Spectroscopy and Chemometrics News Weekly #23, 2021

NIR Calibration-Model Services

9 Reasons why near-Infrared Spectroscopy Applications need periodic Calibration Maintenance | NIR NIRS quality test LINK

Spectroscopy and Chemometrics News Weekly 22, 2021 | 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 22, 2021 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 22, 2021 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK

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Near-Infrared Spectroscopy (NIRS)

” Implementation of Non Destructive FTNIR Method for Quick Estimation of Peanut Quality Based on FFA and Peroxide Value” LINK

“Relating Near-Infrared Light Path-Length Modifications to the Water Content of Scattering Media in Near-Infrared Spectroscopy: Toward a New Bouguer-Beer …” LINK

“PREDICCIÓN DEL CONTENIDO EN HUMEDAD TOTAL EN PELETS DE MADERA MEDIANTE NEAR INFRARED SPECTROSCOPY (NIRS)” LINK

” Discrimination of Fresh Tobacco Leaves with Different Maturity Levels by Near-Infrared (NIR) Spectroscopy and Deep Learning” | LINK

“NIR Spectroscopy Applied to the Oil and Gas Industry” LINK

“New perspective for the in-field analysis of cannabis samples using handheld near-infrared spectroscopy: A case study focusing on the determination of Δ9-tetrahydrocannabinol” | THC NIR UHPLC LINK

“Determination of ethyl octanoate in Chinese liquor using FT-NIR spectroscopy” LINK

“NIRS as a fast screening technique for total nutrients in strawberry leaves and in spent growing media” | LINK

“Estimating the Suitability for the Reintroduced Arabian Oryx (Oryx leucoryx, Pallas 1777) of Two Desert Environments by NIRS-Aided Fecal Chemistry” LINK

“Practical Aspects of Sampling for NIRS Analysis” LINK

“Nondestructive simultaneous prediction of internal browning disorder and quality attributes in ‘Rocha’pear (Pyrus communis L.) using VIS-NIR spectroscopy” LINK

“Application of NIR Spectroscopy to Wood and Wood-Derived Products” LINK

“Preprocessing Methods in NIR Spectroscopy” LINK

“A method for highlighting differences between bacteria grown on nutrient agar using near infrared spectroscopy and principal component analysis” LINK

“Early prediction of the seed yield in winter oilseed rape based on the near-infrared reflectance of vegetation (NIRv)” LINK




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

“User Trust in Assisted Decision-Making Using Miniaturized Near-Infrared Spectroscopy” LINK

“Standards for Near-Infrared Analysis” LINK

“Multi-Way Analysis Coupled with Near-Infrared Spectroscopy in Food Industry: Models and Applications” |LINK

“Measurement of total soluble solids and moisture in puree and dry powder of Kakadu plum (Terminalia ferdinanadiana) samples using hand-held near infrared spectroscopy” LINK

“instrument for near-infrared spectroscopy” LINK

“Assessment of resistance to cavitation in Cordilleran cypress using near-infrared spectroscopy” LINK

“Near Infrared Spectroscopy as a Green Technology for the Quality Prediction of Intact Olives” LINK

“An approach for simultaneous monitoring the content of insensitive agent in the double-base oblate spherical propellant by application of near-infrared spectroscope and partial least squares” LINK

“NearInfrared II Plasmonic Au@AuAg DotinCubic Nanoframes for In Vivo SurfaceEnhanced Raman Spectroscopic Detection and Photoacoustic Imaging” LINK

“Accurate and nondestructive detection of apple brix and acidity based on visible and near-infrared spectroscopy” LINK

“Mineralogy of the far-side lunar surface explored by Chang’E-4 with visible and near-infrared reflectance spectra” LINK

“Innovation in the Meat Industry Using Novel Near-Infrared Spectroscopy Sensors” LINK

“Assessment of the Analytical Performance of Three Near-Infrared Spectroscopy Instruments (Benchtop, Handheld and Portable) through the Investigation of Coriander …” LINK

” Estimation of Andrographolides and Gradation of Andrographis paniculata Leaves Using Near Infrared Spectroscopy Together With Support Vector Machine” LINK




Raman Spectroscopy

“Analysis and Classification of Hepatitis Infections Using Raman Spectroscopy and Multiscale Convolutional Neural Networks” LINK




Hyperspectral Imaging (HSI)

“Measuring the Ripeness of Fruit with Hyperspectral Imaging and Deep Learning” LINK




Chemometrics and Machine Learning

“Classification and Recognition Model of Water Saturation Level of Rock Based on Near-Infrared Spectroscopy” LINK

“Developing a Cloud-based Toolbox for Sensitivity Analysis of a Water Quality Model” LINK

“Prediction performance optimization of different resolution and spectral band ranges for characterizing coco-peat substrate available nitrogen” LINK

” The use of Chemometrics to Discriminate Sample Adulteration in Different Levels: the case of Peruvian Maca” LINK

“An EPSO_CNN Approach to Predict the Soil Texture Properties in Smart Farming” LINK

