1. Prediction of Raw spectra
2. Prediction of Averaged Spectra - compare
3. finding Outliers
Spectroscopy and Chemometrics News Weekly #49, 2019Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #49, 2019Spettroscopia e Chemiometria Weekly News #49, 2019
CalibrationModel.com
Spectroscopy and Chemometrics News Weekly 48, 2019 | NIRS NIR Spectroscopy machinelearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality Check LINKSpektroskopie und Chemometrie Neuigkeiten Wöchentlich 48 2019 | NIRS NIR Spektroskopie MachineLearning Spektrometer SmartSensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Qualitätslabor LINK
Spettroscopia e Chemiometria Weekly News 48, 2019 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem datascience prediction LINK
This week's NIR news Weekly is sponsored by Your-Company-Name-Here - NIR-spectrometers. Check out their product page ... link
Get the Chemometrics and Spectroscopy News in real time on Twitter @ CalibModel and follow us.
Near Infrared (NIR)
"Development of near infrared reflectance spectroscopy (NIRS) calibration model to estimate the forage quality of shrub species" LINK"Estimation and classification of popping expansion capacity in popcorn breeding programs using NIR spectroscopy" LINK
"Authentication of liquid egg composition using ATR-FTIR and NIR spectroscopy in combination with PCA" LINK
"Non-Destructive Method for Predicting Sapodilla Fruit Quality Using Near Infrared Spectroscopy" LINK
"Discrimination of white teas produced from fresh leaves with different maturity by near-infrared spectroscopy" LINK
"AI and InfraRed Spectroscopy to Accelerate Malaria Control" LINK
"Near infrared spectroscopic data for rapid and simultaneous prediction of quality attributes in intact mango fruits." LINK
"Reflectance Properties of Brown Mass Dyed Poly (ethylene terephthalate) Filament Yarns in the Visible-near Infrared Region" LINK
" The contribution of Visible Near Infrared Reflectance spectroscopy to colour determination: the case of the experimental ceramic briquettes" | Mineralogy, Petrology, Economic GeologyLINK
"Non-destructive measurement of soluble solids content of three melon cultivars using portable visible/near infrared spectroscopy" LINK
" Predicting plant available phosphorus using infrared spectroscopy with consideration for future mobile sensing applications in precision farming" LINK
"Molecules, Vol. 24, Pages 3900: Antioxidant Activity of Blueberry (Vaccinium spp.) Cultivar Leaves: Differences Across the Vegetative Stage and the Application of Near Infrared Spectroscopy" LINK
Hyperspectral
"A novel hyperspectral line-scan imaging method for whole surfaces of round shaped agricultural products" LINK"Setting up a methodology to distinguish between green oranges and leaves using hyperspectral imaging" LINK
"Early detection of tomato spotted wilt virus infection in tobacco using the hyperspectral imaging technique and machine learning algorithms" LINK
"The Future of Hyperspectral Imaging" LINK
"Soil fertility status assessment using hyperspectral remote sensing" LINK
Chemometrics / Machine Learning
"Authentication of PGI Gragnano Pasta by Near Infrared (NIR) spectroscopy and chemometrics" LINK" Prediction of Salt in Soil by PLS Regression Using Hyperspectral Laboratory Data" LINK
"Measurement of quality parameters of sugar beet juices using near-infrared spectroscopy and chemometrics" LINK
"Classification of oolong tea varieties based on hyperspectral imaging technology and BOSS-LightGBM model" LINK
"Analytical and sensory data correlation to understand consumers' grape preference" LINK
Process Control
" A review on mechanisms, screening and engineering for pest resistance in sugarcane (Saccharum spp)" LINKEnvironment
"Visible and Near-Infrared Reflectance Spectroscopy Analysis of Soils" LINK"Spektroradyometre teknigi ile toprak özelliklerinin belirlenmesi; Harran Ovasi cullap sulama birligi alani örnegi/Determination of soil properties using …" LINK
Agriculture
" Assessing plant performance in the Enviratron" LINK"Broad near infrared spectroscopy calibrations can predict the nutritional value of over one hundred forage species within the Australian feedbase" LINK
Other
"The study of combustion characteristics of corn stalks and cobs via TGA-DTG-DSC analysis" LINK" Gravimetric and Spectrophotometric Determination of Surface Wax Content in Maize Kernels" LINK
"Detection of Multi-frozen and Single-frozen Fish Using Optical Spectroscopy" LINK
CalibrationModel.com
Spectroscopy and Chemometrics News Weekly 48, 2019 | NIRS NIR Spectroscopy machinelearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality Check LINKSpektroskopie und Chemometrie Neuigkeiten Wöchentlich 48 2019 | NIRS NIR Spektroskopie MachineLearning Spektrometer SmartSensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Qualitätslabor LINK
Spettroscopia e Chemiometria Weekly News 48, 2019 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem datascience prediction LINK
This week's NIR news Weekly is sponsored by Your-Company-Name-Here - NIR-spectrometers. Check out their product page ... link
Get the Chemometrics and Spectroscopy News in real time on Twitter @ CalibModel and follow us.
Near Infrared (NIR)
"Development of near infrared reflectance spectroscopy (NIRS) calibration model to estimate the forage quality of shrub species" LINK"Estimation and classification of popping expansion capacity in popcorn breeding programs using NIR spectroscopy" LINK
"Authentication of liquid egg composition using ATR-FTIR and NIR spectroscopy in combination with PCA" LINK
"Non-Destructive Method for Predicting Sapodilla Fruit Quality Using Near Infrared Spectroscopy" LINK
"Discrimination of white teas produced from fresh leaves with different maturity by near-infrared spectroscopy" LINK
"AI and InfraRed Spectroscopy to Accelerate Malaria Control" LINK
"Near infrared spectroscopic data for rapid and simultaneous prediction of quality attributes in intact mango fruits." LINK
"Reflectance Properties of Brown Mass Dyed Poly (ethylene terephthalate) Filament Yarns in the Visible-near Infrared Region" LINK
" The contribution of Visible Near Infrared Reflectance spectroscopy to colour determination: the case of the experimental ceramic briquettes" | Mineralogy, Petrology, Economic GeologyLINK
"Non-destructive measurement of soluble solids content of three melon cultivars using portable visible/near infrared spectroscopy" LINK
" Predicting plant available phosphorus using infrared spectroscopy with consideration for future mobile sensing applications in precision farming" LINK
"Molecules, Vol. 24, Pages 3900: Antioxidant Activity of Blueberry (Vaccinium spp.) Cultivar Leaves: Differences Across the Vegetative Stage and the Application of Near Infrared Spectroscopy" LINK
Hyperspectral
"A novel hyperspectral line-scan imaging method for whole surfaces of round shaped agricultural products" LINK"Setting up a methodology to distinguish between green oranges and leaves using hyperspectral imaging" LINK
"Early detection of tomato spotted wilt virus infection in tobacco using the hyperspectral imaging technique and machine learning algorithms" LINK
"The Future of Hyperspectral Imaging" LINK
"Soil fertility status assessment using hyperspectral remote sensing" LINK
Chemometrics / Machine Learning
"Authentication of PGI Gragnano Pasta by Near Infrared (NIR) spectroscopy and chemometrics" LINK" Prediction of Salt in Soil by PLS Regression Using Hyperspectral Laboratory Data" LINK
"Measurement of quality parameters of sugar beet juices using near-infrared spectroscopy and chemometrics" LINK
"Classification of oolong tea varieties based on hyperspectral imaging technology and BOSS-LightGBM model" LINK
"Analytical and sensory data correlation to understand consumers' grape preference" LINK
Process Control
" A review on mechanisms, screening and engineering for pest resistance in sugarcane (Saccharum spp)" LINKEnvironment
"Visible and Near-Infrared Reflectance Spectroscopy Analysis of Soils" LINK"Spektroradyometre teknigi ile toprak özelliklerinin belirlenmesi; Harran Ovasi cullap sulama birligi alani örnegi/Determination of soil properties using …" LINK
Agriculture
" Assessing plant performance in the Enviratron" LINK"Broad near infrared spectroscopy calibrations can predict the nutritional value of over one hundred forage species within the Australian feedbase" LINK
Other
"The study of combustion characteristics of corn stalks and cobs via TGA-DTG-DSC analysis" LINK" Gravimetric and Spectrophotometric Determination of Surface Wax Content in Maize Kernels" LINK
"Detection of Multi-frozen and Single-frozen Fish Using Optical Spectroscopy" LINK
CalibrationModel.com
Spectroscopy and Chemometrics News Weekly 48, 2019 | NIRS NIR Spectroscopy machinelearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality Check LINKSpektroskopie und Chemometrie Neuigkeiten Wöchentlich 48 2019 | NIRS NIR Spektroskopie MachineLearning Spektrometer SmartSensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Qualitätslabor LINK
Spettroscopia e Chemiometria Weekly News 48, 2019 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem datascience prediction LINK
This week's NIR news Weekly is sponsored by Your-Company-Name-Here - NIR-spectrometers. Check out their product page ... link
Get the Chemometrics and Spectroscopy News in real time on Twitter @ CalibModel and follow us.
