Spectroscopy and Chemometrics News Weekly #2, 2020


Spectroscopy and Chemometrics News Weekly 1, 2020 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Quality Testing LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 1, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 1, 2020 | NIRS NIR Spettroscopia MachineLearning AI analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio Application analisi qualità QC Analysesystem prediction LINK

Five Mistakes to avoid on Digitalization in NIR-Spectroscopy – that Lab Managers, Executives and CEOs must know! NIRSpectroscopy NIRS Sensors NearInfrared Analyzers DigitalTransformation QualityControl foodtech machinelearning AI datascience LINK

SAFE COST IN MAINTAINING NIR-SPECTROSCOPY METHODS | NIRSpectroscopy NIRS Spectroscopy DigitalTransformation Analysis Lab Laboratory Application Quantitative Analysis Methods Measurements Analytical Parameters Spectrometer Quality Accuracy LINK

Do you develop NIR / NIRS calibrations by yourself? Can you sell it? No? Buy it! Digitalization LabManager LabAutomation CEO Digitalisation Spectroscopy AutoML LowCost lowerCost SaveMoney SaveTime Efficiency Effectivity LINK

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

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

Near Infrared

“Study of chemical compound spatial distribution in biodegradable active films using NIR hyperspectral imaging and multivariate curve resolution” LINK

“Advances in Near Infrared Spectroscopy and Related Computational Methods” MDPI Books – Pages: 496 OpenAccess | NIRSpectroscopy NIRS NIR LINK

” Ampliación de una librería espectral de mezclas unifeed analizadas en un instrumento NIRS de laboratorio” LINK

“Applied Sciences, Vol. 9, Pages 5058: Single-Kernel FT-NIR Spectroscopy for Detecting Maturity of Cucumber Seeds Using a Multiclass Hierarchical Classification Strategy” LINK

” Visible-near Infrared (VIS-NIR) Spectroscopy as a Rapid Measurement Tool to Assess the Effect of Tillage on Oil Contaminated Sites” LINK

“Non-invasive measurements of ‘Yunhe’pears by vis-NIRS technology coupled with deviation fusion modeling approach” LINK

“Standard Analytical Methods, Sensory Evaluation, NIRS and Electronic Tongue for Sensing Taste Attributes of Different Melon Varieties.” LINK

“Control of ascorbic acid in fortified powdered soft drinks using near-infrared spectroscopy (NIRS) and multivariate analysis” LINK

“Prediction Model of the Key Components for Lodging Resistance in Rapeseed Stalk Using Near-Infrared Reflectance Spectroscopy (NIRS)” LINK

“NIR spectroscopic determination of urine components in spot urine: preliminary investigation towards optical point-of-care test.” LINK

“O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression.” LINK

“Authentication of Tokaj Wine (Hungaricum) with the Electronic Tongue and Near Infrared Spectroscopy.” LINK

“Potential of the near-infrared spectroscopy for the discrimination of wood and charcoal of four native Myrtaceae species in southern Brazil” LINK

“Estimating the Carbon Content of Coastal Wetland Vegetation With Visible and Near-Infrared Reflectance Spectroscopy” LINK

“Species-and Moisture-based Sorting of Green Timber Mix with Near Infrared Spectroscopy” LINK

“Potential of Near-Infrared Spectroscopy to Evaluate the Cleaning Performance of Dishwashing Processes” LINK

” Near Infrared Spectroscopic Study of Trioctahedral Chlorites and Its Remote Sensing Application” LINK

” Interactive comment on “Estimation of effective calibration sample size using visible near infrared spectroscopy: deep learning vs machine learning”” LINK


“Remote Sensing, Vol. 11, Pages 2731: Eco-Friendly Estimation of Heavy Metal Contents in Grapevine Foliage Using In-Field Hyperspectral Data and Multivariate Analysis” LINK

Spectral Imaging

“Multispectral cross-polarization reflectance measurements suggest high contrast of demineralization on tooth surfaces at wavelengths beyond 1300 nm due to reduced light scattering in sound enamel.” LINK


