Spectroscopy and Chemometrics News Weekly #49, 2019


Spectroscopy and Chemometrics News Weekly 48, 2019 | NIRS NIR Spectroscopy machinelearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality Check LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 48 2019 | NIRS NIR Spektroskopie MachineLearning Spektrometer SmartSensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Qualitätslabor LINK

Spettroscopia e Chemiometria Weekly News 48, 2019 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem datascience prediction 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 (NIR)

“Development of near infrared reflectance spectroscopy (NIRS) calibration model to estimate the forage quality of shrub species” LINK

“Estimation and classification of popping expansion capacity in popcorn breeding programs using NIR spectroscopy” LINK

“Authentication of liquid egg composition using ATR-FTIR and NIR spectroscopy in combination with PCA” LINK

“Non-Destructive Method for Predicting Sapodilla Fruit Quality Using Near Infrared Spectroscopy” LINK

“Discrimination of white teas produced from fresh leaves with different maturity by near-infrared spectroscopy” LINK

“AI and InfraRed Spectroscopy to Accelerate Malaria Control” LINK

“Near infrared spectroscopic data for rapid and simultaneous prediction of quality attributes in intact mango fruits.” LINK

“Reflectance Properties of Brown Mass Dyed Poly (ethylene terephthalate) Filament Yarns in the Visible-near Infrared Region” LINK

” The contribution of Visible Near Infrared Reflectance spectroscopy to colour determination: the case of the experimental ceramic briquettes” | Mineralogy, Petrology, Economic GeologyLINK

“Non-destructive measurement of soluble solids content of three melon cultivars using portable visible/near infrared spectroscopy” LINK

” Predicting plant available phosphorus using infrared spectroscopy with consideration for future mobile sensing applications in precision farming” LINK

“Molecules, Vol. 24, Pages 3900: Antioxidant Activity of Blueberry (Vaccinium spp.) Cultivar Leaves: Differences Across the Vegetative Stage and the Application of Near Infrared Spectroscopy” LINK


“A novel hyperspectral line-scan imaging method for whole surfaces of round shaped agricultural products” LINK

“Setting up a methodology to distinguish between green oranges and leaves using hyperspectral imaging” LINK

“Early detection of tomato spotted wilt virus infection in tobacco using the hyperspectral imaging technique and machine learning algorithms” LINK

“The Future of Hyperspectral Imaging” LINK

“Soil fertility status assessment using hyperspectral remote sensing” LINK

Chemometrics / Machine Learning

“Authentication of PGI Gragnano Pasta by Near Infrared (NIR) spectroscopy and chemometrics” LINK

” Prediction of Salt in Soil by PLS Regression Using Hyperspectral Laboratory Data” LINK

“Measurement of quality parameters of sugar beet juices using near-infrared spectroscopy and chemometrics” LINK

“Classification of oolong tea varieties based on hyperspectral imaging technology and BOSS-LightGBM model” LINK

“Analytical and sensory data correlation to understand consumers’ grape preference” LINK

Process Control

” A review on mechanisms, screening and engineering for pest resistance in sugarcane (Saccharum spp)” LINK


“Visible and Near-Infrared Reflectance Spectroscopy Analysis of Soils” LINK

“Spektroradyometre teknigi ile toprak özelliklerinin belirlenmesi; Harran Ovasi cullap sulama birligi alani örnegi/Determination of soil properties using …” LINK


” Assessing plant performance in the Enviratron” LINK

“Broad near infrared spectroscopy calibrations can predict the nutritional value of over one hundred forage species within the Australian feedbase” LINK


“The study of combustion characteristics of corn stalks and cobs via TGA-DTG-DSC analysis” LINK

” Gravimetric and Spectrophotometric Determination of Surface Wax Content in Maize Kernels” LINK

“Detection of Multi-frozen and Single-frozen Fish Using Optical Spectroscopy” LINK

Anonymize your NIR spectroscopy data (JCAMP-DX) with JCAMP-Anonymizer Software because of Data Privacy

What is data anonymization?

This helpful tool, the JCAMP-Anonymizer Software, allows you to remove all the sensitive privacy information and metadata from your JCAMP-DX data files.

Why data anonymization?

Without owner name, instrument serial-number, application type, sample names, GPS location, time stamps, the data file can be forwarded to third party services without giving away the sensitive data.

Without these sensitive data fields (meta information) it is still possible to develop calibration models, because only the spectral data and the corresponding property values (constituents) are needed.

Even the names of the properties like “Fat” or “Moisture” gets anonymized.

This software is intended for the use with the CalibrationModel.com service for NIR-Spectral data in JCAMP-DX format, if you don’t want to give sensitive data away.

Note: that these anonymization step is optional for using CalibrationModel.com service.


Single or multiple JCAMP files can put onto the tool by drag&drop or clicking the button to select the files. The original files are kept unchanged and new .anon.dx files are created in the “Anonymized” subdirectory.

The JCAMP-Anonymizer shows you exactly, line by line, which information in the file is removed and which is kept.

You can always check if all the sensitive information is removed, by viewing the .anon.dx file with a text editor (and anonymize it even further if needed).


For more information see also
Anonymized NIR Spectroscopy Data
Trust and Anonymization does not contradict

NIR data format anonymisation technique , JCAMP anonymizer for NIR Spectroscopy , JCAMP .dx . jdx .jcm .jcamp , JCAMP-DX 4.24 , JCAMP-DX 5.01 , JCAMP-DX 6.0 , NIR open data format , NIR Spectroscopy Data , NIR Spectroscopic data , NIR spectral data , NIR raw dataset , NIR Data minimisation , NIR Data anonymization , NIR Data Anonymisation , NIR Pseudonymization , NIR pseudonymisation , NIR Data masking , anonymised NIR data , Anonymous NIR Data , Anonymized NIR Data , NIR Data Anonymizer , anonymise data , rendered anonymous , anonymised datasets , Anonymisation process , data privacy guaranteed , metadata removal , minimum amount of information , NIR Data anonymizer , Spectral Library Data anonymizer , data privacy in spectroscopy , Data Anonymization in NIR Analytics , Data Anonymization in Spectroscopy , NIRS Privacy Consideration , NIR Spectroscopy data protection , NIR Spectroscopy anonymous information , Spectroscopy data anonymization , Spectroscopy Anonymization Service , Removal of all personal and meta data , Remove meta information in spectral data , Removing unnecessary JCAMP rows lines , Anonymization against Data Collection , Spectroscopy Data anonymization , Spectroscopy Information sanitization , strip uneeded JCAMP data , Stripping Data from Spectrum data files , Stripping Data from Spectroscopy data files , scrape JCAMP data , cleaning JCAMP data files , shrinking JCAMP data files , filtering spectroscopy data content , meta data removal , spectral dataset cleanup for data exchange , removing sensitive information from NIR, NIRS, fNIR spectral data , anonymization of clinical trial data , Spectroscopy data cleansing , Spectroscopy data-anonymization , Spectroscopy Anonymization Strategies , anonymizing Spectroscopy data