Method of determining a primary carbon parameter of a selected material
Patent Information
- Application Number
- PCT/DK2026/060045
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2025-04-16
- Filing Date
- 2026-04-10
- Publication Date
- 2026-10-22
Smart Images
Figure DK2026060045_22102026_PF_FP_ABST
Abstract
Description
[0001] P85917PC01
[0002] 1
[0003] METHOD OF DETERMINING A PRIMARY CARBON PARAMETER OF A SELECTED MATERIAL
[0004] TECHNICAL FIELD
[0005] The invention relates to a method of determining primary carbon parameter of a selected material and a system comprising an NMR apparatus. More specifically, the invention relates to a method of determining a primary carbon parameter based on an established secondary carbon parameter of a material, such as a complex material, such as a food product.
[0006] BACKGROUND ART
[0007] In various industries, including the food and biorefining industry, accurate determination of the composition of materials, especially complex materials comprising several components such as fat, water, proteins, carbohydrates, nucleic acids, and nutrients, is critical. Chemical interactions and physical properties between the components in complex materials often makes quantitative composition analysis challenging.
[0008] Many applications, including a production facility, demand a continuous or frequent determination of the composition of components in materials for example by means of flow analysis to monitor variations.
[0009] Methods for quantitative composition analysis are known in the prior art. Mass spectrometry, titration, chromatography, and ICP (Inductively Coupled Plasma) spectroscopy are examples of previously used methods. However, these methods are time consuming, require expensive instrumentation and skilled professionals to run.
[0010] Another known method for determination of the fat content in foods is the Soxhlet method, in which a solvent extraction followed by weighing of the remaining fat is performed.
[0011] Alternatively, nuclear magnetic resonance (NMR) spectroscopy using the signal from hydrogen (1H) in the molecules of the components combined with a prior drying process to avoid disturbance from signals from water has previously been used. However, these methods often require extensive sample preparation and are time-consuming and expensive, and thereby ineffective for continuous or frequent determination of the composition of components in materials.
[0012] Thus, there is a need for an improved method that provides an efficient and cost-effective determination of a composition of a material with high accuracy.
[0013] DISCLOSURE OF THE INVENTIONP85917PC01
[0014] 2
[0015] An objective of the invention is to provide a method for determining a primary carbon parameter of a material, which method is relatively fast and provide a determination with a high accuracy, even where the selected material comprises additional components.
[0016] In an embodiment, an objective of the present invention is to provide a method of determining of determining a primary carbon parameter that is a fat parameter, or a carbohydrate parameter based on13C NMR intensity data of a sample of the selected material, which is non-destructive and relatively fast.
[0017] In an embodiment, an objective of the present invention is to provide a method of determining a primary carbon parameter of a selected material when a secondary carbon parameter of the same selected material is established, wherein the method is desirable accurate and cost-effective.
[0018] In an embodiment, an objective of the present invention is to provide a method of determining a primary carbon parameter of a selected material from carbon data representing a relationship between carbon content and13C NMR signal(s) intensity that may be performed as a non-destructive method with a relatively low workload.
[0019] In an embodiment, an objective of the present invention is to provide a system for use in determining a primary carbon parameter in a selected material, which is fast, relatively simple and with a high accuracy even where the selected material comprises additional components.
[0020] These and other objects have been solved by the invention or embodiments thereof as defined in the claims and as described herein below.
[0021] It has been found that the invention or embodiments thereof have a number of additional advantages, which will be clear to the skilled person from the following description.
[0022] The present invention provides an improved and non-destructive method which is reliable and efficient, and which can determine a primary carbon parameter from a material and even complex materials with multiple components that may interact with each other. Further, the method of the invention can be used in a very flexible way e.g. by performing the measurements on site and / or in-line or by taking suitable samples.P85917PC01
[0023] 3
[0024] The method and systems of the invention and preferred embodiments thereof will be described further below.
[0025] It should be emphasized that the term “comprises / comprising” when used herein is to be interpreted as an open term, i.e. it should be taken to specify the presence of specifically stated feature(s), such as element(s), unit(s), integer(s), step(s) component(s) and combination(s) thereof, but does not preclude the presence or addition of one or more other stated features. Reference made to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with an embodiment is included in at least one embodiment of the subject matter disclosed. Thus, the appearance of the phrases “in one embodiment” or “in an embodiment” in various places throughout the specification is not necessarily referring to the same embodiment. Further, the skilled person will understand that particular features, structures, or characteristics may be combined in any suitable manner within the scope of the invention as defined by the claims.
[0026] The term "substantially" should herein be taken to mean that ordinary product variances and tolerances are comprised.
[0027] Reference made to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with an embodiment is included in at least one embodiment of the subject matter disclosed. Thus, the appearance of the phrases “in one embodiment” or “in an embodiment” in various places throughout the specification is not necessarily referring to the same embodiment. Further, the skilled person will understand that particular features, structures, or characteristics may be combined in any suitable manner within the scope of the invention as defined by the claims.
[0028] The method of the invention is directed to determining a primary carbon parameter of a selected material. The primary carbon parameter is characterized in that it represents a fat content of the selected material and / or carbohydrate content of the selected material. Thus, the primary carbon parameter contributes with a valuable information about and a characteristic of the selected material.P85917PC01
[0029] 4
[0030] The method of the invention of determining a primary carbon parameter of a selected material, comprises
[0031] • providing a material sample comprising at least a portion of the selected material,
[0032] • applying the material sample in a nuclear magnetic resonance apparatus, wherein the NMR apparatus is a low field apparatus,
[0033] • performing an NMR reading comprising subjecting the material sample to one or more pulse sequences and recording at least one NMR signal of at least one NMR active isotope, wherein the at least one NMR active isotope comprises13C, and wherein the NMR signal comprises NMR intensity data of at least a portion of carbon present in the selected material and recording said at least one NMR signal as material NMR data,
[0034] • determining the primary carbon parameter of the selected material from the material NMR data comprising correlating the material NMR data to carbon data comprising data representing a relationship between a carbon content and an associated13C NMR signal, and
[0035] wherein the primary carbon parameter comprises
[0036] i) a fat parameter representing a fat content of the selected material or ii) a carbohydrate parameter representing a carbohydrate content of the selected material.
[0037] The material sample may be constituted entirely of the selected material or it may comprise a portion of the selected material in the form of a dilution thereof, wherein if the dilution material is advantageously free of carbon containing component or alternatively where the carbon content of the dilution material is known.
[0038] The determining of the primary carbon parameter of the selected material from the material NMR data may comprise correlating the material NMR data to carbon data comprising at least one set of data representing a relationship between carbon content of at least one reference sample and an associated13C NMR signal.
[0039] Advantageously, the selected material comprises fat and / or carbohydrate.P85917PC01
[0040] 5
[0041] In an embodiment, the fat parameter comprises the content of fat of the selected material and / or the carbohydrate parameter comprises the content of carbohydrate of the selected material, such as the content of sugar of the selected material.
[0042] In an embodiment, the carbohydrate parameter represents a sugar content of the selected material.
[0043] Thus, the method of the invention has been found to provide a valuable tool for evaluating a selected substance, e.g. by determining a fat content of the selected material or a carbohydrate content of the selected material to evaluate if the determined content is within production or laboratory standards or if a quality parameter of the selected material is fulfilled, or if the selected material has a composition within a preselected range, or to provide information for labelling.
