Spectroscopy and Chemometrics News Weekly #11, 2019

This week’s NIR news Weekly is sponsored by YourCompanyNameHere – BestNIRinstruments. Check out their product page … link

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


Spectroscopy and Chemometrics News Weekly 10, 2019 | NIRS NIR Spectroscopy Chemometrics analysis Spectral Spectrometer Spectrometric Analytical Sensors LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 10, 2019 | NIRS NIR Spektroskopie Chemometrie Proben Analyse Spektrometer Spektral Sensor Nahinfrarot Analysengeräte Analysentechnik Analysemethode Analyzer Nahinfrarotspektroskopie LINK

Spettroscopia e Chemiometria Weekly News 10, 2019 | NIRS Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Sensore Attrezzatura analitica LINK


” First-Principles and Empirical Approaches to Predicting In Vitro Dissolution for Pharmaceutical Formulation and Process Development and for Product Release Testing” LINK

“Near-Infrared Spectroscopy Analytical Model Using Ensemble Partial Least Squares Regression” LINK

Near Infrared

“Consumer perception of d’Anjou pear classified by dry matter at harvest using near-infrared spectroscopy” LINK

“Small interferometer with wide wavelength coverage” NIREOS LINK

“Application of NIRS to the Direct Measurement of Carbonization in Torrefied Wheat Straw Chars” LINK

“New Near-Infrared Imaging and Spectroscopy of NGC 2071-IR [GA]” 400 Parsec away 😉 LINK

“Medicine Discrimination of NIRS Based on Regularized Collaborative Representation Classification with Gabor Optimizer” LINK


“Real-Time Release Testing of Herbal Extract Powder by Near-Infrared Spectroscopy considering the Uncertainty around Specification Limits” LINK

” On-line glucose monitoring by near infrared spectroscopy during the scale up steps of mammalian cell cultivation process development” LINK

“Ex Vivo Assessment of Various Histological Differentiation in Human Carotid Plaque with Near-infrared Spectroscopy Using Multiple Wavelengths.” LINK

“Application of near-infrared spectroscopy for screening the potato flour content in Chinese steamed bread” LINK

“Understanding the role of water in the aggregation of poly(N,N-dimethylaminoethyl methacrylate) in aqueous solution using temperature-dependent near-infrared spectroscopy.” LINK

“Ranking the solubility of ammonia in ionic liquids using near infrared spectroscopy and multivariate curve resolution” LINK

“Breakthrough Potential in Near-Infrared Spectroscopy: Spectra Simulation. A Review of Recent Developments.” LINK

“Screening of maize haploid kernels based on near infrared spectroscopy quantitative analysis” LINK

“An optimized non-invasive glucose sensing based on scattering and absorption separating using near-infrared spectroscopy” LINK


“Improving InSitu Estimation of Soil Profile Properties Using a Multi-Sensor Probe.” LINK

Process Control



“Laboratory Visible and Near-Infrared Spectroscopy with Genetic Algorithm-Based Partial Least Squares Regression for Assessing the Soil Phosphorus Content of Upland and Lowland Rice Fields in Madagascar” RemoteSensing LINK

“Water molecular structure underpins extreme desiccation tolerance of the resurrection plant Haberlea rhodopensis.” LINK

“The Relation between Soil Water Repellency and Water Content can be Predicted by Vis-NIR Spectroscopy” LINK


“Development of a Low-Cost Multi-Waveband LED Illumination Imaging Technique for Rapid Evaluation of Fresh Meat Quality” LINK

“Distinguishing between bread wheat and spelt grains using molecular markers and spectroscopy.” LINK


“FT-IR Spectroscopy Applied for Identification of a Mineral Drug Substance in Drug Products: Application to Bentonite” LINK


“On feasibility of near-infrared spectroscopy for noninvasive blood glucose measurements” LINK

Spectroscopy and Chemometrics News Weekly #7, 2019


Automatic Development of NIR-Spectroscopic Chemometric Models as a Service LINK

Develop near infrared spectroscopy applications & freeing up hours of analysts time QAQC QualityManager QualityAssurance LINK

Optimized NIR-Spectroscopy Accuracy Increases Your Profit manufacturing QA QC Food Feed Lab PetCare vitamins LINK

Rapid development of robust quantitative methods by near-infrared spectroscopy for NIR NIRS LINK

