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

Spectroscopy and Chemometrics News Weekly #49, 2020

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 48, 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 48, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 48, 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)

“NIR spectroscopy of natural medicines supported by novel instrumentation and methods for data analysis and interpretation” LINK

“A fast determination of insecticide deltamethrin by spectral data fusion of UV-vis and NIR based on extreme learning machine” LINK

“Assessing Laser Cleaning of a Limestone Monument by Fiber Optics Reflectance Spectroscopy (FORS) and Visible and Near-Infrared (VNIR) Hyperspectral Imaging …” LINK

“Near infrared spectroscopy combined with chemometrics to detect and quantify adulteration of maca powder ” LINK

“Potential of smartphone-coupled micro NIR spectroscopy for quality control of green tea” LINK


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

“Determination of Adenosine and Cordycepin Concentrations in Cordyceps militaris Fruiting Bodies Using Near-Infrared Spectroscopy.” LINK

“… : Prediction of α-Lactalbumin and β-Lactoglobulin Composition of Aqueous Whey Solutions Using Fourier Transform Mid-Infrared and Near-Infrared Spectroscopy” LINK

“The Effect of Freeze-Drying Pretreatment on the Accuracy of Near Infrared Spectroscopic Food Analysis to Predict the Nutritive Values of Japanese Cooked Foods” LINK

“Estimating hardness and density of wood and charcoal by near-infrared spectroscopy” LINK

“Assessing the interaction between drying and addition of maltodextrin to Kakadu plum powder samples by two dimensional and near infrared spectroscopy” LINK

“Near-infrared Spectroscopy and Hyperspectral Imaging for Sugar Content Evaluation in Potatoes over Multiple Growing Seasons” LINK

“Determination of radial profiles of wood properties using a near infrared scanning system” LINK

“FTIR combined with chemometric tools (Fingerprinting spectroscopy) in comparison to HPLC; Which strategy offers more opportunities as a green analytical chemistry technique for the pharmaceutical analysis” LINK

“Prediction of high-biomass sorghum quality using near infrared spectroscopy to monitoring calorific value, moisture, and ash content.” LINK

Raman Spectroscopy

“Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy” LINK

Hyperspectral Imaging (HSI)

“Hyperspectral Imaging for Minced Meat Classification Using Nonlinear Deep Features” LINK

“Monitoring microstructural changes and moisture distribution of dry-cured pork-A combined confocal laser scanning microscopy and hyperspectral imaging study.” LINK

“Monitoring Urban Black-Odorous Water by Using Hyperspectral Data and Machine Learning” LINK

Chemometrics and Machine Learning

“Development of multi-product calibration models of various root and tuber powders by fourier transform near infra-red (FT-NIR) spectroscopy for the quantification of polysaccharide contents.” LINK

Research on Spectroscopy

“Extraction of rheological-optical characteristics of rice single kernel, in order to develop an instrumental method for determining grain quality” LINK

Equipment for Spectroscopy

“Near-infrared spectroscopy in quality control of Piper nigrum: A Comparison of performance of benchtop and handheld spectrometers” Pepper LINK

Process Control and NIR Sensors

“De-risking excipient particle size distribution variability with automated robust mixing: Integrating quality by design and process analytical technology.” LINK

“Evaluation of IoT-Enabled Monitoring and Electronic Nose Spoilage Detection for Salmon Freshness During Cold Storage” Foods LINK

Agriculture NIR-Spectroscopy Usage

“Impact of Goji Berries (Lycium barbarum) Supplementation on the Energy Homeostasis of Rabbit Does: Uni- and Multivariate Approach” Animals LINK

“Chemometrics in NIR Hyperspectral Imaging: Theory and Applications in the Agricultural Crops and Products Sector” LINK

Horticulture NIR-Spectroscopy Applications

“Watermelon ripeness detector using near infrared spectroscopy” LINK

Food & Feed Industry NIR Usage

“Portable NIR spectrometer for quick identification of fat bloom in chocolates.” LINK

“Non-destructive identification of slightly sprouted wheat kernels using hyperspectral data on both sides of wheat kernels” LINK

Pharma Industry NIR Usage

“Application of Process Analytical Technology in Active Pharmaceutical Ingredient Production (PAT)” LINK

Medicinal Spectroscopy

“Microwave Ablation Efficacy Evaluation of Bone Tissue Based on Near Infrared Spectrum” LINK

Laboratory and NIR-Spectroscopy

“Simultaneous prediction of several soil properties related to engineering uses based on laboratory Vis-NIR reflectance spectroscopy” LINK


“ニューラルネットワークを用いた近赤外ハイパースペクトル画像におけるプラーク検出” Dental Plaque Detection LINK

“Preparation and characterization of triamterene complex with ascorbic acid derivatives” LINK

Spectroscopy and Chemometrics News Weekly #42, 2020

NIR Calibration-Model Services

Stop Paying Too Much Time and Effort for NIRS Chemometrics Calibration Method Development! Use a Service | accuracy measure predictive analytics NIR spectroscopy analysis outsourcing Lab laboratory QA QC QAQC LINK

Spectroscopy and Chemometrics News Weekly 41, 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 41, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 41, 2020 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl 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)

“Modelling potentially toxic elements in forest soils with vis–NIR spectra and learning algorithms” LINK


“In 30 years of near-infrared spectroscopy, I haven’t seen too many drugs that look like that,” said Robert Lodder, PhD, of the UK College of Pharmacy . By . medtwitter medstudenttwitter LINK

