Spectroscopy and Chemometrics News Weekly #47, 2015

Near Infrared

NIR-Sensor ermittelt Trockensubstanz während der Mischwagenbefüllung | Futterkomponente LINK

Ultra-low maintenance FTNIR analyzer for the refining & petrochemical industries | pauto LINK


Infrared

Seeing Through Crude Oil for Efficient Oil Separations using Short-Wave Infrared (SWIR) Cameras – AZoSensors LINK


Facts

RoboBees Can Fly and Swim. What’s Next? Laser Vision – Smithsonian UAS UAV LINK


Equipment

Scientists create an all-organic UV on-chip spectrometer – The U.S. Department of Energy’s Ames LINK


Agriculture

… detection of contaminants in agro-food products, … melamine levels in milk using vibrational spectroscopy LINK


Laboratory

Examining Pigmented Human Tissue using SWIR Raman Spectroscopy – AZoSensors LINK


Other

SCiO Molecular Scanner UNBOXING – Video LINK



CalibrationModel.com

Dear NIR-Spectrometer vendors, this is about how you can improve customer web-traffic | NIRS Spectrometer LINK

Efficient development of new quantitative prediction equations for multivariate NIR spectra | spectra LINK

How to Develop Chemometric Near-Infrared Spectroscopy Calibrations in the 21st Century? | NIR LINK

How to Develop Near-Infrared Spectroscopy Application Today? | pharma lab analysis chemist TechTrends LINK

Improve chemical analysis accuracy by optimized chemometric models for Near-Infra-Red (NIR) Spectroscopy LINK

Improving Accuracy, Precision and Robustness of NIR-analysis LINK

NewsLetter: Spectroscopy and Chemometrics News Weekly 46, 2015 | Molecular Spectroscopy NIRS Chemometrics Raman LINK

Pro Tip: The NIR calibration is the central key to accurate NIR measurement LINK

Services for professional Development of Near-Infrared Spectroscopy Calibration Methods | NIR Quality Testing LINK



Potential usage of NIR analysis and its industry fields of applications

What is typically measured by NIR Analysis? NIR Calibrations are used for the determination of the content of moisture, fat, protein, starch, lactose, fructose, glucose, alcohol, amino acids, oil, sugar, fiber, salt, Brix, caffeine, lysine, ash, gluten, etc. Where is near-infrared spectroscopy analysis used? NIR Analysis used in the industry area of
  • Agriculture
  • Food and Feed
  • Food and Beverages
  • Food and Dairy
  • Malt houses and breweries
  • Milling and Bakery
  • Flour, Grain milling and oils
  • Sugar
  • Feed Ingredients
  • Edible Oils
  • Meats
  • Animal feed
  • Aqua Feed
  • Pet Food and Animal Proteins
  • Dried and Wet Forage
  • Beverage and Biofuels
  • Chemical and Pharma
  • Pharmaceuticals
  • Pulp and Paper
  • Petro
  • Oil and Gas
  • Plastics
  • Polymers
  • Textiles
  • Packaging
  • Environmental
  • Forensics
  • Academia
  • Cosmetics
  • Health care

What is a NIR calibration used for?

NIR calibrations are used for NIR contents analysis as a productive analytical method. That is a two step procedure.
  1. A NIR analyzer does a non-destructive optical scan of a sample that yields a measured spectrum in seconds.
  2. A NIR calibration model can quantitatively predict (analyze, determine, estimate) multiple constituents, ingredients, contents, analytes, assay, API and other parameters and attributes (chemical, physical, biological, biochemical, sensory) summarized as properties, out of a single spectrum in milli seconds.
The NIR analysis is a very fast non-destructive analysis method that can replace or backup slower methods like wet chemical analysis, chemistry laboratory, sensory panels or rheology (viscosity). Or a NIR calibration can open the door to new possibilities of analytics, quality assurance and process control, by developing calibration models for parameters that seems to be impossible, because they are based on human knowledge, empirical values or sensory like taste value. If you have an NIR instrument, you can measure your samples systematically and thus develop your own calibration models.

Recent advanced chemometric methods

You are searching for recent advanced chemometric methods to get better calibration models for NIR? Methods and algorithms like:
  • Artificial Neural Networks (ANN)
  • General Regression Neural Networks (GR-NN)
  • RBF Neural Networks (RBF-NN)
  • Support Vector Machines (SVM)
  • Multiway Partial Least Squares (MPLS),
  • Orthogonal PLS (OPLS), (O-PLS), OPLS-AA, OPLS-ANN
  • R-PLS, UVE-PLS, RUVE-PLS, LOCAL PLS
  • Hierarchical Kernel Partial Least Squares (HKPLS)
  • Random Forest (RF)
  • etc.
and data pre-processing methods like
  • Extended Multiplicative Signal Correction (EMSC)
  • Orthogonal Signal Correction (OSC)
  • Dynamic Orthogonal Projection (DOP)
  • Error Removal by Orthogonal Subtraction (EROS)
  • External Parameter Orthogonalization (EPO)
  • etc.
that are partly available as modules for software packages like Matlab, Octave, R-Project, etc. Why invest a lot of time and money with new tools? Have you tried it really hard to optimize your calibrations with standard chemometrics methods like Partial Least Squares (PLS), Principal Component Regression (PCR) and Multiple Linear Regression (MLR) which are available in all chemometric software packages? Are you sure you have tried all the good rules and optimization possibilities? Get it done right with the compatible standard methods, we are specialized in optimization and development of NIR calibrations, let us help you, give us a try!

The Ghost Calibrator

To explain our service in an other way, I use an analogy between a book and a calibration. Building good calibrations is like writing a good book (a bestseller). You can write in a foreign language (chemometrics) with a high sophisticated word-processor (the chemometric software) that has a grammar checker (an outlier detection). Due to the complexity of the language (chemometrics) and the difficulty of the chosen book topic (the data) and the incomplete automatic grammar checker, you can never be sure if the grammar is correct and may not lead to misunderstanding (bad prediction performance). So the best way is to let a native language speaker check and correct the text. In that way (the analogy), you can see us even as a ghostwriter (a ghost calibration developer, a ghostcalibrator) that helps you, writing the book (with long year experience, consolidated knowledge, time saving, a lot of benefit). The analogy fits very well, because you can define the topic of the book (with your data). Finally you own the calibration and you have the full insight in how it is done. You have it under full control.