[0044] The content of a component is herein used to refer to the mass content, such as weight per product weight or weight per product volume, or to percentage composition, such as weight percentage (wt%) or weight per volume (w / v). The term “product” may herein designate a selected quantity of the selected material.
[0045] The inventors of the present invention have found that the method of the invention provides a very effective tool for characterizing a selected material by determining the primary carbon parameter of a component in the selected material using NMR intensity data. Especially, it has been found that there is a correlation between the NMR intensity of13C related to a carbon containing component in the selected material and the carbon content of the selected material, which can be used to determine the content of the carbon containing component in the selected material. Thus, the method may provide a very detailed analysis of ths selected substance, which may be demonstrated, embedded in or even directly revealed by the determination of the primary carbon parameter.
[0046] Nuclear magnetic resonance - abbreviated NMR - is a phenomenon, which occurs when the nuclei of an isotope with a nuclear spin in a magnetic field absorb and re-emit electromagnetic radiation. The emitted electromagnetic radiation has a specific resonance frequency, which depends on the strength of the magnetic field and the magnetic properties of the isotope. NMR allows the observation of specific quantum mechanicalP85917PC01
[0047] 6
[0048] magnetic properties of the atomic nucleus. Many scientific techniques exploit NMR phenomena to study molecular physics, liquids, crystals, and non-crystalline materials through NMR spectroscopy. NMR is also routinely used in advanced medical imaging techniques, such as in magnetic resonance imaging (MRI).
[0049] An NMR measurement is performed by NMR spectrometer or NMR relaxometer, here also referred to as an NMR apparatus.
[0050] The terms "spectroscopy" and "spectrometry" are used interchangeable and in the same way a spectroscope is the same as a spectrometer.
[0051] NMR spectroscopy is well known in the art and has for many years been applied for laboratory measurements in particular where other measurement methods could not be used. NMR spectroscopy is performed using an NMR spectrometer. Examples of spectrometers are e.g. described in US 6,310,480 and in US 5,023,551. The term NMR spectrometer also includes an NMR relaxometer.
[0052] General background of NMR formation evaluation can be found, for example in U.S 5,023,551.
[0053] A general background description of NMR measurement can be found in "Understanding NMR Spectroscopy" by James Keeler, John Wiley & Sons Ltd, 2005 or in a practically oriented setting in, e.g., "NMR Logging Principles and Applications" by George R. Coates et al, Halliburton Energy Services, 1999. See in particular chapter 4.
[0054] The term “selected material” is herein used to mean a material, which is selected to be analyzed by an embodiment of the method according to the invention by determining the primary carbon parameter.
[0055] The term “component” is herein used to mean any element or group of elements of the selected substance. Examples of components and groups of components comprises water, small organic compounds, carbohydrate, fat, and protein.P85917PC01
[0056] 7
[0057] The term “primary carbon parameter” is herein used to mean a parameter to be determined representing a carbon content of the selected material or a content of a component in the selected material comprising carbon.
[0058] The term “secondary carbon parameter" is herein used to mean a parameter that is established and representing a carbon content of the selected material or a content of a component in the selected material comprising carbon.
[0059] In an embodiment, the primary carbon parameter is established to represent one of the fat parameter representing the fat content of the selected material and the carbohydrate parameter representing the carbohydrate content of the selected material and the secondary carbon parameter is established to represent the other one of the fat parameter representing the fat content of the selected material and the carbohydrate parameter representing the carbohydrate content of the selected material.
[0060] The term “established” is herein used to mean that the parameter or factor has been determined or has been estimated prior to determine the primary carbon parameter, so that the established parameter or factor is known when determining the primary carbon parameter.
[0061] In an embodiment, the selected material comprises fat and carbohydrate, and wherein a content of carbon from both of carbohydrate and fat is recorded and included in the material NMR data.
[0062] In an embodiment, the recorded13C NMR signal intensity is associated with either the fat content or the carbohydrate content.
[0063] In an embodiment, the determining of the primary carbon parameter comprises establishing the primary carbon parameter by correlating the material NMR data to the carbon data.
[0064] The carbon data may advantageously comprise carbon fitting data, wherein the carbon fitting data represents a relationship between carbon content and associated13C NMR signal.P85917PC01
[0065] 8
[0066] In an embodiment the carbon data comprising carbon calibration data, wherein the carbon calibration data represents a carbon calibration curve of13C NMR signal intensity relative to carbon mass content.
[0067] Thus, the inventors have realized that a relationship between13C NMR signal intensity and carbon content can be established, and which can be used to efficiently determine a primary carbon parameter of a selected material.
[0068] In addition, the inventors have provided a method for distinguishing between fat content and carbohydrate based on the determined primary carbon parameter and optional the determined secondary carbon parameter.
[0069] In an embodiment, the obtaining of the carbon fitting data comprises
[0070] • providing a plurality of reference samples with a known content of a carbon containing component selected from fat and carbohydrate, wherein at least two of the plurality of reference samples comprises a different content of the carbon containing component,
[0071] • determining the carbon content of each of the plurality of reference samples from the carbon containing component content,
[0072] • performing an NMR reading of each of the plurality of reference samples comprising subjecting the material sample to one or more pulse sequences and recording at least one reference NMR signal intensity of the least one NMR active isotope comprising13C, wherein the reference NMR signal comprises NMR intensity data of at least a portion of carbon present in the respective reference sample, and
[0073] • processing said recorded NMR signal and said determined carbon content for each of the plurality of references samples by applying a regression analysis or iterative fitting of data to model the relationship between carbon content and the associated13C NMR signal intensity and obtaining said carbon fitting data.
[0074] In an embodiment, the regression analysis comprises performing a linear regression or a second order regression to obtain said carbon fitting data representing a relationship between carbon content and an associated13C NMR signal intensity.
[0075] In an embodiment, the number of the reference samples is at least 4, such as at least 6. The number of reference samples may in principle be any number from 2 and higher.P85917PC01
[0076] 9
[0077] However, it has been found that even a relatively low number of reference samples may be sufficient to ensure a relatively high accuracy of the determination of the primary carbon parameter. Therefore, the number of the reference samples may conveniently be from 2 to 20, such as from 4 to 10.
[0078] The inventors have found and realized that correlating the material NMR data to carbon fitting data representing a relationship between carbon content and an associated13C NMR signal intensity provides a surprisingly fast and highly accurate tool for determining a primary carbon parameter and optionally a secondary carbon parameter of the selected material and thereby determine a fat content and / or a carbohydrate content of the selected material.
[0079] Advantageously, the carbon content from fat is determined as 77 wt% of the fat content in the respective reference sample.
[0080] Advantageously, the carbon content from carbohydrate is determined as 42 wt% of the carbohydrate content of the respective reference sample.
[0081] In an embodiment, the carbon content of respective fat and carbohydrate of a reference sample may be determined based on another conversion parameter. However, the inventors have realized that 77 wt% and 42 wt% provides a relatively good estimate when determining or estimating the carbon content from respectively fat and carbohydrate in the respective reference sample where the content of fat and / or carbohydrate is known independently of the type of fat or the type of carbohydrate. The representative conversion parameter of 77% were established from linoleic acid (C18H32O6), where carbon accounts for 77% of the weight per linoleic acid molecule. The conversion parameter of 42% were established from glucose or fructose (CeH^Oe), where carbon accounts for 42% of the weight per glucose or fructose molecule.
