Spectroscopy and Chemometrics News Weekly #33, 2015

Chemometrics

Near Infrared Spectroscopy Detection and Quantification of Herbal Medicines Adulterated with Sibutramin | forensic LINK

Development of NIRS models to predict protein & amylose content of brown rice and proximate compositions of rice bran LINK


Near Infrared

“Can Near-infrared Spectroscopy Detect and Differentiate Implant-associated Biofilms?” | biofilm LINK

Feature: Using Near-Infrared Spectroscopy to Monitor the Curing Reaction of Silicone Adhesives | via LINK

New UV-VIS-NIR Micro-Spectroscopy Solution uSight from TechnoSpex Pte Ltd | Microspectroscopy UV VIS NIR Spectral LINK

VIS-NIR spectroscopy as process analytical technology for compositional characterization of film… | via LINK


Hyperspectral

Multivariate Curve Resolution Applied to Hyperspectral Imaging Analysis of Chocolate Samples | mixture constituent LINK


Other

A Fly-Though of the GAMA Galaxy Survey (With Voice-Over) [HD] intergalactic wavelength LINK

What 200 people traveling in your city by bus, bike, car looks like: | cplan transit LINK

A Miniature Gas Sensor for Mobile Devices – VTT | IoT gas sensor smartphone LINK

Take a look at the Top 10 most accessed Analytical Methods articles From April – June 2015 | … LINK


CalibrationModel.com

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

How to Develop Near-Infrared Spectroscopy Calibrations Today? | near-infra-red LINK

Increase Your Profit with optimized NIRS Accuracy QA QC Food Feed Lab PetCare vitamins LINK

News Summary: Spectroscopy & Chemometrics News Weekly 32, 2015 | Vibrational Spectroscopy NIRS Chemometrics Raman LINK

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

Spectroscopy and Chemometrics News Weekly 32, 2015 LINK

Stop Paying Too Much Time for NIRS Chemometrics Calibration Method development | accuracy measure LINK

NIR Spectroscopy Calibration Report for quantitative predictive models

When you send your quantitative NIR spectra data to our NIR Calibration Model Service, you get a detailed calibration report (calibration protocol) of the found optimal calibration settings, so you are able to see all insights and easily re-build the model in your NIR/Chemometric software.

Here is a part of our calibration report, that exactly describes the data used in the calibration set (CSet), the validation set (VSet) and the test set (TSet). The numbers are the number ids of the spectra in your delivered NIR data file.


The calibration method settings and parameters are
Waveselection : the variable selection or wavenumber selection or wavelength selection
Pretreatments : the spectral data pre-processing
PCs : the number of  Principal Components (PC) or Latent Variables (LV)
Method : the modeling method algorithm used, e.g. PLS

Then the statistical analysis of the PLS model by the different sets (CSet, VSet, Tset).

Calibration Report

Statistical analysis of calibration, validation and test results : 1 Name, 2 Unit, 3 N : number of spectra, 4 N : number of samples, 5 Average spectra count per sample, 6 Reference values, 7 Min, 8 Mean, 9 Median, 10 Max, 11 Standard deviation, 12 Skewness : left (-) or right (+) lack of symmetry, 13 Kurtosis : flat (-) or peaked (+) shape, 14 Model statistics, 15 RPD, 16 R², 17 RMSEC, RMSEP, RMSET : root mean square of prediction errors, 18 SEC, SEP, SET : standard error (bias corrected), 19 Bias, 20 Skewness of prediction errors, 21 Kurtosis of prediction errors, 22 Intercept, 23 Slope, 24 Intercept (reverse), 25 Slope (reverse), 26 Sample Prediction Repeatability Error, 27 Sample Prediction Repeatability Error (of Missing data MSet)

This shows how we deliver the optimal settings. With the statistical values, the NIR model predicted values of all spectra and additional plots you are able to compare with your re-built model to verify that the models perform nearly equally.