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 #47, 2020

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 46, 2020 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry foodindustry Analysis Lab 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)

“Near infrared absorption spectroscopy for the quantification of unsulfated alcohol in sodium lauryl ether sulfate” LINK

“Estimation of Organic Carbon in Anthropogenic Soil by VIS-NIR Spectroscopy: Effect of Variable Selection” LINK

“Near infrared spectroscopy (NIRS) based high-throughput online assay for key cell wall features that determine sugarcane bagasse digestibility” |) LINK

“Authentication of barley-finished beef using visible and near infrared spectroscopy (Vis-NIRS) and different discrimination approaches” LINK

“Energetic Distribution of States in Irradiated Low-Density Polyethylene from UV-Vis-NIR Spectroscopy” LINK

“Determination of in-situ salinized soil moisture content from visible-near infrared (VIS–NIR) spectroscopy by fractional order derivative and spectral variable selection …” LINK

The smallest near-infrared LED (NIRED) for spectroscopy applications available in the market — Now in stock. OSRAM Opto Semiconductors SFH 4737 IR Broadband Emitter: LINK

“Performance of near-infrared (NIR) spectroscopy in pork shoulder as a predictor for pork belly softness” LINK

“Improved generalization of spectral models associated with Vis-NIR spectroscopy for determining the moisture content of different tea leaves” LINK

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

“Non-destructive determination of bovine milk progesterone concentration during milking using near-infrared spectroscopy” LINK

“Near infrared hyperspectral imaging as a tool for quantifying atmospheric carbonaceous aerosol” LINK

“Partial least square regression versus domain invariant partial least square regression with application to near-infrared spectroscopy of fresh fruit” LINK

“The recent advances of near-infrared spectroscopy in dairy production—a review” LINK

“Fiber Optic Reflection SpectroscopyNear-Infrared Characterization Study of Dry Pigments for Pictorial Retouching” LINK

“Process Analytical Technology for Protein PEGylation using Near Infrared Spectroscopy: G-CSF as a Case Study” LINK

“Determination of gel time of prepreg in copper clad laminate industry by near infrared spectroscopy” LINK

“Use of near infrared hyperspectral imaging as a nondestructive method of determining and classifying shelf life of cakes” LINK

“Detection of Lipid Oxidation in Infant Formulas: Application of Infrared Spectroscopy to Complex Food Systems” LINK

“Authentication of Antibiotics Using Portable Near-Infrared Spectroscopy and Multivariate Data Analysis” LINK

“Modular microreactor with integrated reflection element for online reaction monitoring using infrared spectroscopy” LabOnAChip LINK

“Application of Infrared Spectroscopy in Prediction of Asphalt Aging Time History and Fatigue Life” Coatings LINK

Chemometrics and Machine Learning

“Development of Spectral Disease Indices for Southern Corn Rust Detection and Severity Classification ” LINK

“Comparison of partial least squares-discriminant analysis, support vector machines and deep neural networks for spectrometric classification of seed vigour in a broad range of tree species” LINK

“Near-infrared spectroscopy for the prediction of rare earth elements in soils from the largest uranium-phosphate deposit in Brazil using PLS, iPLS, and iSPA-PLS …” LINK

“Vitamin B2 concentration in cow milk: Quantification by a new UHPLC method and prediction by visible and near-infrared spectral analysis” LINK

Equipment for Spectroscopy

“Evaluation of a handheld ultra-compact NIR spectrometer for rapid and non-destructive determination of apple fruit quality” LINK

Agriculture NIR-Spectroscopy Usage

“Rapid Determination of Nutrient Concentrations in Hass Avocado Fruit by Vis/NIR Hyperspectral Imaging of Flesh or Skin” LINK

“Multivariate Analysis of Spectroscopic Data for Agriculture Applications” LINK

Horticulture NIR-Spectroscopy Applications

“Sequential fusion of information from two portable spectrometers for improved prediction of moisture and soluble solids content in pear fruit” LINK

“Application of Vis/NIR spectroscopy for the estimation of soluble solids, dry matter and flesh firmness in stone fruits” LINK

“Application of Near Infra‐Red Spectroscopy as an instantaneous and simultaneous prediction tool for anthocyanins and sugar in whole fresh raspberry” LINK

Food & Feed Industry NIR Usage

“Rapid and Nondestructive Determination of Egg Freshness Category and Marked Date of Lay using Spectral Fingerprint” LINK

Pharma Industry NIR Usage

“Aspen Technology acquires Camo Analytics” PAT LINK

“Non-destructive and rapid detection of the internal chemical composition of granules samples by spectral transfer” LINK

Laboratory and NIR-Spectroscopy

“The Laboratory at Hand: Plastic Sorting Made Easy: A next‐generation mobile near‐infrared spectroscopy solution” LINK


““动态” 近红外光谱结合深度学习图像识别和迁移学习的模式识别方法研究” LINK

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