[0082] In an embodiment, the at least a portion of carbon recorded in the NMR signal of the material sample and the at least a portion of carbon recorded in the reference NMR signal of at least one of the plurality of reference samples are proportionally similar within a range of up to 10% based on the material sample, such as up to 8%, such as up to 5%.P85917PC01
[0083] 10
[0084] The term “portion” is herein used to mean a part of a given quantity or amount. The given quantity may not be known.
[0085] In an embodiment, the primary carbon parameter comprises a carbon characteristic representing a carbon content of the selected material, such as a total carbon content of the selected material.
[0086] Thus, the method of the invention has been found to provide a valuable tool for use in productions of carbon containing products, for example for evaluating a composition of a selected material by determining the total carbon content of the selected material, which may be used as a quality parameter.
[0087] Thus, the method of the invention has been found to provide a valuable tool for use in productions for example for controlling a quality parameter of a raw material, a precursor material, and / or a produced material, such as a food selected material for example as a part of a process control during production.
[0088] In an embodiment, the selected material comprises both fat and carbohydrate, and wherein a secondary carbon parameter of the selected material is established.
[0089] In an embodiment, determining of the primary carbon parameter comprises
[0090] • processing the material NMR data comprising
[0091] o determining a secondary NMR data portion of the material NMR data originating from the secondary carbon parameter,
[0092] o determining a primary NMR data portion of the material NMR data originating from the primary carbon parameter comprising subtracting the secondary NMR data portion from the material NMR data and o determining the primary carbon parameter from the primary NMR data portion.
[0093] Advantageously, the primary carbon parameter and the secondary parameter respectively comprises
[0094] iii) a fat parameter representing a fat content of the selected material or iv) a carbohydrate parameter representing a carbohydrate content of the selected material, andP85917PC01
[0095] 11
[0096] wherein one of the primary or secondary carbon parameter is ii) and the other one of the primary or secondary carbon parameter is iv).
[0097] The determining of the secondary NMR data portion may advantageously comprise determining a calculated NMR13C intensity of the secondary carbon parameter and adjusting the calculated NMR13C intensity of the secondary carbon parameter with a secondary correlation factor to obtain an adjusted secondary parameter NMR intensity representing the secondary NMR data portion.
[0098] The term “calculated NMR” may advantageously be based on the assumption that essentially all NMR signals of the respective spin-active isotope is considered, measured or recorded.
[0099] In an embodiment, the term “calculated NMR” may be based on the assumption that at least 99% of all NMR signals of the respective spin-active isotope is considered, measured or recorded.
[0100] In an embodiment, the calculated NMR13C intensity of the secondary carbon parameter is determined comprising correlating the established secondary carbon parameter to the carbon data comprising carbon calibration data, wherein the carbon calibration data represents a carbon calibration curve of13C NMR signal intensity relative to carbon mass content.
[0101] In an embodiment, the determining of the primary carbon parameter from the primary NMR data portion, comprises adjusting the primary NMR data portion with a primary correlation factor to determine a calculated NMR13C intensity of the primary carbon parameter and determining the primary carbon parameter from the determined calculated NMR13C intensity of the primary carbon parameter.
[0102] In an embodiment, the determining of the primary carbon parameter from the calculated NMR13C intensity of the primary carbon parameter comprises correlating the calculated NMR13C intensity of the primary carbon parameter to the carbon data comprising carbon calibration data, wherein the carbon calibration data represents a carbon calibration curve of13C NMR signal intensity relative to carbon mass content.P85917PC01
[0103] 12
[0104] The inventors have realized that the method provides an accurate and efficient tool for determining a primary carbon parameter from a selected material, such as a fat content of the selected material when a secondary carbon parameter, such as a carbohydrate content of the selected material is established. Especially,
[0105] In an embodiment, obtaining of the carbon calibration data comprises performing at least one NMR intensity determination of at least one reference samples with a known carbon content, and wherein the reference sample preferably is selected from a lower alcohol or a polyol, such as glycerol.
[0106] In an embodiment, the at least one NMR intensity determination comprises performing an NMR reading comprising subjecting the respective sample to one or more pulse sequences and recording at least one NMR signal of the at least one NMR active isotope, wherein the at least one NMR active isotope comprises13C.
[0107] In an embodiment, NMR intensity determination comprises performing an NMR reading comprising subjecting the respective sample to one or more pulse sequences and recording at least one NMR signal intensity of the at least one NMR active isotope, wherein the at least one NMR active isotope comprises13C.
[0108] Advantageously, the obtaining of the carbon calibration data comprises performing at least one NMR intensity determination of a plurality of reference samples with a known carbon content, wherein at least two of the plurality of reference samples have a different carbon content, and wherein at least one of the reference samples, preferably is selected from a lower alcohol or a polyol, such as glycerol.
[0109] In an embodiment, the obtaining of the carbon calibration data comprises performing at least one NMR intensity determination of a reference sample, wherein the reference sample comprises carbon.
[0110] Advantageously, the low field apparatus is adapted for operating at a magnetic field up to 2 T, such as up to 1 T, such as up to 750 mT.
[0111] The low-field NMR apparatus preferably comprises a permanent magnet for generating the magnetic field for performing the NMR readings.P85917PC01
[0112] 13
[0113] Whereas it is well known that a low-field NMR apparatus configured for operating based on a permanent magnet may have a much lower homogeneity than where the apparatus comprises a superconducting magnet and / or where the NMR apparatus is configured a high field such as above 2 T, such as above 5 T or even higher, it has been found that the use of a low field NMR apparatus in the method of the present invention surprisingly ensures a very accurate result and in addition operated very fast, which for many application is highly desirable or even a need.
[0114] In addition, such a low-field NMR apparatus is also much less costly both in acquisition and in operation and in addition the low-field NMR apparatus may be easily transported e.g. by being arranged on a wheeled wagon and / or being equipped with wheels.
[0115] In an embodiment, the at least one NMR active isotope is at least two different NMR active isotopes comprising13C and at least one NMR active isotope selected from the list containing of1H,14N,19F,23Na,35 / 37CI and31P. Two or more different NMR active isotopes may be relevant when analyzing specific complex foods, wherein chemical interactions between atoms makes it more complicated to determine a primary carbon content.
[0116] In an embodiment, the NMR reading and / or the NMR intensity determination may be performed using a Carr-Purcell-Meiboom-Gill experiment.
[0117] Advantageously, the one or more pulse sequences used to generate the carbon calibration data is the same as the one or more pulse sequences used to obtain material NMR data for the selected material.
[0118] In an embodiment, the NMR reading and / or the NMR intensity determination is performed using at least one of DEPT (Distortionless Enhancement by Polarization Transfer), DEPTQ (DEPT with retention of Quaternaries), HSQC (Heteronuclear Single Quantum Coherence), INEPT (Insensitive Nuclei Enhanced by Polarization Transfer), BIRD (Bilinear Rotation Decoupling pulses), TANGO (Testing for Adjacent Nuclei with a Gyration Operator) or NOE (Nuclear Overhauser Effect).