Near Infrared (NIR)
"Development of near infrared reflectance spectroscopy (NIRS) calibration model to estimate the forage quality of shrub species" LINK"Estimation and classification of popping expansion capacity in popcorn breeding programs using NIR spectroscopy" LINK
"Authentication of liquid egg composition using ATR-FTIR and NIR spectroscopy in combination with PCA" LINK
"Non-Destructive Method for Predicting Sapodilla Fruit Quality Using Near Infrared Spectroscopy" LINK
"Discrimination of white teas produced from fresh leaves with different maturity by near-infrared spectroscopy" LINK
"AI and InfraRed Spectroscopy to Accelerate Malaria Control" LINK
"Near infrared spectroscopic data for rapid and simultaneous prediction of quality attributes in intact mango fruits." LINK
"Reflectance Properties of Brown Mass Dyed Poly (ethylene terephthalate) Filament Yarns in the Visible-near Infrared Region" LINK
" The contribution of Visible Near Infrared Reflectance spectroscopy to colour determination: the case of the experimental ceramic briquettes" | Mineralogy, Petrology, Economic GeologyLINK
"Non-destructive measurement of soluble solids content of three melon cultivars using portable visible/near infrared spectroscopy" LINK
" Predicting plant available phosphorus using infrared spectroscopy with consideration for future mobile sensing applications in precision farming" LINK
"Molecules, Vol. 24, Pages 3900: Antioxidant Activity of Blueberry (Vaccinium spp.) Cultivar Leaves: Differences Across the Vegetative Stage and the Application of Near Infrared Spectroscopy" LINK
Hyperspectral
"A novel hyperspectral line-scan imaging method for whole surfaces of round shaped agricultural products" LINK"Setting up a methodology to distinguish between green oranges and leaves using hyperspectral imaging" LINK
"Early detection of tomato spotted wilt virus infection in tobacco using the hyperspectral imaging technique and machine learning algorithms" LINK
"The Future of Hyperspectral Imaging" LINK
"Soil fertility status assessment using hyperspectral remote sensing" LINK
Chemometrics / Machine Learning
"Authentication of PGI Gragnano Pasta by Near Infrared (NIR) spectroscopy and chemometrics" LINK" Prediction of Salt in Soil by PLS Regression Using Hyperspectral Laboratory Data" LINK
"Measurement of quality parameters of sugar beet juices using near-infrared spectroscopy and chemometrics" LINK
"Classification of oolong tea varieties based on hyperspectral imaging technology and BOSS-LightGBM model" LINK
"Analytical and sensory data correlation to understand consumers' grape preference" LINK
Process Control
" A review on mechanisms, screening and engineering for pest resistance in sugarcane (Saccharum spp)" LINKEnvironment
"Visible and Near-Infrared Reflectance Spectroscopy Analysis of Soils" LINK"Spektroradyometre teknigi ile toprak özelliklerinin belirlenmesi; Harran Ovasi cullap sulama birligi alani örnegi/Determination of soil properties using …" LINK
Agriculture
" Assessing plant performance in the Enviratron" LINK"Broad near infrared spectroscopy calibrations can predict the nutritional value of over one hundred forage species within the Australian feedbase" LINK
Other
"The study of combustion characteristics of corn stalks and cobs via TGA-DTG-DSC analysis" LINK" Gravimetric and Spectrophotometric Determination of Surface Wax Content in Maize Kernels" LINK
"Detection of Multi-frozen and Single-frozen Fish Using Optical Spectroscopy" LINK
Spectroscopy and Chemometrics News Weekly #38, 2019Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #38, 2019Spettroscopia e Chemiometria Weekly News #38, 2019
CalibrationModel.com
New: free NIR-Predictor V2.4 supports file formats out of the box from: @TIDLP @ViaviSolutions @OceanOpticsEMEA @my_scio @SiWareSystems @SpectralEngines @trinamiX_GmbH @StellarNet - Mobile NIRS portable NIR2019 NIR2020 Analyzers LINKSpectroscopy and Chemometrics News Weekly 37, 2019 | NIRS NIR Spectroscopy Chemometrics Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality Checking LINK
Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 37, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK
Spettroscopia e Chemiometria Weekly News 37, 2019 | NIRS NIR Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem prediction models LINK
This week's NIR news Weekly is sponsored by your-Company-Name-here - Best-NIR-instruments. Check out their product page ... link
Chemometrics
"Potential biomonitoring of atmospheric carbon dioxide in Coffea arabica leaves using near-infrared spectroscopy and partial least squares discriminant analysis" LINK"Quantitative Real-Time Release Testing of Rhubarb based on Near-Infrared Spectroscopy and Method Validation" LINK
"Identification of lactic acid bacteria Enterococcus and Lactococcus by near-infrared spectroscopy and multivariate classification" LINK
"Determination of manganese content in cottonseed meal using near-infrared spectrometry and multivariate calibration" LINK
"Advanced Modeling of Soil Biological Properties Using Visible Near Infrared Diffuse Reflectance Spectroscopy" |:ijbs1&volume=5&issue=1&article=001 LINK
"山茶油中油酸和亚油酸近红外光谱分析模型" "Analysis Model of Oleic and Linoleic Acids in Camellia Oilvia Near-Infrared Spectroscopy" LINK
"Determination of 10-Hydroxy-2-Decenoic Acid of Royal Jelly Using Near-Infrared Spectroscopy Combined with Chemometrics." LINK
"Predicting of the Quality Attributes of Orange Fruit Using Hyperspectral Images" LINK
"Rapid and Automatic Classification of Tobacco Leaves Using a Hand-Held DLP-Based NIR Spectroscopy Device" LINK
"Association of mid-infrared-predicted milk and blood constituents with early-lactation disease, removal, and production outcomes in Holstein cows" |(19)30787-8/fulltext LINK
"Machine learning and soil sciences: A review aided by machine learning tools" LINK
Near Infrared
"Soil characterization using Visible Near Infrared Diffuse Reflectance Spectroscopy (VNIR DRS)" LINK"Quantification of soil organic carbon stock in urban soils using visible and near infrared reflectance spectroscopy (VNIRS) in situ or in laboratory conditions" LINK
"Assessment of the human albumin in acid precipitation process using NIRS and multi-variable selection methods combined with SPA" LINK
" Implementación de estrategias de muestreo, inspección y control en la industria agroalimentaria basadas en el empleo automatizado de sensores nirs" LINK
"Determination of glucose concentration in aqueous solution using FT NIR spectroscopy" LINK
"Near infrared spectroscopy for world food security" LINK
"Titanium dioxide as an adsorbent to enhance the detection ability of near-infrared diffuse reflectance spectroscopy" LINK
"Near-infrared diffuse reflectance spectroscopy for discriminating fruit and vegetable products preserved in glass containers" LINK
"Ability of near-infrared spectroscopy for non-destructive detection of internal insect infestation in fruits: Meta-analysis of spectral ranges and optical measurement …" LINK
"Molecules, Vol. 24, Pages 3268: Near-Infrared Hyperspectral Imaging Combined with Deep Learning to Identify Cotton Seed Varieties" LINK
"Improvement of the Fourier Transform Near Infrared Method to Evaluate Extra Virgin Olive Oils by Analyzing 1,2-Diacylglycerols and 1,3-Diacylglycerols and Adding Unesterified Fatty Acids." LINK
Agriculture
"51 Feedstuff fatty acid content, variation, techniques and implications on practical animal nutrition" LINK"Prediction of Milk Coagulation Properties and Individual Cheese Yield in Sheep Using Partial Least Squares Regression" Animals LINK
Food & Feed
"Classifying the fertility of dairy cows using milk mid-infrared spectroscopy" LINKCalibrationModel.com
New: free NIR-Predictor V2.4 supports file formats out of the box from: @TIDLP @ViaviSolutions @OceanOpticsEMEA @my_scio @SiWareSystems @SpectralEngines @trinamiX_GmbH @StellarNet - Mobile NIRS portable NIR2019 NIR2020 Analyzers LINKSpectroscopy and Chemometrics News Weekly 37, 2019 | NIRS NIR Spectroscopy Chemometrics Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality Checking LINK
Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 37, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK
Spettroscopia e Chemiometria Weekly News 37, 2019 | NIRS NIR Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem prediction models LINK
This week's NIR news Weekly is sponsored by your-Company-Name-here - Best-NIR-instruments. Check out their product page ... link
Chemometrics
"Potential biomonitoring of atmospheric carbon dioxide in Coffea arabica leaves using near-infrared spectroscopy and partial least squares discriminant analysis" LINK"Quantitative Real-Time Release Testing of Rhubarb based on Near-Infrared Spectroscopy and Method Validation" LINK
"Identification of lactic acid bacteria Enterococcus and Lactococcus by near-infrared spectroscopy and multivariate classification" LINK
"Determination of manganese content in cottonseed meal using near-infrared spectrometry and multivariate calibration" LINK
"Advanced Modeling of Soil Biological Properties Using Visible Near Infrared Diffuse Reflectance Spectroscopy" |:ijbs1&volume=5&issue=1&article=001 LINK
"山茶油中油酸和亚油酸近红外光谱分析模型" "Analysis Model of Oleic and Linoleic Acids in Camellia Oilvia Near-Infrared Spectroscopy" LINK
"Determination of 10-Hydroxy-2-Decenoic Acid of Royal Jelly Using Near-Infrared Spectroscopy Combined with Chemometrics." LINK
"Predicting of the Quality Attributes of Orange Fruit Using Hyperspectral Images" LINK
"Rapid and Automatic Classification of Tobacco Leaves Using a Hand-Held DLP-Based NIR Spectroscopy Device" LINK
"Association of mid-infrared-predicted milk and blood constituents with early-lactation disease, removal, and production outcomes in Holstein cows" |(19)30787-8/fulltext LINK
"Machine learning and soil sciences: A review aided by machine learning tools" LINK
Near Infrared
"Soil characterization using Visible Near Infrared Diffuse Reflectance Spectroscopy (VNIR DRS)" LINK"Quantification of soil organic carbon stock in urban soils using visible and near infrared reflectance spectroscopy (VNIRS) in situ or in laboratory conditions" LINK
"Assessment of the human albumin in acid precipitation process using NIRS and multi-variable selection methods combined with SPA" LINK
" Implementación de estrategias de muestreo, inspección y control en la industria agroalimentaria basadas en el empleo automatizado de sensores nirs" LINK
"Determination of glucose concentration in aqueous solution using FT NIR spectroscopy" LINK
"Near infrared spectroscopy for world food security" LINK
"Titanium dioxide as an adsorbent to enhance the detection ability of near-infrared diffuse reflectance spectroscopy" LINK
"Near-infrared diffuse reflectance spectroscopy for discriminating fruit and vegetable products preserved in glass containers" LINK
"Ability of near-infrared spectroscopy for non-destructive detection of internal insect infestation in fruits: Meta-analysis of spectral ranges and optical measurement …" LINK
"Molecules, Vol. 24, Pages 3268: Near-Infrared Hyperspectral Imaging Combined with Deep Learning to Identify Cotton Seed Varieties" LINK
"Improvement of the Fourier Transform Near Infrared Method to Evaluate Extra Virgin Olive Oils by Analyzing 1,2-Diacylglycerols and 1,3-Diacylglycerols and Adding Unesterified Fatty Acids." LINK
Agriculture
"51 Feedstuff fatty acid content, variation, techniques and implications on practical animal nutrition" LINK"Prediction of Milk Coagulation Properties and Individual Cheese Yield in Sheep Using Partial Least Squares Regression" Animals LINK
Food & Feed
"Classifying the fertility of dairy cows using milk mid-infrared spectroscopy" LINKCalibrationModel.com
New: free NIR-Predictor V2.4 supports file formats out of the box from: @TIDLP @ViaviSolutions @OceanOpticsEMEA @my_scio @SiWareSystems @SpectralEngines @trinamiX_GmbH @StellarNet - Mobile NIRS portable NIR2019 NIR2020 Analyzers LINKSpectroscopy and Chemometrics News Weekly 37, 2019 | NIRS NIR Spectroscopy Chemometrics Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality Checking LINK
Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 37, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK
Spettroscopia e Chemiometria Weekly News 37, 2019 | NIRS NIR Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem prediction models LINK
This week's NIR news Weekly is sponsored by your-Company-Name-here - Best-NIR-instruments. Check out their product page ... link
Chemometrics