“Prediction of various soil properties for a national spatial dataset of Scottish soils based on four different chemometric approaches: A comparison of near infrared and mid-infrared spectroscopy” LINK

“Discrimination of menstrual and peripheral blood traces using attenuated total reflection Fourier transform-infrared (ATR FT-IR) spectroscopy and chemometrics for forensic purposes” LINK

“Comparison of partial least squaresdiscriminant analysis and soft independent modeling of class analogy methods for classification of Saccharomyces cerevisiae cells based on midinfrared spectroscopy” LINK

“Development of Stable Amorphous Solid Dispersion and Quantification of Crystalline Fraction of Lopinavir by Spectroscopic-chemometric Methods” LINK

“Predicting Moisture Content During Maize Nixtamalization Using Machine Learning with NIR Spectroscopy” LINK

“Prospective inference of bioprocess cell viability through chemometric modeling of fluorescence multiway data” LINK




Optics for Spectroscopy

“Golden Vaterite as a Mesoscopic Metamaterial for Biophotonic Applications” LINK




Facts

” Introduction to Machine Learning and Internet of Things for Management in Agriculture” LINK




Research on Spectroscopy

“Empirical attributes and limitations of methodologies for predicting the degradability of ruminal protein” LINK

“Chemometryassisted UVspectrophotmetric methods for the simultaneous determination of paritaprevir, ritonavir, and ombitasvir in their combined tablet dosage forms: A comparative study” LINK




Equipment for Spectroscopy

“Single-chain antibody-decorated Au nanocages@liposomal layer nanoprobes for targeted SERS imaging and remote-controlled photothermal therapy of melanoma cancer cells” LINK

” Application of hand-held near-infrared and Raman spectrometers in surface treatment authentication of cork stoppers” LINK




Process Control and NIR Sensors

“Bioprocesses” LINK

“Process Measurements” LINK

“IQR CUSUM charts: An efficient approach for monitoring variations in aquatic toxicity” LINK




Environment NIR-Spectroscopy Application

“Saline and Alkaline Stresses Alter Soil Properties And Composition And Structure of Gene-Based Nitrifier And Denitrifier Communities In A Calcareous Desert Soil” LINK

“Modelling of the adsorption of urea herbicides by tropical soils with an AdaptiveNeuralbased Fuzzy Inference System” LINK




Agriculture NIR-Spectroscopy Usage

” Near infrared reflectance spectroscopy for quantification of crop residue, green manure and catch crop C and N f…” LINK

“Remote Sensing, Vol. 13, Pages 1791: Sentinel-2 Exposed Soil Composite for Soil Organic Carbon Prediction” LINK

“Evaluation of cellulose degrading bacteria isolated from the gut-system of cotton bollworm, Helicoverpa armigera and their potential values in biomass conversion” LINK

“Metabolomic Analysis of Cannabinoid and Essential Oil Profiles in Different Hemp (Cannabis sativa L.) Phenotypes” Plants LINK

“A comprehensive and fast microplastics identification based on near-infrared hyperspectral imaging (HSI-NIR) and chemometrics” LINK

“Rapid and Non-Destructive Monitoring of Moisture Content in Livestock Feed Using a Global Hyperspectral Model” LINK




Horticulture NIR-Spectroscopy Applications

“Fast, simultaneous and contactless assessment of intact mango fruit by means of near infrared spectroscopy” LINK




Forestry and Wood Industry NIR Usage

“Remote Sensing, Vol. 13, Pages 1795: Integrating Spectral and Textural Information for Monitoring the Growth of Pear Trees Using Optical Images from the UAV Platform” LINK




Food & Feed Industry NIR Usage

“Foods, Vol. 10, Pages 1004: Physical and Thermal Evaluation of Olive Oils from Minor Italian Cultivars” LINK

“Using optimized three-band spectral indices to assess canopy N uptake in corn and wheat” LINK

” Spectroscopic analysis of chia seeds” LINK

“The influence of Chemical Contaminants on the Physicochemical Properties of Unifloral and Multifloral Honey from the North-East Region of Romania” Foods LINK

“A Magnetic Food Texture Sensor and Comparison of the Measurement Data of Chicken Nuggets” Sensors LINK




Pharma Industry NIR Usage

“Pharmaceutical Analysis” LINK

“Rapid Detection of Cellulose and Hemicellulose” LINK




Medicinal Spectroscopy

“Photoreactivity of Hair Melanin from Different Skin Phototypes-Contribution of Melanin Subunits to the Pigments Photoreactive Properties” LINK




Other

“Structural, thermal, dielectric, nonlinear optical properties and DFT investigations of a novel material 2-(6-chloropyridin-3-yl)-N’-(2, 3-dihydro-1, 4-benzodioxin-6 …” LINK

“Atomic-scale insights into quantum-order parameters in bismuth-doped iron garnet” LINK

“PV Modules and Their Backsheets — A Case Study of a Multi-MW PV Power Station. (arXiv:2105.05462v1 [cond-mat.mtrl-sci])” 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.
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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),
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  • 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

Installation
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.

Upgrade
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.

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


Start Calibrate

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