Spectroscopy and Chemometrics Machine-Learning News Weekly #31, 2022

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 30, 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 30, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 30, 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)

“Peatlands spectral data influence in global spectral modelling of soil organic carbon and total nitrogen using visible-near-infrared spectroscopy” LINK

“A NIRS Based Device for Identification of Acute Ischemic Stroke by Using a Novel Organic Dye in the Human Blood Serum” | LINK

“Interlacing the evaluation of mechanical properties of mortar cement with near-infrared spectroscopy using multivariate data analysis” LINK

“A Preliminary Study to Classify Corn Silage for High or Low Mycotoxin Contamination by Using near Infrared Spectroscopy” | LINK

“Scalable, NanometerAccurate Fabrication of AllDielectric Metasurfaces with Narrow Resonances Tunable from Near Infrared to Visible Wavelengths” LINK

“A Combined Near-Infrared and Mid-Infrared Spectroscopic Approach for the Detection and Quantification of Glycine in Human Serum” | LINK

“Sensors : Determination of Quality Parameters in Mangetout (Pisum sativum L. ssp. arvense) by Using Vis/Near-Infrared Reflectance Spectroscopy” LINK

“Study on the Effect of Apple Size Difference on Soluble Solids Content Model Based on Near-Infrared (NIR) Spectroscopy” | LINK

“Canopy VIS-NIR spectroscopy and self-learning artificial intelligence for a generalised model of predawn leaf water potential in Vitis vinifera” LINK

“Chemical composition of Andropogon gayanus cv. planaltina predicted through nirs and analyzed through wet chemistry” LINK

“A Preliminary Study to Classify Corn Silage for High or Low Mycotoxin Contamination by Using near Infrared Spectroscopy” LINK

“Model robustness in estimation of blueberry SSC using NIRS” LINK

“Non-invasive Measurement of Blood Sugar Using Near-Infrared Spectroscopy” | LINK

“Investigating the Utility of Near Infrared Reflectance (NIR) Imaging for Diabetic Retinopathy Screening” LINK

“Fourier transform near infrared spectroscopy as a tool to predict spawning status in Alaskan fishes with variable reproductive strategies” LINK

“Prediction of dry matter, carbon and ash contents and identification of Calycophyllum spruceanum (Benth) organs by Near-Infrared Spectrophotometry” LINK

“Determination of aflatoxin B1 value in corn based on Fourier transform near-infrared spectroscopy: Comparison of optimization effect of characteristic …” LINK

“Combining different pre-processing and multivariate methods for prediction of soil organic matter by near infrared spectroscopy (NIRS) in Southern Brazil” LINK

“Evaluation of coating uniformity for the digestion-aid tablets by portable near-infrared spectroscopy” LINK

“Novel strategies in near infrared spectroscopy (NIRS) and multivariate analysis (MVA) for detecting and profiling pathogens and diseases of agricultural importance.” LINK

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

“A highly efficient colloidal quantum dot imager that operates at near-infrared wavelengths” LINK

“Green tea grades identification via Fourier transform near‐infrared spectroscopy and weighted global fuzzy uncorrelated discriminant transform” LINK

“Investigation of oxygen saturation in regions of skin by near infrared spectroscopy” LINK

“Spectral variable selection for estimation of soil organic carbon content using midinfrared spectroscopy” LINK

“Plants : Uptake and Presence Evaluation of Nanoparticles in Cicer arietinum L. by Infrared Spectroscopy and Machine Learning Techniques” LINK

“Electric-field-resolved near-infrared microscopy” LINK

Raman Spectroscopy

“A comparative study based on serum SERS spectra in and on the coffee ring for high precision breast cancer detection” LINK

“Raman spectroscopy and multivariate analysis for identification and classification of pharmaceutical pain reliever tablets” LINK

“Foods : High Precisive Prediction of Aflatoxin B1 in Pressing Peanut Oil Using Raman Spectra Combined with Multivariate Data Analysis” LINK

Hyperspectral Imaging (HSI)

” Identification of pesticide residues on black tea by fluorescence hyperspectral technology combined with machine learning” LINK

“Combining hyperspectral imaging and electrochemical sensing for detection of Pseudomonas aeruginosa through pyocyanin production” LINK

Spectral Imaging

“Open-source mobile multispectral imaging system and its applications in biological sample sensing” LINK

