invention concerne un procédé d'étalonnage d'une unité de mesure proche infrarouge permettant de caractériser un paramètre physique, chimique et/ou biologique d'un échantillon minéral et/ou organique. Le procédé comprend une étape consistant à fournir un nombre multiple de données d'étalonnage proche infrarouge d'une classe d'échantillons minéraux et/ou organiques. Le procédé comprend également une étape consistant à introduire des données d'étalonnage proche infrarouge dans un modèle d'étalonnage de mesures proche infrarouge. Selon l'invention, au moins un sous-ensemble des données d'étalonnage proche infrarouge est basé sur des mesures infrarouge moyen.
EP16744886.9A 2015-05-21 2016-05-23 Étalonnage d'une unité de mesure proche infrarouge à l'aide d'un spectre proche infrarouge simulé obtenu à partir d'un spectre infrarouge moyen mesuré Withdrawn EP3298384A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
NL2014836A NL2014836B1 (en) 2015-05-21 2015-05-21 A method for calibrating an near infrared measurement unit, a near infrared measurement unit and a computer program product.
PCT/NL2016/050366 WO2016186507A1 (fr) 2015-05-21 2016-05-23 Étalonnage d'une unité de mesure proche infrarouge à l'aide d'un spectre proche infrarouge simulé obtenu à partir d'un spectre infrarouge moyen mesuré

Publications (1)

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EP3298384A1 true EP3298384A1 (fr) 2018-03-28

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EP16744886.9A Withdrawn EP3298384A1 (fr) 2015-05-21 2016-05-23 Étalonnage d'une unité de mesure proche infrarouge à l'aide d'un spectre proche infrarouge simulé obtenu à partir d'un spectre infrarouge moyen mesuré

Country Status (3)

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EP (1) EP3298384A1 (fr)
NL (1) NL2014836B1 (fr)
WO (1) WO2016186507A1 (fr)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
AU2017377078B2 (en) 2016-12-16 2020-07-09 Farmers Edge Inc. Classification of soil texture and content by near-infrared spectroscopy
CN107576630A (zh) * 2017-09-28 2018-01-12 中国科学院昆明植物研究所 同时测定植物多种重金属含量的中红外光谱便携检测系统
CN112274146B (zh) * 2020-09-18 2021-09-03 西安交通大学 一种用于nirs测量设备检测校准的模拟系统及方法

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Publication number Publication date
NL2014836B1 (en) 2017-01-31
NL2014836A (en) 2016-11-28
WO2016186507A1 (fr) 2016-11-24

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