Spectroscopy and Chemometrics News Weekly 6, 2019 | NIRS NIR Spectroscopy Chemometrics analysis Spectral Spectrometer Spectrometric Analytical Sensors LINK

This week’s NIR news Weekly is sponsored by YourCompanyNameHere – BestNIRinstruments. Check out their product page … link



“Time-Space tradeoff in deep learning models for crop classification on satellite multi-spectral image time series” LINK

“Prediction of Dissolution Profiles from Process Parameters, Formulation and Spectroscopic Measurements.” LINK

“Near-infrared spectroscopy coupled with chemometrics tools: a rapid and non-destructive alternative on soil evaluation” LINK

“Near infrared hyperspectral imaging for the prediction of gaseous and particulate matter emissions from pine wood pellets” LINK

“Development of a general calibration model and long-term performance evaluation of lowcost sensors for air pollutant gas monitoring” LINK

“Volatiles Profiling, Allelopathic Activity, and Antioxidant Potentiality of Xanthium Strumarium Leaves Essential Oil from Egypt: Evidence from Chemometrics Analysis” LINK

Near Infrared

“Application of NIR spectroscopy and image analysis for the characterisation of grated Parmigiano-Reggiano cheese” LINK

“A method for differentiating between exogenous and naturally embedded ash in bio-based feedstock by combining ED-XRF and NIR spectroscopy” LINK

“Use of Visible-Near-Infrared (Vis-NIR) Spectroscopy to Detect Aflatoxin B1 on Peanut Kernels.” LINK

Planning your trip to the 19th International NIR conference also plan to attend pre-conf workshops. Imaging (2 days), R for NIR (2 days), Aquaphotomics (1 day), Sampling (1 day) and PAT (1 day). Limited spots. Register ASAP. LINK

“Comparing vis-NIRS, LIBS, and Combined vis-NIRS-LIBS for Intact Soil Core Soil Carbon Measurement” LINK

“Propiolic Acid in Solid Nitrogen: NIR- and UV-Induced CisTrans Isomerization and Matrix-Site Dependent TransCis Tunneling.” LINK

“Chemical composition of melamine-urea-formaldehyde (MUF) resins assessed by near-infrared (NIR) spectroscopy” LINK


“Detection of malaria in insectary-reared Anopheles gambiae using near-infrared spectroscopy” LINK

“Recognition of wood surface defects with near infrared spectroscopy and machine vision” LINK

“Wearable-band Type Visible-Near Infrared Optical Biosensor for Non-invasive Blood Glucose Monitoring” LINK

“Near-infrared spectroscopy reveals neural perception of vocal emotions in human neonates.” LINK

“Characterization of green, roasted beans, and ground coffee using near infrared spectroscopy: A comparison of two devices” LINK

“Near infrared spectroscopic analysis of total alkaloids as nicotine, total nitrogen and total ash in Cuban cigar tobacco” LINK


“Portable NIR Spectrometer for Prediction of Palm Oil Acidity.” LINK

Process Control

“Manufacturing fit-for-purpose paper packaging containers with controlled biodegradation rate by optimizing addition of natural fillers” LINK


“Quantitatively estimating main soil water-soluble salt ions content based on Visible-near infrared wavelength selected using GC, SR and VIP.” LINK


“Effect of Cereal Grain Source and Cereal Silage Source on Nutrient Utilization and Performance of Finishing Beef” LINK

Food & Feed

“Measurements of lycopene contents in fruit: A review of recent developments in conventional and novel techniques” LINK


“Freshness Evaluation of Three Kinds of Meats Based on the Electronic Nose” Sensors LINK

New post: Smallest optical frequency comb to-date | frequencycomb spectroscopy LINK

Automatic Development of NIR-Spectroscopic Chemometric Models as a Service

For all NIR Spectrometers.
You don’t need a Chemometric Software
use the free NIR-Predictor software!