Chemometrics and Machine Learning

“Sensors : A Model for Predicting Cervical Cancer Using Machine Learning Algorithms” LINK

“Application of miniature fiber near infrared spectroscopy combined with chemometrics in predicting antioxidant activity of Sagittaria sagittifolia L …” LINK

“Comparison of Calibration Models for Rapid Prediction of Lignin Content in Lignocellulosic Biomass Based on Infrared and Near-Infrared Spectroscopy” LINK

“Foods : Shelf-Life Prediction and Critical Value of Quality Index of Sichuan Sauerkraut Based on Kinetic Model and Principal Component Analysis” LINK


“Giorgia Stocco Rapid and non-destructive determination of Ca and P in milk using WDXRF” LINK


” A Review of Machine Learning Techniques for Identifying Weeds in Corn” LINK

Research on Spectroscopy

“Syntheses, Structures, and Properties of Coordination Polymers with 2,5-Dihydroxy-1,4-Benzoquinone and 4,4′-Bipyridyl Synthesized by In Situ Hydrolysis Method” LINK

Equipment for Spectroscopy

“Polymers : Combined Strategy of Wound Healing Using Thermo-Sensitive PNIPAAm Hydrogel and CS/PVA Membranes: Development and In-Vivo Evaluation” LINK

Future topics in Spectroscopy

“The Effect of Task Performance and Partnership on Interpersonal Brain Synchrony during Cooperation” LINK

Process Control and NIR Sensors

“Monitoring of dromedary milk clotting process by Urtica dioica extract using fluorescence, near infrared and rheology measurements” LINK

Environment NIR-Spectroscopy Application

“Remote Sensing : Combination of Hyperspectral and Machine Learning to Invert Soil Electrical Conductivity” LINK

“Sensors : Comparative Study on Recognition Models of Black-Odorous Water in Hangzhou Based on GF-2 Satellite Data” LINK

Agriculture NIR-Spectroscopy Usage

“Vis-NIR Spectroscopy and Machine Learning Methods to Diagnose Chemical Properties in Colombian Sugarcane Soils” LINK

“Nutrients : Long-Term Dietary Patterns Are Reflected in the Plasma Inflammatory Proteome of Patients with Inflammatory Bowel Disease” LINK

“Remote Sensing : Hyperspectral UAV Images at Different Altitudes for Monitoring the Leaf Nitrogen Content in Cotton Crops” LINK

“Plants : Integrated Starches and Physicochemical Characterization of Sorghum Cultivars for an Efficient and Sustainable Intercropping Model” LINK

“Remote Sensing : Estimation of Canopy Structure of Field Crops Using Sentinel-2 Bands with Vegetation Indices and Machine Learning Algorithms” LINK

Horticulture NIR-Spectroscopy Applications

“Foods : Physico-Chemical, Textural and Sensory Evaluation of Spelt Muffins Supplemented with Apple Powder Enriched with Sugar Beet Molasses” LINK

Food & Feed Industry NIR Usage

“Warming increase the N2O emissions from wheat fields but reduce the wheat yield in a rice-wheat rotation system” LINK

“Biochemical study of rapid discolouration mechanisms in bison meat” LINK

“Emerging Nondestructive Techniques for the Quality and Safety Evaluation of Pork and Beef: Recent Advances, Challenges and Future Perspectives” LINK

Pharma Industry NIR Usage

“The Conservation of Cloud Pattern-painted Boots (1800-1600 BP) Excavated in Yingpan, Xinjiang” | LINK


“基于 WOS 的高光谱技术在农业方面应用的计量分析” LINK

“Modified Hybrid Strategy Integrating Online Adjustable Oil Property Characterization and Data-Driven Robust Optimization under Uncertainty: Application in Gasoline …” LINK

“Insights into the Effect of Sludge Retention Times on System Performance, Microbial Structure and Quorum Sensing in an Activated Sludge Bioreactor” | LINK

“Diclofenac Ion Hydration: Experimental and Theoretical Search for Anion Pairs” LINK

“Aort cerrahisinde derin ve ılımlı hipotermik antegrad serebral perfüzyonun nörolojik etkileri” LINK

“Vibrational spectroscopic evaluation of hydrophilic or hydrophobic properties of oxide surfaces” LINK

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

“基于近红外光谱分析技术的栽培香菇产地快速鉴别” LINK