WO2016186507A1

WO2016186507A1 - Calibration of a near infrared measurement unit using simulated near infrared spectra obtained from measured mid infrared spectra

Info

Publication number: WO2016186507A1
Application number: PCT/NL2016/050366
Authority: WO
Inventors: Hermanus Wouter VEDDER; Thomas TERHOEVEN-URSELMANS
Original assignee: Tree Of Knowledge Patents B.V.
Priority date: 2015-05-21
Filing date: 2016-05-23
Publication date: 2016-11-24
Also published as: NL2014836B1; NL2014836A; EP3298384A1

Abstract

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. The method comprising a step of providing a multiple number of near infrared calibration data of a mineral and/or organic sample class said near infrared calibration data including a simulated near infrared spectrum measurement. Further, the method comprises a step of feeding a calibration model of near infrared measurements with the multiple number of near infrared calibration data. Here, at least a subset of the near infrared calibration data is based on mid infrared measurements.

Description

CALIBRATION OF A NEAR INFRARED MEASUREMENT UNIT USING SIMULATED NEAR INFRARED SPECTRA OBTAINED FROM MEASURED MID INFRARED SPECTRA

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. Near infrared

measurements are relatively simple and cheap, but generally need many calibration measurements for providing relatively accurate results. Wet chemical analysis provides accurate calibration data to be fed into a calibration model, but is elaborate, complex, time consuming and expensive.

Further, mid infrared measurement units are known for the same purpose. However, 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. On the other hand, less calibration measurements are required for providing relatively accurate results.

In practice, mid infrared measurement units are applied when a relatively low number of measurements has to be carried out, and the price per measurement is less relevant. Near infrared measurements are attractive in case a relatively high number of measurements has to be carried out, and the price per measurement is an issue. It is an object of the invention to provide a less elaborate calibration method according to the preamble for calibrating an near infrared measurement unit. Thereto according to an aspect of the invention, at least a subset of the near infrared calibration data is based on mid infrared measurements.

By using mid infrared measurements for providing near infrared calibration data in the calibration process of near infrared measurements, at least a subset of calibration data based on wet chemical analysis are superfluous, thereby rendering the calibration process less elaborate, less time consuming and less expensive.

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.

Other advantageous embodiments according to the invention are described in the following claims.

By way of example only, embodiments of the present invention will now be described with reference to the accompanying figures in which

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, and

Fig. 5 shows a flow chart of an embodiment of a method according to the invention.

The figures merely illustrate a preferred embodiment according to the invention. In the figures, the same reference numbers refer to equal or corresponding parts.

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 λ. 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

superposition of spectral responses generated by molecules contained in the sample. In principle, 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. Generally, by interpreting curve characteristics, numerical values for the physical, chemical and/or biological parameters can be determined. The physical, chemical and/or biological parameter of the mineral and/or organic sample to be

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

wavelength λ. In the shown diagrams 1, 11, the near infrared spectra ranges between circa 8000 and circa 4000 cm ¹, while the mid infrared spectra ranges between circa 4000 and circa 500 cm ¹. However, the near infrared spectra and the mid infrared spectra range can be slightly different.

Generally, 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.

However, 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. Further, 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. Preferably, 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. By 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. Here, 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.

For a specific class of samples, 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

measurements. Then, 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. It is noted that, in practice, 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. Then, 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.

Then, then real mid infrared spectra measurements Ml, M2, M3,

M4 are converted into near infrared calibration data C l, C2, C3, C4, using a conversion model. Generally, 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. So, 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. By converting mid infrared spectra measurements into the near infrared spectrum, virtual near infrared spectra measurements are modelled or simulated that can be used for calibrating the near infrared measurement unit. Then, the number of wet chemical calibration measurements can be reduced while maintaining an accuracy level of the near infrared

measurement unit. In addition, near infrared calibration data

advantageously include a value of a physical, chemical and/or biological parameter determined in said mid infrared spectra measurements.

Further, 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. Now, 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. In principle, 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

measurements. By using the mid infrared spectra measurements Ml, M2, M3, M4, a calibration process can be applied on the near infrared

measurement unit 20 to enable relatively accurate near infrared

measurements.

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. As described above, 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.

In Fig. 4, the wet calibration measurements correspondence in the mid infrared calibration scheme and the near infrared calibration scheme has been indicated with a double arrow, while the correspondence in the virtual near infrared calibration data based on mid infrared measurements has been indicated with a single arrow.

The above described process can be repeated for other sample classes, thereby rendering the near infrared measurement unit operational for performing measurements on the respective sample classes. 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. In principle, 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. However, in principle, the conversion model may include a computation model based on theoretic molecule models.

It is noted that in the above described calibration method, 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. In an alternative embodiment, the entire set of near infrared

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. Here, at least a subset of the near infrared calibration data is based on mid infrared measurements. Advantageously, 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. In this process, 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. Then, the calibration data include both the converted mid infrared spectra measurements and the above- mentioned predictions associated with said mid infrared spectra

measurements.

Optionally, 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. Then, 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. The

conversion into a conditioned near infrared measurement spectrum can be performed using a conditioning converting model, e.g. based on empirical data. Optionally, the conditioning converting model determines at least one weather and/or structure parameter from the near infrared measurement itself. Alternatively or additionally, 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 invention is not restricted to the embodiments described herein. It will be understood that many variants are possible.

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.

These and other embodiments will be apparent for the person skilled in the art and are considered to fall within the scope of the invention as defined in the following claims. For the purpose of clarity and a concise description features are described herein as part of the same or separate embodiments. However, it will be appreciated that the scope of the invention may include embodiments having combinations of all or some of the features described.

Claims

1. 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, or a sample including food material, chemical, petrochemical material including plastic material, oil and/or gas, pharmaceutical substances and/or biomaterial, 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,

wherein at least a subset of the near infrared calibration data is based on mid infrared measurements,

and wherein a conversion model is used for converting a mid infrared measurement into near infrared calibration data, said near infrared calibration data including a simulated near infrared spectrum

measurement.

2. A method according to claim 1, wherein the 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.

3. A method according to claim 1 or 2, wherein the conversion model is based on empirical information.

4. A method according to claim 1, 2 or 3, wherein the near calibration data include a value of a physical, chemical and/or biological parameter determined in the corresponding mid infrared measurement.

5. A method according to any of the preceding claims, wherein the mid infrared measurement are obtained using a mid infrared measurement unit that has been calibrated using wet chemical calibration measurements.

6. A method according to any of the preceding claims, wherein the mineral and/or organic sample class is soil, plant, food and/or manure.

7. A method according to any of the preceding claims, wherein the physical, chemical and/or biological parameter of the mineral and/or organic sample to be characterized is e.g. dry substance content, nitrogen content, sulfur content and/or pH value.

8. A near infrared measurement unit for characterizing a physical, chemical and/or biological parameter of a mineral and/or organic sample, or a sample including food material, chemical, petro-chemical material including plastic material, oil and/or gas, pharmaceutical substances and/or biomaterial, comprising a near infrared sensor and a processing unit for retrieving a numerical value of said physical, chemical and/or biological parameter based on a near infrared sensor measurement performed by the sensor, the near infrared measurement unit being cahbrated by the steps of: - providing a multiple number of near infrared calibration data of a mineral and/or organic sample class, and

measurement..

9. A computer program product for calibrating a near infrared measurement unit for characterizing a physical, chemical and/or biological parameter of a mineral and/or organic sample, or a sample including food material, chemical, petro-chemical material including plastic material, oil and/or gas, pharmaceutical substances and/or biomaterial, the computer program product comprising computer readable code for causing a processor to perform a process including the steps of:

measurement..