Spectroscopy and Chemometrics/Machine-Learning News Weekly #43, 2022Spektroskopie und Chemometrie/Machine-Learning News Wöchentlich #43, 2022Spettroscopia e Chemiometria/Machine-Learning Weekly News #43, 2022

NIR Calibration-Model Services

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

Development of quantitative Multivariate Prediction Models for Near Infrared Analyzers | NIRS NIR NIT SWIR LINK

How to develop near-infrared spectroscopy (NIRS) calibrations in the 21st Century? LINK

Knowledge-Based Variable Selection and Model Selection for near infrared spectroscopy NIRS LINK

Spectroscopy and Chemometrics News Weekly 42, 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 42, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 42, 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)

"Remote Sensing : An Unsupervised Cascade Fusion Network for Radiometrically-Accurate Vis-NIR-SWIR Hyperspectral Sharpening" LINK

"PREDIKSI KANDUNGAN KIMIA KOPRA DENGAN FT-NIR SPECTROSCOPY MENGGUNAKAN PLS" LINK

"Use of Near-Infrared Spectroscopy to Estimate Fiber and Crude Protein Content in Fodders" LINK

"Pengukuran Kandungan Gula pada Tanaman Tebu Secara Non-Destruktif Berbasis Portable NIR Spectroscopy" LINK

"Sequential fixed-fluidized bed foam granulation (SFFBFG) and drying: Multivariate model development for water content monitoring with near-infrared spectroscopy" LINK

"NearInfrared Carbonized Polymer Dots for NIRII Bioimaging" LINK

"Rapid determination of the total content of oleanolic acid and ursolic acid in Chaenomelis Fructus using near-infrared spectroscopy" | LINK

"Pengkajian Ulang Metode Near Infrared (NIR) Spectroscopy Pada Penetapan Kadar Fatty Alcohol Ether Sulfate (FAES) dan Kadar Unsulfated Substance (US) Dalam ..." LINK

"Rapid determination of free amino acids and caffeine in matcha using near-infrared spectroscopy: A comparison of portable and benchtop systems" LINK

"Validating Real-Time Assessment of Alfalfa Nutritive Value Using a Portable NIR Unit" LINK

"Comparing visible-near-infrared spectroscopy with classical regression pedotransfer functions for predicting near-saturated and saturated hydraulic conductivity of ..." LINK

"Origins classification of egg with different storage durations using FT-NIR: A characteristic wavelength selection approach based on information entropy" LINK

"Convenient detection of white pepper adulteration by portable NIRS and spectral imaging with chemometrics" LINK

"Foods : Effects of Variations in the Chemical Composition of Individual Rice Grains on the Eating Quality of Hybrid Indica Rice Based on Near-Infrared Spectroscopy" LINK

"Near infrared spectroscopy (NIRS) coupled with chemometric methods to identify and estimate taxonomic relationships of flies with forensic potential (Diptera: Calliphoridae and Sarcophagidae)" LINK

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

"Study on egg sorting model based on visible-near infrared spectroscopy" LINK

Hyperspectral Imaging (HSI)

"Identification of hybrid tuliptree and parental species by near infrared hyperspectral imaging (NIR-HSI) spectroscopy" |) LINK

"Fusion of spectra and texture data of hyperspectral imaging for prediction of myoglobin content in nitrite-cured mutton" LINK

"Fast and non-destructive discriminating the geographical origin of Hangbaiju by hyperspectral imaging combined with chemometrics" LINK

"Nondestructive classification of soft rot disease in napa cabbage using hyperspectral imaging analysis" | LINK

Chemometrics and Machine Learning

"Artificial neural networks vs partial least squares modelling for rice quality prediction based on NIR spectroscopy" LINK

"Correlation between subcutaneous adipose tissue of the head and body mass index: Implications for functional neuroimaging" LINK

Optics for Spectroscopy

"Recent Advances of Bismuth Halide Based Nanomaterials for Photocatalytic Antibacterial and Photodynamic Therapy" LINK

Research on Spectroscopy

"Development and proof of concept of a novel methodology utilizing contrast enhanced ultrasound to assess perfusion of the costal diaphragm muscle in humans" LINK

Equipment for Spectroscopy

"A near-infrared probe for the real-time detection of lysosomal pH in living cells under "wash free" conditions" LINK

"Comparison of benchtop near infrared and micro near infrared spectrometer for quality control of dried ginger and its different degrees of processed products" | LINK

Environment NIR-Spectroscopy Application

"Remote Sensing : Hyperspectral Remote Sensing Inversion and Monitoring of Organic Matter in Black Soil Based on Dynamic Fitness Inertia Weight Particle Swarm Optimization Neural Network" LINK

Other

"Biosensors : Recent Advances in Silver Nanostructured Substrates for Plasmonic Sensors" LINK

"Non-destructive measurement of total phenolic compounds in Arabidopsis under various stress conditions" | LINK

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NIR Calibration-Model Services

Near-Infrared Spectroscopy (NIRS)

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

"Study on egg sorting model based on visible-near infrared spectroscopy" LINK

Hyperspectral Imaging (HSI)

Chemometrics and Machine Learning

Optics for Spectroscopy

"Recent Advances of Bismuth Halide Based Nanomaterials for Photocatalytic Antibacterial and Photodynamic Therapy" LINK

Research on Spectroscopy

"Development and proof of concept of a novel methodology utilizing contrast enhanced ultrasound to assess perfusion of the costal diaphragm muscle in humans" LINK

Equipment for Spectroscopy

Environment NIR-Spectroscopy Application

"Remote Sensing : Hyperspectral Remote Sensing Inversion and Monitoring of Organic Matter in Black Soil Based on Dynamic Fitness Inertia Weight Particle Swarm Optimization Neural Network" LINK

Other

.

NIR Calibration-Model Services

Near-Infrared Spectroscopy (NIRS)

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

"Study on egg sorting model based on visible-near infrared spectroscopy" LINK

Hyperspectral Imaging (HSI)

Chemometrics and Machine Learning

Optics for Spectroscopy

"Recent Advances of Bismuth Halide Based Nanomaterials for Photocatalytic Antibacterial and Photodynamic Therapy" LINK

Research on Spectroscopy

"Development and proof of concept of a novel methodology utilizing contrast enhanced ultrasound to assess perfusion of the costal diaphragm muscle in humans" LINK

Equipment for Spectroscopy

Environment NIR-Spectroscopy Application

"Remote Sensing : Hyperspectral Remote Sensing Inversion and Monitoring of Organic Matter in Black Soil Based on Dynamic Fitness Inertia Weight Particle Swarm Optimization Neural Network" LINK

Other

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March 14, 2022

Spectroscopy and Chemometrics/Machine-Learning News Weekly #10, 2022Spektroskopie und Chemometrie/Machine-Learning News Wöchentlich #10, 2022Spettroscopia e Chemiometria/Machine-Learning Weekly News #10, 2022

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 9, 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 9, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 9, 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)

"Near-infrared solar reflectance and chromaticity properties of novel green ceramic pigment Cr-doped Y3Al5O12" LINK

"Near-Infrared Spectroscopy (NIRS) as a Method for Biological Sex Discrimination in the Endangered Houston Toad (Anaxyrus houstonensis)" LINK

"Kernel Flow: a high channel count scalable time-domain functional near-infrared spectroscopy system" LINK

"Model Development of Non-Destructive Coffee Beans Moisture Content Determination Using Modified Near Infrared Spectroscopy Instrument" LINK

