Spectroscopy and Chemometrics/Machine-Learning News Weekly #22, 2022

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 21, 2022 | 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 21, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 21, 2022 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK

Near-Infrared Spectroscopy (NIRS)

“NIRSCAM: A Mobile Near-Infrared Sensing System for Food Calorie Estimation” LINK

“Nutritional Components of Beverage Granules by Near-Infrared Spectroscopy Based on PLS Model” | LINK

“A new concept of acousto-optic tunable filter-based near-infrared hyperspectral imager for planetary surface exploration” LINK

“Supplementary Materials Determination of the Geographical Origin of Walnuts (Juglans regia L.) Using Near-Infrared Spectroscopy and Chemometrics” LINK

“Characteristic wavelengths optimization improved the predictive performance of near-infrared spectroscopy models for determination of aflatoxin B1 in maize” LINK


“Molecules : Identification of Stingless Bee Honey Adulteration Using Visible-Near Infrared Spectroscopy Combined with Aquaphotomics” LINK

“A review of visible and near-infrared (Vis-NIR) spectroscopy application in plant stress detection” LINK

“Predicting the performance of handheld near-infrared photonic sensors from a master benchtop device” LINK

“A novel handheld FT-NIR spectroscopic approach for real-time screening of major cannabinoids content in hemp” LINK

“Chemometric studies of hops degradation at different storage forms using UV-Vis, NIRS and UPLC analyses” LINK

“Comparison of VIS/NIR spectral curves plus RGB images with hyperspectral images for the identification of Pterocarpus species” | LINK

“Etruscan Fine Ware Pottery: Near-Infrared (NIR) Spectroscopy as a Tool for the Investigation of Clay Firing Temperature and Atmosphere” LINK

“Penilaian Sejawat: Fast and contactless assessment of intact mango fruit quality attributes using near infrared spectroscopy (NIRS). IOP EES.” | EES Mango Kusumiyati (Gabungan).pdf LINK

“Segregation of ‘Hayward’kiwifruit for storage potential using Vis-NIR spectroscopy” LINK

“Portable Near-Infrared Spectroscopy as a Screening Test of Corrosive Solutions Concealed in Plastic Containers” | LINK

“General model of multi-quality detection for apple from different origins by Vis/NIR transmittance spectroscopy” | LINK

“Analytical Chemistry Strategies in the Use of Miniaturised NIR Instruments: An Overview” LINK

“Application of near-infrared spectroscopy to agriculture and forestry” | LINK

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

“NearInfrared LightDriven ThreeDimensional Soft Photonic Crystals Loaded with Upconversion Nanoparticles” LINK

“Gaming behavior and brain activation using functional nearinfrared spectroscopy, Iowa gambling task, and machine learning techniques” LINK

“Metaheuristic algorithms in visible and near infrared spectra to detect excess nitrogen content in tomato plants” LINK

Hyperspectral Imaging (HSI)

“Non-destructive age estimation of biological fluid stains: An integrated analytical strategy based on near-infrared hyperspectral imaging and multivariate regression” LINK

“Prediction of peroxidase activity using near infrared hyperspectral imaging in red delicious apple fruit during storage time” LINK

“Remote Sensing : Detection of Apple Valsa Canker Based on Hyperspectral Imaging” LINK

Spectral Imaging

“Sensors : Sugarcane Nitrogen Concentration and Irrigation Level Prediction Based on UAV Multispectral Imagery” LINK

Chemometrics and Machine Learning


“Unsupervised detection of ash dieback disease (Hymenoscyphus fraxineus) using diffusion-based hyperspectral image clustering” LINK

“IAI SPECIAL EDITION: Infrared spectroscopy chemometric model for determination of phenolic content of plant leaf powder” LINK

“Sensors : Accuracy and Reproducibility of Laboratory Diffuse Reflectance Measurements with Portable VNIR and MIR Spectrometers for Predictive Soil Organic Carbon Modeling” LINK

“Coatings : Nondestructive Evaluation of Thermal Barrier Coatings Thickness Using Terahertz Technique Combined with PCA-GA-ELM Algorithm” LINK

“Prediction of topsoil organic carbon content with Sentinel-2 imagery and spectroscopic measurements under different conditions using an ensemble model approach …” LINK