"Potential biomonitoring of atmospheric carbon dioxide in Coffea arabica leaves using near-infrared spectroscopy and partial least squares discriminant analysis" LINK"Quantitative Real-Time Release Testing of Rhubarb based on Near-Infrared Spectroscopy and Method Validation" LINK
"Identification of lactic acid bacteria Enterococcus and Lactococcus by near-infrared spectroscopy and multivariate classification" LINK
"Determination of manganese content in cottonseed meal using near-infrared spectrometry and multivariate calibration" LINK
"Advanced Modeling of Soil Biological Properties Using Visible Near Infrared Diffuse Reflectance Spectroscopy" |:ijbs1&volume=5&issue=1&article=001 LINK
"山茶油中油酸和亚油酸近红外光谱分析模型" "Analysis Model of Oleic and Linoleic Acids in Camellia Oilvia Near-Infrared Spectroscopy" LINK
"Determination of 10-Hydroxy-2-Decenoic Acid of Royal Jelly Using Near-Infrared Spectroscopy Combined with Chemometrics." LINK
"Predicting of the Quality Attributes of Orange Fruit Using Hyperspectral Images" LINK
"Rapid and Automatic Classification of Tobacco Leaves Using a Hand-Held DLP-Based NIR Spectroscopy Device" LINK
"Association of mid-infrared-predicted milk and blood constituents with early-lactation disease, removal, and production outcomes in Holstein cows" |(19)30787-8/fulltext LINK
"Machine learning and soil sciences: A review aided by machine learning tools" LINK
Near Infrared
"Soil characterization using Visible Near Infrared Diffuse Reflectance Spectroscopy (VNIR DRS)" LINK"Quantification of soil organic carbon stock in urban soils using visible and near infrared reflectance spectroscopy (VNIRS) in situ or in laboratory conditions" LINK
"Assessment of the human albumin in acid precipitation process using NIRS and multi-variable selection methods combined with SPA" LINK
" Implementación de estrategias de muestreo, inspección y control en la industria agroalimentaria basadas en el empleo automatizado de sensores nirs" LINK
"Determination of glucose concentration in aqueous solution using FT NIR spectroscopy" LINK
"Near infrared spectroscopy for world food security" LINK
"Titanium dioxide as an adsorbent to enhance the detection ability of near-infrared diffuse reflectance spectroscopy" LINK
"Near-infrared diffuse reflectance spectroscopy for discriminating fruit and vegetable products preserved in glass containers" LINK
"Ability of near-infrared spectroscopy for non-destructive detection of internal insect infestation in fruits: Meta-analysis of spectral ranges and optical measurement …" LINK
"Molecules, Vol. 24, Pages 3268: Near-Infrared Hyperspectral Imaging Combined with Deep Learning to Identify Cotton Seed Varieties" LINK
"Improvement of the Fourier Transform Near Infrared Method to Evaluate Extra Virgin Olive Oils by Analyzing 1,2-Diacylglycerols and 1,3-Diacylglycerols and Adding Unesterified Fatty Acids." LINK
Agriculture
"51 Feedstuff fatty acid content, variation, techniques and implications on practical animal nutrition" LINK"Prediction of Milk Coagulation Properties and Individual Cheese Yield in Sheep Using Partial Least Squares Regression" Animals LINK
Food & Feed
"Classifying the fertility of dairy cows using milk mid-infrared spectroscopy" LINKNIR-Predictor – Manual
- NIR-Predictor – Manual
- Predicting Spectra
- Creating your own Calibrations
- Configure the Calibrations for prediction usage
- Applications
- Prediction Result Report
- Enter lab values to NIR spectra
- Create Calibration Request
- Program Settings
- Further References
NIR-Predictor – Manual
Predicting Spectra
It’s easy to use with NIR-Predictor,
just drag & drop your data for getting the prediction results.
It supports an automatic file format detection.
So you don’t need to specify the instrument type and settings! See the list of supported formats and NIR Vendors: NIR-Predictor supported Spectral Data File Formats
Use the included data to checkout how it feels:
- Open the demo Spectra folder by using the Menu >
Open Demo Spectra
or pressF8
.
There are files with spectra from different Vendors. - Drag & drop a spectra file onto the NIR-Predictor window (or press
Ctrl+O
as for ’Open some files). - The spectra will be
- loaded
- pre-processed
- predicted and
- reported
Note:
All the steps are fully automatic.
All calibrations that are compatible with the spectra, will produce prediction results in one go.
To select specific calibrations choose the Application
. Where the ” ” empty means use all the calibrations.
To define a Application
read more in chapter “Applications”
Hint:
To get access to Statistics of Predictions and Reports use the Menu > Show more/less (Ctrl+M)
or you can simply resize the window. Here you can also re-do the Analyze
step manually with changed inputs (e.g. Result Ordering).
Creating your own Calibrations
How it works – step by step
- You have measured your samples with you NIR-Instrument Software.
And got the Lab-values of these samples.samples
-> measuredNIR-spectra
->Lab-references
analytics - Now you need to combine these data.
NIR-spectra
+Lab-references
->PropertiesBySamples
Note: If you combined these data already in your NIR software used,
and you can export it as aJCAMP-DX
file then use
Menu >Create Request File .req ...
(F2
)
and read the “Help.html” and NIR-Predictor JCAMP.
Else proceed as below.The NIR-Predictor provides tooling for that:
Menu >
Create Properties File...
(F6
)Select the folder with your NIR spectra measured for an application.
NIR-Predictor creates a customized Properties file template for that data to enter the Lab values.Note: You don’t need to specify your instrument or vendor or an application. It’s all done automatically. And also the sample spectra are detected and grouped automatically!
- Use your favorite editor or spreadsheet program to enter and copy&paste
theLab-references
Values into the columns “Prop1”, “Prop2” etc. and save the file. - A final check of your entered data is done by NIR-Predictor,
to make sure your data ist complete and all is fine.Menu >
Create Calibration Request...
(F7
)Select the folder with the filled file.
ACalibrationRequest.zip
is created with the necessary data
if enougth diverse Lab values are entered. - Email the
CalibrationRequest.zip
file
toinfo@CalibrationModel.com
to develop the calibrations. - When your calibrations are ready, you will receive an email with a link
to the CalibrationModel WebShop where
you can purchase and download the calibration files,
that work with our free NIR-Predictor software without internet access.Note: Your sent NIR data is deleted after processing.
We do not collect your NIR data!
Note: Further details can be found under “Create Properties File” and “Create Calibration Request”.
Configure the Calibrations for prediction usage
Configuration:
- in NIR-Predictor : Menu > Open Calibrations (F9)
- an explorer window is opened where the calibrations are located
- create a folder for your application, choose a name
- copy the calibration file(s) (*.cm) into that folder
- in NIR-Predictor : Menu > Search and load Applications (F4)
Usage:
- in NIR-Predictor : open the Application drop down list, and select your application by name
- if all is fine, the calibration file is valid and not expired, it shows : Calibration “1 valid calibation”
- the NIR-Predictor is now ready to predict
- to switch the application, goto 6.
Applications
The Application concept allows to group multiple Calibrations together for an Application. By selecting an Application before prediction, only the Calibrations belonging to the Application will be used for Prediction. In the Demo Data this is used to have multiple spectrometer as Application. This can be used easily as e.g. as Application “Meat Products” containing Fat and Moisture Calibration.
To create an Application, create a folder with the Application’s name inside the Calibrations folder, and move/copy all the Calibrations files to this Application folder. To remove a Calibration from the Application, remove the Calibration file from the Application folder.
After creating an new Application folder, press menu Search and load Applications
(F4
) to update the NIR-Predictor dialog where the Application can be selected via the dropdown list. You don’t need to close the NIR-Predictor.
After moving Calibration files around, press menu Search and load Calibrations
(F5
) to update the NIR-Predictor dialog.
The use-all case
In the NIR-Predictor dialog where the Application can be selected via the dropdown list, the empty ""
name means that all (yes all) valid Calibrations will be used for prediction.
Note: The Prediction Report will contain only results from spectral compatible Calibrations with the given spectra. That allows to automatically handle the multi vendor NIR instrument usage.
Prediction Result Report
Histograms of Prediction Values per Property
Shows the distribution of the predicted results per calibration. The histogram range contains the range of the calibrated property and includes the predicted results.
The histogram bar (bin) color is defined as follow:
- blue : all predictions inside calibration range.
- red : all predictions outside calibration range.
- orange : some overlaps with calibration range.
So not all spectra in a orange bin are outside calibration range.
Note: Predicted values are always shown in Histogram
table and Prediction Value List
table, even if the spectrum does not fit into model (spectrum different to model, aka Residual Outlier) shown as Out = X
.
Note: Old browsers like Microsoft Internet Explorer 11 don’t support the grafics for Histogram charts. Use an current browser like Firefox or Chrome or Edge.
Note: If your browser opens the report too slow, try to deactivate some browser plugins, because they can filter what you look at and some add-ons are really slow.
Spectra Plot Thumbnail on the Prediction Report
Visualizes the min,median,max spectrum of the spectra dropped as files on the NIR-Predictor. This gives a minimal and good spectral overview of the predicted property results.
- Spectra Plot color legend: min,median,max spectrum by predicted property or if no calibration is available by spectral intensity.
- The min,median,max is determined from the predicted properties or if not available from the intensity of the spectra.
- Beside the histogram of the predicted properties, where the distribution can be seen, the spectra shown are the ones from min,median,max predicted property.
- This gives a minimal and good spectral overview of the predicted property results.
- The “Spectral Range” and number of datapoints is shown in the Prediction Report Header below the listed spectra files.
- To zoom the spectra plot a little, zoom the report in the browser (hold ctrl + mouse wheel, or pinch on touch screen).
- The spectra plots and histograms are stored with the report and can be archived.
Note
- Note that the spectra are shown in the raw values that are loaded, they are not shown pre-processed as the calibration model uses them to make the prediction.
- Note that the median property spectrum is the median from the predicted property pobulation and not the “median” of the calibration property range.
- Note that in the multi calibration prediction case, the spectra are selected for each property based on the related predicted property values and so the spectra plots shows typical different spectra.
Outlier Detection
To safeguard the prediction results, outliers are automatically checked for each individual prediction. This is based on limits that are determined when creating the calibration with the base data. Thus, a strange spectral measurement can be detected and signaled as an outlier even without base data only by means of the calibration and the NIR predictor. A prediction result with outlier warning is to be distrusted. How the various outlier tests are interpreted and how to avoid them in practice is described here.
The spectrum is an outlier to the model, if the spectrum is not similar with the spectra and lab-values the model is built with.
This legend is shown on each NIR-Predictor prediction report below the results:
Outlier (Out) Symbol Description
- “X” : spectrum does not fit into model (spectrum different to model)
- “O” : spectrum is wide outside model center (spectrum similar to model but far away)
- “=” : prediction is outside upper or lower range of model (property outside model range)
- “-” : spectrum is incompatible to calibration
Note: A prediction result with outlier warning is to be distrusted.
There are 3 outlier cases (X, O, =) and the incompatible data case “-”.