“Chemometric strategies for nondestructive and rapid assessment of nitrate content in harvested spinach using VisNIR spectroscopy” LINK


Using Near-infrared reflectance spectroscopy (NIRS) to predict glucobrassicin concentrations in cabbage and brussels sprout leaf tissue LINK

“Age estimation of red snapper (Lutjanus campechanus) using FT-NIR spectroscopy: feasibility of application to production ageing for management” LINK

“Rapid Assessment of Exercise State through Athlete’s Urine Using Temperature-Dependent NIRS Technology” LINK

“Multivariate calibration: Identification of phenolic compounds in PROPOLIS using FTNIR” LINK

“FT-NIR spectroscopy and RP-HPLC combined with multivariate analysis reveals differences in plant cell suspension cultures of Thevetia peruviana treated with salicylic acid and methyl jasmonate.” LINK

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

“Non-destructive detection of foreign contaminants in toast bread with near infrared spectroscopy and computer vision techniques” LINK

“Knowledge-based genetic algorithm for resolving the near-infrared spectrum and understanding the water structures in aqueous solution” LINK

“Estimation of heavy metals using deep neural network with visible and infrared spectroscopy of soil.” LINK

“Lipid Core Plaque Distribution Using Near-infrared Spectroscopy Is Consistent with Pathological Evaluation in Carotid Artery Plaques” LINK

“Elucidation of the Molecular Mechanism of Wet Granulation for Pharmaceutical Standard Formulations in a High-Speed Shear Mixer Using Near-Infrared Spectroscopy” LINK

“Nearinfrared spectroscopy and data analysis for predicting milk powder quality attributes” LINK

“Near Infrared Reflectance Spectroscopy and Multivariate Analyses for Fast and Non-Destructive Prediction of Corn Seed Germination” LINK

“Effect of Sample Preparation Methods on the Prediction Performances of Near Infrared Reflectance Spectroscopy for Quality Traits of Fresh Yam (Dioscorea spp.)” LINK

“Comparison of artificial neural networks and multiple regression tools applied to near infrared spectroscopy for predicting sensory properties of products from Quality …” LINK

Raman Spectroscopy

Raman spectra‐based deep learning: A tool to identify microbial contamination LINK

“Temperature-Induced Chemical Changes in Lubricant Automotive Oils Evaluated Using Raman Spectroscopy” LINK

“Study of Blood Serum in Rats with Transplanted Cholangiocarcinoma Using Raman Spectroscopy” LINK

Hyperspectral Imaging (HSI)

“Early detection of black Sigatoka in banana leaves using hyperspectral images” LINK

Chemometrics and Machine Learning

“Weights or measures for better calibration” spectroscopy LINK

“Feasibility of rapid piperine quantification in whole and black pepper using near infrared spectroscopy and chemometrics” LINK

“Rethinking AI talent strategy as automated machine learning comes of age” | employment MachineLearning automated AutoML LINK

“Developing Calibration Model for Prediction of Malt Barley Genotypes Quality Traits using Fourier Transform near Infrared Spectroscopy” LINK

Equipment for Spectroscopy

“Discriminant analysis of pyrrolizidine alkaloid contamination in bee pollen based on near-infrared data from lab-stationary and portable spectrometers” | LINK

Future topics in Spectroscopy

“Journal of Global Trends in Pharmaceutical Sciences” LINK

Agriculture NIR-Spectroscopy Usage

“Evaluation of soybean condition under various fertilizer application by the relationship of the red and near-infrared bands reflectance in scatter plot” LINK

“Nutrient Prediction for Tef (Eragrostis tef) Plant and Grain with Hyperspectral Data and Partial Least Squares Regression: Replicating Methods and Results across Environments” LINK

“A spectral parameter for the estimation of soil total nitrogen and nitrate nitrogen of winter wheat growth period” LINK

“Animal species identification in parchments by light.” LINK

Food & Feed Industry NIR Usage

“Intrinsic and Extrinsic Quality Attributes of Fresh and Semi-Hard Goat Cheese from Low- and High-Input Farming Systems” LINK

“Non-Invasive Characterization of Single-, Double- and Triple-Viral Diseases of Wheat With a Hand-Held Raman Spectrometer” | LINK


“Physicochemical Fingerprint of “Pera Rocha do Oeste”. A PDO Pear Native from Portugal.” LINK

“Polymer types ingested by northern fulmars (Fulmarus glacialis) and southern hemisphere relatives” LINK


NIR-Predictor Download

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.
See more Videos

Beside the free NIR-Predictor software with Windows user interface,
the real-time Predictor Engine is also available
  • 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.
See NIR Method Development Service for Labs and NIR-Vendors (OEM, White-Label)

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

Minimal System Requirements
Windows 7 Starter 32Bit, 1.6 GHz, 2 GB RAM, non-Administrator account

There are no administrator rights required, unpack the zip file to a folder “NIR-Predictor” in your documents or on your desktop.
Read the ReadMe.txt and double click the NIR-Predictor.exe file.

If you have installed an older version of NIR-Predictor then unpack into a different folder named e.g. “NIR-PredictorVx.y”. All versions can run side-by-side. Copy the Calibrations in use to the new version into the “Calibration” folder. That’s all.

Make sure to backup your reports and calibrations inside your “NIR-Predictor” folder. Delete the “NIR-Predictor” folder.

Start Calibrate

See also: