Spectroscopy and Chemometrics/Machine-Learning News Weekly #21, 2022

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 20, 2022 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 20, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 20, 2022 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK




Near-Infrared Spectroscopy (NIRS)

“Agriculture : Feasibility of Near-Infrared Spectroscopy for Rapid Detection of Available Nitrogen in Vermiculite Substrates in Desert Facility Agriculture” LINK

“Blood discrimination based on NIR spectroscopy and BP neural network combined with genetic algorithm” LINK

“Automated surface mapping via unsupervised learning and classification of Mercury Visible-Near-Infrared reflectance spectra” LINK

“At-line and inline prediction of droplet size in mayonnaise with near-infrared spectroscopy” LINK

“Use of near-infrared spectroscopy and chemometrics for fast discrimination of Sargassum fusiforme” LINK

” Chemometric studies of hops degradation at different storage forms using UVVis, NIRS and UPLC analyses” LINK

“Portable NIR spectroscopy and PLS based variable selection for adulteration detection in quinoa flour” LINK

“Foods : Assessment of Pumpkin Seed Oil Adulteration Supported by Multivariate Analysis: Comparison of GC-MS, Colourimetry and NIR Spectroscopy Data” LINK

“Near infrared spectroscopy to evaluate the effect of a hybrid exercise programme on peripheral muscle metabolism in patients with intermittent claudication: an …” LINK

“Plants : Prediction and Comparisons of Turpentine Content in Slash Pine at Different Slope Positions Using Near-Infrared Spectroscopy” LINK

“Teknologi Near Infrared Reflectance Spectroscopy (NIRS) dan Metode Kemometri untuk Deteksi Pemalsuan Minyak Nilam” LINK

“Raman and near Infrared Spectroscopy for Quantification of Fatty Acids in Muscle Tissue—A Salmon Case Study” LINK

“Multi-information based on ATR-FTIR and FT-NIR for identification and evaluation for different parts and harvest time of Dendrobium officinale with chemometrics” LINK

“Application of near infrared spectroscopy to predict contents of various lactones in chromatographic process of Ginkgo Folium” LINK

“A feasibility study on improving the non-invasive detection accuracy of bottled Shuanghuanglian oral liquid using near infrared spectroscopy” LINK

“The application of NIR spectroscopy in moisture determining of vegetable seeds” | seedtesting seedquality NIRS methodDevelopment Calibration solution content analysis seed grain grains LINK

“Aplicación de imágenes hiperespectrales (HSI-NIR) para la determinación de estrés hídrico en hojas de patata.” LINK

“Analyzing Classification Performance of fNIRS-BCI for Gait Rehabilitation Using Deep Neural Networks” | LINK

“Near-infrared spectroscopy and machine learning-based technique to predict quality-related parameters in instant tea” | LINK

“Prediction of Wheat Quality Parameters Combining Raman, Fluorescence and Near‐Infrared Spectroscopy (NIRS)” LINK




Infrared Spectroscopy (IR) and Near-Infrared Spectroscopy (NIR)

“Extending Effective Dynamic Range of Hyperspectral Line Cameras for Short Wave Infrared Imaging” | LINK

“Single-domain nearinfrared protein provides a scaffold for antigen-dependent fluorescent nanobodies” LINK

“Analyzing the Water Confined in Hydrogel Using Near-Infrared Spectroscopy” LINK

“Application of infrared spectroscopic techniques to cheese authentication: A review” LINK

“Estimation of grain quality parameters in rice for highthroughput screening with nearinfrared spectroscopy and deep learning” LINK




Hyperspectral Imaging (HSI)

“Multispectral camera system design for replacement of hyperspectral cameras for detection of aflatoxin B1” LINK

“Hyperspectral Imaging for cherry tomato” LINK

“A novel 3D convolutional neural network model with supervised spectral regression for recognition of hyperspectral images of colored wool fiber” LINK

“Channel and band attention embedded 3D CNN for model development of hyperspectral image in object-scale analysis” LINK

“A novel high-throughput hyperspectral scanner and analytical methods for predicting maize kernel composition and physical traits” LINK