[0119] Advantageously, the selected material is a food product, such as a dairy product, meat, fish, vegetables or any fragments or combinations thereof.P85917PC01
[0120] 14
[0121] The term organic macronutrients are herein used to refer to carbon-based macronutrients. Carbon-based macronutrients comprise fats, carbohydrates and proteins.
[0122] A correlation factor is used to calibrate the NMR signal depending on the difference between the observed carbon-13 and the known content of carbon-13. Typically, a correlation factor for each organic macronutrient in the correlation sample will be determined.
[0123] In an embodiment, the primary correlation factor and / or the secondary correlation factor is determined by estimating the primary correlation factor and / or the secondary correlation factor from historical NMR intensity data. Historical NMR intensity data is NMR intensity data obtained in the past. Examples of historical NMR intensity data comprise NMR intensity data from previous conducted NMR experiments, NMR intensity data from other relevant NMR experiments, NMR intensity data from relevant textbooks and similar.
[0124] In an embodiment, the primary and / or the secondary correlation factor is determined comprising performing at least one NMR intensity determination of each of a plurality of correlation samples with a known fat and carbohydrate content to obtain a set of correlation NMR data, and processing said set of correlation NMR data and the known content of fat and carbohydrate in the plurality of correlation samples to obtain the primary and / or the second correlation factor.
[0125] Advantageously, at least two of the plurality of correlation samples have a different content of fat and / or carbohydrate.
[0126] In an embodiment, the processing comprises
[0127] determining a calculated NMR intensity of each of the plurality of correlation samples by correlating the known content of fat and carbohydrate in the plurality of correlation samples to carbon calibration data,
[0128] estimating or determining the carbon content for respective fat and carbohydrate for each of the plurality of correlation samples,
[0129] determining the primary and / or the secondary correlation factor from a system of equations based on a formula F, wherein each correlation sample of the plurality of correlation samples is represented by an equation F:P85917PC01
[0130] 15
[0131] Y
[0132]
[0133] xCalculatedNMRx* (jji * carboncarboh.ydratex"T Q2 *
[0134] In formula F, Y is the NMR intensity of the respective correlation sample in the set of correlation NMR data, calculatedNMR is the calculated NMR intensity of the respective correlation sample, carboncarbohydrate is the estimated or determined carbon content from carbohydrate of the respective correlation sample, carbonfat is the estimated or determined carbon content from fat of the respective correlation sample, qi and q2 are the respective correlation factors, and x is the number of correlation samples.
[0135] The correlation factors, qi and q2, may be determined or estimated, such as by evaluating previous experiments with similar selected materials or material types. The correlation factors can be determined from a system of equations comprising at least two equations based on formula F. In an embodiment, each of the correlation factors provides a scaling of the carbon from either fat or carbohydrate.
[0136] It has been found that the correlation factors provide a desirable accurate determination of the primary carbon parameter in a selected material, especially when the selected material is a complex selected material where a portion of the total carbon is detected, which makes it possible to use low field NMR to determine a primary carbon parameter efficiently, for example in a production as an on-line or in-line monitoring of the produced material, e.g. for quality control.
[0137] The inventors have realized that the method of the invention provides a desirable accurate tool for determining a primary carbon parameter of a selected material, such as a carbohydrate or a fat content of a food product, using a low field NMR apparatus, by determining a correlation factor for each relevant carbon containing component in the selected material to compensate for carbon in the selected material, which is not detected by the low field NMR apparatus. Thus, using the method of the invention it is possible to use a low field NMR apparatus for determining a primary carbon parameter efficiently and cost-effective.
[0138] In an embodiment, qi is the primary correlation factor and q2 is the secondary correlation factor, or wherein qi is the secondary correlation factor and q2 is the primary correlation factor.P85917PC01
[0139] 16
[0140] Advantageously, the plurality of correlation samples and the selected material is from a single material type.
[0141] The term “material type” is herein used to mean a class of materials, which may be defined based on their composition, degree of processing, or chemical structure. A material type may also be used to define different food products, such as fresh food, processed food, ultra-processed foods, dairy products, meat, meat alternatives, grains and cereals, beverages and snacks. The different examples may even be further classified into more specific material types, such as ketchup, mayonnaise, chips and rye bread.
[0142] The terms “material type” and “material species” may be applied interchangeable.
[0143] In an embodiment, the plurality of correlation samples and the selected material comprises fat, and wherein the fat comprises a carbon chain length between 4 to 24 carbon atoms, preferably between 4-12 carbon atoms. Carbon chain length is herein used to refer to the amount of carbon atoms in a molecule.
[0144] In an embodiment, the plurality of correlation samples and the selected material comprises carbohydrate, and wherein the carbohydrate in the correlation samples and the selected material comprises a carbon chain length between 5 to 12 carbon atoms, preferably between 4 to 6 carbon atoms.
[0145] In an embodiment, the plurality of correlation samples comprises an organic macronutrient profile similarity of at least 60% compared to the selected material, preferably at least 70%, more preferably at least 85%.
[0146] Advantageously, the organic macronutrient profile is associated with or represents the content of carbon-containing macronutrients.
[0147] In an embodiment, the carbon-containing macronutrients are selected from the list containing fat, carbohydrate, nucleic acids, and protein.P85917PC01
[0148] 17
[0149] In an embodiment, the selected material is a multi-component material comprising at least two components selected from the list containing water, small organic compounds, carbohydrate, fat, and protein.
[0150] A multi-component material and a complex material are herein used interchangeably.
[0151] In an embodiment, the multi-component material comprises at least two components selected from the list containing carbohydrate, fat, and protein.
[0152] In an embodiment, the material sample is a liquid material sample, preferably an aqueous material sample.
[0153] In an embodiment, the selected material is a food product, and wherein the material sample is a flowable material sample, optionally the material sample is a diluted material sample or a concentrated material sample of the food product.
[0154] Advantageously, the selected material is a solid food product, and preferably wherein the material sample comprises the solid food product dissolved and / or suspended in a liquid.
[0155] In an embodiment, the selected material comprises a weight percentage (wt%) of fat or carbohydrate above 30 wt%, preferably above 40wt%, such as above 50wt%.
[0156] The weight percentage may be determined according to any method detailed above.
[0157] In an embodiment, a difference in density between each of the plurality of correlation materials and the selected material is 0.5 g / cm3or below, preferably 0.35 g / cm3or below, more preferably 0.3 g / cm3or below.
[0158] In an embodiment, the selected material comprises at least 10 % liquid by volume of the selected material, such as at least about 25 %, such as from about 40 % to 95% liquid by volume of the selected material.
[0159] In an embodiment, the fat parameter comprises the content of fat of the selected material and / or wherein the carbohydrate parameter comprises the content of the carbohydrate of the selected material.P85917PC01
[0160] 18
[0161] In an embodiment, where the selected material comprises proteins and / or nucleic acids, the method comprises suppressing NMR signal intensity of carbon of proteins and / or nucleic acids. The suppression of NMR signal intensity of carbon of proteins and / or nucleic acids may be performed by selecting the magnetic field to be very low e.g. below 1 T, such as below 0.5 T.
