Digitization in the field of NIR spectroscopy (smart sensors)

Digitalization is advancing, also in NIR spectroscopy, which enables trainable miniature smart sensors e.g. for analyses in the food&feed, chemical and pharmaceutical sectors.

The calibration is the core of a NIR spectroscopy sensor, it enables the numerous applications and should therefore not be the weakest link in the measurement chain.

The development of calibrations that turn NIR spectrometers into smart sensors is done manually by experts (NIR specialist, chemometrician, data scientist) with so-called chemometrics software.

This is very time-consuming (time to market) and the result is person-dependent and thus suboptimal, because each expert has his own preferred way of proceeding. In addition, the calibrations have to be maintained, as new data has been collected in the meantime, which can be used to extend and improve the calibrations.

This is where our automated service comes in, combining the knowledge and good practices of NIR spectroscopy and chemometrics collected in one software and using machine learning to generate optimal calibrations.

Based on this, we have developed a complete technology platform (Time to Market) that covers the entire process from sending NIR + Lab data, to NIR Calibration as a Service, from online purchase of calibrations, to NIR Predictor software that directly evaluates newly measured NIR data locally and generates result reports.

Besides the free desktop version with user interface, the NIR Predictor can also be integrated (OEM). This can be integrated in parallel as a complement to your current Predictor, allowing the user to choose how they want to calibrate. And give them the advantage in NIR feasibility studies and NIR spectrometer evaluations to quickly provide the customer with a solid and accurate calibration that will make their NIR system deliver better results.

Advantages for your NIR users (internal or external)
  • no initial costs (no chemometrics software license required),
  • calculable operating costs (fixed amount instead of time and hourly rate) (calibration development, calibration maintenance)
  • easy to use (no chemometrics and software training),
  • quicker to use (no calibration development work) and
  • better calibrations (precision, accuracy, robustness, …)

Our chargeable service is based on the calibration development and the annual calibration use. Calibration development and calibration use can also be carried out separately (manufacturer / user).

For you as a spectrometer manufacturer, this means that you can deliver your system pre-calibrated for certain applications without incurring software license costs. And without your application specialists having to provide additional calibration services.

The unique advantages of our calibration service together with the free NIR Predictor are:
  • no software license costs (chemometrics software, predictor software, OEM integration)
  • no chemometrics know-how necessary
  • no time needed to develop optimal NIR calibrations.

If interested in using/evaluating the service :

About CalibrationModel.com : Time and knowledge intensive creation and optimization of chemometric evaluation methods for spectrometers as a service to enable more accurate analysis and measurement results.

see also

Paradigm Change in NIR

Five Mistakes to avoid on Digitalization in NIR

NIR – Total cost of ownership (TCO)

OEM / White Label Software

White Paper

NIR Analysis in Laboratory and Laboratories – aka NIR Labs and NIR testing

Do you have a NIR spectrometer in your Lab?

How many other analytics you do in the Lab could be done faster and cheaper with NIR?

Is this possible and precise enough?

Try, we have the solution for you!
You have the NIR, scan the samples, you have the lab values and the spectra, we calibrate for you!

To see if the application is possible and how precise it can be due to knowledge based intensive model optimizations.

We do the NIR feasibility study with data for you. Fixed prices

NIR has huge application potentials and it’s a Green analytical method, that’s fast and easy to use. And has today the possibility to scale out with inexpensive mobile NIR spectrometers.

Bring the Lab to the sample. To avoid sample transport and get immediate results for decision at the place or in the process.

Just try the NIR application, use the NIR daily, collect data in parallel, we develop, optimize and maintain the calibration models for you.

How do you think?

Start Calibrate

What is possible today with NIR?
The number of different Applications exploded in the last 2-3 years!
See NIR research papers news daily on @CalibModel or the 7-day summariesNIR News Weekly” here.

Spectroscopy and Chemometrics News Weekly #36, 2020

NIR Calibration-Model Services

Get the Chemometrics and Spectroscopy News in real time on Twitter @ CalibModel and follow us.

