Spectroscopy and Chemometrics News Weekly #1, 2020

CalibrationModel.com

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

5 Fehler, die es bei der Digitalisierung in der NIR-Spektroskopie zu vermeiden gilt – das müssen Labormanager, Führungskräfte und CEOs wissen! NIRSpectroscopy NIRS Sensor NearInfrared Analyzers DigitalTransformation foodtech machinelearning LINK

Spectroscopy & Chemometrics News Weekly 52, 2019 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Food Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality Check LINK

Spectroscopy & Chemometrics News Weekly 51, 2019 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory AI 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 Chemometrics and Spectroscopy News in real time on Twitter @ CalibModel and follow us.



Near Infrared

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

“Simultaneous detection of quality and safety in spinach plants using a new generation of NIRS sensors” LINK

“Identification of Genuine and Adulterated Pinellia ternata by Mid-Infrared (MIR) and Near-Infrared (NIR) Spectroscopy with Partial Least Squares – Discriminant …” LINK

“Monitoring coffee roasting cracks and predicting with in situ near-infrared spectroscopy” LINK

“Assessment of a soil fertility index using visible and near-infrared spectroscopy in the rice paddy region of southern China” LINK

“Conversion of the Felixton Mill laboratory from conventional to NIRS analysis.” LINK

“Automatic cancer discrimination based on near-infrared spectrum and class-modeling technique” LINK

“Food powders classification using handheld Near-Infrared Spectroscopy and Support Vector Machine” LINK

“Development and validation of a method for separation of pregabalin and gabapentin capsules using Near Infrared hyperspectral imaging” LINK

“Field-resolved infrared spectroscopy of biological systems” Nature LINK

“Infrared spectroscopy finally sees the light” nature LINK

“Journal Highlight: Estimation of protein and fatty acid composition in shellintact cottonseed by near Infrared reflectance spectroscopy” LINK

” Visible/near-infrared Spectroscopy as a Novel Technology for Nondestructive Detection of Escherichia coli ATCC 8739 in Lettuce Samples” LINK

“The model updating based on near infrared spectroscopy for the sex identification of silkworm pupae from different varieties by a semi-supervised learning with pre …” LINK

“… Study on the Determination of ppm-Level Concentration of Histamine in Tuna Fish Using a Dry Extract System for Infrared Coupled with Near-Infrared Spectroscopy” LINK




Raman

“Transmission Raman Spectroscopic Quantification of Active Pharmaceutical Ingredient in Coated Tablets of Hot-Melt Extruded Amorphous Solid Dispersion” LINK




Hyperspectral

“Plastic waste monitoring and recycling by hyperspectral imaging technology” LINK

“Comparison of Ink Classification Capabilities of Classic Hyperspectral Similarity Features” LINK




Chemometrics

“DEVELOPING NEAR INFRARED SPECTROSCOPIC MODELS FOR PREDICTING DENSITY OF Eucalyptus WOOD BASED ON INDIRECT MEASUREMENT” LINK

“Development of Partial Least Square (PLS) Prediction Model to Measure the Ripeness of Oil Palm Fresh Fruit Bunch (FFB) by Using NIR Spectroscopy” LINK




Facts

“Bombs and cocaine: detecting nefarious nitrogen sources using remote sensing and machine learning” LINK




Agriculture

“Laboratory-based hyperspectral image analysis for the classification of soil texture” LINK

“Research on simultaneous detection of SSC and FI of blueberry based on hyperspectral imaging combined MS-SPA” LINK

“Polymers, Vol. 12, Pages 78: Insight into the Intermolecular Interaction and Free Radical Polymerizability of Methacrylates in Supercritical Carbon Dioxide” LINK

“Optimizing the procedure of grain nutrient predictions in barley via hyperspectral imaging.” LINK




Other

“绿泥石矿物近红外光谱吸收谱带的位移机理与控制机制研究” LINK

“Spektroskopie – Unverwechselbarer molekularer Fingerabdruck” LINK





NIR-Predictor

New: NIR-Predictor V2.4 with new features

The new Version of the free NIR-Predictor
supports multiple native file formats
of miniature, mobile and desktop spectrometers
get your spectra analyced as easy as Drag’n’Drop.

  • NIR-Predictor is an easy to use NIR software for all NIR devices
    to produce quantitative results out of NIR data.

  • CalibrationModel Service provides development of
    customized calibrations out of NIR and Lab data.

  • It allows to use NIR with your own customized
    models without the need of Chemometric Software!