"Machine Learning Approach Using a Handheld Near-Infrared (NIR) Device to Predict the Effect of Storage Conditions on Tomato Biomarkers" LINK

"Adaptively Optimized Gas Analysis Model with Deep Learning for Near-Infrared Methane Sensors" LINK

"Development of non-invasive blood glucose regression based on near-infrared spectroscopy combined with a deep learning method" LINK

"Assessing the Spectral Characteristics of Dye-and Pigment-Based Inkjet Prints by VNIR Hyperspectral Imaging" LINK

"Fusion of a Low-cost Electronic Nose and Near Infrared Spectroscopy for Qualitative and Quantitative Detection of Beef Adulterated with Duck" LINK

"NEAR INFRARED SPECTROSCOPY (NIRS) COUPLED WITH CHEMOMETRIC TOOLS USED FOR FOOD PRODUCTS ADULTERATION DETECTION" LINK

" A Nondestructive Identification Method of Producing Regions of Citrus Based on Near Infrared Spectroscopy" LINK

"Detecting the content of the bright blue pigment in cream based on deep learning and near-infrared spectroscopy" LINK

"A NIR Study on Hydrogen Bonds of Bamboo-Based Cellulose Ⅱ" LINK

"Vis-NIR Spectra Discriminant of Pesticide Residues on the Hami Melon Surface by GADF and Multi-Scale CNN" LINK

"Pedometric tools for classification of southwestern Amazonian soils: A quali-quantitative interpretation incorporating visible-near infrared spectroscopy" LINK

"... Frozen-Thawed Tuna with Non-Destructive Methods and Classification Models: Bioelectrical Impedance Analysis (BIA), Near-Infrared Spectroscopy (NIR) and Time ..." LINK

"NIRS and Aquaphotomics Trace Robusta-to-Arabica Ratio in Liquid Coffee Blends" LINK

"Effect of Soil Particle Size on Prediction of Soil Total Nitrogen Using Discrete Wavelength NIR Spectral Data" LINK

"Research on Construction of Visible-Near Infrared Spectroscopy Analysis Model for Soluble Solid Content in Different Colors of Jujube" LINK

"A Nondestructive Identification Method of Producing Regions of Citrus Based on Near Infrared Spectroscopy" LINK

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

"Accessing High-Power Near-Infrared Spectroscopy Using Cr3+-Substituted Metal Phosphate Phosphors" LINK

"Can Grassland Chemical Quality Be Quantified Using Transform Near-Infrared Spectroscopy?" LINK

"System Design and Preliminary Analysis of the UQ Near Infrared Spectroscopy Data of the Hayabusa2 Re-entry" LINK

"A fast method to measure the degree of oxidation of dialdehyde celluloses using multivariate calibration and infrared spectroscopy" LINK

" In-Line Identification of Different Grades of GPPS Based on Near-Infrared Spectroscopy" LINK

"Eu2+Doped Layered Double Borate Phosphor with Ultrawide NearInfrared Spectral Distribution in Response to UltravioletBlue Light Excitation" LINK

"Near-Infrared Spectroscopy Applied to the Detection of Multiple Adulterants in Roasted and Ground Arabica Coffee" LINK

Raman Spectroscopy

"RAMANMETRIX: a delightful way to analyze Raman spectra. (arXiv:2201.07586v1 [physics.data-an])" LINK

Hyperspectral Imaging (HSI)

"Rapid and nondestructive determination of sorghum purity combined with deep forest and near-infrared hyperspectral imaging" LINK

"Intraoperative hyperspectral imaging (HSI) as a new diagnostic tool for the detection of cartilage degeneration" | LINK

"Application of Visible/Near-Infrared Hyperspectral Imaging with Convolutional Neural Networks to Phenotype Aboveground Parts to Detect Cabbage Plasmodiophora ..." LINK

"Detection of nutshells in cumin powder using NIR Hyperspectral Imaging and chemometrics tools" LINK

"Gastric Cancer Detection by Two-step Learning in Near-Infrared Hyperspectral Imaging" LINK

"A Spectral and Spatial Attention Network for Change Detection in Hyperspectral Images" LINK

Chemometrics and Machine Learning

"Analysis and classification of peanuts with fungal diseases based on real-time spectral processing" LINK

"Chemometrics: An Excavator in Temperature-Dependent Near-Infrared Spectroscopy" LINK

"PLS-R Calibration Models for Wine Spirit Volatile Phenols Prediction by Near-Infrared Spectroscopy" LINK

"Development and assessment of spectroscopy methodologies and chemometrics strategies to detect pharmaceuticals blend endpoint in a pharmaceutical ..." LINK

"Quick Measurement Method of Condensation Point of Diesel Based on Temperature-Compensation Model" LINK

"Prediction Model of TVB-N Concentration in Mutton Based on Near Infrared Characteristic Spectra" LINK

"Evaluation of a robust regression method (RoBoost-PLSR) to predict biochemical variables for agronomic applications: Case study of grape berry maturity monitoring" LINK

Facts

"Nondestructive internal quality evaluation of pears using X-ray imaging and Machine Learning" LINK

Research on Spectroscopy

"Mechanical-based and Optical-based Methods for Nondestructive Evaluation of Fruit Firmness" | LINK

Equipment for Spectroscopy

"Application of a portable near-infrared spectrometer for rapid, non-destructive evaluation of moisture content in Para rubber timber" | LINK

"The Feasibility of Two Handheld Spectrometers for Meat Speciation Combined with Chemometric Methods and Its Application for Halal Certification" LINK

"Rapid identification of the storage age of dried tangerine peel using a hand-held near infrared spectrometer and machine learning" LINK

"pType NearInfrared Transparent Delafossite Thin Films with Ultrahigh Conductivity" LINK

Agriculture NIR-Spectroscopy Usage

"Agricultural practices of perennial energy crops affect nitrogen cycling microbial communities" LINK

"The Simultaneous Prediction of Soil Properties and Vegetation Coverage from Vis-NIR Hyperspectral Data with a One-Dimensional Convolutional Neural Network: A ..." LINK

"Alginate-enabled green synthesis of S/Ag1. 93S nanoparticles, their photothermal property and in-vitro assessment of their anti-skin-cancer effects augmented by a ..." LINK

"The Relative Performance of a Benchtop Scanning Monochromator and Handheld Fourier Transform Near-Infrared Reflectance Spectrometer in Predicting Forage ..." LINK

"Compact meta-spectral image sensor for mobile applications" | LINK

"Detection of insect damaged rice grains using visible and near infrared hyperspectral imaging technique" LINK

"Terrain analysis, erosion simulations, and sediment fingerprinting: a case study assessing the erosion sensitivity of agricultural catchments in the border of the ..." | LINK

" THE QUALITY OF FRESH AND ENSILED BIOMASS OF Brassica napus oleifera AND PROSPECTS OF ITS USE" LINK

Horticulture NIR-Spectroscopy Applications

"Interactions of Linearly Polarized and Unpolarized Light on Kiwifruit Using Aquaphotomics" LINK

Beverage and Drink Industry NIR Usage

"Beyond Beers Law: Quasi-Ideal Binary Liquid Mixtures" LINK

Other

" From Polymorph Screening to Dissolution Testing" LINK

"Charge and Spin Delocalization in Mixed-Valent Vinylruthenium-Triarylamine-Conjugates with Planarized Triarylamines" LINK

"РАЗРАБОТКА МЕТОДИКИ ВЫЯВЛЕНИЯ ФАЛЬСИФИКАЦИИ ЛЬНЯНОГО МАСЛА МЕТОДОМ БИК-СПЕКТРОСКОПИИ С ПРИМЕНЕНИЕМ ..." LINK

"Bioelectrochemical Partial-Denitrification Coupled with Anammox for Autotrophic Nitrogen Removal" LINK

