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 #44, 2020

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 43, 2020 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Food Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality LINK

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

Near-Infrared Spectroscopy (NIRS)

“Quality of Eucalyptus benthamii wood for pulp production by Near Infrared Spectroscopy (NIRS).” LINK

“Aplicaciones de la Espectroscopia de Infrarrojo Cercano (NIR) para predecir el contenido y la actividad de agua del embutido tipo “Fuet “” LINK

“Monitoring the Processing of Dry Fermented Sausages with a Portable NIRS Device” LINK

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

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

“Visible and near-infrared hyperspectral imaging techniques allow the reliable quantification of prognostic markers in lymphomas: a pilot study using the Ki67 proliferation index as an example.” LINK

“Key variables selection and models development based on near-infrared spectra for the multi-qualities in formula feedstuff for swine.” LINK

“Comparison of Reflectance and Interactance Modes of Visible and Near-Infrared Spectroscopy for Predicting Persimmon Fruit Quality” LINK

“Effectiveness of different approaches for in situ measurements of organic carbon using visible and near infrared spectrometry in Poyang basin” LINK

“Near-Infrared Transmittance Spectral Imaging for Nondestructive Measurement of Internal Disorder in Korean Ginseng.” LINK

“Deep Spectral-Spatial Features of Near Infrared Hyperspectral Images for Pixel-Wise Classification of Food Products” Sensors LINK

“Confirmation of brand identification in infant formulas by using near-infrared spectroscopy fingerprints.” LINK

“Rapid detection of quality of Japanese fermented soy sauce using near-infrared spectroscopy.” LINK

“Fast, direct and in situ monitoring of lipid oxidation in an oil-in-water emulsion by near infrared spectroscopy.” LINK

“Feasibility of near-infrared spectroscopy as a tool for anatomical mapping of the human epicardium.” LINK

“Predicting Marian Plum Fruit Quality without Environmental Condition Impact by Handheld Visible–Near-Infrared Spectroscopy” LINK

“Application of miniaturized near-infrared spectroscopy in pharmaceutical identification” LINK

“Two standard-free approaches to correct for external influences on near-infrared spectra to make models widely applicable” LINK

Hyperspectral Imaging (HSI)

“Selecting Key Wavelengths of Hyperspectral imagine for Nondestructive Classification of Moldy Peanuts using Ensemble Classifier” LINK

“A rapid and non-destructive detection of Escherichia coli on the surface of fresh-cut potato slices and application using hyperspectral imaging” LINK

“Using Machine Learning for Estimating Rice Chlorophyll Content from In Situ Hyperspectral Data” RemoteSensing LINK

Chemometrics and Machine Learning

“Comparison of chemometrics and official AOCS methods for predicting the shelf life of edible oil” LINK

“Study on a twodimensional correlation visiblenear infrared spectroscopy kinetic model for the moisture content of fresh walnuts stored at room temperature” LINK

“Chemometric Strategies for Spectroscopy-Based Food Authentication” LINK

“Development of a Near Infrared Spectroscopy Model for Prediction of Fibre Compounds in Alfalfa” LINK

“Tracing the Geographical Origins of Dendrobe (Dendrobium spp.) by Near-Infrared Spectroscopy Sensor Combined with Porphyrin and Chemometrics” LINK

Equipment for Spectroscopy

“Evaluation of a micro-spectrometer for the real-time assessment of liver graft with mild-to-moderate macrosteatosis: A proof of concept study.” hepatology LINK

“Application of a Handheld Near-Infrared Spectrometer to Predict Gelatinized Starch, Fiber Fractions, and Mineral Content of Ground and Intact Extruded Dry Dog Food” Animals LINK

Process Control and NIR Sensors

“Development of analytical methods based on Near Infrared Spectroscopy for monitoring of pharmaceutical and biotechnological processes and control of new …” LINK

“Nondestructive monitoring of polyphenols and caffeine during green tea processing using VisNIR spectroscopy” LINK

Agriculture NIR-Spectroscopy Usage

“Unique contributions of chlorophyll and nitrogen to predict crop photosynthetic capacity from leaf spectroscopy” LINK

“Online Application of a Hyperspectral Imaging System for the Sorting of Adulterated Almonds” LINK

Food & Feed Industry NIR Usage

“Verifying the Geographical Origin and Authenticity of Greek Olive Oils by Means of Optical Spectroscopy and Multivariate Analysis.” LINK

“Non-Destructive Quality Assessment of Tomato Paste by Using Portable Mid-Infrared Spectroscopy and Multivariate Analysis” Foods LINK


“On-board Sensorik zur Erkennung der Kraftstoffzusammen-setzung” LINK