Optics for Spectroscopy

“Artificial Intelligence in Classical and Quantum Photonics” LINK

Research on Spectroscopy

” A dataset for spectral radiative properties of black poly (methyl methacrylate)” LINK

Process Control and NIR Sensors

“Pharmaceutics : Tailoring Rational Manufacturing of Extemporaneous Compounding Oral Dosage Formulations with a Low Dose of Minoxidil” LINK

Environment NIR-Spectroscopy Application

“Polymers : Antioxidant and Anti-Aging Activity of Freeze-Dried Alcohol-Water Extracts from Common Nettle (Urtica dioica L.) and Peppermint (Mentha piperita L.) in Elastomer Vulcanizates” LINK

“Particle densities of cultivated south greenlandic soils can be explained by a threecompartment model, pedotransfer functions, and a visNIR spectroscopy model” LINK

Agriculture NIR-Spectroscopy Usage

“Influence of ingredient quality and diet formulation on amino acid digestibility and growth performance of poultry and swine” LINK

“Guidelines for Optimal Use of NIRSC Forage and Feed Calibrations in Membership Laboratories” LINK

“Linear Support Vector Machine Classification of Plant Stress From Soybean Aphid (Hemiptera: Aphididae) Using Hyperspectral Reflectance” LINK

“Goat milk authentication by one-class classification of digital image-based fingerprint signatures: detection of adulteration with cow milk” LINK

“Agronomy : Crop Monitoring Strategy Based on Remote Sensing Data (Sentinel-2 and Planet), Study Case in a Rice Field after Applying Glycinebetaine” LINK

“Estimation of Vertisols Soil Nutrients by Hyperion Satellite Data: Case Study in Deccan Plateau of India” | LINK

“Real-time milk analysis integrated with stacking ensemble learning as a tool for the daily prediction of cheese-making traits in Holstein cattle” LINK

“The effect of nitrogen fertility rate and seeding rate on yield, nutritive value and economics of forage corn in a low corn heat unit region of Western Canada” LINK

Food & Feed Industry NIR Usage

“Near-infrared techniques for fraud detection in dairy products: A review” | LINK

Laboratory and NIR-Spectroscopy

“Digital technologies to assess yoghurt quality traits and consumers acceptability” LINK


“Tantalum – 2D Light Transport” | optics physically simulation spectroscopy spectrum prism lens mirror light lighttransport multiple scattering LINK

“Characterizing tourniquet induced hemodynamics during total knee arthroplasty using diffuse optical spectroscopy” LINK


Spectroscopy and Chemometrics News Weekly #19, 2021

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 18, 2021 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality LINK

This week’s NIR news Weekly is sponsored by Your-Company-Name-Here – NIR-spectrometers. Check out their product page … link

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

Near-Infrared Spectroscopy (NIRS)

“Integrated (1)H NMR fingerprint with NIR spectroscopy, sensory properties, and quality parameters in a multi-block data analysis using ComDim to evaluate coffee blends” LINK

“Efficient Nearinfrared Pyroxene Phosphor LiInGe2O6:Cr3+ for NIR Spectroscopy Application” LINK

“Transfer learning and wavelength selection method in NIR spectroscopy to predict glucose and lactate concentrations in culture media using VIPBoruta” LINK

“Theranostic Near-Infrared-Active Conjugated Polymer Nanoparticles” LINK

“Integrated NIRS and QTL assays reveal minor mannose and galactose as contrast lignocellulose factors for biomass enzymatic saccharification in rice” LINK

“Age estimation of barramundi (Lates calcarifer) over multiple seasons from the southern Gulf of Carpentaria using FT-NIR spectroscopy” | LINK

“Evaluation of Minimum Preparation Sampling Strategies for Sugarcane Quality Prediction by vis-NIR Spectroscopy” LINK

“Differentiation between Fresh and Thawed Cephalopods Using NIR Spectroscopy and Multivariate Data Analysis” LINK

“Foods, Vol. 10, Pages 885: Histamine Control in Raw and Processed Tuna: A Rapid Tool Based on NIR Spectroscopy” LINK

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

“RenalClearable NickelDoped Carbon Dots with Boosted Photothermal Conversion Efficiency for Multimodal ImagingGuided Cancer Therapy in the Second NearInfrared Biowindow” LINK