"Broadband Optical Phase Modulation by Colloidal CdSe Quantum Wells" LINK

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NIR Calibration-Model Services

Near-Infrared Spectroscopy (NIRS)

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

Raman Spectroscopy

"RAMANMETRIX: a delightful way to analyze Raman spectra. (arXiv:2201.07586v1 [physics.data-an])" LINK

Hyperspectral Imaging (HSI)

Chemometrics and Machine Learning

Facts

"Nondestructive internal quality evaluation of pears using X-ray imaging and Machine Learning" LINK

Research on Spectroscopy

"Mechanical-based and Optical-based Methods for Nondestructive Evaluation of Fruit Firmness" | LINK

Equipment for Spectroscopy

Agriculture NIR-Spectroscopy Usage

Horticulture NIR-Spectroscopy Applications

"Interactions of Linearly Polarized and Unpolarized Light on Kiwifruit Using Aquaphotomics" LINK

Beverage and Drink Industry NIR Usage

"Beyond Beers Law: Quasi-Ideal Binary Liquid Mixtures" LINK

Other

.

NIR Calibration-Model Services

Near-Infrared Spectroscopy (NIRS)

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

Raman Spectroscopy

"RAMANMETRIX: a delightful way to analyze Raman spectra. (arXiv:2201.07586v1 [physics.data-an])" LINK

Hyperspectral Imaging (HSI)

Chemometrics and Machine Learning

Facts

"Nondestructive internal quality evaluation of pears using X-ray imaging and Machine Learning" LINK

Research on Spectroscopy

"Mechanical-based and Optical-based Methods for Nondestructive Evaluation of Fruit Firmness" | LINK

Equipment for Spectroscopy

Agriculture NIR-Spectroscopy Usage

Horticulture NIR-Spectroscopy Applications

"Interactions of Linearly Polarized and Unpolarized Light on Kiwifruit Using Aquaphotomics" LINK

Beverage and Drink Industry NIR Usage

"Beyond Beers Law: Quasi-Ideal Binary Liquid Mixtures" LINK

Other

.

June 15, 2020

Spectroscopy and Chemometrics News Weekly #24, 2020Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #24, 2020Spettroscopia e Chemiometria Weekly News #24, 2020

NIR Calibration-Model Services

Machine Learning for NIR Spectroscopy as a Service, a Game Changer for Productivity and Accuracy/Precision! Use the free NIR-Predcitor software to combine NIRS + Lab data and send your Calibration Request. LabManager Analysis MachineLearning LINK

"Food quality digitized at the "speed of light" " : Food Sample -> measured with a NIRS spectrometer -> spectral data -> ⚖️ predicted with a NIRPredictor & CalibrationModel -> % quantitative results -> quality decision -> LINK

Spectroscopy and Chemometrics News Weekly 23, 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 23, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 23, 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)

"Fiber Content Determination of Linen/Viscose Blends Using NIR Spectroscopy" LINK

"Characterization of a high power time-domain NIRS device: towards faster and deeper investigation of biological tissues" LINK

"… chamosite from an hydrothermalized oolitic ironstone (Saint-Aubin-des-Châteaux, Armorican Massif, France): crystal chemistry, Vis-NIR spectroscopy (red variety) and …" LINK

"Study on evolution methods for the optimization of machine learning models based on FT-NIR spectroscopy" LINK

"Vibrational coupling to hydration shell - Mechanism to performance enhancement of qualitative analysis in NIR spectroscopy of carbohydrates in aqueous environment." LINK

" RAPID EVALUATION OF DRY WHITE KIDNEY BEANS COOKING CHARACTERISTICS BY NEAR-INFRARED (NIR) SPECTROSCOPY" LINK

For food analysts, how to choose between a ‘classic’ method and a ‘modern’ technique such as FT-NIR or RMN? Our recently available paper tries to answer that question based on error evaluation: LINK

"FT-NIR combined with chemometrics versus classic chemical methods as accredited analytical support for decision-making: application to chemical compositional compliance of feedingstuffs" LINK

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

"Functional Classification of Feed Items in Pampa Grassland, Based on Their Near-Infrared Spectrum" LINK

"A Rapid and Nondestructive Approach for the Classification of Different-Age Citri Reticulatae Pericarpium Using Portable Near Infrared Spectroscopy" LINK

"Near-infrared spectroscopy as a new method for post-harvest monitoring of white truffles" LINK

"Rapid Prediction of Apparent Amylose, Total Starch, and Crude Protein by Near‐Infrared Reflectance Spectroscopy for Foxtail Millet (Setaria italica)" LINK

"New Induced Mutation Genetic Algorithm for Spectral Variables Selection in Near Infrared Spectroscopy" LINK

"Quantification of Plant Root Species Composition in Peatlands Using FTIR Spectroscopy" LINK

"Functional classification of feed items in pampa grassland, based on their near-infrared spectrum" LINK

"A feasibility of nondestructive rapid detection of total volatile basic nitrogen content in frozen pork based on portable near-infrared spectroscopy" LINK

" Machine Learning Classification of Articular Cartilage Integrity Using Near Infrared Spectroscopy" LINK

"Has the time come to use near-infrared spectroscopy in your science classroom?" LINK

"Feasibility of using near-infrared measurements to detect changes in water quality" LINK

"A novel CC-tSNE-SVR model for rapid determination of diesel fuel quality by near infrared spectroscopy" LINK

"Optimizing analysis of coal property using laser-induced breakdown and near-infrared reflectance spectroscopies" LINK

"Probing Active Sites and Reaction Intermediates of Electrocatalysis Through Confocal Near-Infrared Photoluminescence Spectroscopy: A Perspective." LINK

"Determination of in situ ruminal degradation of phytate phosphorus from single and compound feeds in dairy cows using chemical analysis and near-infrared spectroscopy" LINK

"Non-destructive assessment of moisture content and modulus of rupture of sawn timber Hevea wood using near infrared spectroscopy technique" LINK

"Accurate prediction of glucose concentration and identification of major contributing features from hardly distinguishable near-infrared spectroscopy" LINK

" Multiblock PLS-DA on fecal and plasma visible-near-infrared spectra for discriminating young bulls according to their efficiency. Preliminary results" LINK

"Examining the Utility of Visible Near-Infrared and Optical Remote Sensing for the Early Detection of Rapid ‘Ōhi‘a Death" LINK

"Developing deep learning based regression approaches for determination of chemical compositions in dry black goji berries (Lycium ruthenicum Murr.) using near-infrared hyperspectral …" LINK

" RAPID, NONDESTRUCTIVE AND SIMULTANEOUS PREDICTIONS OF SOIL CONTENT IN WULING MOUNTAIN AREA USING NEAR INFRARED …" LINK

Raman Spectroscopy

"Differentiating cancer cells using Raman spectroscopy (Conference Presentation)" LINK

"Applied Sciences, Vol. 10, Pages 3545: Raman Spectral Analysis for Quality Determination of Grignard Reagent" LINK

"Surfaceenhanced Raman spectroscopy for onsite analysis: A review of recent developments" LINK

Hyperspectral Imaging (HSI)

"Estimating leaf mercury content in Phragmites australis based on leaf hyperspectral reflectance" LINK

"A hyperspectral microscope based on a birefringent ultrastable common-path interferometer (Conference Presentation)" LINK

"Hyperspectral imaging of beet seed germination prediction" LINK

"Hyperspectral imaging for discrimination of Keemun black tea quality categories: Multivariate calibration analysis and data fusion" LINK

"Potential of deep learning and snapshot hyperspectral imaging for classification of species in meat" LINK

"Performance of Fluorescence and Diffuse Reflectance Hyperspectral Imaging for Characterization of Lutefisk: A Traditional Norwegian Fish Dish" LINK

Spectral Imaging

"Identify the ripening stage of avocado by multispectral camera using semi-supervised learning on small dataset" LINK

"Multispectral imaging for predicting the water status in mushroom during hotair dehydration" LINK

Chemometrics and Machine Learning

"Sample selection, calibration and validation of models developed from a large dataset of near infrared spectra of tree leaves" Eucalyptus forage quality LINK

"Determination of Loline Alkaloids and Mycelial Biomass in Endophyte-Infected Schedonorus Pratensis by Near-Infrared Spectroscopy and Chemometrics" LINK

"Detection and Assessment of Nitrogen Effect on Cold Tolerance for Tea by Hyperspectral Reflectance with PLSR, PCR, and LM Models" LINK

"Application of vibrationnal spectroscopy and chemometrics to access the quality of Locally produced antimalarial medicines in the Democratic Republic of Congo." LINK

"Predicting total petroleum hydrocarbons in field soils with VisNIR models developed on laboratoryconstructed samples" LINK

"National spectral data and learning algorithms for potentially toxic elements modelling in forest soil horizons" LINK

"Rapid determination of the textural properties of silver carp (Hypophthalmichthys molitrix) using near-infrared reflectance spectroscopy and chemometrics" LINK

"Vibrational spectroscopy and chemometrics for quantifying key bioactive components of various plum cultivars grown in New Zealand" LINK

Equipment for Spectroscopy

"NearInfrared Multipurpose LanthanideImaging Nanoprobes" LINK

Process Control and NIR Sensors

"Non-invasive measurement of quality attributes of processed pomegranate products" LINK

Environment NIR-Spectroscopy Application

"Spectral Feature Selection Optimization for Water Quality Estimation." LINK

"Remote Sensing, Vol. 12, Pages 931: Optical Water Type Guided Approach to Estimate Optical Water Quality Parameters" LINK

"Estimation of total nitrogen and organic carbon contents in mine soils with NIR reflectance spectroscopy and various chemometric methods" LINK

Agriculture NIR-Spectroscopy Usage

"Development of a compact multimodal imaging system for rapid characterisation of intrinsic optical properties of freshly excised tissue (Conference Presentation)" LINK

"Agriculture, Vol. 10, Pages 181: Grafting and ShadingThe Influence on Postharvest Tomato Quality" LINK

"Remote Sensing, Vol. 12, Pages 940: Editorial for the Special Issue Estimation of Crop Phenotyping Traits using Unmanned Ground Vehicle and Unmanned Aerial Vehicle Imagery"" LINK

"Predicting grain protein content of field-grown winter wheat with satellite images and partial least square algorithm." LINK

"The development of models to predict the nutritional value of feedstuffs and feed mixture using NIRS" LINK

"Permafrost soil complexity evaluated by laboratory imaging Vis‐NIR spectroscopy" LINK

Horticulture NIR-Spectroscopy Applications

"Recent advances in imaging techniques for bruise detection in fruits and vegetables" LINK

Forestry and Wood Industry NIR Usage

"Nutritional characterization of trees from the Amazonian piedmont, Putumayo department, Colombia" LINK

Food & Feed Industry NIR Usage

"Approaches, applications, and future directions for hyperspectral vegetation studies: An emphasis on yieldlimiting factors in wheat" LINK

"Beef Nutritional Quality Testing and Food Packaging" LINK

Laboratory and NIR-Spectroscopy

"UV Irradiation and Near Infrared Characterization of Laboratory Mars Soil Analog Samples: the case of Phthalic Acid, Adenosine 5'-Monophosphate, L-Glutamic Acid …" molecular biosignatures; spectroscopy; lifedetection LINK

Other

LINK

"Effect of substrate temperature on the microstructural and optical properties of RF sputtered grown ZnO thin films" LINK

Using near-infrared light to 3-D print an ear inside the body LINK

"Eco-friendly dye sensitized solar cell using natural dye with solid polymer electrolyte as hole transport material" solarcell LINK

NIR Calibration-Model Services

Near-Infrared Spectroscopy (NIRS)

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

Raman Spectroscopy

Hyperspectral Imaging (HSI)

Spectral Imaging

Chemometrics and Machine Learning

Equipment for Spectroscopy

"NearInfrared Multipurpose LanthanideImaging Nanoprobes" LINK

Process Control and NIR Sensors

"Non-invasive measurement of quality attributes of processed pomegranate products" LINK

Environment NIR-Spectroscopy Application

Agriculture NIR-Spectroscopy Usage

Horticulture NIR-Spectroscopy Applications

"Recent advances in imaging techniques for bruise detection in fruits and vegetables" LINK

Forestry and Wood Industry NIR Usage

"Nutritional characterization of trees from the Amazonian piedmont, Putumayo department, Colombia" LINK

Food & Feed Industry NIR Usage

Laboratory and NIR-Spectroscopy

Other

NIR Calibration-Model Services

Near-Infrared Spectroscopy (NIRS)

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

Raman Spectroscopy

Hyperspectral Imaging (HSI)

Spectral Imaging

Chemometrics and Machine Learning

Equipment for Spectroscopy

"NearInfrared Multipurpose LanthanideImaging Nanoprobes" LINK

Process Control and NIR Sensors

"Non-invasive measurement of quality attributes of processed pomegranate products" LINK

Environment NIR-Spectroscopy Application

Agriculture NIR-Spectroscopy Usage

Horticulture NIR-Spectroscopy Applications

"Recent advances in imaging techniques for bruise detection in fruits and vegetables" LINK

Forestry and Wood Industry NIR Usage

"Nutritional characterization of trees from the Amazonian piedmont, Putumayo department, Colombia" LINK

Food & Feed Industry NIR Usage

Laboratory and NIR-Spectroscopy

Other

June 8, 2020June 8, 2020

Spectroscopy and Chemometrics News Weekly #23, 2020Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #23, 2020Spettroscopia e Chemiometria Weekly News #23, 2020

NIR Calibration-Model Services

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

Plot of predicted Spectra — Spectra Plot

Spectroscopy and Chemometrics News Weekly 22, 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 22, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 22, 2020 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK

This week's NIR news Weekly is sponsored by Your-Company-Name-Here - NIR-spectrometers. Check out their product page ... link

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Near-Infrared Spectroscopy (NIRS)

"Potential of Vis-NIR spectroscopy for detection of chilling injury in kiwifruit" LINK

"The application of NIR spectroscopy in moisture determining of vegetable seeds" LINK

"Detection and quantification of active pharmaceutical ingredients as adulterants in Garcinia cambogia slimming preparations using NIR spectroscopy combined with …" LINK

"Vibrational coupling to hydration shell–Mechanism to performance enhancement of qualitative analysis in NIR spectroscopy of carbohydrates in aqueous environment" LINK

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

"The past, present, and prospective on UV-VIS-NIR skin photonics and spectroscopy-a wavelength guide." LINK

"Differentiation of South African Game Meat Using Near-Infrared (NIR) Spectroscopy and Hierarchical Modelling" LINK

"Study on Detection Methods for Frying Times of Soybean Oil Based on NIRS" LINK

"Non-destructive Detection the Content of Acid Detergent Fiber in Corn Stalk Using NIRS" LINK

"Changes in chemical components with NIR spectroscopy and durability of samama wood treated with boron, methyl methacrylate and heat treatment" LINK

"Principle Component Analysis (PCA)-Classification of Arabica green bean coffee of North Sumatera Using FT–NIRS" LINK

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

"Near-infrared wavelength-selection method based on joint mutual information and weighted bootstrap sampling" LINK

"Rapid and simultaneous analysis of direct and indirect bilirubin indicators in serum through reagent-free visible-near-infrared spectroscopy combined with …" LINK

"Fast Detection Method of Antarctic Krill Meat Quality Based on Near Infrared Spectroscopy" LINK

"Sensors, Vol. 20, Pages 1472: Fusion of Mid-Wave Infrared and Long-Wave Infrared Reflectance Spectra for Quantitative Analysis of Minerals" LINK

"Determination of pectin content in orange peels by Near Infrared Hyperspectral Imaging" LINK

"Near-infrared spectroscopy as a quantitative spasticity assessment tool: A systematic review." LINK

"Determination of nutritional parameters of bee pollen by Raman and infrared spectroscopy." LINK

"Detection of aflatoxin B1 on corn kernel surfaces using visible-near infrared spectroscopy" LINK

"Soil NPK Levels Characterization Using Near Infrared and Artificial Neural Network" LINK

" Estimation of moisture in wood chips by Near Infrared Spectroscopy" LINK

"Biosensors, Vol. 10, Pages 41: Rapid Nondestructive Detection of Water Content and Granulation in Postharvest Shatian Pomelo Using Visible/Near-Infrared Spectroscopy" LINK

"Prognostic value of near-infrared spectroscopy in hypoxic-ischaemic encephalopathy" LINK

Raman Spectroscopy

"Quantitative models for detecting the presence of lead in turmeric using Raman spectroscopy" LINK

Hyperspectral Imaging (HSI)

"Dual-camera design for hyperspectral and panchromatic imaging, using a wedge shaped liquid crystal as a spectral multiplexer" | |)/S/URI LINK

"Discriminative Reconstruction for Hyperspectral Anomaly Detection With Spectral Learning" LINK

"Classification of common recyclable garbage based on hyperspectral imaging and deep learning" LINK

"Based on hyperspectral polarization to build the quantitative remote sensing model of jujube in Southern Xinjiang" LINK

"Study on quality distribution characteristics of jujube canopy based on multi-angle hyperspectral polarization" LINK

"Germination Prediction of Sugar Beet Seeds Based on HSI and SVM-RBF" LINK

Chemometrics and Machine Learning

"ATR-MIR spectroscopy to predict commercial milk major components: A comparison between a handheld and a benchtop instrument" LINK

"Simultaneous determination of goat milk adulteration with cow milk and their fat and protein contents using NIR spectroscopy and PLS algorithms" LINK

"Optimization and comparison of models for prediction of soluble solids content in apple by online Vis/NIR transmission coupled with diameter correction method" LINK

"Building kinetic models for apple crispness to determine the optimal freshness preservation time during shelf life based on spectroscopy" LINK

"Incorporation of two-dimensional correlation analysis into discriminant analysis as a potential tool for improving discrimination accuracy: Near-infrared spectroscopic discrimination of adulterated olive oils." LINK

"Spectroscopic techniques combined with chemometrics for fast on-site characterization of suspected illegal antimicrobials" LINK

Environment NIR-Spectroscopy Application

"Improved mapping of soil heavy metals using a Vis-NIR spectroscopy index in an agricultural area of eastern China" LINK

Agriculture NIR-Spectroscopy Usage

"The Use of Multi-temporal Spectral Information to Improve the Classification of Agricultural Crops in Landscapes" LINK

"Remote Sensing, Vol. 12, Pages 1308: Machine Learning Based On-Line Prediction of Soil Organic Carbon after Removal of Soil Moisture Effect" LINK

"Detection of Nutrition and Toxic Elements in Pakistani Pepper Powders Using Laser Induced Breakdown Spectroscopy" LINK

"Agriculture, Vol. 10, Pages 177: Prediction of Soil Oxalate Phosphorus using Visible and Near-Infrared Spectroscopy in Natural and Cultivated System Soils of Madagascar" LINK

Forestry and Wood Industry NIR Usage

"Linear Discriminant Analysis of spectral measurements for discrimination between healthy and diseased trees of Olea europaea L. artificially infected by Fomitiporia …" LINK

Food & Feed Industry NIR Usage

"Quantification of Ash and Moisture in Wheat Flour by Raman Spectroscopy" LINK

"Visualization accuracy improvement of spectral quantitative analysis for meat adulteration using Gaussian distribution of regression coefficients in hyperspectral …" LINK

Laboratory and NIR-Spectroscopy

"Laboratory-Scale Preparation and Characterization of Dried Extract of Muirapuama (Ptychopetalumolacoides Benth) by Green Analytical Techniques" LINK

Other

"Machine vision detection of pests, diseases, and weeds: A review" LINK

"On-Site Identification of the Material Composition of PV Modules with Mobile Spectroscopic Devices" LINK

"Synthesis of N-Doped ZnO Nanocomposites for Sunlight Photocatalytic Degradation of Textile Dye Pollutants" LINK

.

NIR Calibration-Model Services

Near-Infrared Spectroscopy (NIRS)

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

Raman Spectroscopy

"Quantitative models for detecting the presence of lead in turmeric using Raman spectroscopy" LINK

Hyperspectral Imaging (HSI)

Chemometrics and Machine Learning

Environment NIR-Spectroscopy Application

"Improved mapping of soil heavy metals using a Vis-NIR spectroscopy index in an agricultural area of eastern China" LINK

Agriculture NIR-Spectroscopy Usage

Forestry and Wood Industry NIR Usage

"Linear Discriminant Analysis of spectral measurements for discrimination between healthy and diseased trees of Olea europaea L. artificially infected by Fomitiporia …" LINK

Food & Feed Industry NIR Usage

Laboratory and NIR-Spectroscopy

"Laboratory-Scale Preparation and Characterization of Dried Extract of Muirapuama (Ptychopetalumolacoides Benth) by Green Analytical Techniques" LINK

Other

.

NIR Calibration-Model Services

Near-Infrared Spectroscopy (NIRS)

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

Raman Spectroscopy

"Quantitative models for detecting the presence of lead in turmeric using Raman spectroscopy" LINK

Hyperspectral Imaging (HSI)

Chemometrics and Machine Learning

Environment NIR-Spectroscopy Application

"Improved mapping of soil heavy metals using a Vis-NIR spectroscopy index in an agricultural area of eastern China" LINK

Agriculture NIR-Spectroscopy Usage

Forestry and Wood Industry NIR Usage

"Linear Discriminant Analysis of spectral measurements for discrimination between healthy and diseased trees of Olea europaea L. artificially infected by Fomitiporia …" LINK

Food & Feed Industry NIR Usage

Laboratory and NIR-Spectroscopy

"Laboratory-Scale Preparation and Characterization of Dried Extract of Muirapuama (Ptychopetalumolacoides Benth) by Green Analytical Techniques" LINK

Other

.