- The bad case is “X”
- the medium case is “O”
- and the soft case is “=”.
The technical names in literature correspond to:
- “X” : Spectral Residual Outlier
- “O” : Leverage Outlier
- “=” : Property Range Outlier
These 3 outlier cases can appear in combinations, like “XO=” or “XO” or “O=” or “X=”. The more outlier marker are shown the more likely the spectrum is an Outlier.
The default setting in NIR-Predictor Menu > “Report with Simplified Outlier Symbols”
- is ON, that will show only the worst case instead of all combinations to have a simplified minimal information.
- if OFF, that will show the combinations (e.g. “XO=” or “XO” or “O=” or “X=”), which is more informative for analyzing problem cases.
Some hints to avoid these Outliers:
- “X” : spectrum does not fit into model (spectrum different to model)
Check if the spectrum is noise only, or has no proper signal. That can happen when measured past the sample or measured into the air or at a different substance. If you have multiple NIR instruments of the same type, use spectra measured with different instruments for the calibration. - “O” : spectrum is wide outside model center (spectrum similar to model but far away) Sample temperature has an effect on NIR spectra shape, use spectra measured at different (typical use) temperatures (sample temperature, instrument temperature).
- “=” : prediction is outside upper or lower range of model (property outside model range)
Use more spectra for the calibration in the Lab value region where your special interest is. If the predicted value is only a little bit out of the calibration range, it can be Ok. Add these spectra to the calibration spectra (with the Lab values), to extend the prediction range of the calibration. - “-” : spectrum is incompatible to calibration
The spectra (from the NIR instrument) has a different wavelength range or a different resolution than the spectra used for calibration. Check Instrument settings (wavelength range, resolution)
Result Ordering
To change the ordering, a drop-down-box is located below the Analyze
button. If there is an analysis from the current session, and the Result Ordering
is changed, the data is re-Analyzed and reported with the new Result Ordering
setting. That allows to compare the different orderings. The Result Ordering
is listed in the Prediction Report above the Prediction Value List
and stored in the settings.
The order/sorting of the prediction results of the spectra can be defined:
- GivenOrder (default) the given order of the spectra from file select dialog or drag&drop
*) sorted : ascending sort
- Date_Name sorted by Date (if any) and then by Name
- Name_Date sorted by Name and then by Date
- Date_NamesWithNumbers sorted by Date (if any) and then by Name with number logic
- NamesWithNumbers_Date sorted by Name with number logic (e.g. “ABC1” is before “ABC002” ) and then by Date
*) as above but sorted Rev : reverse sort = descending sort
- Rev_Date_Name
- Rev_Name_Date
- Rev_Date_NamesWithNumbers
- Rev_NamesWithNumbers_Date
E.g. with reverse sort by Rev_Date_Name, the newest spectra appear on top.
Print to PDF
Depending on how many calibrations are used the result table is getting broader. To print the report (e.g. to Adobe PDF, FreePDF or Microsoft XPS), sometimes the landscape format is shorter in number of pages or in portrait a scale of 80% fits nicely. Or try another internet browser (Mozilla Firefox, Google Chrome, Microsoft Edge, …) to print the report and set the browser as your default browser so it will be opened by default.
Archiving Reports
Each report is contained in one file only, including the grafics. To save storage space the report file folder can be compressed to a zip file (.zip, .7z).
Enter lab values to NIR spectra
Entering the laboratory reference values for NIR calibrations
We have developed specialized tools into NIR-Predictor to combine the NIR and Lab data is a sample-based safe manner.
The main target is to improve Data Quality during the step of combining of the Lab data and the NIR data, because to model a good reliable calibration the data that build the base needs to be of high quality.
It also simplifies to enter the lab values manually to the corresponding NIR data, because of automatically grouping repeated NIR measurements of the same sample, so the lab values can be entered sample based and not by spectrum.
It helps to avoid false reference data, because of the broken relation of NIR spectra and reference values, data entry on the wrong position in the table.
And Helps to detect errors of duplicated or multiple copies of spectra files, and checks for inconsistencies in Date-Time and Sample-Naming. It also checks for missing values.
That all increases the Data Quality for the next step of Calibration Development, and makes data entry a less time consuming and less risky work.
How it works
- Menu >
Create Properties File...
(F6
) select the folder with your NIR spectra measured for an application. NIR-Predictor creates a Properties file template for that data :PropertiesBySamples.csv.txt
- Use your favorite editor or spreadsheet program to enter and copy&paste the Lab Values into the columns and save the file.
- Menu >
Create Calibration Request...
(F7
) select the folder with the filled file for a last check and a Calibration Request file is created with the needed data as a single zip file. - Email the Calibration Request file to
info@CalibrationModel.com
to develop the calibrations.
Ok that is it, the NIR-Predictor guides you through the steps needed. And if you need to know more details, the Chapter “Create Properties File” is for you.
Create Properties File
Note:
- If you have (exported) JCAMP-DX files containing the Lab-Values, you don’t need to do this step.
You can send the JCAMP file with your Request (.req) file directly to the calibration service at info@CalibrationModel.com. - If your JCAMP-DX files does NOT contain Lab-Values, this is a way to go.
For calibrating the spectra to the lab-values you need to assign the lab-values to the spectra. The easiest way is to have a table where each spectrum (row) is linked to multiple lab-values (columns). This function Create Properties File
build such a table for the selected spectra folder automatically!
This table is stored in the file PropertiesBySamples.csv.txt
. This can be created for any spectra folder you like. The file extension is .csv.txt
to make it easy to edit in a text editor and also in a spreadsheet (excel). The columns are standard TAB separated.
The file header line contains :
Sample Replicates Names Prop1 Prop2 Prop3 DateFirst DateLast Hashes
Where Name and Date describes the spectrum.
Prop1, Prop2, Prop3 are the place to enter the Lab Reference Concentrations properties corresponding to each spectrum. It can be extended to Prop4, Prop5, … etc. Of course you can enter real word names like “Fat (%)” instead of “Prop1”. It’s recommended to put the measurement unit beside the name.
Replicates is the number of replicated or repeated spectra of a sample that is grouped together in the Sample based property file. Sample name and the DateFirst / DateLast between the sample spectra are measured.
Date format is ISO-8601. Missing Dates are 0002-02-02T00:00:00.0000000.
If the file PropertiesBySamples.csv.txt
already exist in the selected folder, the user will be notified (it will not be overwritten, because the file may contain user entered Lab-values). The Lab Reference Concentrations values are initialized to 0 (zero) and needed to be changed.
Note: 0 is not interpreted as missing value! If you have a 0 concentration value, put in 0 or 0.0 .
The entry of properties is as easy as possible, because it’s organized by Sample (and not by Spectra), so it’s like your Lab-Value Table that is sample based. The sample rows are sorted in a special way by Sample name. Sorting by Date or alphabetically by Sample can done easily in a spreadsheet program.
Note: when coping lab values to the samples make sure they correspond, so that there are no gaps and the sorting is the same.
The Spectra (rows) are initially sorted by name (and date) to have the replicates/repeats together. You can sort for your convenience in a spreadsheet program.
Enter the Lab Reference Concentrations to the spectra/sample.
Enter the Lab-Values in spreadsheet (e.g. Excel) or a text editor (e.g. Notepad++). If done, use the next menu Create Calibration Request
.
Hints: Data handling:
- The NIR-Predictor creates the
PropertiesBySamples.csv.txt
once, after that the user is responsible for its content. That means NIR-Predictor does not change this file anymore. - You can remove entire rows (spectra) in the property file. You don’t need to remove the spectra files. The NIR-Predictor is aware of the relation, the
PropertiesBySamples.csv.txt
defines what will be calibrated. - How to add more spectra files?
The additional spectra can be handled in a separate folder, create the property file and copy the spectra to the other folder and copy/merge the property files together in your editor or spreadsheet.
Or
Copy the spectra into the folder, rename the
PropertiesBySamples.csv.txt
to e.g. “PropertiesBySamples-Part1.csv.txt” and useCreate Properties File
to create a newPropertiesBySamples.csv.txt
with all the spectra. You can copy/merge the content of the Properties files together in your editor or spreadsheet. - What happens with possible duplicate rows? It does no harm to the Calibration because we do an exact checking and data cleaning in the calibration process.
- What happens to duplicate spectra names? The spectra names are not relevant for the calibration process. The spectra names are helpful to assign the lab-values to the corresponding spectrum entry. That’s why the table is initially sorted by name. The spectra names can be edited by the user.
Create Calibration Request
The menu function Create Calibration Request
packs a created Properties file (see “Create Properties File”) and it’s linked spectra files in a compressed ZIP file for sending to the CalibrationModel.com Service.
Please note that the number of measured quantitative samples need to be at least 60 . That means you need at least 60 different spectra (not counting the replicate/repeated measurements).
It shows additional property information
about the data you have entered, like – the property type (Quantitative) – it’s range (min – max) and – the number of unique values and – if the Lab-values are enough diverse to get calibrated.
First select the folder with the PropertiesBySamples.csv.txt
and measured spectra files of samples you have Lab-values. The data is checked and you get notified what is missing or might be wrong. If something needs to be changed, edit the PropertiesBySamples.csv.txt
and do Create Calibration Request
again. Your last selected folder is remembered, so you can press return in the folder selection dialog.
Hint: The keyboard shortcuts for redoing it after you edited some entries is : F7 Return
– that allows you to get the property information
quickly.
Hint: If you open the PropertiesBySamples.csv.txt
in a spreadsheet program, you can create Histogram plots of the entered Lab-values, to see in which range are to less samples measurements.
When all is fine
When all is fine the “CalibrationRequest.zip” file is created for that data.
The ZIP file contains:
- your PropertiesBySamples.csv.txt
- your personal REQuest file for your computer system, that looks like
e.g. “337dcdc06b2d6dfb0b5c4bba578642312edf2ae84d909281624d7e26283e8b07 WIN-GB0PB48GSK4.req” - the spectra data files
Note: If the CalibrationRequest.zip
file is already created and you change the PropertiesBySamples.csv.txt
make sure to delete the old CalibrationRequest.zip
file first! In the dialog it states if it was successfully created or NOT because it already exist. So you are always on the safe side.
Note: CalibrationRequest.zip
file name contains the property names to know what would be calibrated and at the end an identification number
for referencing the file. E.g. “CalibrationRequest ‘Prop1’ – ‘Prop2’ h31T3wOH.zip”
Program Settings
- The users program settings are stored in
UserSettings.json
- The program counters are stored in
GlobalCounters.json
Further References
- Data File Formats : NIR-Predictor supported Spectral Data File Formats
- Release Notes : NIR-Predictor – Release Notes History
- Frequently Asked Questions: NIR-Predictor – FAQ
Spectroscopy and Chemometrics News Weekly #33, 2019Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #33, 2019Spettroscopia e Chemiometria Weekly News #33, 2019
CalibrationModel.com
SAFE COST IN MAINTAINING NIR-SPECTROSCOPY METHODS | NIRSpectroscopy NIRS Spectroscopy DigitalTransformation Analysis Lab Laboratory Application Quantitative Analysis Methods Measurements Analytical Parameters Spectrometer Quality Accuracy LINKSpectroscopy and Chemometrics News Weekly 32, 2019 | NIRS NIR Spectroscopy Chemometrics Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality Checking LINK
Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 32, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LaborNIR LINK
Spettroscopia e Chemiometria Weekly News 32, 2019 | NIRS NIR Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem prediction NIRmodels LINK
Get the Chemometrics and Spectroscopy News in real time on Twitter @ CalibModel and follow us.
