Spectroscopy and Chemometrics News Weekly #22, 2020

NIR Calibration-Model Services

New Free NIR-Predictor V2.6 software is released – Reads and predicts *.spc spectra file format (Thermo-Scientific / Galactic GRAMS) – Spectra Plots on the Prediction Reports NIRS NIR Spectroscopy Spectrometer QualityControl Lab Laboratory Analysis LINK
Spectra Plot

Spectroscopy and Chemometrics News Weekly 21, 2020 | 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 21, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 21, 2020 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK

Near-Infrared Spectroscopy (NIRS)

“NIR spectroscopy application for determination caffeine content of Arabica green bean coffee” LINK

“Review of NIR spectroscopy methods for nondestructive quality analysis of oilseeds and edible oils” LINK

“Omega-3 and Omega-6 Determination in Nile Tilapia’s Fillet Based on MicroNIR Spectroscopy and Multivariate Calibration” LINK

“Determination of metmyoglobin in cooked tan mutton using Vis/NIR hyperspectral imaging system” LINK

“Prediction of water content in Lintong green bean coffee using FT-NIRS and PLS method” LINK

Discrimination of legal and illegal Cannabis spp. according to European legislation using near infrared spectroscopy and chemometrics. LINK

“A system using in situ NIRS sensors for the detection of product failing to meet quality standards and the prediction of optimal postharvest shelf-life in the case of oranges kept in cold storage” LINK

“Estimation of Harumanis (Mangifera indica L.) Sweetness using Near-Infrared (NIR) Spectroscopy” LINK

“Near-Infrared (NIR) Spectroscopy to Differentiate Longissimus thoracis et lumborum (LTL) Muscles of Game Species” LINK

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

“Rapid and Non-destructive Detecting Frying Times of Peanut Oil Based on Near Infrared Reflectance Spectroscopy” LINK

“Different Supervised and unsupervised classification approaches based on Visible/Near infrared spectral analysis for discrimination of microbial contaminated lettuce …” LINK

“Nondestructive determination of lignin content in Korla fragrant pear based on near-infrared spectroscopy” LINK

“Monitoring the Progress and Healing Status of Burn Wounds Using Infrared Spectroscopy” LINK

“Detection of melamine and sucrose as adulterants in milk powder using near-infrared spectroscopy with DD-SIMCA as one-class classifier and MCR-ALS … forensic evidence” LINK

“Differentiating Between Malignant Mesothelioma and Other Pleural Lesions Using Fourier Transform Infrared Spectroscopy” LINK

“Confirmation of brand identification in infant formulas by near-infrared spectroscopy fingerprints” LINK

“Near-infrared spectroscopy of the placenta for monitoring fetal oxygenation during labour.” LINK

“Impact of H2O on atmospheric CH4 measurement in near-infrared absorption spectroscopy.” LINK

“Application of near-infrared hyperspectral imaging to identify a variety of silage maize seeds and common maize seeds” LINK

“Protein, weight, and oil prediction by single-seed near-infrared spectroscopy for selection of seed quality and yield traits in pea (Pisum sativum).” phenotyping LINK

“Multiple-depth Modeling of Soil Organic Carbon using Visible–Near Infrared Spectroscopy” LINK

“Non-Invasive Blood Glucose Monitoring using Near-Infrared Spectroscopy based on Internet of Things using Machine Learning” LINK

“Simultaneous determination of antioxidant properties and total phenolic content of Siraitia grosvenorii by near infrared spectroscopy” LINK

“Rapid quantitative detection of mineral oil contamination in vegetable oil by near-infrared spectroscopy” LINK

“Estimating δ15N and δ13C in Barley and Pea Mixtures Using Near-Infrared Spectroscopy with Genetic Algorithm Based Partial Least Squares Regression” LINK

“Investigating the Quality of Antimalarial Generic Medicines Using Portable Near-Infrared Spectroscopy” LINK


“Protein, weight, and oil prediction by singleseed nearinfrared spectroscopy for selection of seed quality and yield traits in pea (Pisum sativum)” LINK

Raman Spectroscopy

“Raman Technology for Today’s Spectroscopists” LINK

“Diagnosis of Citrus Greening using Raman Spectroscopy-Based Pattern Recognition” LINK

Hyperspectral Imaging (HSI)

“Classification of Hyperspectral Endocrine Tissue Images Using Support Vector Machines.” LINK

“Using dual-channel CNN to classify hyperspectral image based on spatial-spectral information” LINK

“Diagnosis of Late Blight of Potato Leaves Based on Deep Learning Hyperspectral Images” LINK

“Rapid detection of quality index of postharvest fresh tea leaves using hyperspectral imaging.” LINK

“Applied Sciences, Vol. 10, Pages 2259: Hyperspectral Inversion Model of Chlorophyll Content in Peanut Leaves” LINK

“Non-Destructive Detection of Tea Leaf Chlorophyll Content Using Hyperspectral Reflectance and Machine Learning Algorithms” LINK

“Rapid detection of quality index of postharvest fresh tea leaves using hyperspectral imaging” LINK

Chemometrics and Machine Learning

“Rapid detection of saffron (Crocus sativus L.) Adulterated with lotus stamens and corn stigmas by near-infrared spectroscopy and chemometrics” LINK

“Simultaneous quantification of active constituents and antioxidant capability of green tea using NIR spectroscopy coupled with swarm intelligence algorithm” LINK

“Comparison of CNN Algorithms on Hyperspectral Image Classification in Agricultural Lands” LINK

“Molecules, Vol. 25, Pages 1453: Characterization, Quantification and Quality Assessment of Avocado (Persea americana Mill.) Oils” LINK

“Identification of Tea Diseases Based on Spectral Reflectance and Machine Learning” LINK

“Machine learning estimators for the quantity and quality of grass swards used for silage production using drone-based imaging spectrometry and …” LINK

Research on Spectroscopy

“Lanthanide complexes with N-(2, 6-dimethylphenyl) oxamate: Synthesis, characterisation and cytotoxicity” LINK

“Automatisierte und digitale Dokumentation der Applikation organischer Düngemittel” LINK

Equipment for Spectroscopy

“Evaluation of Depth Measurement Method Based on Spectral Characteristics Using Hyperspectrometer” LINK

“Monitoring wine fermentation deviations using an ATR-MIR spectrometer and MSPC charts” LINK

Process Control and NIR Sensors

“Process analytical technology tools for process control of roller compaction in solid pharmaceuticals manufacturing.” LINK

Agriculture NIR-Spectroscopy Usage

“The effect of bubble formation within carbonated drinks on the brewage foamability, bubble dynamics and sensory perception by consumers” LINK

“Rapid Measurement of Soybean Seed Viability Using Kernel-Based Multispectral Image Analysis” LINK

“Remote Sensing, Vol. 12, Pages 1256: Crop Separability from Individual and Combined Airborne Imaging Spectroscopy and UAV Multispectral Data” LINK

“Portable IoT NIR Spectrometer for Detecting Undesirable Substances in Forages of Dairy Farms” LINK

“Hyperspectral imaging using multivariate analysis for simulation and prediction of agricultural crops in Ningxia, China” LINK

“Automatisierte und digitale Dokumentation der Applikation organischer Düngemittel” LINK

Horticulture NIR-Spectroscopy Applications

” Nondestructive determining the soluble solids content of citrus using near infrared transmittance technology combined with the variable selection algorithm” LINK

Food & Feed Industry NIR Usage

“Statistical Analysis of Protein Content in Wheat Germplasm Based on Near-infrared Reflectance Spectroscopy” LINK

“Prediction of infertile chicken eggs before hatching by the Naïve-Bayes method combined with visible near infrared transmission spectroscopy” LINK


“Microsoft lays off journalists to replace them with AI” LINK

NIR-Predictor Download

The free NIR-Predictor software
  • comes with demo data, so you can predict sample spectra with demo calibrations.
  • has no functional limitations, no nagging, no ads and needs no license-key.
  • you need no account and no registration to download and use.
  • runs on Microsoft Windows 10/8/7 (Starter, Basic, Professional) (32 bit / 64 bit).
  • no data is ever transmitted from your local machine. We don’t even collect usage data.
See more Videos

Software Size Date Comment
NIR-Predictor V2.6 (download)

What’s new, see Release Notes

By downloading and/or using the software
you accept the Software License Agreement (EULA)
3.7 MB 1. June 2020 public release

Minimal System Requirements
Windows 7 Starter 32Bit, 1.6 GHz, 2 GB RAM, non-Administrator account

There are no administrator rights required, unpack the zip file to a folder “NIR-Predictor” in your documents or on your desktop.
Read the ReadMe.txt and double click the NIR-Predictor.exe file.

If you have installed an older version of NIR-Predictor then unpack into a different folder a named e.g. “NIR-PredictorVx.y”. All versions can run side-by-side. Copy the Calibrations in use to the new version into the “Calibration” folder. That’s all.

Make sure to backup your reports and calibrations inside your “NIR-Predictor” folder. Delete the “NIR-Predictor” folder.

Start Calibrate

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