“Simultaneous Broadening and Enhancement of Cr3+ Photoluminescence in LiIn2SbO6 by Chemical Unit Cosubstitution: NightVision and NearInfrared Spectroscopy Detection Applications” LINK

“Applied Sciences, Vol. 11, Pages 3701: Measurement of Temperature and H2O Concentration in Premixed CH4/Air Flame Using Two Partially Overlapped H2O Absorption Signals in the Near Infrared Region” LINK

“Fourier-Transform Infrared Spectroscopy as a Discriminatory Tool for Myotonic Dystrophy Type 1 Metabolism: A Pilot Study” IJERPH LINK

“Application of machine learning to estimate fireball characteristics and their uncertainty from infrared spectral data” LINK

“Cross Target Attributes and Sample Types Quantitative Analysis Modeling of Near-infrared Spectroscopy Based on Instance Transfer Learning” LINK

“Fast at-line characterization of solid organic waste: Comparing analytical performance of different compact near infrared spectroscopic systems with different …” LINK

“On-line identification of silkworm pupae gender by short-wavelength near infrared spectroscopy and pattern recognition technology” LINK

“The Use of Multispectral Imaging and Single Seed and Bulk Near-Infrared Spectroscopy to Characterize Seed Covering Structures: Methods and Applications in Seed …” LINK

” The use of infrared reflectance spectroscopy to predict the dry matter intake of lactating grazing dairy cows” LINK

“Development of a Novel Green Tea Quality Roadmap and the Complex Sensory-associated Characteristics exploration using Rapid Near-Infrared Spectroscopy …” LINK

“… of the Neutral and Acid Detergent Fiber Fractions of Chickpea (Cicer arietinum L.) by Combining Modified PLS and Visible with Near-Infrared Spectroscopy” LINK

“Non-destructive estimation of fibre morphological parameters and chemical constituents of Tectona grandis Lf wood by near infrared spectroscopy” LINK


“A simple multiple linear regression model in near infrared spectroscopy for soluble solids content of pomegranate arils based on stability competitive adaptive re …” LINK

“Intelligent assessment of the histamine level in mackerel (Scomber australasicus) using near-infrared spectroscopy coupled with a hybrid variable selection strategy” LINK

“Portable Near Infrared Spectroscopy as a Tool for Fresh Tomato Quality Control Analysis in the Field” LINK

” Focused echocardiography, end-tidal carbon dioxide, arterial blood pressure or near-infrared spectroscopy monitoring during paediatric cardiopulmonary …” LINK

“EXPRESS: Fourier Transform Infrared (FT-IR) Imaging Analysis of Interactions Between Polypropylene Grafted with Maleic Anhydride (MAPP) and Silica Spheres (SS) …” LINK

Hyperspectral Imaging (HSI)

“Hazelnuts classification by hyperspectral imaging coupled with variable selection methods” LINK

“Towards the development of a sterile model cheese for assessing the potential of hyperspectral imaging as a non-destructive fungal detection method” LINK

“Geographical origin discriminant analysis of Chia seeds (Salvia hispanica L.) using hyperspectral imaging” LINK

Chemometrics and Machine Learning

“Bayesian subset selection and variable importance for interpretable prediction and classification. (arXiv:2104.10150v1 [stat.ML])” LINK

“MachineLearning and Feature Selection Methods for EGFR Mutation Status Prediction in Lung Cancer” LINK

“Remote Sensing, Vol. 13, Pages 1598: Development of Novel Classification Algorithms for Detection of Floating Plastic Debris in Coastal Waterbodies Using Multispectral Sentinel-2 Remote Sensing Imagery” LINK

“Sensors, Vol. 21, Pages 2871: A Novel Runtime Algorithm for the Real-Time Analysis and Detection of Unexpected Changes in a Real-Size SHM Network with a Quasi-Distributed FBG Sensors” LINK

“NIR spectroscopy coupled with chemometric algorithms for the prediction of cadmium content in rice samples” LINK

” Determination of petroleum hydrocarbon contamination in soil using VNIR DRS and PLSR modeling” LINK

” Establishment and applicant of near-infrared reflectance spectroscopy models for predicting protein, linolenic acid and lignan contents of flaxseed” LINK

“Detection of chlorpyrifos and carbendazim residues in the cabbage using visible/near-infrared spectroscopy combined with chemometrics” LINK

“A Model Based on Clusters of Similar Color and NIR to Estimate Oil Content of Single Olives” LINK

“The Organochlorine Pesticide Residues of Mesona Chinensis Benth by Near Infrared (NIR) Spectroscopy and Chemometrics” LINK

“Strategies for the Development of Spectral Models for Soil Organic Matter Estimation” Remote Sensing LINK



“IJMS, Vol. 22, Pages 4347: Mitochondrial Bioenergetic, Photobiomodulation and Trigeminal Branches Nerve Damage, Whats the Connection? A Review” LINK

Research on Spectroscopy

“ndothelial and microvascular function in CKD: Evaluation methods and associations with outcomes” LINK

Equipment for Spectroscopy

“On-line monitoring of egg freshness using a portable NIR spectrometer in tandem with machine learning” LINK

Environment NIR-Spectroscopy Application

” Current sensor technologies for in situ and on-line measurement of soil nitrogen for variable rate fertilization-A review.” LINK

” Mid-Infrared Spectroscopy Supports Identification of the Origin of Organic Matter in Soils. Land 2021, 10, 215″ LINK

Agriculture NIR-Spectroscopy Usage

“Crystals, Vol. 11, Pages 458: Boron Influence on Defect Structure and Properties of Lithium Niobate Crystals” | LINK

“Remote Sensing, Vol. 13, Pages 1620: Estimating Plant Nitrogen Concentration of Rice through Fusing Vegetation Indices and Color Moments Derived from UAV-RGB Images” LINK

“Consensus rule for wheat cultivar classification on VL, VNIR and SWIR imaging” LINK

” Changes in the Milk Market in the United States on the Background of the European Union and the World” LINK

“High-Resolution Airborne Hyperspectral Imagery for Assessing Yield, Biomass, Grain N Concentration, and N Output in Spring Wheat” RemoteSensing LINK

” Near infrared hyperspectral imaging of the hemodynamic and metabolic states of the exposed cortex: in vivo investigation on small animal models” LINK

“Engineered Protein PhotoThermal Hydrogels for Outstanding In Situ Tongue Cancer Therapy” LINK

Food & Feed Industry NIR Usage

“The quality and shelf life of biscuits with cryoground proso millet and buckwheat byproducts” LINK

“Performance of different portable and hand-held near-infrared spectrometers for predicting beef composition and quality characteristics in the abattoir without meat sampling” LINK

“New Approaches to Detect Compositional Shifts in Fish Oils” LINK

Medicinal Spectroscopy

“Aplicação de espectroscopia no infravermelho próximo e análise multivariada para identificação e quantificação de hidrocarbonetos totais do petróleo em solo” | LINK


“Vibrational Analysis of Benziodoxoles and Benziodazolotetrazoles” LINK

“Recent advances in Unmanned Aerial Vehicles forest remote sensing—A systematic review. Part II: Research applications” LINK

“Physical and thermal properties of gold nanoparticles embedded Nd3+-doped borophosphate glasses: Spectroscopic parameters” LINK

“Spectral Assessment of Organic Matter with Different Composition Using Reflectance Spectroscopy” Remote Sensing LINK

NIR-Predictor – Frequently Asked Questions (FAQ)

NIR-Predictor – FAQ

Please also refer to the NIR-Predictor – Manual and check the Hints and Notes.

How to Configure / Load / Import / Activate / Setup / Use the Calibrations (*.cm) in NIR-Predictor?

Chapter “Configure the Calibrations for prediction usage” – NIR-Predictor – Manual

Do you have a calibration file for XY ?

We create custom calibrations out of your NIR + Lab measurements of XY.
We do not sell off-the-shelf calibrations.

I have downloaded the software but can’t see it?

Please note, that the download time will be very short, because of the small file size.
Check your browser’s download folder. The download is the file “NIR-PredictorVx.y.zip”

Why a .zip and no installer (Setup.exe) ?

Because a .zip deploy keeps it simple for all:

  • easy : no Administrator rights needed to install, delete it to uninstall
  • harmless : no system changes during setup
  • transparency : you see what you get

Is there a command line (CLI) version of NIR-Predictor ?

If you want to customize it in all details, our OEM API for NIR-instrument-software (White-Label) integration gives you full access. If you are an NIR-Vendor (or similar) please contact us via email info@CalibrationModel.com

The free NIR-Predictor does not create a model, what is wrong ?