Starting at €393.-
per Chemometric Model
(NIRS Calibration Equation)

See detailed Price List

Start Calibrate

It Enables

  • Quantitative Analysis of Concentrations and Constituents Using NIR Spectroscopy (NIRS is fast, harmless, non-destructive and it’s miniaturized)
  • Chemometric Analysis for NIR-Spectroscopy Made Easy
  • NIR-Calibration Optimization and Running Prediction Models
  • Using NIR-Spectrometer with Calibration Curves/Equations

Our Knowhow

Why you can Trust us

Spectroscopy and Chemometrics News Weekly #4, 2019


“Digitalization meets NIR Spectroscopy Prediction Modelling” NIRS PredictiveAnalytics GDPR DSGVO LINK

How to Develop Near-Infrared Spectroscopy Calibrations in the 21st Century? | near-infra-red LINK

Improve Accuracy of fast Nondestructive NIR-Analysis with Optimal Calibration | Feed ag Lab NIRS pauto QAQC LINK

Spectroscopy and Chemometrics News Weekly 3, 2019 | NIRS Spectroscopy Chemometrics analysis Spectral Spectrometer Spectrometric Analytical Sensors LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 3, 2019 | NIRS NIR Spektroskopie Chemometrie Proben Analyse Spektrometer Spektral Sensor Nahinfrarot Analysengeräte Analysentechnik Analysemethode Analyzer Nahinfrarotspektroskopie LINK

Spettroscopia e Chemiometria Weekly News 3, 2019 | NIRS Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Sensore Attrezzatura analitica LINK

Use Calibration Model for your customized NIRS Applications. Start Optimizing | quantitative Analytical NIR Spectroscopy QAQC quality LINK

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


“Partial Least Squares (PLS) Integrated Fourier Transform Infrared (FTIR) Approach for Prediction of Moisture in Transformer Oil and Lubricating Oil” LINK

“Metabolic Profiling of Nine Mentha Species and Prediction of Their Antioxidant Properties Using Chemometrics” LINK

“A Vis-NIR Spectral Library to Predict Clay in Australian Cotton Growing WSoil” LINK

“Tracing Geographical Origins of Teas Based on FT-NIR Spectroscopy: Introduction of Model Updating and Imbalanced Data Handling Approaches” LINK

“Simultaneous Recognition of Species, Quality Grades, and Multivariate Calibration of Antioxidant Activities for 12 Famous Green Teas Using Mid-and Near-Infrared Spectroscopy Coupled with Chemometrics” LINK

“How qualitative spectral information can improve soil profile classification?” LINK

New JSI Paper: Application of hyperspectral imaging and chemometrics for classifying plastics with brominated flame retardants. wasterecycling, plasticsrecycling, NIR hyperspectral imaging, polymer, flameretardants, hierarchicalclassification LINK

How MachineLearning Works [INFOGRAPHICS] by | Read more here: | ML DL DeepLearning DataMining Cloud AI ArtificialIntelligence Algorithms MachineIntelligence RT Cc: LINK

“Nocturnal Hypoglycemic Alarm Based on Near-Infrared Spectroscopy: In Vivo Studies with a Rat Animal Model” LINK

“Generalized two-dimensional correlation NIR spectroscopy analysis of the structures on n-propanol and n-butanol” LINK

“Simultaneous Determination of Several Fiber Contents in Blended Fabrics by Near-Infrared Spectroscopy and Multivariate Calibration” LINK

“Classification of Frozen Corn Seeds Using Hyperspectral VIS/NIR Reflectence Imaging.” LINK

“Discrimination of Chinese Liquors Based on Electronic Nose and Fuzzy Discriminant Principal Component Analysis” Foods LINK

“Ripeness Prediction of Postharvest Kiwifruit Using a MOS E-Nose Combined with Chemometrics” Sensors LINK

Near Infrared

“The application of FTNIRS for the detection of bruises and the prediction of rot susceptibility of Hass avocado fruit” LINK

“Non-destructive determination of vitamin C and lycopene contents of intact cv. Newton tomatoes using NIR spectroscopy” LINK

DLP technology enables high-power industrial and 3D printing systems using near-infrared wavelengths. LINK

“Exploring brain functions in autism spectrum disorder: A systematic review on functional near-infrared spectroscopy (fNIRS) studies.” LINK

Mikroplastik in Böden schnell und genau nachweisen: Mit NIR-Sprektroskopie. Was das ist und wie das geht? Steht im PaperdesMonats Umwelt => LINK


“Near infrared spectroscopy in the supply chain monitoring of Annurca apple” LINK

“Effects of mechanical stretching, desorption and isotope exchange on deuterated eucalypt wood studied by near infrared spectroscopy” LINK