Chemometrics
"Predicting the dry matter intake of grazing dairy cows using infrared reflectance spectroscopy analysis." LINK"Simultaneous determination of food colorants in liquid samples by UVVisible spectroscopy and multivariate data analysis using a reduced calibration matrix" LINK
"Coupling MicroNIR / Chemometrics for the on-site detection of cannabinoids in hemp flours" LINK
"Calibration and Characterization of Hyperspectral Imaging Systems Used for Natural Scene Imagery" LINK
"Analysis of wood thermal degradation using 2D correlation of near infrared and visible-light spectroscopy" LINK
"Rapid method for the quantification and identification of emerging compounds in wastewater based in nir spectroscopy and chemometrics" LINK
"Predicting the dry matter intake of grazing dairy cows using infrared reflectance spectroscopy analysis" |(19)30642-3/fulltext LINK
Near Infrared
"Application of Artificial Neural Networks (ANN) Coupled with Near-InfraRed (NIR) Spectroscopy for Detection of Adulteration in Honey" LINK"Statistical Analysis of Amylose and Protein Content in Landrace Rice Germplasm Collected from East Asian Countries Based on Near-Infrared Reflectance Spectroscopy (NIRS)" LINK
"Identification of wheat kernels by fusion of RGB, SWIR, and VNIR samples." LINK
"Purity analysis of multi-grain rice seeds with non-destructive visible and near-infrared spectroscopy" LINK
"Development of a methodology to analyze leaves from Prunus dulcis varieties using near infrared spectroscopy." LINK
"Analysis of hydration water around human serum albumin using near-infrared spectroscopy" LINK
"Real-time Biomass Characterization in Energy Conversion Processes using Near Infrared Spectroscopy-A Machine Learning Approach" LINK
"Support vector machine regression on selected wavelength regions for quantitative analysis of caffeine in tea leaves by near infrared spectroscopy" LINK
"Near Infrared Reflectance Spectroscopy to analyze texture related characteristics of sous vide pork loin." LINK
"Estimation of the Alcoholic Degree in Beers through Near Infrared Spectrometry Using Machine Learning" LINK
"The quantitative detection of botanical impurities contained in seed cotton with near infrared spectroscopy method" LINK
Raman
New post: Raman spectroscopy may make thyroid cancer diagnosis less invasive | Raman spectroscopy thyroid cancer LINKOptics
"A multi-pixel diffuse correlation spectroscopy system based on a single photon avalanche diode array." LINKAgriculture
"The acute influence of sucrose consumption with and without vitamin C co-ingestion on microvascular reactivity in healthy young adults" vitaminC LINK"Identification and characterization of a fast-neutron-induced mutant with elevated seed protein content in soybean" LINK
"Quantitative analysis and hyperspectral remote sensing of the nitrogen nutrition index in winter wheat" LINK
Food & Feed
"Multidimensional scaling assisted Fourier-transform Infrared spectroscopic analysis of fruit wine samples: Introducing a novel analytical approach" LINKCalibrationModel.com
SAFE COST IN MAINTAINING NIR-SPECTROSCOPY METHODS | NIRSpectroscopy NIRS Spectroscopy DigitalTransformation Analysis Lab Laboratory Application Quantitative Analysis Methods Measurements Analytical Parameters Spectrometer Quality Accuracy LINKSpectroscopy and Chemometrics News Weekly 32, 2019 | NIRS NIR Spectroscopy Chemometrics Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality Checking LINK
Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 32, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LaborNIR LINK
Spettroscopia e Chemiometria Weekly News 32, 2019 | NIRS NIR Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem prediction NIRmodels LINK
Get the Chemometrics and Spectroscopy News in real time on Twitter @ CalibModel and follow us.
Chemometrics
"Predicting the dry matter intake of grazing dairy cows using infrared reflectance spectroscopy analysis." LINK"Simultaneous determination of food colorants in liquid samples by UVVisible spectroscopy and multivariate data analysis using a reduced calibration matrix" LINK
"Coupling MicroNIR / Chemometrics for the on-site detection of cannabinoids in hemp flours" LINK
"Calibration and Characterization of Hyperspectral Imaging Systems Used for Natural Scene Imagery" LINK
"Analysis of wood thermal degradation using 2D correlation of near infrared and visible-light spectroscopy" LINK
"Rapid method for the quantification and identification of emerging compounds in wastewater based in nir spectroscopy and chemometrics" LINK
"Predicting the dry matter intake of grazing dairy cows using infrared reflectance spectroscopy analysis" |(19)30642-3/fulltext LINK
Near Infrared
"Application of Artificial Neural Networks (ANN) Coupled with Near-InfraRed (NIR) Spectroscopy for Detection of Adulteration in Honey" LINK"Statistical Analysis of Amylose and Protein Content in Landrace Rice Germplasm Collected from East Asian Countries Based on Near-Infrared Reflectance Spectroscopy (NIRS)" LINK
"Identification of wheat kernels by fusion of RGB, SWIR, and VNIR samples." LINK
"Purity analysis of multi-grain rice seeds with non-destructive visible and near-infrared spectroscopy" LINK
"Development of a methodology to analyze leaves from Prunus dulcis varieties using near infrared spectroscopy." LINK
"Analysis of hydration water around human serum albumin using near-infrared spectroscopy" LINK
"Real-time Biomass Characterization in Energy Conversion Processes using Near Infrared Spectroscopy-A Machine Learning Approach" LINK
"Support vector machine regression on selected wavelength regions for quantitative analysis of caffeine in tea leaves by near infrared spectroscopy" LINK
"Near Infrared Reflectance Spectroscopy to analyze texture related characteristics of sous vide pork loin." LINK
"Estimation of the Alcoholic Degree in Beers through Near Infrared Spectrometry Using Machine Learning" LINK
"The quantitative detection of botanical impurities contained in seed cotton with near infrared spectroscopy method" LINK
Raman
New post: Raman spectroscopy may make thyroid cancer diagnosis less invasive | Raman spectroscopy thyroid cancer LINKOptics
"A multi-pixel diffuse correlation spectroscopy system based on a single photon avalanche diode array." LINKAgriculture
"The acute influence of sucrose consumption with and without vitamin C co-ingestion on microvascular reactivity in healthy young adults" vitaminC LINK"Identification and characterization of a fast-neutron-induced mutant with elevated seed protein content in soybean" LINK
"Quantitative analysis and hyperspectral remote sensing of the nitrogen nutrition index in winter wheat" LINK
Food & Feed
"Multidimensional scaling assisted Fourier-transform Infrared spectroscopic analysis of fruit wine samples: Introducing a novel analytical approach" LINKCalibrationModel.com
SAFE COST IN MAINTAINING NIR-SPECTROSCOPY METHODS | NIRSpectroscopy NIRS Spectroscopy DigitalTransformation Analysis Lab Laboratory Application Quantitative Analysis Methods Measurements Analytical Parameters Spectrometer Quality Accuracy LINKSpectroscopy and Chemometrics News Weekly 32, 2019 | NIRS NIR Spectroscopy Chemometrics Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality Checking LINK
Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 32, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LaborNIR LINK
Spettroscopia e Chemiometria Weekly News 32, 2019 | NIRS NIR Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem prediction NIRmodels LINK
Get the Chemometrics and Spectroscopy News in real time on Twitter @ CalibModel and follow us.
Chemometrics
"Predicting the dry matter intake of grazing dairy cows using infrared reflectance spectroscopy analysis." LINK"Simultaneous determination of food colorants in liquid samples by UVVisible spectroscopy and multivariate data analysis using a reduced calibration matrix" LINK
"Coupling MicroNIR / Chemometrics for the on-site detection of cannabinoids in hemp flours" LINK
"Calibration and Characterization of Hyperspectral Imaging Systems Used for Natural Scene Imagery" LINK
"Analysis of wood thermal degradation using 2D correlation of near infrared and visible-light spectroscopy" LINK
"Rapid method for the quantification and identification of emerging compounds in wastewater based in nir spectroscopy and chemometrics" LINK
"Predicting the dry matter intake of grazing dairy cows using infrared reflectance spectroscopy analysis" |(19)30642-3/fulltext LINK
Near Infrared
"Application of Artificial Neural Networks (ANN) Coupled with Near-InfraRed (NIR) Spectroscopy for Detection of Adulteration in Honey" LINK"Statistical Analysis of Amylose and Protein Content in Landrace Rice Germplasm Collected from East Asian Countries Based on Near-Infrared Reflectance Spectroscopy (NIRS)" LINK
"Identification of wheat kernels by fusion of RGB, SWIR, and VNIR samples." LINK
"Purity analysis of multi-grain rice seeds with non-destructive visible and near-infrared spectroscopy" LINK
"Development of a methodology to analyze leaves from Prunus dulcis varieties using near infrared spectroscopy." LINK
"Analysis of hydration water around human serum albumin using near-infrared spectroscopy" LINK
"Real-time Biomass Characterization in Energy Conversion Processes using Near Infrared Spectroscopy-A Machine Learning Approach" LINK
"Support vector machine regression on selected wavelength regions for quantitative analysis of caffeine in tea leaves by near infrared spectroscopy" LINK
"Near Infrared Reflectance Spectroscopy to analyze texture related characteristics of sous vide pork loin." LINK
"Estimation of the Alcoholic Degree in Beers through Near Infrared Spectrometry Using Machine Learning" LINK
"The quantitative detection of botanical impurities contained in seed cotton with near infrared spectroscopy method" LINK
Raman
New post: Raman spectroscopy may make thyroid cancer diagnosis less invasive | Raman spectroscopy thyroid cancer LINKOptics
"A multi-pixel diffuse correlation spectroscopy system based on a single photon avalanche diode array." LINKAgriculture
"The acute influence of sucrose consumption with and without vitamin C co-ingestion on microvascular reactivity in healthy young adults" vitaminC LINK"Identification and characterization of a fast-neutron-induced mutant with elevated seed protein content in soybean" LINK
"Quantitative analysis and hyperspectral remote sensing of the nitrogen nutrition index in winter wheat" LINK
Food & Feed
"Multidimensional scaling assisted Fourier-transform Infrared spectroscopic analysis of fruit wine samples: Introducing a novel analytical approach" LINKSpectroscopy and Chemometrics News Weekly #27, 2019Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #27, 2019Spettroscopia e Chemiometria Weekly News #27, 2019
CalibrationModel.com
Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 26, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINKSpectroscopy and Chemometrics News Weekly 26, 2019 | NIRS NIR Spectroscopy Chemometrics Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality Checking LINK
Spettroscopia e Chemiometria Weekly News 26, 2019 | NIRS NIR Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem predictionmodels LINK
This week's NIR news Weekly is sponsored by YourCompanyNameHere - BestNIRinstruments. Check out their product page ... link
Get the Chemometrics and Spectroscopy News in real time on Twitter @ CalibModel and follow us.
