Spectroscopy and Chemometrics Machine-Learning News Weekly #31, 2022

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 30, 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 30, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 30, 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)

“Peatlands spectral data influence in global spectral modelling of soil organic carbon and total nitrogen using visible-near-infrared spectroscopy” LINK

“A NIRS Based Device for Identification of Acute Ischemic Stroke by Using a Novel Organic Dye in the Human Blood Serum” | LINK

“Interlacing the evaluation of mechanical properties of mortar cement with near-infrared spectroscopy using multivariate data analysis” LINK

“A Preliminary Study to Classify Corn Silage for High or Low Mycotoxin Contamination by Using near Infrared Spectroscopy” | LINK

“Scalable, NanometerAccurate Fabrication of AllDielectric Metasurfaces with Narrow Resonances Tunable from Near Infrared to Visible Wavelengths” LINK

“A Combined Near-Infrared and Mid-Infrared Spectroscopic Approach for the Detection and Quantification of Glycine in Human Serum” | LINK

“Sensors : Determination of Quality Parameters in Mangetout (Pisum sativum L. ssp. arvense) by Using Vis/Near-Infrared Reflectance Spectroscopy” LINK

“Study on the Effect of Apple Size Difference on Soluble Solids Content Model Based on Near-Infrared (NIR) Spectroscopy” | LINK

“Canopy VIS-NIR spectroscopy and self-learning artificial intelligence for a generalised model of predawn leaf water potential in Vitis vinifera” LINK

“Chemical composition of Andropogon gayanus cv. planaltina predicted through nirs and analyzed through wet chemistry” LINK

“A Preliminary Study to Classify Corn Silage for High or Low Mycotoxin Contamination by Using near Infrared Spectroscopy” LINK

“Model robustness in estimation of blueberry SSC using NIRS” LINK

“Non-invasive Measurement of Blood Sugar Using Near-Infrared Spectroscopy” | LINK

“Investigating the Utility of Near Infrared Reflectance (NIR) Imaging for Diabetic Retinopathy Screening” LINK

“Fourier transform near infrared spectroscopy as a tool to predict spawning status in Alaskan fishes with variable reproductive strategies” LINK

“Prediction of dry matter, carbon and ash contents and identification of Calycophyllum spruceanum (Benth) organs by Near-Infrared Spectrophotometry” LINK

“Determination of aflatoxin B1 value in corn based on Fourier transform near-infrared spectroscopy: Comparison of optimization effect of characteristic …” LINK

“Combining different pre-processing and multivariate methods for prediction of soil organic matter by near infrared spectroscopy (NIRS) in Southern Brazil” LINK

“Evaluation of coating uniformity for the digestion-aid tablets by portable near-infrared spectroscopy” LINK

“Novel strategies in near infrared spectroscopy (NIRS) and multivariate analysis (MVA) for detecting and profiling pathogens and diseases of agricultural importance.” LINK

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

“A highly efficient colloidal quantum dot imager that operates at near-infrared wavelengths” LINK

“Green tea grades identification via Fourier transform near‐infrared spectroscopy and weighted global fuzzy uncorrelated discriminant transform” LINK

“Investigation of oxygen saturation in regions of skin by near infrared spectroscopy” LINK

“Spectral variable selection for estimation of soil organic carbon content using midinfrared spectroscopy” LINK

“Plants : Uptake and Presence Evaluation of Nanoparticles in Cicer arietinum L. by Infrared Spectroscopy and Machine Learning Techniques” LINK

“Electric-field-resolved near-infrared microscopy” LINK

Raman Spectroscopy

“A comparative study based on serum SERS spectra in and on the coffee ring for high precision breast cancer detection” LINK

“Raman spectroscopy and multivariate analysis for identification and classification of pharmaceutical pain reliever tablets” LINK

“Foods : High Precisive Prediction of Aflatoxin B1 in Pressing Peanut Oil Using Raman Spectra Combined with Multivariate Data Analysis” LINK

Hyperspectral Imaging (HSI)

” Identification of pesticide residues on black tea by fluorescence hyperspectral technology combined with machine learning” LINK

“Combining hyperspectral imaging and electrochemical sensing for detection of Pseudomonas aeruginosa through pyocyanin production” LINK

Spectral Imaging

“Open-source mobile multispectral imaging system and its applications in biological sample sensing” LINK

Chemometrics and Machine Learning

“Sensors : A Model for Predicting Cervical Cancer Using Machine Learning Algorithms” LINK

“Application of miniature fiber near infrared spectroscopy combined with chemometrics in predicting antioxidant activity of Sagittaria sagittifolia L …” LINK

“Comparison of Calibration Models for Rapid Prediction of Lignin Content in Lignocellulosic Biomass Based on Infrared and Near-Infrared Spectroscopy” LINK