[0162] The invention also comprises a system. The system comprises an NMR apparatus and means for executing the steps of the method according to any one of the embodiments detailed above.
[0163] Advantageously, the means for executing the steps of the method comprises a device, such as a computer, adapted to execute the method of the invention. Advantageously, the NMR apparatus and the device are connected, such as wireless connected to each other.
[0164] Preferably, the NMR apparatus is a low field NMR apparatus adapted for operating at a magnetic field up to 2 T, such as up to 1 T, such as up to 750 mT.
[0165] The invention also comprises a computer program comprising instructions to cause the system of the invention to execute the steps of the method of the invention.
[0166] The invention also comprises a computer-readable medium having stored thereon the computer program of the invention.P85917PC01
[0167] 19
[0168] BRIEF DESCRIPTION OF THE EXAMPLES AND FIGURES
[0169] In the following, the invention will be further illustrated by the description of a number of illustrative and non-limiting embodiments and examples of the present invention, with reference to the appended drawings.
[0170] The figures are schematic, are not drawn to scale, and may be simplified for clarity.
[0171] Throughout, the same reference numerals are used for identical or corresponding parts.
[0172] Figure 1 is a process diagram illustrating an embodiment of the method of the invention comprising determining a primary carbon parameter of a selected material.
[0173] Figure 2 is a process diagram illustrating an embodiment of the method of the invention comprising determining a primary carbon parameter of a selected material comprising fat or carbohydrate
[0174] Figure 3 is a process diagram illustrating an embodiment of the method of the invention comprising obtaining carbon fitting data.
[0175] Figure 4 is a process diagram illustrating an embodiment of the method of the invention comprising determining a primary carbon parameter when one component is established.
[0176] Figure 5 illustrates results of Example 1 , showing that the method of the invention can be used to determine the fat content of a complex food product.
[0177] Figures 6a and 6b illustrate results of Example 2.
[0178] With reference to Figure 1 , an embodiment of the method of the invention will now be detailed.
[0179] In step 10, a sample of a selected material is provided. As shown in Example 1 a selected material may be a mayonnaise product. The sample is usually a complex material comprising different components, such as carbohydrate, fat, water, and protein. In step 11, the sample is applied to an NMR apparatus which operates in a low field typically between 0.3 - 2 T. The applied sample may be a fluid sample or a solid sample of theP85917PC01
[0180] 20
[0181] selected material. Preferably, a solid sample is diluted before applied to the NMR apparatus.
[0182] In step 12, the NMR apparatus performs an NMR reading of the13C isotope to obtain NMR intensity data of the sample based on the amount of carbon present in the sample. Interactions between molecules may influence the NMR signal intensity. Sometimes several isotopes are included to provide more information about the composition of the selected material. In step 13, the primary carbon parameter is determined based on the NMR intensity data of the sample. The primary carbon parameter is determined using carbon data representing a relationship between carbon content and associated13C NMR intensity. The determined primary carbon parameter may be a fat parameter or a carbohydrate parameter, for example presented as a weight percentage (wt%), which can be used for food labelling or for monitoring a production of a selected material. There are different ways to determine the primary carbon parameter as exemplified illustrated in Figure 2 and Figure 4.
[0183] The process diagram of Figure 2 illustrates an embodiment for determining a primary carbon parameter of a selected material, wherein the primary carbon parameter is established using carbon fitting data, as shown in step 23. The primary carbon parameter is established by correlating the obtained NMR intensity data of the sample with the carbon fitting data, which is obtained from a regression analysis between carbon content and associated NMR intensity data of a plurality reference samples. One embodiment of obtaining the carbon fitting data is illustrated in Figure 3.
[0184] Figure 3 illustrates an embodiment of obtaining carbon fitting data. In step 30, a plurality (X) reference samples with a known fat and / or carbohydrate content are provided. The content of fat and / or carbohydrate are at least different for two of the X reference samples. X may be a number between 2 and 50, such as a number between 2 and 10. The reference samples are usually associated or comparable to the selected material, such as from the same material type.
[0185] In step 31 , the carbon content of each of the X reference samples is determined.
[0186] Typically, an estimated conversion parameter of 77% for fat and 42% for carbohydrate are used, but the conversion parameter may also be determined depending on the type of carbohydrate, such as type of sugar, and the type of fat present in the reference samples.P85917PC01
[0187] 21
[0188] In step 32, an NMR reading of each of the X reference samples is performed using a low field NMR apparatus to obtain NMR intensity data of the 13C isotope reflecting the amount of carbon present in each of the X reference samples. In step 33, the obtained NMR intensity data and the determined carbon content of each of the X reference samples is processed using a linear regression analysis. In some embodiments, a second order regression analysis may be preferred. The regression analysis is used to identify the relationship between carbon content and associated NMR intensity in the X reference samples. Alternatively, the obtained NMR intensity data and the determined carbon content of each of the X reference samples are processed by fitting the data to obtain an equation representing a relationship between carbon content and associated NMR intensity.
[0189] Figure 4 illustrates an embodiment of determining a primary carbon parameter from a material NMR portion when a secondary carbon parameter is established. The established secondary carbon parameter may be declared fat content or a declared carbohydrate content of the selected material.
[0190] In step 40, a secondary NMR data portion is determined based on the secondary carbon parameter. The secondary data portion may be determined by estimation or determined using a conversion parameter. The inventors have realized that a conversion parameter of 77% for fat and 42% for carbohydrate provides a desirable accurate determination.
[0191] Alternatively, the conversion parameter may be determined as detailed above. In step 41, a primary data portion of the material NMR data is determined by subtracting the secondary NMR portion from the material NMR data. Thus, from this step, a primary data portion representing the NMR intensity of a component in the selected material is obtained. From this primary data portion, the primary carbon parameter can be determined from carbon data, for example from carbon calibration data. The primary carbon parameter may be a fat content or a carbohydrate content, such as a sugar content, of the selected material.
[0192] EXAMPLE 1
[0193] Determining a primary carbon parameter in different mayonnaise samplesP85917PC01
[0194] 22
[0195] This example illustrates the use of the method of the invention for determining a fat content of mayonnaise samples when the carbohydrate content is established.
[0196] 26 mayonnaise products with a declared carbohydrate content were provided. From the 26 mayonnaise products 4 products were randomly selected to be applied as reference mayonnaise products and accordingly these 4 reference mayonnaise products were numbered 1-4 and the remaining mayonnaise products were numbered 5-26 (see Table 1). A sample of each of the 26 mayonnaise products were provided and distributed to a laboratory for determining the fat content as comparison. All data is provided in Table 1, including both fat (determined by the laboratory tests) and carbohydrate contents (as declared on the mayonnaise products) are shown as weight percentage (wt%).
[0197] Samples from the mayonnaise products 1-4 were used as reference samples for obtaining the carbon data. The carbon content was determined from the known content of carbohydrate using a conversion parameter of 42% and the determined content of fat from the laboratory using a conversion parameter of 77%. The four reference samples were applied to a low field NMR apparatus (NanoNord TVESKAEG™ NMR sensor - 1 Tesla) for obtaining NMR intensity of the13C isotope.
