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 #9, 2020


Efficient development of new quantitative prediction equations for multivariate NIR spectra data NIRS NIR NIT LINK

NIR Calibration Service explained | NIRS NIR Near Infrared Spectroscopy Prediction Analysis Results Calibration Model multivariate Chemometrics equations SaaS LINK

Service für professionelle Entwicklung von Nah-Infrarot Spektroskopie Kalibrations Methoden | NIRS Qualität Prüfen LINK

Spectroscopy and Chemometrics News Weekly 8, 2020 | NIRS NIR Spectroscopy MachineLearning Spectrometer Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory automation Software IoT Sensors QA QC QAQC qualitycontrol LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 8, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot WetChemistry Lab Lab40 FoodTech FoodAnalysis Analysentechnik Analysemethode Nahinfrarotspektroskopie LINK

Spettroscopia e Chemiometria Weekly News 8, 2020 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK

Near Infrared

“Prediction of starch reserves in intact and ground grapevine cane wood tissues using near infrared reflectance spectroscopy (NIRS).” LINK

“An application to analyzing and correcting for the effects of irregular topographies on NIR hyperspectral images to improve identification of moldy peanuts” LINK

“Data Fusion Approach Improves the Prediction of Single Phenolic Compounds in Honey: A Study of NIR and Raman Spectroscopies” LINK

Monitoring roasting of coffee beans by NIR spectroscopy using a method called REP-ASCA coffee ☕️ chemical information related to flavors and aromas. LINK

“The Effect of Light Intensity, Sensor Height, and Spectral Pre-Processing Methods when using NIR Spectroscopy to Identify Different Allergen-Containing Powdered Foods.” LINK

“Immediate measurement of fuel characteristics of bio-char using NIRS” LINK

“Nonlinear Manifold Dimensionality Reduction Methods for Quick Discrimination of Tea at Different Altitude by Near Infrared Spectroscopy” LINK

Phenome2020 Yufeng Ge Univ Nebraska VIS-NIR-SWIR spectroscopy to analyse leaf chemistry and physiology LINK

“Rapid assessment of pork freshness using miniaturized NIR spectroscopy” LINK

“On-line prediction of hazardous fungal contamination in stored maize by integrating Vis/NIR spectroscopy and computer vision” LINK

“Chemical Characterization of Wine Vinegars Belonging to the Vinagre de Montilla-Moriles Protected Designation of Origin, Using Near-Infrared Spectroscopy” LINK

“Application of Near-Infrared Spectroscopy for the identification of rock mineralogy from Kos Island, Aegean Sea, Greece” LINK

“Assessment of Spinal Cord Ischemia With Near-Infrared Spectroscopy: Myth or Reality?” LINK

“Portable Near-Infrared spectroscopy for rapid authentication of adulterated paprika powder” LINK

“Study on the Quality Assessment of Canola Oil after Prolonged Frying Using Near-Infrared Spectroscopy” LINK


“Statistical Analysis of Amylose and Protein Content in Breeding Line Rice Germplasm Collected from East Asian Countries Based on Near-infrared reflectance …” LINK

“Assessment of pork freshness based on changes in constituting chromophores using visible to near-infrared spectroscopy” LINK

“Sensors, Vol. 20, Pages 273: Near-Infrared Transmittance Spectral Imaging for Nondestructive Measurement of Internal Disorder in Korean Ginseng” LINK



On NationalScienceDay, we celebrate the discovery of the RamanEffect by great scientist CVRaman. Do you know? The Raman effect forms the basis for Raman spectroscopy which is used by chemists & physicists to gain information about materials. LINK

“Handheld device weeds out cannabis from hemp. Raman device that measures levels of tetrahydrocannabinol could be a useful tool for police and customs agents” LINK


“Essential processing methods of hyperspectral images of agricultural and food products” LINK

“Determine Reducing Sugar Content in Potatoes Using Hyperspectral Combined with VISSA Algorithm” LINK

“Spatial variation of wood density for Eucalyptus grandis by near infra red hyperspectral imaging combined with X-ray analysis” LINK


“The detection of cannabinoids in veterinary feeds by microNIR/chemometrics: a new analytical platform.” LINK

“Qualitative discrimination of Chinese dianhong black tea grades based on a handheld spectroscopy system coupled with chemometrics” LINK

” Validation of NutriOpt dietary formulation strategies on broiler growth and economic performance” LINK

” A preliminary near infrared spectroscopy calibration for the prediction of un-dried fresh grass quality” LINK

“Water content prediction of ‘crystal’guava using visible-near infrared spectroscopy and chemometrics approach” LINK

“Spectroscopy based novel spectral indices, PCA- and PLSR-coupled machine learning models for salinity stress phenotyping of rice.” LINK


“When Will AutoML Replace Data Scientists (if ever)?” MachineLearning Poll LINK


“Probeless non-invasive near-infrared spectroscopic bioprocess monitoring using microspectrometer technology” LINK

“Confirmatory non-invasive and non-destructive differentiation between hemp and cannabis using a handheld Raman spectrometer” LINK

“Simple Defocused Fiber Optic Volume Probe for Subsurface Raman Spectroscopy in Turbid Media” LINK


“Applications of Vis-NIR spectroscopy proximal sensing to estimate and mapping the calcium carbonates (CaCO3) in the semi-arid soils of the Triffa Plain …” LINK


“IJMS, Vol. 21, Pages 408: Genome-Wide Identification of QTLs for Grain Protein Content Based on Genotyping-by-Resequencing and Verification of qGPC1-1 in Rice” LINK


“Comparative data on effects of alkaline pretreatments and enzymatic hydrolysis on bioemulsifier production from sugarcane straw by Cutaneotrichosporon mucoides” LINK



” Detection and Separation of Recyclable Plastics from Municipal Solid Waste” | Report.pdf LINK


“Falsified tadalafil tablets distributed in Japan via the internet” LINK