March 2, 2020

Spectroscopy and Chemometrics News Weekly #9, 2020Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #9, 2020Spettroscopia e Chemiometria Weekly News #9, 2020

CalibrationModel.com

Efficient development of new quantitative prediction equations for multivariate NIR spectra data NIRS NIR NIT LINK

NIR Calibration Service explained | NIRS NIR Near Infrared Spectroscopy Prediction Analysis Results Calibration Model multivariate Chemometrics equations SaaS LINK

Service für professionelle Entwicklung von Nah-Infrarot Spektroskopie Kalibrations Methoden | NIRS Qualität Prüfen LINK

Spectroscopy and Chemometrics News Weekly 8, 2020 | NIRS NIR Spectroscopy MachineLearning Spectrometer Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory automation Software IoT Sensors QA QC QAQC qualitycontrol LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 8, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot WetChemistry Lab Lab40 FoodTech FoodAnalysis Analysentechnik Analysemethode Nahinfrarotspektroskopie LINK

Spettroscopia e Chemiometria Weekly News 8, 2020 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK

Near Infrared

"Prediction of starch reserves in intact and ground grapevine cane wood tissues using near infrared reflectance spectroscopy (NIRS)." LINK

"An application to analyzing and correcting for the effects of irregular topographies on NIR hyperspectral images to improve identification of moldy peanuts" LINK

"Data Fusion Approach Improves the Prediction of Single Phenolic Compounds in Honey: A Study of NIR and Raman Spectroscopies" LINK

Monitoring roasting of coffee beans by NIR spectroscopy using a method called REP-ASCA coffee ☕️ chemical information related to flavors and aromas. LINK

"The Effect of Light Intensity, Sensor Height, and Spectral Pre-Processing Methods when using NIR Spectroscopy to Identify Different Allergen-Containing Powdered Foods." LINK

"Immediate measurement of fuel characteristics of bio-char using NIRS" LINK

"Nonlinear Manifold Dimensionality Reduction Methods for Quick Discrimination of Tea at Different Altitude by Near Infrared Spectroscopy" LINK

Phenome2020 Yufeng Ge Univ Nebraska VIS-NIR-SWIR spectroscopy to analyse leaf chemistry and physiology LINK

"Rapid assessment of pork freshness using miniaturized NIR spectroscopy" LINK

"On-line prediction of hazardous fungal contamination in stored maize by integrating Vis/NIR spectroscopy and computer vision" LINK

"Chemical Characterization of Wine Vinegars Belonging to the Vinagre de Montilla-Moriles Protected Designation of Origin, Using Near-Infrared Spectroscopy" LINK

"Application of Near-Infrared Spectroscopy for the identification of rock mineralogy from Kos Island, Aegean Sea, Greece" LINK

"Assessment of Spinal Cord Ischemia With Near-Infrared Spectroscopy: Myth or Reality?" LINK

"Portable Near-Infrared spectroscopy for rapid authentication of adulterated paprika powder" LINK

"Study on the Quality Assessment of Canola Oil after Prolonged Frying Using Near-Infrared Spectroscopy" LINK

" CRUDE PROTEIN PREDICTION OF HETEROGENEOUS MOUNTAIN GRASSLAND WITH VISIBLE-NEAR-INFRARED SPECTROSCOPY" LINK

"Statistical Analysis of Amylose and Protein Content in Breeding Line Rice Germplasm Collected from East Asian Countries Based on Near-infrared reflectance …" LINK

"Assessment of pork freshness based on changes in constituting chromophores using visible to near-infrared spectroscopy" LINK

"Sensors, Vol. 20, Pages 273: Near-Infrared Transmittance Spectral Imaging for Nondestructive Measurement of Internal Disorder in Korean Ginseng" LINK

"APPLICATION of NEAR INFRARED SPECTROSCOPY TO DETERMINE SUGARCANE QUALITY in CORE SAMPLER SYSTEM" LINK

Raman

On NationalScienceDay, we celebrate the discovery of the RamanEffect by great scientist CVRaman. Do you know? The Raman effect forms the basis for Raman spectroscopy which is used by chemists & physicists to gain information about materials. LINK

"Handheld device weeds out cannabis from hemp. Raman device that measures levels of tetrahydrocannabinol could be a useful tool for police and customs agents" LINK

Hyperspectral

"Essential processing methods of hyperspectral images of agricultural and food products" LINK

"Determine Reducing Sugar Content in Potatoes Using Hyperspectral Combined with VISSA Algorithm" LINK

"Spatial variation of wood density for Eucalyptus grandis by near infra red hyperspectral imaging combined with X-ray analysis" LINK

Chemometrics

"The detection of cannabinoids in veterinary feeds by microNIR/chemometrics: a new analytical platform." LINK

"Qualitative discrimination of Chinese dianhong black tea grades based on a handheld spectroscopy system coupled with chemometrics" LINK

" Validation of NutriOpt dietary formulation strategies on broiler growth and economic performance" LINK

" A preliminary near infrared spectroscopy calibration for the prediction of un-dried fresh grass quality" LINK

"Water content prediction of 'crystal'guava using visible-near infrared spectroscopy and chemometrics approach" LINK

"Spectroscopy based novel spectral indices, PCA- and PLSR-coupled machine learning models for salinity stress phenotyping of rice." LINK

Facts

"When Will AutoML Replace Data Scientists (if ever)?" MachineLearning Poll LINK

Equipment

"Probeless non-invasive near-infrared spectroscopic bioprocess monitoring using microspectrometer technology" LINK

"Confirmatory non-invasive and non-destructive differentiation between hemp and cannabis using a handheld Raman spectrometer" LINK

"Simple Defocused Fiber Optic Volume Probe for Subsurface Raman Spectroscopy in Turbid Media" LINK

Environment

"Applications of Vis-NIR spectroscopy proximal sensing to estimate and mapping the calcium carbonates (CaCO3) in the semi-arid soils of the Triffa Plain …" LINK

Agriculture

"IJMS, Vol. 21, Pages 408: Genome-Wide Identification of QTLs for Grain Protein Content Based on Genotyping-by-Resequencing and Verification of qGPC1-1 in Rice" LINK

" INFLUENCE OF PLANT SPACING AND GENETIC MATERIAL ON WOOD DENSITY AND STIFFNESS IN Eucalyptus STANDS" LINK

"Comparative data on effects of alkaline pretreatments and enzymatic hydrolysis on bioemulsifier production from sugarcane straw by Cutaneotrichosporon mucoides" LINK

" MODERN STATISTICAL ANALYSIS OF FORAGE QUALITY ASSESSMENT WITH NIR SPECTROSCOPY" LINK

Chemical

" Detection and Separation of Recyclable Plastics from Municipal Solid Waste" | Report.pdf LINK

Other

"Falsified tadalafil tablets distributed in Japan via the internet" LINK

NIR-Predictor – Manual

NIR-Predictor – Manual
Predicting Spectra
Creating your own Calibrations
Configure the Calibrations for prediction usage
Applications
- The use-all case
Prediction Result Report
Enter lab values to NIR spectra
- Entering the laboratory reference values for NIR calibrations
- Create Properties File
Create Calibration Request
- When all is fine
Program Settings
Further References

NIR-Predictor – Manual

Predicting Spectra

It’s easy to use with NIR-Predictor,
just drag & drop your data for getting the prediction results.

It supports an automatic file format detection.
So you don’t need to specify the instrument type and settings! See the list of supported formats and NIR Vendors: NIR-Predictor supported Spectral Data File Formats

Use the included data to checkout how it feels:

Open the demo Spectra folder by using the Menu > Open Demo Spectra or press F8.
There are files with spectra from different Vendors.
Drag & drop a spectra file onto the NIR-Predictor window (or press Ctrl+O as for ’Open some files).
The spectra will be
- loaded
- pre-processed
- predicted and
- reported

Note:
All the steps are fully automatic.
All calibrations that are compatible with the spectra, will produce prediction results in one go.
To select specific calibrations choose the Application. Where the ” ” empty means use all the calibrations.
To define a Application read more in chapter “Applications”

Hint:
To get access to Statistics of Predictions and Reports use the Menu > Show more/less (Ctrl+M) or you can simply resize the window. Here you can also re-do the Analyze step manually with changed inputs (e.g. Result Ordering).