[0198] The obtained NMR intensity data for each of the reference samples were processed by applying a linear regression analysis of a first order to model the relationship between carbon content and the associated13C NMR signal intensity to obtain the carbon data in the form of a carbon calibration curve of13C NMR signal intensity relative to carbon mass content.
[0199] A sample from each of the 26 mayonnaise products including the reference mayonnaise products were provided and applied as a samples of respective selected materials. Each of the samples were applied to an NMR apparatus (NanoNord TVESKAEG™ NMR sensor - 1 Tesla) for obtaining NMR intensity of the13C isotope.
[0200] The13C NMR intensity was obtained using a low field NMR apparatus in a standard calibrated state.P85917PC01
[0201] 23
[0202] The carbon content from carbohydrate of each of the 26 samples were determined using a conversion parameter of 42%. From the determined carbon content from carbohydrate of each sample, it was possible to determine the secondary NMR data portion.
[0203] The fat content of each sample was then determined by subtracting the secondary NMR data portion from the obtained13C NMR intensity values to obtain a primary NMR data portion of each sample, which was correlated with carbon data to determine the fat content of each sample. The determined fat content of each mayonnaise sample is illustrated in the column “Fat, NMR (wt%) in Table 1 as wt%.
[0204] All data and results are shown in Table 1.
[0205] Table 1
[0206] Fat, Laboratory Carbohydrate, Declared Fat, NMR Product Number (wt%) (wt%) (wt%)
[0207] 1 70,0 3,0 70,3 2 69,3 3,4 67,8 3 73,5 3,2 74,7 4 51,5 5,8 50,6 5 79,6 1,4 81,3 6 26,8 8,0 25,5 7 21,4 11,4 20,4 8 78,7 0,7 76,4 9 54,0 13,1 53,8 10 29,0 6,6 27,9 11 23,1 13,3 22,0 12 65,0 5,8 62,3 13 61,0 5,4 61,5 14 30,0 5,4 29,3 15 81,0 1,4 80,2 16 26,9 8,0 26,4 17 27,0 6,1 26,5 18 26,0 6,0 25,7
[0208]
[0209] P85917PC01
[0210] 24
[0211] 19 10,1 11,0 9,1 20 52,2 6,3 50,1 21 70,1 3,0 70,1 22 67,9 2,9 69,4 23 71,7 3,4 70,8 24 52,3 4,4 52,9 25 60,2 8,3 59,7 26 20,3 13,0 19,1
[0212]
[0213] Figure 5 compares the fat content obtained using the method of the invention and the fat content obtained from the laboratory using a known method for determining fat, and from the coefficient of determination, R2, there is a statistically significant relationship within a 95% confidence interval. Thus, it is illustrated that the method of the invention can be used to determine a fat content of a complex material from13C NMR data when the carbohydrate content is established.
[0214] EXAMPLE 2
[0215] This example illustrates the use of the method of the invention for determining a degree of Brix (°Bx) of a selected material. In this example the primary carbon parameter represents a content of carbohydrate / sugar.
[0216] Commonly, °Bx is used in food industries, primarily for liquid food products to indicate sweetness by quantifying the content of sugar content I dissolved solids in liquids. Per definition, 1°Bx corresponds to 1 gram of sucrose in 100 grams of solution.
[0217] The method of the invention may in an embodiment be applied to measure °Bx for a selected material, such as a selected liquid food product.
[0218] For the present example, the fat contribution to the NMR signal is assumed to be zero. Furthermore, it was used that the total sucrose content is found as 1 / 0.42 (-1,38) times the calibrated carbon NMR measurement, and the density of the sample were calculatedP85917PC01
[0219] 25
[0220] based on measured mass / volume concentration of assumed carbohydrate and the temperature of the sample.
[0221] Using this density, the final measurement results may be provided in mass / mass concentration such as °Bx. For the present example, the density determination was performed using the density model for sucrose from the following reference: Roger Darros- Barbosa, Murat O. Balaban & Arthur A. Teixeira (2003), Temperature and Concentration Dependence of Density of Model Liquid Foods, International Journal of Food Properties, 6:2, 195-214, DOI: 10.1081 / JFP-120017815, hereby incorporated by reference.
[0222] Six sucrose solutions were prepared by dissolving different, known amounts of sucrose (regular consumer sugar) in demineralized water. A sample of each of the six sucrose solutions was applied to an NMR apparatus (NanoNord TVESKAEG™ NMR sensor - 1 Tesla) for determine the NMR intensity of the13C isotope of the respective samples.
[0223] For 5 of the samples, namely sample F205, F206, F207, F208 and F2010 with sugar content of about 2 - 50 °Bx, resulting NMR13C isotope intensity determinations were obtained as the mean of three 1 -min measurements for each sample. For the sample F209 with a relatively low sugar content, namely about 1 °Bx, the resulting NMR13C isotope intensity determinations were obtained as the mean of three 9-min measurements.
[0224] Based on the resulting NMR13C isotope intensity determinations for the six samples, the Brix degree of the respective of the six sucrose solutions were determined using the method of an embodiment of the invention as further discussed below.
[0225] Table 2 and Figures 6a and 6b show the results of measurement of samples of six sucrose solutions.
[0226] The error bars in Figures 6a and 6b indicate the standard deviations obtained from the three measurement results for each sample (the error bars are shown in both graphs but are hardly visible on the Figure A). We note that standard deviation is much smaller for the sample with sugar content of about 1 °Bx since the measuring time was longer for this sample (9 min vs. 1 min).P85917PC01
[0227] Table 2: List of sucrose solutions and the results of NMR-based Brix measurements.
[0228] Sample name Prepared (°Bx) NMR mean (°Bx)* NMR STD (°Bx)**
[0229] F205 20.00 19.75 0.23
[0230] F206 9.97 10.37 0.69
[0231] F207 4.98 5.49 0.80
[0232] F208 1.99 1.86 0.45
[0233] F209 0.99 0.99 0.15
[0234] F210 50.03 50.48 0.51
[0235]
[0236] * Mean result of three 1-min NMR measurements for samples F205 - F208 and F210, and of three 9-min measurements for sample F209.
[0237] ** Standard deviation (STD) calculated from the three NMR measurements on each sample.
[0238] Figure 6a shows Brix degree (°Bx) determined by NMR versus the known sugar content (°Bx) of the prepared samples F205-F2010 given in Table A.
[0239] Figure 6b shows Brix degree (°Bx) determined by NMR versus the known sugar content (°Bx) of the prepared samples F206-F209: Zoom of the graph shown in Figure 6a.