“Learning Multiscale Temporal-Spatial-Spectral Features via a Multi-path Convolutional LSTM Neural Network for Change Detection with Hyperspectral Images” LINK

“The relationship between the spatial pattern of lakeside wetlands and water quality utilizing UAV hyperspectral remote sensing” LINK

“Building spectral catalogue for salt marsh vegetation, hyperspectral and multispectral remote sensing” LINK

“Hyperspectral Unmixing Based on Nonnegative Matrix Factorization: A Comprehensive Review” LINK

“A systematic review on hyperspectral imaging technology with a machine and deep learning methodology for agricultural applications” LINK

“Using hyperspectral imaging technology for assessing internal quality parameters of persimmon fruits during the drying process” LINK

“Near-Infrared Hyperspectral Imaging Pipelines for Pasture Seed Quality Evaluation: An Overview” | LINK




Chemometrics and Machine Learning

“Chemometrics for Raman Spectroscopy Harmonization” LINK

“Determination of active ingredients in alcoholbased gel by spectroscopic techniques and chemometric analysis” LINK

“Effect of variable selection algorithms on model performance for predicting moisture content in biological materials using spectral data” LINK

Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding project page: sota FID(7.27 on COCO), without ever training on COCO, human raters find Imagen samples to be on par with the COCO data itself in image-text alignment LINK

“Validação prática de modelos de infravermelho próximo para tomate: sólidos solúveis e acidez” LINK




Facts

“Does active sitting provide more physiological changes than traditional sitting and standing workstations?” LINK




Research on Spectroscopy

“Destructive and rapid non-invasive methods used to detect adulteration of dried powdered horticultural products: A review” LINK

“Development of a spectroscopic approach for non-destructive and rapid screening of cucumbers based on maximum limit of nitrate accumulation” LINK




Equipment for Spectroscopy

“Review of portable near infrared spectrometers: Current status and new techniques” LINK

“Discrimination of the Red Jujube Varieties Using a Portable NIR Spectrometer and Fuzzy Improved Linear Discriminant Analysis” | LINK




Process Control and NIR Sensors

“Applied Sciences : Process Monitoring Using Kernel PCA and Kernel Density Estimation-Based SSGLR Method for Nonlinear Fault Detection” LINK

“Distinctive Microbial Processes and Controlling Factors Related to Indirect N2O Emission from Agricultural and Urban Rivers in Taihu Watershed” LINK




Environment NIR-Spectroscopy Application

“Monitoring the Concentrations of Cd, Cu, Pb, Ni, Cr, Zn, Mn and Fe in Cultivated Haplic Luvisol Soils Using Near-Infrared Reflectance Spectroscopy” LINK

“Plants : Variations in Total Phenolic, Total Flavonoid Contents, and Free Radicals’ Scavenging Potential of Onion Varieties Planted under Diverse Environmental Conditions” LINK

“Vis-NIR-spectroscopy-and loss-on-ignition-based functions to estimate organic matter content of calcareous soils” | LINK

“Remote Sensing : Mapping Soil Properties with Fixed Rank Kriging of Proximally Sensed Soil Data Fused with Sentinel-2 Biophysical Parameter” LINK

“Effects of hyperspectral data with different spectral resolutions on the estimation of soil heavy metal content: From ground-based and airborne data to satellite …” LINK

“Comparing Two Different Development Methods of External Parameter Orthogonalization for Estimating Organic Carbon from Field-Moist Intact Soils by Reflectance …” LINK

“Towards recycling of challenging waste fractions: Identifying flame retardants in plastics with optical spectroscopic techniques” LINK




Agriculture NIR-Spectroscopy Usage

“Plants : Comparative Analysis of the NDVI and NGBVI as Indicators of the Protective Effect of Beneficial Bacteria in Conditions of Biotic Stress” LINK

“Agriculture : Online Detection and Classification of Moldy Core Apples by Vis-NIR Transmittance Spectroscopy” LINK

“Aggregate size distribution of arid and semiarid laboratory soils (< 2 mm) as predicted by VIS-NIR-SWIR spectroscopy” LINK