  • We do the Machine Leraning for your NIR-Spectrometer
    and with the free NIR-Predictor you are
    able to analyze new measured samples.

  • For NIR-Vendors we also offer the
    Software Development Kit (SDK) for OEM Predictor use
    via the Application Programming Interface (API).
    Think of a sencod predictor engine,
    as a second heart in your system.



Download

Key Features of NIR-Predictor

  • Super flexible prediction with automatic file format detection
  • Support for many mobile and desktop NIR Spectrometers file format
  • Application concept allows to group multiple Calibrations together for an Application
  • Prediction Report shows Histogram Charts of the tabulated prediction results
  • Sample based Properties File Creator for combining NIR and Lab reference data
  • Checked creation of a single file Calibration Request

Super flexible prediction

Loads multiple files at once in

  • different file-formats and …
  • different wave-ranges and wave-resolutions and …
  • predicts each spectrum with all compatible calibrations and …
  • merges the results in a report and …
  • saves the report as HTML.

It allows you to

  • comparing measurements
  • compare different calibrations
  • compare different spectrometers,
    carry out your own round-robin amongst the vendors’ instruments.
  • compare different spectra file formats

With no configuration and no special menu command,
just drag & drop your data files.

Videos


Properties File Creator

A tool for the NIR-User to create the property file easily. It helps to create a CSV file from the measured spectra files with sample names and properties to edit in Spreadsheet/EXCEL software. Lets you enter Lab-Reference-Values in a sample-based manner, corresponding to your sample spectra for calibration. It contains clever automatic analysis mechanisms of inconsistencies in your raw-data to increase the data quality for calibration. Provides detailed analyzer information for manual data cleanup when needed.

It’s time saving and less error prone because you DON’T need to open each spectrum file separately in an editor and copy the spectral values into a table grid beside the Lab-values.

Properties File Creator saves you from:

  • manually error prone and boring tasks
  • importing multiple data files and combining it’s content manually into a single data file to append the lab reference values (aka properties)
  • programming and writing scripts to transform the data into the shape needed
  • no trouble with data handling of
    • Wavelength / Wavenumber information (x-axis)
    • Absorbance / Reflectance labeling (y-axis)
    • checking compatibility of the raw data before merging
    • Averaging Spectral Intensities of a Sample
    • coping, flipping and transposing rows and colums to get the X-Block and Y-Block data sets ready for calibration modeling
    • limited and error prone table grid functionality

Because it’s all automatic and you can check the results and get the analysis information!

Properties File Creator provides you – a individual template based on your raw-data for combining NIR and Lab-values – analysis and checks for better data quality for calibration

Top 8 Reasons why you should use
Automated NIR Calibration Service

  • No subjective model selection
  • No variation in results and interpretation
  • No overfitting model
  • Better accuracy
  • Better precision
  • Time saving!
  • No software cost (no need for Chemometric software and training)
  • One free prediction software for all your NIR systems

Reduce Total Cost of Ownership (TCO) of your NIR

To be ahead of competitors
  • by not owning a chemometric software
  • by not struggling days with these complicated software
  • by not deep dive into chemometrics theory
It takes significant know-how and continous investment to develop calibrations
  • You need to have the relevant skill sets in your organization.
  • That means salaries (the biggest expense in most organizations)
To get most out of it, start now!
  • use the free NIR-Predictor together with your NIR-Instrument software
  • as an NIR-Vendor, integrate the free NIR-Predictor OEM into your NIR-Instrument software
  • don’t delay time-to-market
Read more about NIR Total cost of ownership (TCO)

Download


About the included Demo-Spectra and Demo-Calibrations

The demo calibrations for the spectrometers from

  • Si-Ware Systems
  • Spectral Engines
  • Texas Instruments
  • VIAVI

are built with the raw data, thankfully provided from Prof. Heinz W Siesler, from this publication

“Hand-held near-infrared spectrometers:
State-of-the-art instrumentation and practical applications”
Hui Yan, Heinz W Siesler
First Published August 20, 2018 Research Article
https://doi.org/10.1177/0960336018796391

The demo calibrations for the FOSS are built with the

ANSIG Kaji Competition 2014 shootout data
http://www.anisg.com.au/the-kaji-competition


References

Quickstart: NIR-Predictor – Manual

Features and Version History: NIR-Predictor – Release Notes History

Supported NIR Spectra Formats: NIR-Predictor supported Spectral Data File Formats

Frequently Asked Questions: NIR-Predictor – FAQ

WebShop : CalibrationModel WebShop