Chemometrics
"Non-destructive Classification for Maturity of Pomelo CV. Tubtim Siam" Brix LINK"Authentication of "Avola Almonds" by Near Infrared (NIR) Spectroscopy and chemometrics" LINK
"Feature selection based convolutional neural network pruning and its application in calibration modeling for NIR spectroscopy" LINK
" Geographical origin traceability of Cabernet Sauvignon wines based on Infrared fingerprint technology combined with chemometrics" LINK
Near Infrared
"Compositional Analysis of Cement Raw Meal by Near-Infrared (NIR) Spectroscopy" LINKA joint project by researchers from and IMB_CNM will explore the possibility of developing silicon sensors for near-infrared light detection with single photon resolution funded by the LINK
"Molecular (Raman, NIR, and FTIR) spectroscopy and multivariate analysis in consumable products analysis" LINK
"Influences of Detection Position and Double Detection Regions on Determining Soluble Solids Content (SSC) for Apples Using On-line Visible/Near-Infrared (Vis/NIR) …" LINK
"Non-destructive determination of strawberry fruit and juice quality parameters using ultraviolet, visible, and near infrared spectroscopy" LINK
"Determination of API Gravity and Total and Basic Nitrogen Content by Mid-and Near-Infrared Spectroscopy in Crude Oil with Multivariate Regression and Variable Selection" LINK
"Selecting Near-infrared Hyperspectral Wavelengths Based on One-way ANOVA to Identify the Origin of Lycium Barbarum" LINK
"Rapid and Nondestructive Measurement of Rice Seed Vitality of Different Years Using Near-Infrared Hyperspectral Imaging." LINK
"Rapid estimation of soil heavy metal nickel content based on optimized screening of near-infrared spectral bands" LINK
"Distinguishing watermelon maturity based on acoustic characteristics and near infrared spectroscopy fusion technology" LINK
"Development of a methodology to analyze leaves from Prunus dulcis varieties using near infrared spectroscopy" LINK
"Rapid fingerprinting technology of heavy oil spill by Mid-infrared spectroscopy" LINK
"Evaluation of high alcohol concentration using a 1.7-µm band near-infrared spectroscopy system using multi-mode optical fibers" LINK
Raman
"Journal Highlight: Raman Open Database: first interconnected RamanXray diffraction openaccess resource for material identification" LINKEquipment
"Water as a probe for serum-based diagnosis by temperature-dependent near-infrared spectroscopy" LINKProcess Control
"Detecting special-cause variation 'events' from process data signatures" LINKEnvironment
"Soil macrofauna and leaf functional traits drive the decomposition of secondary metabolites in leaf litter" LINKAgriculture
"Plants, Vol. 8, Pages 205: Comparison of Sugar Profile between Leaves and Fruits of Blueberry and Strawberry Cultivars Grown in Organic and Integrated Production System" LINK"Sensors, Vol. 19, Pages 2934: Combining Fourier Transform Mid-Infrared Spectroscopy with Chemometric Methods to Detect Adulterations in Milk Powder" LINK
"Utilising near-infrared hyperspectral imaging to detect low-level peanut powder contamination of whole wheat flour" LINK
Chemical
"All Donor Electrochromic Polymers Tunable across the Visible Spectrum via Random Copolymerization" LINKOther
"Effet du moment d'acquisition des spectres proche infrarouge sur la qualité de prédiction du taux de lipides et du taux de fonte du foie gras chez le canard" LINK"Investigation of the prevalence and characterisation of infection by Kudoa thyrsites and K. paniformis in South African marine fish species" LINK
CalibrationModel.com
Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 26, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINKSpectroscopy and Chemometrics News Weekly 26, 2019 | NIRS NIR Spectroscopy Chemometrics Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality Checking LINK
Spettroscopia e Chemiometria Weekly News 26, 2019 | NIRS NIR Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem predictionmodels LINK
This week's NIR news Weekly is sponsored by YourCompanyNameHere - BestNIRinstruments. Check out their product page ... link
Get the Chemometrics and Spectroscopy News in real time on Twitter @ CalibModel and follow us.
Chemometrics
"Non-destructive Classification for Maturity of Pomelo CV. Tubtim Siam" Brix LINK"Authentication of "Avola Almonds" by Near Infrared (NIR) Spectroscopy and chemometrics" LINK
"Feature selection based convolutional neural network pruning and its application in calibration modeling for NIR spectroscopy" LINK
" Geographical origin traceability of Cabernet Sauvignon wines based on Infrared fingerprint technology combined with chemometrics" LINK
Near Infrared
"Compositional Analysis of Cement Raw Meal by Near-Infrared (NIR) Spectroscopy" LINKA joint project by researchers from and IMB_CNM will explore the possibility of developing silicon sensors for near-infrared light detection with single photon resolution funded by the LINK
"Molecular (Raman, NIR, and FTIR) spectroscopy and multivariate analysis in consumable products analysis" LINK
"Influences of Detection Position and Double Detection Regions on Determining Soluble Solids Content (SSC) for Apples Using On-line Visible/Near-Infrared (Vis/NIR) …" LINK
"Non-destructive determination of strawberry fruit and juice quality parameters using ultraviolet, visible, and near infrared spectroscopy" LINK
"Determination of API Gravity and Total and Basic Nitrogen Content by Mid-and Near-Infrared Spectroscopy in Crude Oil with Multivariate Regression and Variable Selection" LINK
"Selecting Near-infrared Hyperspectral Wavelengths Based on One-way ANOVA to Identify the Origin of Lycium Barbarum" LINK
"Rapid and Nondestructive Measurement of Rice Seed Vitality of Different Years Using Near-Infrared Hyperspectral Imaging." LINK
"Rapid estimation of soil heavy metal nickel content based on optimized screening of near-infrared spectral bands" LINK
"Distinguishing watermelon maturity based on acoustic characteristics and near infrared spectroscopy fusion technology" LINK
"Development of a methodology to analyze leaves from Prunus dulcis varieties using near infrared spectroscopy" LINK
"Rapid fingerprinting technology of heavy oil spill by Mid-infrared spectroscopy" LINK
"Evaluation of high alcohol concentration using a 1.7-µm band near-infrared spectroscopy system using multi-mode optical fibers" LINK
Raman
"Journal Highlight: Raman Open Database: first interconnected RamanXray diffraction openaccess resource for material identification" LINKEquipment
"Water as a probe for serum-based diagnosis by temperature-dependent near-infrared spectroscopy" LINKProcess Control
"Detecting special-cause variation 'events' from process data signatures" LINKEnvironment
"Soil macrofauna and leaf functional traits drive the decomposition of secondary metabolites in leaf litter" LINKAgriculture
"Plants, Vol. 8, Pages 205: Comparison of Sugar Profile between Leaves and Fruits of Blueberry and Strawberry Cultivars Grown in Organic and Integrated Production System" LINK"Sensors, Vol. 19, Pages 2934: Combining Fourier Transform Mid-Infrared Spectroscopy with Chemometric Methods to Detect Adulterations in Milk Powder" LINK
"Utilising near-infrared hyperspectral imaging to detect low-level peanut powder contamination of whole wheat flour" LINK
Chemical
"All Donor Electrochromic Polymers Tunable across the Visible Spectrum via Random Copolymerization" LINKOther
"Effet du moment d'acquisition des spectres proche infrarouge sur la qualité de prédiction du taux de lipides et du taux de fonte du foie gras chez le canard" LINK"Investigation of the prevalence and characterisation of infection by Kudoa thyrsites and K. paniformis in South African marine fish species" LINK
CalibrationModel.com
Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 26, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINKSpectroscopy and Chemometrics News Weekly 26, 2019 | NIRS NIR Spectroscopy Chemometrics Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality Checking LINK
Spettroscopia e Chemiometria Weekly News 26, 2019 | NIRS NIR Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem predictionmodels LINK
This week's NIR news Weekly is sponsored by YourCompanyNameHere - BestNIRinstruments. Check out their product page ... link
Get the Chemometrics and Spectroscopy News in real time on Twitter @ CalibModel and follow us.