“Application of near-infrared spectroscopy to agriculture and forestry” LINK

“Dry heating, moist heating, and microwave irradiation of coldclimateadapted barley grainEffects on ruminantrelevant carbohydrate and molecular structural spectral profiles” LINK

“Nutrient digestibility and predicting the energy content of pig feeds” LINK

“Comparative study of different wavelength selection methods in the transfer of crop kernel qualitive near-infrared models” LINK

“Agronomy : Monitoring of Nitrogen Indices in Wheat Leaves Based on the Integration of Spectral and Canopy Structure Information” LINK

“… visualization and quantification of total acid and reducing sugar contents in fermented grains by combining spectral and color data through hyperspectral imaging” LINK

“Biomarkers and biosensors for the diagnosis of noncompliant pH, dark cutting beef predisposition, and welfare in cattle” LINK




Forestry and Wood Industry NIR Usage

“A spectral analysis of stem bark for boreal and temperate tree species” | LINK

“Optical properties of transparent wood composites prepared using transverse sections of poplar wood” | LINK




Food & Feed Industry NIR Usage

“Foods : Oxidative Stability and Antioxidant Activity of Selected Cold-Pressed Oils and Oils Mixtures” LINK

“Predicting Single Kernel Moisture and Protein Content of Mushroom Popcorn Using NIR Spectroscopy: Tool for Determining Their Effect on Popping Performance” LINK

“Research on Physicochemical Properties, Microscopic Characterization and Detection of Different Freezing-damaged Corn Seeds” LINK

“Estimating cadmium-lead concentrations in rice blades through fractional order derivatives of foliar spectra” LINK

“Recent advances in emerging techniques for non-destructive detection of seed viability: A review” seedtesting seedGermination seedquality NDT nondestructiveTesting seeds LINK




Laboratory and NIR-Spectroscopy

“Optimizing a Standard Spectral Measurement Protocol to Enhance the Quality of Soil Spectra: Exploration of Key Variables in Lab-Based VNIR-SWIR Spectral …” LINK




Other

“A Robust Functional Partial Least Squares for ScalaronMultipleFunction Regression” LINK

“Planetary Terrestrial Analogues Library Project: 3. Characterization of Samples With MicrOmega” LINK

“LASER-BASED SORTING OF CONSTRUCTION AND DEMOLITION WASTE FOR THE CIRCULAR ECONOMY” LINK

“A robust functional partial least squares for scalaronmultiplefunction regression” LINK

“Facebook trained AI to fool facial recognition systems, and it works on live video” deepfakes deidentification LINK

“Optical properties and novelty preparation PVA/PVP doping with Cu as surface plasmonic ions” LINK





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NIR-Predictor – Frequently Asked Questions (FAQ)


NIR-Predictor – FAQ

Please also refer to the NIR-Predictor – Manual and check the Hints and Notes.


How to Configure / Load / Import / Activate / Setup / Use the Calibrations (*.cm) in NIR-Predictor?

Chapter “Configure the Calibrations for prediction usage” – NIR-Predictor – Manual


Do you have a calibration file for XY ?

We create custom calibrations out of your NIR + Lab measurements of XY.
We do not sell off-the-shelf calibrations.


I have downloaded the software but can’t see it?

Please note, that the download time will be very short, because of the small file size.
Check your browser’s download folder. The download is the file “NIR-PredictorVx.y.zip”


Why a .zip and no installer (Setup.exe) ?

Because a .zip deploy keeps it simple for all:

  • easy : no Administrator rights needed to install, delete it to uninstall
  • harmless : no system changes during setup
  • transparency : you see what you get

Is there a command line (CLI) version of NIR-Predictor ?

If you want to customize it in all details, our OEM API for NIR-instrument-software (White-Label) integration gives you full access. If you are an NIR-Vendor (or similar) please contact us via email info@CalibrationModel.com


The free NIR-Predictor does not create a model, what is wrong ?

As the name says, the NIR-Predictor just predicts NIR data with a model. To create a model you need to send your data to the CalibrationModel service, after development process you get an email with a link to the calibration where it can be purchased and downloaded.