Creating your own Calibrations

How it works – step by step

You have measured your samples with you NIR-Instrument Software.
And got the Lab-values of these samples.

samples
-> measured NIR-spectra
-> Lab-references analytics
Now you need to combine these data.
NIR-spectra + Lab-references
-> PropertiesBySamples

Note: If you combined these data already in your NIR software used,
and you can export it as a JCAMP-DX file then use
Menu > Create Request File .req ... (F2)
and read the “Help.html” and NIR-Predictor JCAMP.
Else proceed as below.

The NIR-Predictor provides tooling for that:

Menu > Create Properties File... (F6)

Select the folder with your NIR spectra measured for an application.
NIR-Predictor creates a customized Properties file template for that data to enter the Lab values.

Note: You don’t need to specify your instrument or vendor or an application. It’s all done automatically. And also the sample spectra are detected and grouped automatically!
Use your favorite editor or spreadsheet program to enter and copy&paste
the Lab-references Values into the columns “Prop1”, “Prop2” etc. and save the file.
A final check of your entered data is done by NIR-Predictor,
to make sure your data ist complete and all is fine.

Menu > Create Calibration Request... (F7)

Select the folder with the filled file.
A CalibrationRequest.zip is created with the necessary data
if enougth diverse Lab values are entered.
Email the CalibrationRequest.zip file
to info@CalibrationModel.com to develop the calibrations.
When your calibrations are ready, you will receive an email with a link
to the CalibrationModel WebShop where
you can purchase and download the calibration files,
that work with our free NIR-Predictor software without internet access.

Note: Your sent NIR data is deleted after processing.
We do not collect your NIR data!

Note: Further details can be found under “Create Properties File” and “Create Calibration Request”.

Configure the Calibrations for prediction usage

Configuration:

in NIR-Predictor : Menu > Open Calibrations (F9)
an explorer window is opened where the calibrations are located
create a folder for your application, choose a name
copy the calibration file(s) (*.cm) into that folder
in NIR-Predictor : Menu > Search and load Applications (F4)

Usage:

in NIR-Predictor : open the Application drop down list, and select your application by name
if all is fine, the calibration file is valid and not expired, it shows : Calibration “1 valid calibation”
the NIR-Predictor is now ready to predict
to switch the application, goto 6.

Applications

The Application concept allows to group multiple Calibrations together for an Application. By selecting an Application before prediction, only the Calibrations belonging to the Application will be used for Prediction. In the Demo Data this is used to have multiple spectrometer as Application. This can be used easily as e.g. as Application “Meat Products” containing Fat and Moisture Calibration.

To create an Application, create a folder with the Application’s name inside the Calibrations folder, and move/copy all the Calibrations files to this Application folder. To remove a Calibration from the Application, remove the Calibration file from the Application folder.

After creating an new Application folder, press menu Search and load Applications (F4) to update the NIR-Predictor dialog where the Application can be selected via the dropdown list. You don’t need to close the NIR-Predictor.

After moving Calibration files around, press menu Search and load Calibrations (F5) to update the NIR-Predictor dialog.

The use-all case

In the NIR-Predictor dialog where the Application can be selected via the dropdown list, the empty "" name means that all (yes all) valid Calibrations will be used for prediction.

Note: The Prediction Report will contain only results from spectral compatible Calibrations with the given spectra. That allows to automatically handle the multi vendor NIR instrument usage.

Prediction Result Report

Histograms of Prediction Values per Property

Shows the distribution of the predicted results per calibration. The histogram range contains the range of the calibrated property and includes the predicted results.

The histogram bar (bin) color is defined as follow:

blue : all predictions inside calibration range.
red : all predictions outside calibration range.
orange : some overlaps with calibration range.
So not all spectra in a orange bin are outside calibration range.

Histograms of Prediction Values — Histograms

Note: Predicted values are always shown in Histogram table and Prediction Value List table, even if the spectrum does not fit into model (spectrum different to model, aka Residual Outlier) shown as Out = X.

Note: Old browsers like Microsoft Internet Explorer 11 don’t support the grafics for Histogram charts. Use an current browser like Firefox or Chrome or Edge.

Note: If your browser opens the report too slow, try to deactivate some browser plugins, because they can filter what you look at and some add-ons are really slow.

Spectra Plot Thumbnail on the Prediction Report

Visualizes the min,median,max spectrum of the spectra dropped as files on the NIR-Predictor. This gives a minimal and good spectral overview of the predicted property results.

Spectra Plot color legend: min,median,max spectrum by predicted property or if no calibration is available by spectral intensity.
The min,median,max is determined from the predicted properties or if not available from the intensity of the spectra.
Beside the histogram of the predicted properties, where the distribution can be seen, the spectra shown are the ones from min,median,max predicted property.
This gives a minimal and good spectral overview of the predicted property results.
The “Spectral Range” and number of datapoints is shown in the Prediction Report Header below the listed spectra files.
To zoom the spectra plot a little, zoom the report in the browser (hold ctrl + mouse wheel, or pinch on touch screen).
The spectra plots and histograms are stored with the report and can be archived.

Note

Note that the spectra are shown in the raw values that are loaded, they are not shown pre-processed as the calibration model uses them to make the prediction.
Note that the median property spectrum is the median from the predicted property pobulation and not the “median” of the calibration property range.
Note that in the multi calibration prediction case, the spectra are selected for each property based on the related predicted property values and so the spectra plots shows typical different spectra.

Outlier Detection

To safeguard the prediction results, outliers are automatically checked for each individual prediction. This is based on limits that are determined when creating the calibration with the base data. Thus, a strange spectral measurement can be detected and signaled as an outlier even without base data only by means of the calibration and the NIR predictor. A prediction result with outlier warning is to be distrusted. How the various outlier tests are interpreted and how to avoid them in practice is described here.

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.

This legend is shown on each NIR-Predictor prediction report below the results:

Outlier (Out) Symbol Description

“X” : spectrum does not fit into model (spectrum different to model)
“O” : spectrum is wide outside model center (spectrum similar to model but far away)
“=” : prediction is outside upper or lower range of model (property outside model range)
“-” : spectrum is incompatible to calibration

Note: A prediction result with outlier warning is to be distrusted.

There are 3 outlier cases (X, O, =) and the incompatible data case “-”.

The bad case is “X”
the medium case is “O”
and the soft case is “=”.

The technical names in literature correspond to:

“X” : Spectral Residual Outlier
“O” : Leverage Outlier
“=” : Property Range Outlier

These 3 outlier cases can appear in combinations, like “XO=” or “XO” or “O=” or “X=”. The more outlier marker are shown the more likely the spectrum is an Outlier.

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.