Chemometrics
"Non-destructive Classification for Maturity of Pomelo CV. Tubtim Siam" Brix LINK"Authentication of "Avola Almonds" by Near Infrared (NIR) Spectroscopy and chemometrics" LINK
"Feature selection based convolutional neural network pruning and its application in calibration modeling for NIR spectroscopy" LINK
" Geographical origin traceability of Cabernet Sauvignon wines based on Infrared fingerprint technology combined with chemometrics" LINK
Near Infrared
"Compositional Analysis of Cement Raw Meal by Near-Infrared (NIR) Spectroscopy" LINKA joint project by researchers from and IMB_CNM will explore the possibility of developing silicon sensors for near-infrared light detection with single photon resolution funded by the LINK
"Molecular (Raman, NIR, and FTIR) spectroscopy and multivariate analysis in consumable products analysis" LINK
"Influences of Detection Position and Double Detection Regions on Determining Soluble Solids Content (SSC) for Apples Using On-line Visible/Near-Infrared (Vis/NIR) …" LINK
"Non-destructive determination of strawberry fruit and juice quality parameters using ultraviolet, visible, and near infrared spectroscopy" LINK
"Determination of API Gravity and Total and Basic Nitrogen Content by Mid-and Near-Infrared Spectroscopy in Crude Oil with Multivariate Regression and Variable Selection" LINK
"Selecting Near-infrared Hyperspectral Wavelengths Based on One-way ANOVA to Identify the Origin of Lycium Barbarum" LINK
"Rapid and Nondestructive Measurement of Rice Seed Vitality of Different Years Using Near-Infrared Hyperspectral Imaging." LINK
"Rapid estimation of soil heavy metal nickel content based on optimized screening of near-infrared spectral bands" LINK
"Distinguishing watermelon maturity based on acoustic characteristics and near infrared spectroscopy fusion technology" LINK
"Development of a methodology to analyze leaves from Prunus dulcis varieties using near infrared spectroscopy" LINK
"Rapid fingerprinting technology of heavy oil spill by Mid-infrared spectroscopy" LINK
"Evaluation of high alcohol concentration using a 1.7-µm band near-infrared spectroscopy system using multi-mode optical fibers" LINK
Raman
"Journal Highlight: Raman Open Database: first interconnected RamanXray diffraction openaccess resource for material identification" LINKEquipment
"Water as a probe for serum-based diagnosis by temperature-dependent near-infrared spectroscopy" LINKProcess Control
"Detecting special-cause variation 'events' from process data signatures" LINKEnvironment
"Soil macrofauna and leaf functional traits drive the decomposition of secondary metabolites in leaf litter" LINKAgriculture
"Plants, Vol. 8, Pages 205: Comparison of Sugar Profile between Leaves and Fruits of Blueberry and Strawberry Cultivars Grown in Organic and Integrated Production System" LINK"Sensors, Vol. 19, Pages 2934: Combining Fourier Transform Mid-Infrared Spectroscopy with Chemometric Methods to Detect Adulterations in Milk Powder" LINK
"Utilising near-infrared hyperspectral imaging to detect low-level peanut powder contamination of whole wheat flour" LINK
Chemical
"All Donor Electrochromic Polymers Tunable across the Visible Spectrum via Random Copolymerization" LINKOther
"Effet du moment d'acquisition des spectres proche infrarouge sur la qualité de prédiction du taux de lipides et du taux de fonte du foie gras chez le canard" LINK"Investigation of the prevalence and characterisation of infection by Kudoa thyrsites and K. paniformis in South African marine fish species" LINK
NIR Method Development Service for Labs and NIR-Vendors (OEM)
CalibrationModel.com ia a perfect match for
– NIR Vendors , selling NIR , with limited capacity for NIR method development
– Labs , using NIR , with limited capacity for NIR method development
– small Labs , starting with NIR , with no or less Chemometric knowledge
The Triple to success : faster better analytics
LAB Reference Analytics + NIR Spectroscopy + ChemoMetrics
LAB + NIR + CM
=> use CM as a Service : CalibrationModel
NIR Method Development : Before / After
Before
– The need of a chemometric software ($$)
– The need of expert training courses (time,$$)
– The need of manual expert work (time,$$$)
with CalibrationModel
– The freedom without a chemometric software
– The freedom without being an expert
– The freedom of using a Service ($)
=> work smart, not hard
See Cost Comparision
Workflow:
Cloud Service
DATA -> CalibrationModel -> CALIB
fix cost, pay per CALIB development and usage
Local Usage (no internet connection)
DATA -> CALIB + Predictor -> RESULT
included, no extra cost
DATA = exported Spectra and (Lab-)reference values as JCAMP-DX or other data formats
CALIB = single quantitative property
Sending DATA
DATA is sent by email, 2-3 days later, receive email with link to
WebShop to purchase CALIB with PayPal/CreditCard
DATA is deleted after processing (Terms of Service TOS)
optional: JCAMP–Anonymizer (removes sensitive information) before sending DATA
As Middleman you can hide/cover the Service (white-label)
Customer <=============> CalibrationModel
or
Customer <==> Middleman <==> CalibrationModel
NIR Company
NIR Sales, Consultancy
Riskless Predictor OEM integration (white label) (in NIR-Vendors Instrument Software)
Predictor as a hidden second engine (second Heart)
Windows .NET, easy programming interface (API)
Ownership
DATA owner -> CALIB owner ==> use as your Pre-CALIB
CALIB is licensed to owner and so copy protected
The owner can Re-License a CALIB to others
owner can re-sell CALIBs in its own WebShop with own prices
Re-Calibration
DATA + DATA -> CALIB same easy workflow as DATA -> CALIB
optimize from scratch, benefit from complete optimization possibilities
learn more
NIR-Predictor Software
Contact us for predictor integration
NIR-Predictor Download
- comes with demo data, so you can predict sample spectra with demo calibrations.
- has no functional limitations, no nagging, no ads and needs no license-key.
- you need no account and no registration to download and use.
- runs on Microsoft Windows 10/8/7 (Starter, Basic, Professional) (32 bit / 64 bit).
- no data is ever transmitted from your local machine. We don't even collect usage data.
- for embedded integration in application, cloud and instrument-software (ICT).
- As a light-weigt single library file (DLL) with application programming interface (API), documentation and software development kit (SDK) including sample source code (C#).
- Easy integration and deployment, no software license protection (no serial key, no dongle).
- Put your spectrum as an array into the multivariate predictor, no specific file format needed.
- Fast prediction speed and low latency because of compiled code library (direct call, no cloud API).
- Protected prediction results with outlier detection information.
Software | Size | Date | Comment |
NIR-Predictor V2.6.0.2 (download) What's new, see Release Notes By downloading and/or using the software you accept the Software License Agreement (EULA) | 3.7 MB | 18.08.2021 | public release |
- NIR-Predictor Description
- NIR-Predictor Announcement
- NIR-Predictor FAQ
- Software License Agreement (EULA)
- Terms of Service (TOS)
The free NIR-Predictor software
- comes with demo data, so you can predict sample spectra with demo calibrations.
- has no functional limitations, no nagging, no ads and needs no license-key.
- you need no account and no registration to download and use.
- runs on Microsoft Windows 10/8/7 (Starter, Basic, Professional) (32 bit / 64 bit).
- no data is ever transmitted from your local machine. We don't even collect usage data.
- für die eingebettete Integration in Applikations-, Cloud- und Geräte-Software (ICT).
- Als leichtgewichtige Einzelbibliotheksdatei (DLL) mit Anwendungsprogrammier-Schnittstelle (API), Dokumentation und Software Development Kit (SDK) inklusive Beispiel-Quellcode (C#).
- Einfache Integration und Bereitstellung, kein Software-Lizenzschutz (kein Serienschlüssel, kein Dongle).
- Geben Sie Ihr Spektrum als Array in den multivariaten Prädiktor ein, es ist kein spezielles Dateiformat erforderlich.
- Schnelle Vorhersagegeschwindigkeit und niedrige Latenz aufgrund der kompilierten Code-Bibliothek (direkter Aufruf, keine Cloud-API).
- Geschützte Vorhersageergebnisse mit Informationen zur Ausreißererkennung.
Software | Size | Date | Comment |
NIR-Predictor V2.6.0.2 (download) What's new, see Release Notes By downloading and/or using the software you accept the Software License Agreement (EULA) | 3.7 MB | 18.08.2021 | public release |
- NIR-Predictor Description
- NIR-Predictor Announcement
- NIR-Predictor FAQ
- Software License Agreement (EULA)
- Terms of Service (TOS)
The free NIR-Predictor software
- comes with demo data, so you can predict sample spectra with demo calibrations.
- has no functional limitations, no nagging, no ads and needs no license-key.
- you need no account and no registration to download and use.
- runs on Microsoft Windows 10/8/7 (Starter, Basic, Professional) (32 bit / 64 bit).
- no data is ever transmitted from your local machine. We don't even collect usage data.
- per l'integrazione embedded in applicazioni, cloud e strumenti-software (ICT).
- Come un singolo file di libreria leggera (DLL) con interfaccia di programmazione dell'applicazione (API), documentazione e kit di sviluppo del software (SDK) incluso il codice sorgente di esempio (C#).
- Facile integrazione e distribuzione, nessuna protezione della licenza software (nessuna chiave seriale, nessun dongle).
- Inserisci il tuo spettro come array nel predittore multivariato, non è necessario alcun formato di file specifico.
- Velocità di predizione veloce e bassa latenza grazie alla libreria di codice compilata (chiamata diretta, nessuna API cloud).
- Risultati di predizione protetti con informazioni di rilevamento degli outlier.
Software | Size | Date | Comment |
NIR-Predictor V2.6.0.2 (download) What's new, see Release Notes By downloading and/or using the software you accept the Software License Agreement (EULA) | 3.7 MB | 18.08.2021 | public release |
NIR-PredictorNIR-PrädiktorNIR-Predittore
New: NIR-Predictor V2.6 with new features
The new Version of the free NIR-Predictor
supports GRAMS .SPC, CSV, JCAMP and multiple native file formats
of miniature, mobile and desktop spectrometers
get your spectra analyced as easy as Drag’n’Drop.
-
NIR-Predictor is an easy to use NIR software for all NIR devices
to produce quantitative results out of NIR data. -
CalibrationModel Service provides development of
customized calibrations out of NIR and Lab data. -
It allows to use NIR with your own customized
models without the need of Chemometric Software! -
We do the Machine Leraning for your NIR-Spectrometer
and with the free NIR-Predictor you are
able to analyze new measured samples. -
For NIR-Vendors we also offer the
Software Development Kit (SDK) for OEM Predictor use
via the Application Programming Interface (API).
Think of a sencod predictor engine,
as a second heart in your system.
Download
Key Features of NIR-Predictor
- Super flexible prediction with automatic file format detection
- Support for many mobile and desktop NIR Spectrometers file format
- Application concept allows to group multiple Calibrations together for an Application
- Prediction Report shows Histogram Charts of the tabulated prediction results
- Sample based Properties File Creator for combining NIR and Lab reference data
- Checked creation of a single file Calibration Request
Super flexible prediction
Loads multiple files at once in
- different file-formats and …
- different wave-ranges and wave-resolutions and …
- predicts each spectrum with all compatible calibrations and …
- merges the results in a report and …
- saves the report as HTML.
It allows you to
- comparing measurements
- compare different calibrations
- compare different spectrometers,
carry out your own round-robin amongst the vendors’ instruments. - compare different spectra file formats
With no configuration and no special menu command,
just drag & drop your data files.
Properties File Creator
A tool for the NIR-User to create the property file easily. It helps to create a CSV file from the measured spectra files with sample names and properties to edit in Spreadsheet/EXCEL software. Lets you enter Lab-Reference-Values in a sample-based manner, corresponding to your sample spectra for calibration. It contains clever automatic analysis mechanisms of inconsistencies in your raw-data to increase the data quality for calibration. Provides detailed analyzer information for manual data cleanup when needed.
It’s time saving and less error prone because you DON’T need to open each spectrum file separately in an editor and copy the spectral values into a table grid beside the Lab-values.
Properties File Creator saves you from:
- manually error prone and boring tasks
- importing multiple data files and combining it’s content manually into a single data file to append the lab reference values (aka properties)
- programming and writing scripts to transform the data into the shape needed
- no trouble with data handling of
- Wavelength / Wavenumber information (x-axis)
- Absorbance / Reflectance labeling (y-axis)
- checking compatibility of the raw data before merging
- Averaging Spectral Intensities of a Sample
- coping, flipping and transposing rows and colums to get the X-Block and Y-Block data sets ready for calibration modeling
- limited and error prone table grid functionality
Because it’s all automatic and you can check the results and get the analysis information!
Properties File Creator provides you - a individual template based on your raw-data for combining NIR and Lab-values - analysis and checks for better data quality for calibration
Top 8 Reasons why you should use
Automated NIR Calibration Service
- No subjective model selection
- No variation in results and interpretation
- No overfitting model
- Better accuracy
- Better precision
- Time saving!