As the name says, the NIR-Predictor just predicts NIR data with a model. To create a model you need to send your data to the CalibrationModel service, after development process you get an email with a link to the calibration where it can be purchased and downloaded.

Why does the creation of the PropertyFile.txt take so long with hundrets of spectra files?

It normally takes only 1-10 seconds not minutes.
Make sure that the spectra data files are stored locally on your main drive
and not on a cloud-drive or network storage or slow USB thumb drive or SD-Card.

Is there a way to use converted ASCII spectrum data to be used in NIR-Predictor?

Yes, this is the simplest ASCII CSV file format the NIR-Predictor supports.
And there are other formats supported.

Can you convert old calibration data from vendor A to be integrated to our new vendor B NIRS calibration data in our instrument?

No, we don’t do model or spectra conversion / transformation (aka model transfer).
We build optimized models with wavelength compatible data.

Does NIR-Predictor contain any malware, spyware or adware?

No, NIR-Predictor does not contain any malware, spyware or adware.

How to copy the prediction results from the table in the browser?

Copy selected columns from the table.
By holding down the Ctrl key, rectangular areas in the table can be selected with the mouse and copied to the clipboard with Ctrl+C and then copied to a spreadsheet program with Ctrl+V.

Will an expired calibration still work?

No. Until you extend the usage time.
The expired calibration file will be moved to the CalibrationExpired folder on the next start of NIR-Predictor or “Search and load Calibrations” menu function.

Selected Calibration files from the folder CalibrationExpired can be send to info@CalibrationModel.com with your Request file (.req) files for extending their usage time.

There is the possibility to get a perpetual usage, which means their is no expiration (valid until 2050).

That way you can get the time extended calibration back, that behaves exactly as the one before with extended usage time.

What does the calibration Expiration date mean exactly on the Prediction Report?

The Expiration date, it is the final day when the calibration will be valid (similar to credit cards).

What does the (number) in brackets after the [range] mean?

During the creation of a Calibration Request the NIR-Predictor shows a message containing
” ‘Prop1’ / “Quantitative [1.40 – 2.90] (154) ”
here 154 is the number of unique values in the property range.

How long does it take to create of the property file and calibration request file from 500 spectra files?

Use a local folder on your computer (not a network drive) for your spectra files then the property file and the calibration request file is created in around 1-3 seconds. (measured on a system with SSD drive, Intel i7, 2.4 GHz)

I tried to create the calibration request and got the error message: The number of Property Values of all spectra are different?

Use the generated PropertiesBySpectra (Note: Spectra not Sample) template file.
Do not reformat the generated template file, just fill in the Property values and save as Text CSV (*.csv) file (not as Excel file “.xlsx”).

Are you able to create the calibration if we only have 20 spectra?

To create a reliable quantitative calibration you need measured spectra of at least 48..60 (more is better) different samples with different Lab-values in the required measuring range!
The NIR-Predictor will check for that automatically.

Same sample measured multiple times (replicate measurements), how to enter the Lab-value only once in Property file?

Use the created PropertiesBySample template (not the PropertiesBySpectra).

Different samples with exact the same Lab-value, how to enter the Lab-Values?

Entering the Lab-values into the generated PropertiesBySpectra template the NIR-Predictor detects them as the same Sample and as a result we have too less different values to build a calibration. But in my case these are different samples with exact the same Lab-value, how to do?

You have to cheat a little bit to make NIR-Predictor do not detect same sample as measured multiple times. This is because most NIR users do replicate measurements on the same sample and NIR-Predictor looks for that. In PropertiesBySpectra modify the values a little bit to make them different, e.g.

Is the free NIR-Predictor software you provide for anyone to download and use?

Yes, if downloaded directly from our homepage by the user.
See also Software License Agreement

What is an Outlier?

The spectrum is an outlier to the model, if the spectrum is not similar with the spectra and lab-values the model is built with.

The default setting in NIR-Predictor Menu > “Report with Simplified Outlier Symbols”
is ON, that will show only the worst case instead of all combinations to have a simplified minimal information.
if OFF, that will show the combinations (e.g. “XO=” or “XO” or “O=” or “X=”), which is more informative for analyzing problem cases.
See also manual chapter Outliers.

If something is wrong, please tell us