Why does the creation of the PropertyFile.txt take so long with hundrets of spectra files?

It normally takes only 1-10 seconds not minutes.
Make sure that the spectra data files are stored locally on your main drive
and not on a cloud-drive or network storage or slow USB thumb drive or SD-Card.


Is there a way to use converted ASCII spectrum data to be used in NIR-Predictor?

Yes, this is the simplest ASCII CSV file format the NIR-Predictor supports.
And there are other formats supported.


Can you convert old calibration data from vendor A to be integrated to our new vendor B NIRS calibration data in our instrument?

No, we don’t do model or spectra conversion / transformation (aka model transfer).
We build optimized models with wavelength compatible data.


Does NIR-Predictor contain any malware, spyware or adware?

No, NIR-Predictor does not contain any malware, spyware or adware.


How to copy the prediction results from the table in the browser?

Copy selected columns from the table.
By holding down the Ctrl key, rectangular areas in the table can be selected with the mouse and copied to the clipboard with Ctrl+C and then copied to a spreadsheet program with Ctrl+V.


Will an expired calibration still work?

No. Until you extend the usage time.
The expired calibration file will be moved to the CalibrationExpired folder on the next start of NIR-Predictor or “Search and load Calibrations” menu function.

Selected Calibration files from the folder CalibrationExpired can be send to info@CalibrationModel.com with your Request file (.req) files for extending their usage time.

There is the possibility to get a perpetual usage, which means their is no expiration (valid until 2050).

That way you can get the time extended calibration back, that behaves exactly as the one before with extended usage time.


What does the calibration Expiration date mean exactly on the Prediction Report?

The Expiration date, it is the final day when the calibration will be valid (similar to credit cards).


What does the (number) in brackets after the [range] mean?

During the creation of a Calibration Request the NIR-Predictor shows a message containing
” ‘Prop1’ / “Quantitative [1.40 – 2.90] (154) ”
here 154 is the number of unique values in the property range.


How long does it take to create of the property file and calibration request file from 500 spectra files?

Use a local folder on your computer (not a network drive) for your spectra files then the property file and the calibration request file is created in around 1-3 seconds. (measured on a system with SSD drive, Intel i7, 2.4 GHz)


I tried to create the calibration request and got the error message: The number of Property Values of all spectra are different?

Use the generated PropertiesBySpectra (Note: Spectra not Sample) template file.
Do not reformat the generated template file, just fill in the Property values and save as Text CSV (*.csv) file (not as Excel file “.xlsx”).


Are you able to create the calibration if we only have 20 spectra?

To create a reliable quantitative calibration you need measured spectra of at least 48..60 (more is better) different samples with different Lab-values in the required measuring range!
The NIR-Predictor will check for that automatically.


Same sample measured multiple times (replicate measurements), how to enter the Lab-value only once in Property file?

Use the created PropertiesBySample template (not the PropertiesBySpectra).


Different samples with exact the same Lab-value, how to enter the Lab-Values?

Entering the Lab-values into the generated PropertiesBySpectra template the NIR-Predictor detects them as the same Sample and as a result we have too less different values to build a calibration. But in my case these are different samples with exact the same Lab-value, how to do?

You have to cheat a little bit to make NIR-Predictor do not detect same sample as measured multiple times. This is because most NIR users do replicate measurements on the same sample and NIR-Predictor looks for that. In PropertiesBySpectra modify the values a little bit to make them different, e.g.
0.18
0.18001
0.18002


Is the free NIR-Predictor software you provide for anyone to download and use?

Yes, if downloaded directly from our homepage by the user.
See also Software License Agreement


What is an Outlier?

The spectrum is an outlier to the model, if the spectrum is not similar with the spectra and lab-values the model is built with.

The default setting in NIR-Predictor Menu > “Report with Simplified Outlier Symbols”
is ON, that will show only the worst case instead of all combinations to have a simplified minimal information.
if OFF, that will show the combinations (e.g. “XO=” or “XO” or “O=” or “X=”), which is more informative for analyzing problem cases.
See also manual chapter Outliers.


If something is wrong, please tell us