“In-line monitoring of Ibuprofen during and after tablet compression using near-infrared spectroscopy.” LINK

“Breakthrough potential in near-infrared spectroscopy: spectra simulation. A review of recent developments” LINK

“Application of visible-near infrared spectroscopy to evaluate the quality of button mushrooms” LINK

“Application of infrared spectroscopy as Process Analytics Technology (PAT) approach in biodiesel production process utilizing Multivariate Curve Resolution Alternative Least Square (MCR-ALS)” LINK


“Applications of Raman spectroscopic techniques for quality and safety evaluation of milk: A review of recent developments.” LINK


“Contactless In Situ Electrical Characterization Method of Printed Electronic Devices with Terahertz Spectroscopy” Sensors LINK


Defects in photovoltaic solar cells reduce their efficiency. NIR hyperspectral imaging reveals information on crystal imperfections in a recent paper in JSI-Journal of Spectral Imaging | hyperspectral imaging photovoltaic solarenergy LINK


How AI Will Define New Industries: by DataScience MachineLearning BigData Automation FutureOfWork DigitalTransformation “Accelerating the pace of scientific discovery may be the most important societal use of AI” LINK

13 Common Mistakes Amateur Data Scientists Make and How to Avoid Them [Infographic] | v/ DataScience AI MachineLearning BigData Analytics LINK

“Could the reliability of classical descriptors of fruit quality be influenced by irrigation and cold storage? The case of mango, a climacteric fruit” LINK


“Characterization of a Robust 3D- and Inkjet-Printed Capacitive Position Sensor for a Spectrometer Application” Sensors LINK

“In vivo and in vitro application of near-infrared fiber optic probe for Ehrlich carcinoma distinction: Towards the development of real-time tumor margins assessment tool” LINK


“Composition of Plastic Fractions in Waste Streams: Toward More Efficient Recycling and Utilization” Polymers LINK


“Rapid Measurement of Soybean Seed Viability Using Kernel-Based Multispectral Image Analysis” Sensors LINK

“Rapid evaluation of soil fertility in tea plantation based on near-infrared spectroscopy” LINK


“NearInfrared Spectroscopy in Laboratory and Process Analysis” LINK

What users of NIR Analyzers and NIR Analysis must know. howto automate KnowledgeWork DigitalTransformation NIRS Spectroscopy Lab LabManagement QAQC laboratory LabTesting LabEfficiency LabResults LaboratorySoftware LINK


“近红外光谱技术快速测定三七水分和醇溶性浸出物” LINK

“We analyzed 16,625 papers to figure out where AI is headed next” LINK

“The Hemodynamic changes during cupping therapy monitored by using an optical sensor embedded cup” LINK

“无创血红蛋白监测在急诊患者中的应用研究” LINK

Spectroscopy and Chemometrics News Weekly #43, 2016


SWIR region contains chemical spectral info. Chemometrics differentiate 4 sugars. Realtime spectral processing LINK

Near Infrared

Using advanced NIR sensors, our hygenic TS line measures fluid absorption for FoodandBeverage applications: LINK!

“NIR penetrates much further into samples and, unlike Raman, is unaffected by fluorescence.” | Env… LINK

Qualitätskontrolle während der Extrusion – Folie Fremdpolymeren NIRAnalyse Inspektionssystem LINK

Pre-grazing significantly boosts first cut silage quality | NIRanalycer NIRmachine via LINK


Selective Weighted Least Squares Method for Fourier Transform Infrared Quantitative Analysis LINK

Multivariate Analysis of Hemicelluloses in Bleached Kraft Pulp Using Infrared Spectroscopy LINK


Combining hyperspectral and lidar is a great approach to identify & monitor invasive plants species… LINK




US FDA Purchases Transmission Raman for Quantitative Analysis of Tablets & Capsules – European Pharmaceutical Review LINK


“Washington State University (WSU) portable smartphone spectrometer laboratory detects cancer” LINK

Spectroscopy Outside the Lab: LINK


Spectroscopy and Chemometrics News 42, 2016 | NIRS Spectroscopic Chemometric Software LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 42, 2016 | NIRS Spektroskopie Chemometrie Kalibration LINK

Spettroscopia e Chemiometria Weekly News 42, 2016 | NIRS Spettroscopia Chemiometria news LINK