“Foods : Shelf-Life Prediction and Critical Value of Quality Index of Sichuan Sauerkraut Based on Kinetic Model and Principal Component Analysis” LINK


“Giorgia Stocco Rapid and non-destructive determination of Ca and P in milk using WDXRF” LINK


” A Review of Machine Learning Techniques for Identifying Weeds in Corn” LINK

Research on Spectroscopy

“Syntheses, Structures, and Properties of Coordination Polymers with 2,5-Dihydroxy-1,4-Benzoquinone and 4,4′-Bipyridyl Synthesized by In Situ Hydrolysis Method” LINK

Equipment for Spectroscopy

“Polymers : Combined Strategy of Wound Healing Using Thermo-Sensitive PNIPAAm Hydrogel and CS/PVA Membranes: Development and In-Vivo Evaluation” LINK

Future topics in Spectroscopy

“The Effect of Task Performance and Partnership on Interpersonal Brain Synchrony during Cooperation” LINK

Process Control and NIR Sensors

“Monitoring of dromedary milk clotting process by Urtica dioica extract using fluorescence, near infrared and rheology measurements” LINK

Environment NIR-Spectroscopy Application

“Remote Sensing : Combination of Hyperspectral and Machine Learning to Invert Soil Electrical Conductivity” LINK

“Sensors : Comparative Study on Recognition Models of Black-Odorous Water in Hangzhou Based on GF-2 Satellite Data” LINK

Agriculture NIR-Spectroscopy Usage

“Vis-NIR Spectroscopy and Machine Learning Methods to Diagnose Chemical Properties in Colombian Sugarcane Soils” LINK

“Nutrients : Long-Term Dietary Patterns Are Reflected in the Plasma Inflammatory Proteome of Patients with Inflammatory Bowel Disease” LINK

“Remote Sensing : Hyperspectral UAV Images at Different Altitudes for Monitoring the Leaf Nitrogen Content in Cotton Crops” LINK

“Plants : Integrated Starches and Physicochemical Characterization of Sorghum Cultivars for an Efficient and Sustainable Intercropping Model” LINK

“Remote Sensing : Estimation of Canopy Structure of Field Crops Using Sentinel-2 Bands with Vegetation Indices and Machine Learning Algorithms” LINK

Horticulture NIR-Spectroscopy Applications

“Foods : Physico-Chemical, Textural and Sensory Evaluation of Spelt Muffins Supplemented with Apple Powder Enriched with Sugar Beet Molasses” LINK

Food & Feed Industry NIR Usage

“Warming increase the N2O emissions from wheat fields but reduce the wheat yield in a rice-wheat rotation system” LINK

“Biochemical study of rapid discolouration mechanisms in bison meat” LINK

“Emerging Nondestructive Techniques for the Quality and Safety Evaluation of Pork and Beef: Recent Advances, Challenges and Future Perspectives” LINK

Pharma Industry NIR Usage

“The Conservation of Cloud Pattern-painted Boots (1800-1600 BP) Excavated in Yingpan, Xinjiang” | LINK


“基于 WOS 的高光谱技术在农业方面应用的计量分析” LINK

“Modified Hybrid Strategy Integrating Online Adjustable Oil Property Characterization and Data-Driven Robust Optimization under Uncertainty: Application in Gasoline …” LINK

“Insights into the Effect of Sludge Retention Times on System Performance, Microbial Structure and Quorum Sensing in an Activated Sludge Bioreactor” | LINK

“Diclofenac Ion Hydration: Experimental and Theoretical Search for Anion Pairs” LINK

“Aort cerrahisinde derin ve ılımlı hipotermik antegrad serebral perfüzyonun nörolojik etkileri” LINK

“Vibrational spectroscopic evaluation of hydrophilic or hydrophobic properties of oxide surfaces” 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

Beside the free NIR-Predictor software with Windows user interface,
the real-time Predictor Engine is also available
  • for embedded integration in application, cloud and instrument-software (ICT).
  • As a light-weigt single library file (DLL)
    with application programming interface (API),
    documentation and software development kit (SDK)
    including sample source code (C#).
  • Easy integration and deployment,
    no software license protection (no serial key, no dongle).
  • Put your spectrum as an array into the multivariate predictor,
    no specific file format needed.
  • Fast prediction speed and low latency
    because of compiled code library (direct call, no cloud API).
  • Protected prediction results with outlier detection information.
See NIR Method Development Service for Labs and NIR-Vendors (OEM, White-Label)

Software Size Date Comment
NIR-Predictor V2.6.0.2 (download)

What’s new, see Release Notes

By downloading and/or using the software
you accept the Software License Agreement (EULA)
3.7 MB 18.08.2021 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 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

See also: