Spectroscopy and Chemometrics/Machine-Learning News Weekly #20, 2022

NIR Calibration-Model Services

NIR User? Get better results faster | Food Science QC Lab Laboratory Manager chemist LabWork Chemie analytik LINK

Spectroscopy and Chemometrics News Weekly 19, 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 19, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 19, 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)

“Why People and AI Make Good Business Partners” | human AI relationships AI as a Service ( AIaaS ) LabManager NIRS MachineLearning LINK

“A novel aquaphotomics based approach for understanding salvianolic acid A conversion reaction with near infrared spectroscopy” LINK

“ex type determination in papaya seeds and leaves using near infrared spectroscopy combined with multivariate techniques and machine learnin” LINK


“Rapid authentication and composition determination of cellulose films by UV-VIS-NIR spectroscopy” LINK

“Interoceptive Attentiveness Induces Significantly More PFC Activation during a Synchronized Linguistic Task Compared to a Motor Task as Revealed by Functional Near-Infrared Spectroscopy” | LINK

“Near-infrared spectroscopy and machine learning-based technique to predict quality-related parameters in instant tea” | LINK

“Sensors : LASSO Homotopy-Based Sparse Representation Classification for fNIRS-BCI” LINK

“Using metaheuristic algorithms to improve the estimation of acidity in Fuji apples using NIR spectroscopy” LINK

“Analyzing Classification Performance of fNIRS-BCI for Gait Rehabilitation Using Deep Neural Networks” LINK

“Multimodal diffuse optical system integrating DSCA-NIRS and cSFDI for measuring tissue metabolism” LINK

extruded granules extruder NIR AEE audible acoustic emission granule drying process PAT LINK

“Fast Noniterative Data Analysis Method for Frequency-Domain Near-Infrared Spectroscopy with the Microscopic Beer-Lambert Law” LINK

“Vis-NIR Hyperspectral Dimensionality Reduction for Nondestructive Identification of China Northeast Rice” | LINK

“FT-NIR Spectroscopy for the Non-Invasive Study of Binders and Multi-Layered Structures in Ancient Paintings: Artworks of the Lombard Renaissance as Case Studies” LINK

“In Vivo Measurement Strategy for Near-Infrared Noninvasive Glucose Detection and Human Body Verification” LINK

“A Standard-Free Calibration Transfer Strategy for a Discrimination Model of Apple Origins Based on Near-Infrared Spectroscopy” LINK

“Comparative study on the real-time monitoring of a fluid bed drying process of extruded granules using near-infrared spectroscopy and audible acoustic emission” LINK

“Fast detection of cotton content in silk/cotton textiles by handheld near-infrared spectroscopy: a performance comparison of four different instruments” LINK

“Evaluation of optical properties of tofu samples produced with different coagulation temperatures and times using near-infrared transmission spectroscopy” LINK

“Near-Infrared Spectroscopy and Mode Cloning (NIR-MC) for In-Situ Analysis of Crude Protein in Bamboo” LINK

“Near-infrared spectroscopy to estimate the chemical element concentration in soils and sediments in a rural catchment” LINK

“Ensemble classification and regression techniques combined with portable near infrared spectroscopy for facile and rapid detection of water adulteration in bovine …” LINK

“Characterization of crude oils with a portable NIR spectrometer” CrudeOil NIRspectrometer LINK

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

“A Device for Measuring Apple Sweetness Using Near Infrared Spectroscopy” LINK

“Nearinfrared fluorophores based on heptamethine cyanine dyes: from their synthesis and photophysical properties to recent optical sensing and bioimaging applications” LINK

“Use of Attenuated Total Reflection Fourier Transform Infrared Spectroscopy and Principal Component Analysis for the Assessment of Engine Oils” | LINK

“Near-Infrared Hyperspectral Imaging Pipelines for Pasture Seed Quality Evaluation: An Overview” LINK

“Analyzing the Water Confined in Hydrogel Using Near-Infrared Spectroscopy” LINK

“Near-infrared spectra of aqueous glucose solutions” LINK

“Determination of storage period of harvested plums by nearinfrared spectroscopy and quality attributes” LINK

Hyperspectral Imaging (HSI)

“Rapid Detection of Different Types of Soil Nitrogen Using Near-Infrared Hyperspectral Imaging” LINK

“Near-Infrared Hyperspectral Imaging Pipelines for Pasture Seed Quality Evaluation: An Overview” LINK

“Estimating soil moisture content under grassland with hyperspectral data using radiative transfer modelling and machine learning” LINK

“Improving rice nitrogen stress diagnosis by denoising strips in hyperspectral images via deep learning” LINK

“Identification of Soil Arsenic Contamination in Rice Paddy Field Based on Hyperspectral Reflectance Approach” LINK