“Visible-Near Infrared Spectroscopy and Chemometric Methods for Wood Density Prediction and Origin/Species Identification” Forests LINK

“Comparison of two augmented classical least squares algorithms and PLS for determining nifuroxazide and its genotoxic impurities using UV spectroscopy” LINK

“Why should the pharmaceutical industry claim for the implementation of second-order chemometric models-A critical review.” LINK

“Use of near infrared spectroscopy coupled with chemometrics for fast detection of irradiated dry fermented sausages” LINK

” Hyperspectral analysis for a robust assessment of soil properties using adapted PLSR method” LINK


“Toward complete oral cavity cancer resection using a handheld diffuse reflectance spectroscopy probe.” LINK

Process Control

“Combining convolutional neural networks and inline nearinfrared spectroscopy for realtime monitoring of the chromatographic elution process in commercial production of notoginseng total saponins” LINK


“Fast measurement of phosphates and ammonium in fermentation-like media: a feasibility study.” LINK

“Application of Near-Infrared Hyperspectral Imaging with Machine Learning Methods to Identify Geographical Origins of Dry Narrow-Leaved Oleaster (Elaeagnus angustifolia) Fruits” LINK

“Rapid visible-near infrared (Vis-NIR) spectroscopic detection and quantification of unripe banana flour adulteration with wheat flour.” LINK

“Molecules, Vol. 24, Pages 4310: Chemometric Characterization of Strawberries and Blueberries according to Their Phenolic Profile: Combined Effect of Cultivar and Cultivation System” LINK

“Evaluating Soybean Meal Quality Using Near-Infrared Reflectance Spectroscopy” LINK

“Changes in Human Milk Fatty Acid Composition During Lactation: The Ulm SPATZ Health Study” Nutrients LINK

Food & Feed

“Photothermal treatment of port-wine stains using erythrocyte-derived particles doped with indocyanine green: a theoretical study.” LINK


” Breeding and Testing Corn for Reduced Aflatoxin Contamination and Increased Drought Tolerance for Texas” LINK

Five Mistakes to avoid on Digitalization in NIR-Spectroscopy – that Lab Managers, Executives and CEOs must know!

The fast and non-destructive NIR-Spectroscopy analysis method is based on predictive models that are built upon spectral and Lab reference data.

Developing such models with Chemometric techniques or Machine Learning Algorithms can now be fully automatized with many advantages.

If your company uses NIR-Spectroscopy, do you know if your company yet tried this calibration service? And if not, why not?

Here are some possible reasons why such services are blocked in your company.

With the knowledge where and why it may be blocked, you are able to overcome the barriers and go for innovation.

Misbeliefs of People that may block Advanced Services (AI and Automatic Machine Learning)

5 Mistakes to avoid on Digitalization in NIR-Spectroscopy
Misbeliefs People Remove barriers
1 You need to program or scripting with data modeling tools (R, Phyton, TensorFlow, Matlab, sas, SPSS, H2O, scikit, …..) The opinion that only PhD (statisticians, data scientists) are smart enough to create models. Give the service a try, and compare! There are free trials for calibration development.
2 We have done it always manually by hand. We must see the plots and interpret the stats in every step.
Job protectionism : “My job will dramatically change if that will work, so I will never prepare real-life data to give someone a possibility to try such a service.”
AI / ML haters (NIR-Specialists, NIR-Experts) don’t belive in automated calibration. Give the service a try, and compare! You will see plots and stats! There are free trials for calibration development.
3 Against any new hardware, software or service because of supposed new problems. Preserving ones – the permission gate keepers (IT) Give it a try, without an account, download the free NIR-Predictor software (full version, no limitations) with included demo data, it installs and runs without Administrator priviledge!
4 Ensures that new methodologies follow the rules. Any new thing will give extra work for them. Compliance and Regulation officers. Get access to the detailed model blueprint (ISO 12099) – there is no vendor lock-in or black-box model. You can even anonymize your data for Knowledge Protection – see JCAMP-Anonymizer.
5 Our employees are open for new things. Our employees do not block. Managers, executives, board level. Remove the Barriers to Innovation!

Start Calibrate