- No software cost (no need for Chemometric software and training)
- One free prediction software for all your NIR systems
Reduce Total Cost of Ownership (TCO) of your NIR
To be ahead of competitors- by not owning a chemometric software
- by not struggling days with these complicated software
- by not deep dive into chemometrics theory
- You need to have the relevant skill sets in your organization.
- That means salaries (the biggest expense in most organizations)
- use the free NIR-Predictor together with your NIR-Instrument software
- as an NIR-Vendor, integrate the free NIR-Predictor OEM into your NIR-Instrument software
- don’t delay time-to-market
Download
About the included Demo-Spectra and Demo-Calibrations
The demo calibrations for the spectrometers from
- Si-Ware Systems
- Spectral Engines
- Texas Instruments
- VIAVI
are built with the raw data, thankfully provided from Prof. Heinz W Siesler, from this publication
“Hand-held near-infrared spectrometers:
State-of-the-art instrumentation and practical applications”
Hui Yan, Heinz W Siesler
First Published August 20, 2018 Research Article
https://doi.org/10.1177/0960336018796391
The demo calibrations for the FOSS are built with the
ANSIG Kaji Competition 2014 shootout data
http://www.anisg.com.au/the-kaji-competition
References
Quickstart: NIR-Predictor - Manual
Features and Version History: NIR-Predictor - Release Notes History
Supported NIR Spectra Formats: NIR-Predictor supported Spectral Data File Formats
Frequently Asked Questions: NIR-Predictor - FAQ
WebShop : CalibrationModel WebShop
New: NIR-Predictor V2.6 with new features
The new Version of the free NIR-Predictor
supports GRAMS .SPC, CSV, JCAMP and multiple native file formats
of miniature, mobile and desktop spectrometers
get your spectra analyced as easy as Drag’n’Drop.
-
NIR-Predictor is an easy to use NIR software for all NIR devices
to produce quantitative results out of NIR data. -
CalibrationModel Service provides development of
customized calibrations out of NIR and Lab data. -
It allows to use NIR with your own customized
models without the need of Chemometric Software! -
We do the Machine Leraning for your NIR-Spectrometer
and with the free NIR-Predictor you are
able to analyze new measured samples. -
For NIR-Vendors we also offer the
Software Development Kit (SDK) for OEM Predictor use
via the Application Programming Interface (API).
Think of a sencod predictor engine,
as a second heart in your system.
Download
Key Features of NIR-Predictor
- Super flexible prediction with automatic file format detection
- Support for many mobile and desktop NIR Spectrometers file format
- Application concept allows to group multiple Calibrations together for an Application
- Prediction Report shows Histogram Charts of the tabulated prediction results
- Sample based Properties File Creator for combining NIR and Lab reference data
- Checked creation of a single file Calibration Request
Super flexible prediction
Loads multiple files at once in
- different file-formats and …
- different wave-ranges and wave-resolutions and …
- predicts each spectrum with all compatible calibrations and …
- merges the results in a report and …
- saves the report as HTML.
It allows you to
- comparing measurements
- compare different calibrations
- compare different spectrometers,
carry out your own round-robin amongst the vendors’ instruments. - compare different spectra file formats
With no configuration and no special menu command,
just drag & drop your data files.
Properties File Creator
A tool for the NIR-User to create the property file easily. It helps to create a CSV file from the measured spectra files with sample names and properties to edit in Spreadsheet/EXCEL software. Lets you enter Lab-Reference-Values in a sample-based manner, corresponding to your sample spectra for calibration. It contains clever automatic analysis mechanisms of inconsistencies in your raw-data to increase the data quality for calibration. Provides detailed analyzer information for manual data cleanup when needed.
It’s time saving and less error prone because you DON’T need to open each spectrum file separately in an editor and copy the spectral values into a table grid beside the Lab-values.
Properties File Creator saves you from:
- manually error prone and boring tasks
- importing multiple data files and combining it’s content manually into a single data file to append the lab reference values (aka properties)
- programming and writing scripts to transform the data into the shape needed
- no trouble with data handling of
- Wavelength / Wavenumber information (x-axis)
- Absorbance / Reflectance labeling (y-axis)
- checking compatibility of the raw data before merging
- Averaging Spectral Intensities of a Sample
- coping, flipping and transposing rows and colums to get the X-Block and Y-Block data sets ready for calibration modeling
- limited and error prone table grid functionality
Because it’s all automatic and you can check the results and get the analysis information!
Properties File Creator provides you - a individual template based on your raw-data for combining NIR and Lab-values - analysis and checks for better data quality for calibration
Top 8 Reasons why you should use
Automated NIR Calibration Service
- No subjective model selection
- No variation in results and interpretation
- No overfitting model
- Better accuracy
- Better precision
- Time saving!
- No software cost (no need for Chemometric software and training)
- One free prediction software for all your NIR systems
Reduce Total Cost of Ownership (TCO) of your NIR
To be ahead of competitors- by not owning a chemometric software
- by not struggling days with these complicated software
- by not deep dive into chemometrics theory
- You need to have the relevant skill sets in your organization.
- That means salaries (the biggest expense in most organizations)
- use the free NIR-Predictor together with your NIR-Instrument software
- as an NIR-Vendor, integrate the free NIR-Predictor OEM into your NIR-Instrument software
- don’t delay time-to-market
Download
About the included Demo-Spectra and Demo-Calibrations
The demo calibrations for the spectrometers from
- Si-Ware Systems
- Spectral Engines
- Texas Instruments
- VIAVI
are built with the raw data, thankfully provided from Prof. Heinz W Siesler, from this publication
“Hand-held near-infrared spectrometers:
State-of-the-art instrumentation and practical applications”
Hui Yan, Heinz W Siesler
First Published August 20, 2018 Research Article
https://doi.org/10.1177/0960336018796391
The demo calibrations for the FOSS are built with the
ANSIG Kaji Competition 2014 shootout data
http://www.anisg.com.au/the-kaji-competition
References
Quickstart: NIR-Predictor - Manual
Features and Version History: NIR-Predictor - Release Notes History
Supported NIR Spectra Formats: NIR-Predictor supported Spectral Data File Formats
Frequently Asked Questions: NIR-Predictor - FAQ
WebShop : CalibrationModel WebShop
New: NIR-Predictor V2.6 with new features
The new Version of the free NIR-Predictor
supports GRAMS .SPC, CSV, JCAMP and multiple native file formats
of miniature, mobile and desktop spectrometers
get your spectra analyced as easy as Drag’n’Drop.
-
NIR-Predictor is an easy to use NIR software for all NIR devices
to produce quantitative results out of NIR data. -
CalibrationModel Service provides development of
customized calibrations out of NIR and Lab data. -
It allows to use NIR with your own customized
models without the need of Chemometric Software! -
We do the Machine Leraning for your NIR-Spectrometer
and with the free NIR-Predictor you are
able to analyze new measured samples. -
For NIR-Vendors we also offer the
Software Development Kit (SDK) for OEM Predictor use
via the Application Programming Interface (API).
Think of a sencod predictor engine,
as a second heart in your system.
Download
Key Features of NIR-Predictor
- Super flexible prediction with automatic file format detection
- Support for many mobile and desktop NIR Spectrometers file format
- Application concept allows to group multiple Calibrations together for an Application
- Prediction Report shows Histogram Charts of the tabulated prediction results
- Sample based Properties File Creator for combining NIR and Lab reference data
- Checked creation of a single file Calibration Request
Super flexible prediction
Loads multiple files at once in
- different file-formats and …
- different wave-ranges and wave-resolutions and …
- predicts each spectrum with all compatible calibrations and …
- merges the results in a report and …
- saves the report as HTML.
It allows you to
- comparing measurements
- compare different calibrations
- compare different spectrometers,
carry out your own round-robin amongst the vendors’ instruments. - compare different spectra file formats
With no configuration and no special menu command,
just drag & drop your data files.
Properties File Creator
A tool for the NIR-User to create the property file easily. It helps to create a CSV file from the measured spectra files with sample names and properties to edit in Spreadsheet/EXCEL software. Lets you enter Lab-Reference-Values in a sample-based manner, corresponding to your sample spectra for calibration. It contains clever automatic analysis mechanisms of inconsistencies in your raw-data to increase the data quality for calibration. Provides detailed analyzer information for manual data cleanup when needed.
It’s time saving and less error prone because you DON’T need to open each spectrum file separately in an editor and copy the spectral values into a table grid beside the Lab-values.
Properties File Creator saves you from:
- manually error prone and boring tasks
- importing multiple data files and combining it’s content manually into a single data file to append the lab reference values (aka properties)
- programming and writing scripts to transform the data into the shape needed
- no trouble with data handling of
- Wavelength / Wavenumber information (x-axis)
- Absorbance / Reflectance labeling (y-axis)
- checking compatibility of the raw data before merging
- Averaging Spectral Intensities of a Sample
- coping, flipping and transposing rows and colums to get the X-Block and Y-Block data sets ready for calibration modeling
- limited and error prone table grid functionality
Because it’s all automatic and you can check the results and get the analysis information!
Properties File Creator provides you - a individual template based on your raw-data for combining NIR and Lab-values - analysis and checks for better data quality for calibration
Top 8 Reasons why you should use
Automated NIR Calibration Service
- No subjective model selection
- No variation in results and interpretation
- No overfitting model
- Better accuracy
- Better precision
- Time saving!
- No software cost (no need for Chemometric software and training)
- One free prediction software for all your NIR systems
Reduce Total Cost of Ownership (TCO) of your NIR
To be ahead of competitors- by not owning a chemometric software
- by not struggling days with these complicated software
- by not deep dive into chemometrics theory
- You need to have the relevant skill sets in your organization.
- That means salaries (the biggest expense in most organizations)
- use the free NIR-Predictor together with your NIR-Instrument software
- as an NIR-Vendor, integrate the free NIR-Predictor OEM into your NIR-Instrument software
- don’t delay time-to-market
Download
About the included Demo-Spectra and Demo-Calibrations
The demo calibrations for the spectrometers from
- Si-Ware Systems
- Spectral Engines
- Texas Instruments
- VIAVI
are built with the raw data, thankfully provided from Prof. Heinz W Siesler, from this publication
“Hand-held near-infrared spectrometers:
State-of-the-art instrumentation and practical applications”
Hui Yan, Heinz W Siesler
First Published August 20, 2018 Research Article
https://doi.org/10.1177/0960336018796391
The demo calibrations for the FOSS are built with the
ANSIG Kaji Competition 2014 shootout data
http://www.anisg.com.au/the-kaji-competition
References
Quickstart: NIR-Predictor - Manual
Features and Version History: NIR-Predictor - Release Notes History
Supported NIR Spectra Formats: NIR-Predictor supported Spectral Data File Formats
Frequently Asked Questions: NIR-Predictor - FAQ
WebShop : CalibrationModel WebShop