[0240] Opposed to some prior art Brix measurements, contents of non-carbon constituents (e.g. NaCI) in the samples subject to analysis, has no, or little, effect on the determined NMR-based Brix measurement. The only effect of NaCI concentration on the NMR-based Brix measurements are possible changes in density. Such change in density may be neglected (particularly in cases of small NaCI contents) or it may be compensated for to improve accuracy. Compensation for NaCI-induced density deviations (specific gravity different from one) may be achieved by measuring the sodium content for example using23Na NMR). Where high accuracy is demanded, similar compensation may be used for other constituents as well.P85917PC01
[0241] 27
[0242] Exemplifying the minor effect if any of NaCI, and the ability to compensate for such potential effect, NMR-based Brix determination of an embodiment of the invention was performed on a sample of a prepared aqueous solution (here called F211) comprising both sucrose and NaCI (8.95 °Bx, 10.62 w / w-% NaCI). The NMR-based Brix determination, without accounting effects of NaCI concentration on the density (only the effect from the sucrose concentration), showed 9.73 + / - 0.30 °Bx (mean + / - standard deviation of three 1-min NMR13C isotope intensity measurements). A23Na NMR-based determination showed w / v-% NaCI concentration of 11.82 + / - 0.0043 w / v-% (obtained using23Na NMR intensity measurement and scaled to NaCI by the ratio of molar masses for NaCI vs Na). Based on a reference model the density of the sample was predicted to be about 1.115 g / ml based on the sucrose and NaCI concentrations. Using this, the NMR-based NaCI determination equals 10.60 w / w-% NaCI, which is in excellent agreement with the NaCI concentration prepared of the prepared aqueOus solution F211. Moreover, using a reference model accounting for both sucrose and NaCI effects on the density, the NMR-based Brix determination shows 9.03 °Bx in excellent agreement with the content of the prepared aqueous solution F211.
[0243] Furthermore, to exemplify the use of embodiments of the method of the invention for natural products, various products have been analyzed. For example, a sample of “Rynkeby” Apple juice purchased from a local supermarket. The declared carbohydrate content of the sample was 11 g / 100 ml (of which sugars: 10 g / 100 ml). An NMR-based Brix determination was performed as described above in this example. The result of the NMR-based Brix determination showed 10.02 + / - 0.76 °Bx (mean + / - standard deviation of three 1-minute NMR13C isotope measurements), which is in good agreement with the declared content.P85917PC01
[0244] 28
[0245] Although the present invention has been described in connection with the specified embodiments, it should not be construed as being in any way limited to the presented examples. Also, the mentioning of references such as “a” or “an” etc. should not be construed as excluding a plurality. Furthermore, individual features mentioned in different claims, may possibly be advantageously combined, and the mentioning of these features in different claims does not exclude that a combination of features is not possible and advantageous.
Claims
P85917PC0129PATENT CLAIMS1. A method of determining a primary carbon parameter of a selected material, the method comprising• providing a material sample comprising at least a portion of the selected material, • applying the material sample in a nuclear magnetic resonance (NMR) apparatus, wherein the NMR apparatus is a low field apparatus,• performing an NMR reading comprising subjecting the material sample to one or more pulse sequences and recording at least one NMR signal of at least one NMR active isotope, wherein the at least one NMR active isotope comprises13C, and wherein the NMR signal comprises NMR intensity data of at least a portion of carbon present in the selected material and recording said at least one NMR signal as material NMR data,• determining the primary carbon parameter of the selected material from the material NMR data comprising correlating the material NMR data to carbon data, wherein the carbon data comprises data representing a relationship between carbon a content and an associated13C NMR signal,wherein the primary carbon parameter comprisesi) a fat parameter representing a fat content of the selected material and / or ii) a carbohydrate parameter representing a carbohydrate content of the selected material.
2. The method according to claim 1, wherein the selected material comprises fat and / or carbohydrate.
3. The method according to any one of claims 1 or 2, wherein the determining of the primary carbon parameter comprises establishing the primary carbon parameter by correlating the material NMR data to the carbon data, wherein the carbon data comprising carbon fitting data, wherein the carbon fitting data represents a relationship between carbon content and associated13C NMR signal.
4. The method according to claim 3, wherein the obtaining of the carbon fitting data comprisesP85917PC0130• providing a plurality of reference samples with a known content of a carbon containing component selected from fat and carbohydrate, wherein at least two of the plurality of reference samples comprises a different content of the carbon containing component,• determining the carbon content of each of the plurality of reference samples from the carbon containing component content,• performing an NMR reading of each of the plurality of reference samples comprisingsubjecting the material sample to one or more pulse sequences and recording at least one reference NMR signal intensity of the least one NMR active isotope comprising13C, wherein the reference NMR signal comprises NMR intensity data of at least a portion of carbon present in the reference sample, and• processing said recorded NMR signal intensity and said determined carbon content for each of the plurality of references samples by applying a regression analysis to model the relationship between carbon content and the associated13C NMR signal and determine said carbon fitting data.
5. The method according to claim 4, wherein the regression analysis comprises performing a linear regression to determine said carbon fitting data associated with a linear equation representing a relationship between carbon content and an associated13C NMR signal intensity.
6. The method according to any one of the claims 4 or 5, wherein the carbon content from fat is determined as 77% of the fat content in the respective reference sample.
7. The method according to any one of the claims 4 or 5, wherein the carbon content from carbohydrate is determined as 42% of the carbohydrate content of the respective reference sample.
8. The method according to any one of the claims 4-7, wherein the at least a portion of carbon recorded in the NMR signal of the material sample and the at least a portion of carbon recorded in the reference NMR signal of at least one of the plurality of reference samples are proportionally similar within a range of up to 10% based on the material sample.P85917PC01319. The method according to any one of the preceding claims, wherein the primary carbon parameter comprises a carbon characteristic representing a carbon content of the selected material, such as a total carbon content of the selected material.
10. The method according to claim 1, wherein the selected material comprises fat and carbohydrate, and wherein the method comprises establishing a secondary carbon parameter of the selected material.
11. The method according to claim 10, wherein the determining of the primary carbon parameter comprises• processing the material NMR intensity data comprisingo determining a secondary NMR intensity data portion of the material NMR data originating from the secondary carbon parameter,o determining a primary NMR intensity data portion of the material NMR data originating from the primary carbon parameter comprising subtracting the secondary NMR intensity data portion from the material NMR intensity data ando determining the primary carbon parameter from the primary NMR intensity data portion.
12. The method of claim 11, wherein the primary carbon parameter and the secondary parameter respectively comprisesi) a fat parameter representing a fat content of the selected material or ii) a carbohydrate parameter representing a carbohydrate content of the selected material, andwherein one of the primary or secondary carbon parameter is iii) and the other one of the primary or secondary carbon parameter is iv).
13. The method of any one of claims 11 or 12, wherein the determining of the secondary NMR data portion comprising determining a calculated NMR13C intensity of the secondary carbon parameter and adjusting the calculated NMR13C intensity of the secondary carbon parameter with a secondary correlation factor to obtain an adjusted secondary parameter NMR intensity representing the secondary NMR data portion.P85917PC013214. The method of claim 13, wherein the calculated NMR13C intensity of the secondary carbon parameter is determined comprising correlating the established secondary carbon parameter to the carbon data comprising carbon calibration data, wherein the carbon calibration data represents a carbon calibration curve of13C NMR signal intensity relative to carbon mass content.
15. The method of any one of claims 11-14, wherein the determining of the primary carbon parameter from the primary NMR data portion, comprises adjusting the primary NMR intensity data portion with a primary correlation factor to determine a calculated NMR13C intensity of the primary carbon parameter and determining the primary carbon parameter from the determined calculated NMR13C intensity of the primary carbon parameter.
16. The method of claim 15, wherein the determining of the primary carbon parameter from the calculated NMR13C intensity of the primary carbon parameter comprises correlating the calculated NMR13C intensity of the primary carbon parameter to the carbon data comprising carbon calibration data, wherein the carbon calibration data represents a carbon calibration curve of13C NMR signal relative to carbon mass content.
17. The method of any one of claims 14 or 16, wherein the obtaining of the carbon calibration data comprises performing at least one NMR intensity determination of at least one reference samples with a known carbon content, and wherein the reference sample preferably is selected from a lower alcohol or a polyol, such as glycerol.
18. The method of any one of claims 14, 16 or 17, wherein the obtaining of the carbon calibration data comprises performing at least one NMR intensity determination of a plurality of reference samples with a known carbon content, wherein at least two of the plurality of reference samples have a different carbon content, and wherein the reference sample preferably is selected from a lower alcohol or a polyol, such as glycerol.
19. The method of any one of claims 14, 16-18, wherein the obtaining of the carbon calibration data comprises performing at least one NMR intensity determination of a reference sample, comprising carbon.P85917PC013320. The method of any one of the preceding claims, wherein the low field apparatus is adapted for operating at a magnetic field up to 2 T, such as up to 1 T, such as up to 750 mT.
21. The method according to any one of the preceding claims, wherein the selected material is a food product, such as a dairy product, meat, fish, vegetables or any fragments or combinations thereof.
22. The method according to any one of claims 13-19, wherein the primary correlation factor and / or the secondary correlation factor is determined by estimating the primary correlation factor and / or the secondary correlation factor, and preferably wherein the primary correlation factor and / or the secondary correlation factor is estimated from historical NMR intensity data.
23. The method according to any one of claims 13-19, wherein the primary and / or the secondary correlation factor is determined comprising performing at least one NMR intensity determination of each of a plurality of correlation samples with a known fat and carbohydrate content to obtain a set of correlation NMR data, wherein at least two of the plurality of correlation samples have a different content of fat and / or carbohydrate, and processing said set of correlation NMR data and the known content of fat and carbohydrate in the plurality of correlation samples to obtain the primary and / or the second correlation factor.
24. The method of claim 23, wherein the processing comprisesdetermining a calculated NMR intensity of each of the plurality of correlation samples by correlating the known content of fat and carbohydrate in the plurality of correlation samples to carbon calibration data,estimating or determining the carbon content for respective fat and carbohydrate for each of the plurality of correlation samples,determining the primary and / or the secondary correlation factor from a system of equations based on a formula F, wherein each correlation sample of the plurality of correlation samples is represented by an equation, and wherein F is:Yj. CalculatedNMRx* (jji * carboncarboh.ydratexTP85917PC0134, wherein Y is the NMR intensity of the respective correlation sample in the set of correlation NMR data, calculatedNMR is the calculated NMR intensity of the respective correlation sample, carboncarbohydrate is the estimated or determined carbon content from carbohydrate of the respective correlation sample, carbontat is the estimated or determined carbon content from fat of the respective correlation sample, qi and q2 are the respective correlation factors, and x is the number of correlation samples.
25. The method according to any one of claims 23 or 24, wherein the plurality of correlation samples and the selected material is from a single material type.
26. The method according to any one of claims 23-25, wherein the plurality of correlation samples and the selected material comprises fat, and wherein the fat comprises a carbon chain length between 4 to 24 carbon atoms, preferably between 4-12 carbon atoms.
27. The method according to any one of claims 23-26, wherein the plurality of correlation samples and the selected material comprises carbohydrate, and wherein the carbohydrate in the correlation samples and the selected material comprises a carbon chain length between 5 to 12 carbon atoms, preferably between 4 to 6 carbon atoms.
28. The method according to any one of claims 23-27, wherein the plurality of correlation samples comprises an organic macronutrient profile similarity of at least 60% compared to the selected material, preferably at least 70%, more preferably at least 85%, wherein the organic macronutrient profile is associated or represents the content of carbon-containing macronutrients.
29. The method of claim 28, wherein carbon-containing macronutrients are selected from the list containing fat, carbohydrate, nucleic acids, and protein.
30. The method according to any one of the preceding claims, wherein the at least one NMR active isotope is at least two different NMR active isotopes comprising13C and at least one NMR active isotope selected from the list containing of1H,14N,19F,23Na,35 / 37CI and31P.P85917PC013531. The method according to any one of the preceding claims, wherein the NMR reading and / or the NMR intensity determination is performed using a Carr-Purcell-Meiboom-Gill experiment.
32. The method according to any one of the claims 1-30, wherein the NMR reading and / or the NMR intensity determination is performed using at least one of DEPT (Distortionless Enhancement by Polarization Transfer), DEPTQ (DEPT with retention of Quaternaries), HSQC (Heteronuclear Single Quantum Coherence), INEPT (Insensitive Nuclei Enhanced by Polarization Transfer), BIRD (Bilinear Rotation Decoupling pulses), TANGO (Testing for Adjacent Nuclei with a Gyration Operator) or NOE (Nuclear Overhauser Effect).
33. The method of any one of the preceding claims, wherein the selected material is a multi-component material comprising at least two components selected from the list containing water, small organic compounds, carbohydrate, fat, and protein.
34. The method of claim 33, wherein the multi-component material comprises at least two components selected from the list containing carbohydrate, fat, and protein.
35. The method of any one of the preceding claims, wherein the material sample is a liquid material sample, preferably an aqueous material sample.
36. The method of any one of the preceding claims, wherein the selected material is a food product, and wherein the material sample is a flowable material sample, optionally the material sample is a diluted material sample or a concentrated material sample of the food product.
37. The method of any one of the preceding claims, wherein the selected material is a solid material, such as a solid food product, and preferably wherein the material sample comprises the solid food product dissolved and / or suspended in a liquid.
38. The method of any one of the preceding claims, wherein the selected material comprises a weight percentage (wt%) of fat or carbohydrate above 30 wt%, preferably above 40wt%, such as above 50wt%.P85917PC013639. The method of claim 17, wherein the one or more pulse sequences used to generate the carbon calibration data is the same as the one or more pulse sequences used to obtain material NMR data for the selected material.
40. The method according to any one of claims 23-29, wherein a difference in density between each of the plurality of correlation materials and the selected material is 0.5 g / cm3or below, preferably 0.35 g / cm3or below, more preferably 0.3 g / cm3or below.
41. The method of any one of the preceding claims, wherein the selected material comprises at least 10 % liquid by volume of the selected material, such as at least about 25 %, such as from about 40 % to 95% liquid by volume of the selected material.
42. The method of claim 24, wherein qi is the primary correlation factor and q2 is the secondary correlation factor, or wherein qi is the secondary correlation factor and q2 is the primary correlation factor.
43. The method of any one of the claims 17, 18, 23-29, 31, or 32, wherein the NMR intensity determination comprises performing an NMR reading comprising subjecting the respective sample to one or more pulse sequences and recording at least one NMR signal of the at least one NMR active isotope, wherein the at least one NMR active isotope comprises13C.
43. A system comprising an NMR apparatus and means adapted to execute the steps of the method according to any one of the preceding claims.
44. The system of claim 43, wherein the NMR apparatus is a low field NMR apparatus.
45. A computer program comprising instructions to cause the system of any one of claims 43 or 44 to execute the steps of the method according to any one of claims 1-41.
46. A computer-readable medium having stored thereon the computer program according to claim 45.