Spectroscopy and Chemometrics News Weekly #38, 2019

CalibrationModel.com

New: free NIR-Predictor V2.4 supports file formats out of the box from: @TIDLP @ViaviSolutions @OceanOpticsEMEA @my_scio @SiWareSystems @SpectralEngines @trinamiX_GmbH @StellarNet – Mobile NIRS portable NIR2019 NIR2020 Analyzers LINK

Spectroscopy and Chemometrics News Weekly 37, 2019 | NIRS NIR Spectroscopy Chemometrics Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality Checking LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 37, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 37, 2019 | NIRS NIR Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem prediction models LINK

This week’s NIR news Weekly is sponsored by your-Company-Name-here – Best-NIR-instruments. Check out their product page … link




Chemometrics

“Potential biomonitoring of atmospheric carbon dioxide in Coffea arabica leaves using near-infrared spectroscopy and partial least squares discriminant analysis” LINK

“Quantitative Real-Time Release Testing of Rhubarb based on Near-Infrared Spectroscopy and Method Validation” LINK

“Identification of lactic acid bacteria Enterococcus and Lactococcus by near-infrared spectroscopy and multivariate classification” LINK

“Determination of manganese content in cottonseed meal using near-infrared spectrometry and multivariate calibration” LINK

“Advanced Modeling of Soil Biological Properties Using Visible Near Infrared Diffuse Reflectance Spectroscopy” |:ijbs1&volume=5&issue=1&article=001 LINK

“山茶油中油酸和亚油酸近红外光谱分析模型” “Analysis Model of Oleic and Linoleic Acids in Camellia Oilvia Near-Infrared Spectroscopy” LINK

“Determination of 10-Hydroxy-2-Decenoic Acid of Royal Jelly Using Near-Infrared Spectroscopy Combined with Chemometrics.” LINK

“Predicting of the Quality Attributes of Orange Fruit Using Hyperspectral Images” LINK

“Rapid and Automatic Classification of Tobacco Leaves Using a Hand-Held DLP-Based NIR Spectroscopy Device” LINK

“Association of mid-infrared-predicted milk and blood constituents with early-lactation disease, removal, and production outcomes in Holstein cows” |(19)30787-8/fulltext LINK

“Machine learning and soil sciences: A review aided by machine learning tools” LINK




Near Infrared

“Soil characterization using Visible Near Infrared Diffuse Reflectance Spectroscopy (VNIR DRS)” LINK

“Quantification of soil organic carbon stock in urban soils using visible and near infrared reflectance spectroscopy (VNIRS) in situ or in laboratory conditions” LINK

“Assessment of the human albumin in acid precipitation process using NIRS and multi-variable selection methods combined with SPA” LINK

” Implementación de estrategias de muestreo, inspección y control en la industria agroalimentaria basadas en el empleo automatizado de sensores nirs” LINK

“Determination of glucose concentration in aqueous solution using FT NIR spectroscopy” LINK

“Near infrared spectroscopy for world food security” LINK

“Titanium dioxide as an adsorbent to enhance the detection ability of near-infrared diffuse reflectance spectroscopy” LINK

“Near-infrared diffuse reflectance spectroscopy for discriminating fruit and vegetable products preserved in glass containers” LINK

“Ability of near-infrared spectroscopy for non-destructive detection of internal insect infestation in fruits: Meta-analysis of spectral ranges and optical measurement …” LINK

“Molecules, Vol. 24, Pages 3268: Near-Infrared Hyperspectral Imaging Combined with Deep Learning to Identify Cotton Seed Varieties” LINK

“Improvement of the Fourier Transform Near Infrared Method to Evaluate Extra Virgin Olive Oils by Analyzing 1,2-Diacylglycerols and 1,3-Diacylglycerols and Adding Unesterified Fatty Acids.” LINK




Agriculture

“51 Feedstuff fatty acid content, variation, techniques and implications on practical animal nutrition” LINK

“Prediction of Milk Coagulation Properties and Individual Cheese Yield in Sheep Using Partial Least Squares Regression” Animals LINK




Food & Feed

“Classifying the fertility of dairy cows using milk mid-infrared spectroscopy” 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

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