Chemometrics and Machine Learning

“Remote Sensing : Early Detection of Dendroctonus valens Infestation with Machine Learning Algorithms Based on Hyperspectral Reflectance” LINK

“Applied microwave power estimation of black carrot powders using spectroscopy combined with chemometrics” LINK

DataScientist Job: Expectation vs. Reality [infographic] BigData DataScience Analytics AI MachineLearning ArtificialIntelligence Data DataAnalytics Python SQL Statistics DataViz Careers Jobs FeatureEngineering DataPrep DataCleaning LINK

“Agronomy : Detection of Adulterations in Fruit Juices Using Machine Learning Methods over FT-IR Spectroscopic Data” LINK

“Reflectance Based Models for Non-Destructive Prediction of Lycopene Content in Tomato Fruits” | LINK

“The evolution of chemometrics coupled with near infrared spectroscopy for fruit quality evaluation” LINK

“Machine Learning Strategies for the Retrieval of Leaf-Chlorophyll Dynamics: Model Choice, Sequential Versus Retraining Learning, and Hyperspectral Predictors” | LINK

“In-line near-infrared analysis of milk coupled with machine learning methods for the daily prediction of blood metabolic profile in dairy cattle” LINK

“Near-infrared spectroscopy with chemometrics for identification and quantification of adulteration in high-quality stingless bee honey” LINK

“Rapid identification and quantification of intramuscular fat adulteration in lamb meat with VIS-NIR spectroscopy and chemometrics methods” LINK

Optics for Spectroscopy

“Spectrum Reconstruction with Filter-Free Photodetectors Based on Graded-Band-Gap Perovskite Quantum Dot Heterojunctions” LINK


“Sensors : Dietary Patterns Associated with Diabetes in an Older Population from Southern Italy Using an Unsupervised Learning Approach” | LINK

Research on Spectroscopy

“A Study of C= O… HO and OH… OH (Dimer, Trimer, and Oligomer) Hydrogen Bonding in a Poly (4-vinylphenol) 30%/Poly (methyl methacrylate) 70% Blend and its …” LINK

“Deeper insights into the photoluminescence properties and (photo) chemical reactivity of cadmium red (CdS1− xSex) paints in renowned twentieth century …” | LINK

Equipment for Spectroscopy

“Green Textile Materials for Surface Enhanced Raman Spectroscopy Identification of Pesticides Using a Raman Handheld Spectrometer for In-Field Detection” LINK

“Characterization of Crude Oils with a Portable Nir Spectrometer” LINK

“Discrimination of the Red Jujube Varieties Using a Portable NIR Spectrometer and Fuzzy Improved Linear Discriminant Analysis” LINK

“Rapid authentication of the geographical origin of milk using portable near‐infrared spectrometer and fuzzy uncorrelated discriminant transformation” LINK

Environment NIR-Spectroscopy Application

“Remote Sensing : Estimating Forest Soil Properties for Humus Assessment—Is Vis-NIR the Way to Go?” LINK

“Sensors : Evaluation of Two Portable Hyperspectral-Sensor-Based Instruments to Predict Key Soil Properties in Canadian Soils” LINK

“Evaluation of Vis-Nir Pretreatments Combined with Pls Regression for Estimation SOC, Cec and Clay in Silty Soils from Eastern Croatia” LINK

“Comparing Two Different Development Methods of External Parameter Orthogonalization for Estimating Organic Carbon from Field-Moist Intact Soils by Reflectance …” LINK

Agriculture NIR-Spectroscopy Usage

“Site-specific seeding for maize production using management zone maps delineated with multi-sensors data fusion scheme” LINK

“Rapid Identification of Soybean Varieties by Terahertz Frequency-Domain Spectroscopy and Grey Wolf Optimizer-Support Vector Machine” | LINK

“A LUCASbased midinfrared soil spectral library: Its usefulness for soil survey and precision agriculture” LINK

“Identification of Microplastics in Biosolids Using Ftir and Vis-Nir Spectroscopy Enhanced by Chemometric Methods” LINK

“Agriculture : Feature Wavelength Selection Based on the Combination of Image and Spectrum for Aflatoxin B1 Concentration Classification in Single Maize Kernels” LINK

Food & Feed Industry NIR Usage

“Agronomy : Analysis of Physico-Chemical and Organoleptic Fruit Parameters Relevant for Tomato Quality” LINK

Chemical Industry NIR Usage

“Polymers : Microscopic and Structural Studies of an Antimicrobial Polymer Film Modified with a Natural Filler Based on Triterpenoids” LINK

Laboratory and NIR-Spectroscopy

“Laboratory Hyperspectral Image Acquisition System Setup and Validation” LINK


“A sensor combination based automatic sorting system for waste washing machine parts” 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