We make NIR Chemometrics easy

Hi, we’re CalibrationModel. Our aim is to transform your NIR data to superior calibration models. We do this by using knowledge driven software applying good practices and rules from literature, publications, regulatory guidelines and more. Our service is used by NIR specialists to deliver a valuable model for their NIR analysis measurements. With CalibrationModel services, NIR specialists can find out how their NIR Data can be robust and optimally modeled by which data preprocessing and wavelength selection, etc. You can implement CalibrationModel in a matter of minutes using our contact form and send your NIR data to receive optimized model settings as a blueprint.
NIR specialists (Spectroscopist, Chemometricians) love perfect models. They’re curious about how to improve their models even further, because all NIR models need continuous maintenance and updates.
Using CalibrationModel services, NIR Specialists can deliver real value to their measurement results through powerful model optimization capabilities.
CalibrationModel We make NIR Chemometrics easy. Near-Infrared Data Modeling Calibration Service

Procedures for NIR calibration – Creation of NIRS spectroscopy calibration curves

Do you know the effect that you prefer to try out their favorite data pretreatments in combination and often try the same wavelength selections based spectra of the visualized?

You try as six to ten combinations until one of them selects his favorite calibration model, to then continue to optimize. Since then suddenly fall to outliers, because it goes in depth, so is familiar with the data, we know now the spectra of numbers of outliers and is familiar with the extreme values.

Now, the focus is on the major components (principal components, Latent Variables, factors) and makes sure not to over-fit and under-fit not to. The whole takes a few hours and finally one is content with the model found.

So what would happen if you all in the beginning tried variants found outliers removed and re-evaluated and compared? The results would be better than that of the previous model choice? One does not try out? Because it is cumbersome and takes hours again?

We have developed a software which simplifies this so that also the number of model variations can be increased as desired. The variants generation is automated with an intelligent control system, as well as the optimization and comparing the models and finally the final selection of the best calibration model.

Our software includes all the usual known data pretreatment methods (data pre-processing) and can combine them useful. Since many Preteatments are directly dependent on the wavelength selection, such as the normalization the determined within a wavelength range of the scaling factors to normalize the spectra so that pretreatments with the wavelength ranges may be combined. So a variety of settings sensible model comes together that are all calculated and optimized. For the automatic selection of the relevant wavelength ranges, different methods are used, which are based on the spectral intensities. Thus, for example, regions with total absorption is not used, and often interfering water bands removed or retained.

Over all the calculated model variations as a summary outlier analysis can be made. Are there any new outliers (hidden outlier) discovered, all previous models can be automatically recalculated, optimized and compared without these outliers.

From this great number of calculated models with the statistical quality reviews (prediction performance) the optimum calibration can now be selected. For this purpose, not simply sorting by the prediction error (prediction error, SEP RMSEP) or the coefficient of determination (coefficient of determination r2), but by several statistical and test values are used jointly toward the final assessment of optimal calibration.

Thus we have created a platform that allows the highly automated work what a man can never do with a commercial software.

We therefore offer the largest number of matched to your application problem modeling calculations and choose the best calibration for you!

This means that our results are faster, more accurate, robust and objective basis (person independent) and quite easy for you to apply.

You have the full control of the models supplied by us, because we provide a clearly structured and detailed blueprint of the complete calibration, with all settings and parameters, with all necessary statistical characteristics and graphics.

Using this blueprint, you can adjust the quantitative calibration model itself in the software you use, understand and compare. You have everything under control form model creation, model validation and model refinement.

Your privacy is very important to us. The NIR data that you briefly provide us for the custom calibration development will remain of course your property. Your NIR data will be deleted after the job with us.

Interested, then do not hesitate to contact us.

How to develop near-infrared spectroscopy calibrations in the 21st Century?

The Problem

Calibration modeling is a complex and very important part of NIR spectroscopy, especially for quantitative analysis. If the model is badly designed the best instrument precision and highest data quality does not help getting good and robust measurement results. And NIR Spectroscopy requires periodically recalibration and validation.

How are NIR models built today?

In a typical usage in industry, a single person is responsible to develop the models (see survey). He or she uses a Chemometric software that has a click-and-wait working process to adjust all the possible settings for the used algorithms in dialogs and wait for calculations and graphics and then to think about the next modeling steps and the time is limited to do so. Do we expect to find the best use-able or optimal model that way? How to develop near-infrared spectroscopy calibrations in the 21st Century?