This week’s NIR news Weekly is sponsored by Your-Company-Name-Here – NIR-spectrometers. Check out their product page … link

Spectroscopy and Chemometrics News Weekly 35, 2020 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 35, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 35, 2020 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK

Near-Infrared Spectroscopy (NIRS)

“Estimating Roughage Quality with Near Infrared Reflectance (NIR) Spectroscopy and Chemometric Techniques” LINK

“Detection of Insect Damage in Green Coffee Beans Using VIS-NIR Hyperspectral Imaging” LINK

“Revisiting Water Speciation in Hydrous Alumino-Silicate glasses: A Discrepancy between Solid-state 1H NMR and NIR spectroscopy in the Determination of X-OH …” LINK

“Prediction of Organic Carbon Content of Intertidal Sediments Based on Visible-Near Infrared Spectroscopy” “可见-近红外光谱的潮间带沉积物有机碳含量的几种模型预测方法” LINK

Infrared Spectroscopy (IR) and Near-Infrared Spectroscopy (NIR)

“Predicting soil phosphorus and studying the effect of texture on the prediction accuracy using machine learning combined with near-infrared spectroscopy” LINK

“CIC nanoGUNE reaches new depths in infrared nanospectroscopy” LINK

“Distinguishing Hemp from Marijuana by Mid-Infrared Spectroscopy” LINK

“Glucobrassicin Enhancement Using Low Red to Far-Red Light Ratio in ‘Ruby Ball’ Cabbage and High-Throughput Glucobrassicin Estimation Using Near-Infrared …” LINK

“Near-infrared spectroscopy outperforms genomic selection for predicting sugarcane feedstock quality traits” LINK

“Estimation of critical nitrogen contents in peach orchards using visible-near infrared spectral mixture analysis” LINK

“Non-destructive and rapid measurement of sugar content in growing cane stalks for breeding programmes using visible-near infrared spectroscopy” LINK

“Quantitative Analysis of Protein and Polysaccharide in Lilium Lanzhou Based on Near Infrared Spectroscopy” LINK

“Time-stretch infrared spectroscopy” LINK

“Using near infrared reflectance spectroscopy for estimating nutritional quality of Brachiaria humidicola in breeding selections” LINK

“Quantification of phenolic acids by partial least squares Fouriertransform infrared (PLSFTIR) in extracts of medicinal plants” LINK

Chemometrics and Machine Learning

“Predicting adulteration of Palm oil with Sudan IV dye using shortwave handheld spectroscopy and comparative analysis of models” LINK

“Self-adaptive models for predicting soluble solid content of blueberries with biological variability by using near-infrared spectroscopy and chemometrics” LINK

“Rapid identification and quantitative pit mud by near infrared Spectroscopy with chemometrics” LINK

“Methane emission detection and flux quantification from exploratory hydraulic fracturing in the United Kingdom, using unmanned aerial vehicle sampling” LINK

Research on Spectroscopy

“MD dating: molecular decay (MD) in pinewood as a dating method” LINK

“Improved Dimensional Stability and Mold Resistance of Bamboo via In Situ Growth of Poly(Hydroxyethyl Methacrylate-N-Isopropyl Acrylamide)” Polymers LINK

Equipment for Spectroscopy

“Applied Sciences, Vol. 10, Pages 4896: A Novel Single-Channel Arrangement in Chirp Transform Spectrometer for High-Resolution Spectrum Detection” LINK

Agriculture NIR-Spectroscopy Usage

“Angle Distribution Measurement of Scattered Light Intensity from Needle-shaped Crystals in a Magnetic Field for Gout Diagnosis” LINK

“Use of barley silage or corn silage with dry-rolled barley, corn, or a blend of barley and corn on predicted nutrient total tract digestibility and growth performance of …” LINK

“Identification of Leaf-Scale Wheat Powdery Mildew (Blumeria graminis f. sp. Tritici) Combining Hyperspectral Imaging and an SVM Classifier” Plants LINK

“Smartphone-supported portable micro-spectroscopy/imaging system to character morphology and spectra of samples at microscale” LINK

“Novel Antioxidant Packaging Films Based on Poly(-Caprolactone) and Almond Skin Extract: Development and Effect on the Oxidative Stability of Fried Almonds” LINK

“Applied Sciences, Vol. 10, Pages 4907: Experimental Comparison of Diesel and Crude Rapeseed Oil Combustion in a Swirl Burner” LINK

“Molecules, Vol. 25, Pages 3260: Comparison of Bioactive Phenolic Compounds and Antioxidant Activities of Different Parts of Taraxacum mongolicum” LINK

Horticulture NIR-Spectroscopy Applications

“Application of a Vis-NIR Spectroscopic Technique to Measure the Total Soluble Solids Content of Intact Mangoes in Motion on a Belt Conveyor” LINK

Forestry and Wood Industry NIR Usage

“Online analysis of wood extractives” LINK

Food & Feed Industry NIR Usage

Near-Infrared Spectroscopy as a Beef Quality Tool to Predict Consumer Acceptance” Foods LINK

“Rapid Vitality Estimation and Prediction of Corn Seeds Based on Spectra and Images Using Deep Learning and Hyperspectral Imaging Techniques” LINK

“Identification of Bacterial Blight Resistant Rice Seeds Using Terahertz Imaging and Hyperspectral Imaging Combined With Convolutional Neural Network.” LINK

“A simple design for the validation of a FT-NIR screening method: Application to the detection of durum wheat pasta adulteration.” LINK

Laboratory and NIR-Spectroscopy

In-line UV-Vis Spectroscopy Market Research Report 2019-2030 | Industry Report, Industry …: Success of this technology depends on the in-depth knowledge of the link between optical instrumentation design and its effect on data quality. LINK


“The Detection of Substitution Adulteration of Paprika with Spent Paprika by the Application of Molecular Spectroscopy Tools” LINK

“Non-destructive Detection of Apple Maturity by Constructing Spectral Index based on Reflectance Spectrum” LINK

Spectroscopy and Chemometrics News Weekly #35, 2020

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 34, 2020 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality 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 Spectroscopy (NIRS)

“Modelos NIRS para as características químicas da madeira de Eucalyptus benthamii Maiden & Cambage” LINK

“Application of in situ near infra-red spectroscopy (NIRS) for monitoring biopharmaceuticals production by cell cultures” LINK

“Using the NIRS for analyzes of soil clay content” LINK

“Determination of compost maturity using near infrared spectroscopy (NIRS)” LINK

“Screening Risk Assessment of Agricultural Areas under a High Level of Anthropopressure Based on Chemical Indexes and VIS-NIR Spectroscopy” LINK

“… an algorithm for processing Red Green Blue (RGB) images for the estimation of crude protein in grasses vs Near Infrared Reflectance Spectroscopy Technology (NIRS …” LINK

“Monitoring of cheese maturation using near infrared-hyperspectral imaging (NIR-HIS)” LINK

“Selection of sugarcane clones via multivariate models using near-infrared (NIR) spectroscopy data” LINK

Infrared Spectroscopy (IR) and Near-Infrared Spectroscopy (NIR)

“Rapid and simultaneous analysis of multiple wine quality indicators through near-infrared spectroscopy with twice optimization for wavelength model” LINK

“Manuka honey adulteration detection based on near-infrared spectroscopy combined with aquaphotomics” LINK

” Identification of Marine Fish Taxa by Linear Discriminant Analysis of Reflection Spectra in the Near-Infrared Region” LINK

“Assessment of Intact Macadamia Nut Internal Defects Using Near-Infrared Spectroscopy” LINK

“Rational design of near-infrared platinum(ii)-acetylide conjugated polymers for photoacoustic imaging-guided synergistic phototherapy under 808 nm irradiation.” LINK

“Classification of fish species from different ecosystems using the near infrared diffuse reflectance spectra of otoliths” LINK

“Three new Amazonian species of Myrcia sect. Myrcia (Myrtaceae) based on morphology and near-infrared spectroscopy” LINK

“Rapid Online Determination of Feed Concentration in Nitroguanidine Spray Drying Process by Near Infrared Spectroscopy” LINK

Raman Spectroscopy

“Monitoring the Caustic Dissolution of Aluminum Alloy in a Radiochemical Hot Cell Using Raman Spectroscopy” LINK

Hyperspectral Imaging (HSI)

“Hyperspectral Imaging and Deep Learning for Food Safety Assessment” LINK

Chemometrics and Machine Learning

“Rapid and Nondestructive Freshness Determination of Tilapia Fillets by a Portable Near-Infrared Spectrometer Combined with Chemometrics Methods” LINK

“Non-Targeted Detection of Adulterants in Almond Powder Using Spectroscopic Techniques Combined with Chemometrics.” LINK

Environment NIR-Spectroscopy Application

“Mobile Proximal Sensing with Visible and Near Infrared Spectroscopy for Digital Soil Mapping” LINK

Agriculture NIR-Spectroscopy Usage

“Imaging Techniques for Chicken Products Detection” LINK

“Usage of visual and near-infrared spectroscopy to predict soil properties in forest stands” LINK


“Robustness of visible near-infrared and mid-infrared spectroscopic models to changes in the quantity and quality of crop residues in soil” LINK

“Use of leaf hyperspectral data and different regression models to estimate photosynthetic parameters (Vcmax and Jmax) in three different row crops” LINK

“Rapid and direct detection of small microplastics in aquatic samples by a new near infrared hyperspectral imaging (NIR-HSI) method” LINK

Horticulture NIR-Spectroscopy Applications

“Prediction of Soluble Solids Content During Storage of Apples with Different Maturity Based on VIS/NIR Spectroscopy” LINK

“A new spectral pretreatment method for detecting soluble solids content of pears using Vis/NIR spectroscopy” LINK

“Research on the Performance of Juicy Peach Sugar Content Detection Model Based on Near Infrared Spectroscopy” LINK

Forestry and Wood Industry NIR Usage

“The Effect of Construction and Demolition Waste Plastic Fractions on Wood-Polymer Composite Properties” LINK

Food & Feed Industry NIR Usage

“Non-destructive Assessment of Flesh Firmness and Dietary Antioxidants of Greenhouse-grown Tomato (Solanum lycopersicum L.) at Different Fruit Maturity Stages” LINK

“Comparative analysis of rice seed viability detection based on different spectral bands” LINK

“Detection of chocolate powder adulteration with peanut using near-infrared hyperspectral imaging and Multivariate Curve Resolution” LINK

Spectroscopy and Chemometrics News Weekly #1, 2020


Five Mistakes to avoid on Digitalization in NIR-Spectroscopy – that Lab Managers, Executives and CEOs must know! NIRSpectroscopy NIRS Sensors NearInfrared Analyzers DigitalTransformation QualityControl foodtech machinelearning AI datascience LINK

SAFE COST IN MAINTAINING NIR-SPECTROSCOPY METHODS | NIRSpectroscopy NIRS Spectroscopy DigitalTransformation Analysis Lab Laboratory Application Quantitative Analysis Methods Measurements Analytical Parameters Spectrometer Quality Accuracy LINK

Do you develop NIR / NIRS calibrations by yourself? Can you sell it? No? Buy it! Digitalization LabManager LabAutomation CEO Digitalisation Spectroscopy AutoML LowCost lowerCost SaveMoney SaveTime Efficiency Effectivity LINK

5 Fehler, die es bei der Digitalisierung in der NIR-Spektroskopie zu vermeiden gilt – das müssen Labormanager, Führungskräfte und CEOs wissen! NIRSpectroscopy NIRS Sensor NearInfrared Analyzers DigitalTransformation foodtech machinelearning LINK