Our Solution

Why not put all the knowledge a good model builder is using into software and let the machines do the possibilities of calculations and presenting the result? Designing the software that way, that the domain knowledge is built-in, not just only the algorithms for machine learning and make it possible to scale the calculations to multi-core computers and up to cloud servers. Extend the Chemometric Software with the Domain Knowledge and make as much computer power available as needed.

As it was since the beginning

User  → Chemometric Software → one Computer → some results to choose from

==> User’s time needed to click-and-wait for creating results

Our Solution

User → (Domain Knowledge → automatized Chemometric Software) → many Computers → the best models

==> User’s time used to study the best models and reasoning about his product / process

Note that the “Domain Knowledge” here does perfectly support the User’s product and process knowledge to get the things done right and efficient.

Scaling at three layers

  • Knowledge : use the domain knowledge to drive the Chemometric Software
  • Chemometric Software : support many machine learning algorithms and data pre-processings and make it automatic
  • Computer : support multi-core calculations and scale it to the cloud

The hard part in doing this, is of course the aggregation of the needed domain knowledge and transform it into software. The Domain Knowledge for building Chemometric NIR Spectroscopic models is well known and it’s huge and spreads multiple disciplines. Knowledge-driven software for computing helps to find the gold needle in the haystacks. It’s all about scaling that makes it possible. See Proof of Concept.

New possibilities

  • NIR users can get help working more efficient and getting better models.
  • New types of applications for NIR can be discovered.
  • Evaluation of NIR Applications to replace conventional analytical methods.
  • Hopeless calibrations development efforts can be re-started.
  • Higher model accuracy and robustness can be delivered.
  • Automate the experimental data part of your application study.
  • Person independent optimization will show new solutions, because it’s not limited by a single mindset => combining all the aggregated knowledge and its combinations.
  • Software independent optimization will show new solutions, because none of vendor specific limitations and missing algorithms are present => combining all open available algorithms and there permutations.
  • Computing service is included.

Contact us for trial

Your NIR data is modeled by thousands of different useful calibration models and you get the best of them! That was not possible before in such a easy and fast way! See How it works

Summary of the NIR Chemometric survey polls

Summary of the NIR Chemometric survey polls (as of end of Sept. 2013)

The interesting finding is that most of the answers fit the following pattern. The most companies that use NIR have one NIR Instrument and only one employee that is able to develop NIR calibrations. For that the most common off-the-shelf chemometrics program is used and spent 2 hours or over a month and therefore gets no calibration training about the complex topics like Chemometrics and NIR Spectroscopy or only once (introduction). The calibration maintenance ranges from never to 3 times a year. Interestingly, there was no one who uses portable NIR instruments. We continue our surveys, for the discovery of new trends. Conclusion Seeing this picture, we think that there is huge potential to improve the calibrations. Advanced knowledge can help individuals to build the calibrations with best practices and improve their models accuracy and reliability. Once the decision and investment in NIR technology is done, you should get the best out of your data, because this extra NIR performance can be given by calibration optimization. We offer this as an easy to use and independent service.

Customized NIR Calibrations

Increase Your Profit with optimized NIR Accuracy

We help you to find the optimal settings for higher NIR accuracy and reliability.

You can build your own custom NIR calibration model with this valuable settings.

We offer a quantitative NIR Calibration development and optimization service.

New: free NIR-Predictor Software

White Paper about the details, what’s behind.

Improve NIR Measurement Accuracy

  • going closer to your product specification limits and maximize profitability
  • optimizing your models yield to process optimization and optimizing productivity
  • compete against other NIR vendors in a feasibility study (NIR salesman)

Easy to use

  • compatible with any NIR vendor
  • no installation, no learning
  • quantitative NIR Calibration Development as a Service


  • help users avoid common pitfalls of method development
  • before you validate and approve your solution for use in production process:
    • check if a better calibration can be found,
    • compare your calibration with other experts solutions.


  • no cumbersome trial-and-error modeling steps
  • calculation time is spent on our high performance infrastructure
  • fast results, developed calibrations within days

Fix price

  • fix costs, depends only on data size (not hourly rate for service)
  • huge saving in method development costs
  • easy to plan
More benefits, for whom and where, learn more , contact