Spectroscopy & Chemometrics News Weekly 52, 2019 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Food Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality Check LINK

Spectroscopy & Chemometrics News Weekly 51, 2019 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory AI Software IoT Sensors QA QC Testing Quality 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

“Estimation and classification of popping expansion capacity in popcorn breeding programs using NIR spectroscopy” LINK

“Simultaneous detection of quality and safety in spinach plants using a new generation of NIRS sensors” LINK

“Identification of Genuine and Adulterated Pinellia ternata by Mid-Infrared (MIR) and Near-Infrared (NIR) Spectroscopy with Partial Least Squares – Discriminant …” LINK

“Monitoring coffee roasting cracks and predicting with in situ near-infrared spectroscopy” LINK

“Assessment of a soil fertility index using visible and near-infrared spectroscopy in the rice paddy region of southern China” LINK

“Conversion of the Felixton Mill laboratory from conventional to NIRS analysis.” LINK

“Automatic cancer discrimination based on near-infrared spectrum and class-modeling technique” LINK

“Food powders classification using handheld Near-Infrared Spectroscopy and Support Vector Machine” LINK

“Development and validation of a method for separation of pregabalin and gabapentin capsules using Near Infrared hyperspectral imaging” LINK

“Field-resolved infrared spectroscopy of biological systems” Nature LINK

“Infrared spectroscopy finally sees the light” nature LINK

“Journal Highlight: Estimation of protein and fatty acid composition in shellintact cottonseed by near Infrared reflectance spectroscopy” LINK

” Visible/near-infrared Spectroscopy as a Novel Technology for Nondestructive Detection of Escherichia coli ATCC 8739 in Lettuce Samples” LINK

“The model updating based on near infrared spectroscopy for the sex identification of silkworm pupae from different varieties by a semi-supervised learning with pre …” LINK

“… Study on the Determination of ppm-Level Concentration of Histamine in Tuna Fish Using a Dry Extract System for Infrared Coupled with Near-Infrared Spectroscopy” LINK


“Transmission Raman Spectroscopic Quantification of Active Pharmaceutical Ingredient in Coated Tablets of Hot-Melt Extruded Amorphous Solid Dispersion” LINK


“Plastic waste monitoring and recycling by hyperspectral imaging technology” LINK

“Comparison of Ink Classification Capabilities of Classic Hyperspectral Similarity Features” LINK



“Development of Partial Least Square (PLS) Prediction Model to Measure the Ripeness of Oil Palm Fresh Fruit Bunch (FFB) by Using NIR Spectroscopy” LINK


“Bombs and cocaine: detecting nefarious nitrogen sources using remote sensing and machine learning” LINK


“Laboratory-based hyperspectral image analysis for the classification of soil texture” LINK

“Research on simultaneous detection of SSC and FI of blueberry based on hyperspectral imaging combined MS-SPA” LINK

“Polymers, Vol. 12, Pages 78: Insight into the Intermolecular Interaction and Free Radical Polymerizability of Methacrylates in Supercritical Carbon Dioxide” LINK

“Optimizing the procedure of grain nutrient predictions in barley via hyperspectral imaging.” LINK


“绿泥石矿物近红外光谱吸收谱带的位移机理与控制机制研究” LINK

“Spektroskopie – Unverwechselbarer molekularer Fingerabdruck” LINK


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.

Spectra Plots and Histograms on the Prediction Report
  • 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.


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
It takes significant know-how and continous investment to develop calibrations
  • You need to have the relevant skill sets in your organization.
  • That means salaries (the biggest expense in most organizations)
To get most out of it, start now!
  • 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
Read more about NIR Total cost of ownership (TCO)


About the included Demo-Spectra and Demo-Calibrations

The demo calibrations for the spectrometers from

  • Si-Ware Systems
  • Spectral Engines
  • Texas Instruments

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

The demo calibrations for the FOSS are built with the

ANSIG Kaji Competition 2014 shootout data


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