Some hints to avoid these Outliers:

“X” : spectrum does not fit into model (spectrum different to model)
Check if the spectrum is noise only, or has no proper signal. That can happen when measured past the sample or measured into the air or at a different substance. If you have multiple NIR instruments of the same type, use spectra measured with different instruments for the calibration.
“O” : spectrum is wide outside model center (spectrum similar to model but far away) Sample temperature has an effect on NIR spectra shape, use spectra measured at different (typical use) temperatures (sample temperature, instrument temperature).
“=” : prediction is outside upper or lower range of model (property outside model range)
Use more spectra for the calibration in the Lab value region where your special interest is. If the predicted value is only a little bit out of the calibration range, it can be Ok. Add these spectra to the calibration spectra (with the Lab values), to extend the prediction range of the calibration.
“-” : spectrum is incompatible to calibration
The spectra (from the NIR instrument) has a different wavelength range or a different resolution than the spectra used for calibration. Check Instrument settings (wavelength range, resolution)

Result Ordering

To change the ordering, a drop-down-box is located below the Analyze button. If there is an analysis from the current session, and the Result Ordering is changed, the data is re-Analyzed and reported with the new Result Ordering setting. That allows to compare the different orderings. The Result Ordering is listed in the Prediction Report above the Prediction Value List and stored in the settings.

The order/sorting of the prediction results of the spectra can be defined:

GivenOrder (default) the given order of the spectra from file select dialog or drag&drop

*) sorted : ascending sort

Date_Name sorted by Date (if any) and then by Name
Name_Date sorted by Name and then by Date
Date_NamesWithNumbers sorted by Date (if any) and then by Name with number logic
NamesWithNumbers_Date sorted by Name with number logic (e.g. “ABC1” is before “ABC002” ) and then by Date

*) as above but sorted Rev : reverse sort = descending sort

Rev_Date_Name
Rev_Name_Date
Rev_Date_NamesWithNumbers
Rev_NamesWithNumbers_Date

E.g. with reverse sort by Rev_Date_Name, the newest spectra appear on top.

Print to PDF

Depending on how many calibrations are used the result table is getting broader. To print the report (e.g. to Adobe PDF, FreePDF or Microsoft XPS), sometimes the landscape format is shorter in number of pages or in portrait a scale of 80% fits nicely. Or try another internet browser (Mozilla Firefox, Google Chrome, Microsoft Edge, …) to print the report and set the browser as your default browser so it will be opened by default.

Archiving Reports

Each report is contained in one file only, including the grafics. To save storage space the report file folder can be compressed to a zip file (.zip, .7z).

Enter lab values to NIR spectra

Entering the laboratory reference values for NIR calibrations

We have developed specialized tools into NIR-Predictor to combine the NIR and Lab data is a sample-based safe manner.

The main target is to improve Data Quality during the step of combining of the Lab data and the NIR data, because to model a good reliable calibration the data that build the base needs to be of high quality.

It also simplifies to enter the lab values manually to the corresponding NIR data, because of automatically grouping repeated NIR measurements of the same sample, so the lab values can be entered sample based and not by spectrum.

It helps to avoid false reference data, because of the broken relation of NIR spectra and reference values, data entry on the wrong position in the table.

And Helps to detect errors of duplicated or multiple copies of spectra files, and checks for inconsistencies in Date-Time and Sample-Naming. It also checks for missing values.

That all increases the Data Quality for the next step of Calibration Development, and makes data entry a less time consuming and less risky work.

How it works

Menu > Create Properties File... (F6) select the folder with your NIR spectra measured for an application. NIR-Predictor creates a Properties file template for that data : PropertiesBySamples.csv.txt
Use your favorite editor or spreadsheet program to enter and copy&paste the Lab Values into the columns and save the file.
Menu > Create Calibration Request... (F7) select the folder with the filled file for a last check and a Calibration Request file is created with the needed data as a single zip file.
Email the Calibration Request file to info@CalibrationModel.com to develop the calibrations.

Ok that is it, the NIR-Predictor guides you through the steps needed. And if you need to know more details, the Chapter “Create Properties File” is for you.

Create Properties File

Note:

If you have (exported) JCAMP-DX files containing the Lab-Values, you don’t need to do this step.
You can send the JCAMP file with your Request (.req) file directly to the calibration service at info@CalibrationModel.com.
If your JCAMP-DX files does NOT contain Lab-Values, this is a way to go.

For calibrating the spectra to the lab-values you need to assign the lab-values to the spectra. The easiest way is to have a table where each spectrum (row) is linked to multiple lab-values (columns). This function Create Properties File build such a table for the selected spectra folder automatically!

This table is stored in the file PropertiesBySamples.csv.txt. This can be created for any spectra folder you like. The file extension is .csv.txt to make it easy to edit in a text editor and also in a spreadsheet (excel). The columns are standard TAB separated.

The file header line contains :

Sample Replicates Names Prop1 Prop2 Prop3 DateFirst DateLast Hashes

Where Name and Date describes the spectrum.

Prop1, Prop2, Prop3 are the place to enter the Lab Reference Concentrations properties corresponding to each spectrum. It can be extended to Prop4, Prop5, … etc. Of course you can enter real word names like “Fat (%)” instead of “Prop1”. It’s recommended to put the measurement unit beside the name.

Replicates is the number of replicated or repeated spectra of a sample that is grouped together in the Sample based property file. Sample name and the DateFirst / DateLast between the sample spectra are measured.

Date format is ISO-8601. Missing Dates are 0002-02-02T00:00:00.0000000.

If the file PropertiesBySamples.csv.txt already exist in the selected folder, the user will be notified (it will not be overwritten, because the file may contain user entered Lab-values). The Lab Reference Concentrations values are initialized to 0 (zero) and needed to be changed.

Note: 0 is not interpreted as missing value! If you have a 0 concentration value, put in 0 or 0.0 .

The entry of properties is as easy as possible, because it’s organized by Sample (and not by Spectra), so it’s like your Lab-Value Table that is sample based. The sample rows are sorted in a special way by Sample name. Sorting by Date or alphabetically by Sample can done easily in a spreadsheet program.

Note: when coping lab values to the samples make sure they correspond, so that there are no gaps and the sorting is the same.

The Spectra (rows) are initially sorted by name (and date) to have the replicates/repeats together. You can sort for your convenience in a spreadsheet program.

Enter the Lab Reference Concentrations to the spectra/sample.

Enter the Lab-Values in spreadsheet (e.g. Excel) or a text editor (e.g. Notepad++). If done, use the next menu Create Calibration Request.

Hints: Data handling:

The NIR-Predictor creates the PropertiesBySamples.csv.txt once, after that the user is responsible for its content. That means NIR-Predictor does not change this file anymore.
You can remove entire rows (spectra) in the property file. You don’t need to remove the spectra files. The NIR-Predictor is aware of the relation, the PropertiesBySamples.csv.txt defines what will be calibrated.
How to add more spectra files?
The additional spectra can be handled in a separate folder, create the property file and copy the spectra to the other folder and copy/merge the property files together in your editor or spreadsheet.

Or

Copy the spectra into the folder, rename the PropertiesBySamples.csv.txt to e.g. “PropertiesBySamples-Part1.csv.txt” and use Create Properties File to create a new PropertiesBySamples.csv.txt with all the spectra. You can copy/merge the content of the Properties files together in your editor or spreadsheet.
What happens with possible duplicate rows? It does no harm to the Calibration because we do an exact checking and data cleaning in the calibration process.
What happens to duplicate spectra names? The spectra names are not relevant for the calibration process. The spectra names are helpful to assign the lab-values to the corresponding spectrum entry. That’s why the table is initially sorted by name. The spectra names can be edited by the user.

Create Calibration Request

The menu function Create Calibration Request packs a created Properties file (see “Create Properties File”) and it’s linked spectra files in a compressed ZIP file for sending to the CalibrationModel.com Service.

Please note that the number of measured quantitative samples need to be at least 60 . That means you need at least 60 different spectra (not counting the replicate/repeated measurements).

It shows additional property information about the data you have entered, like – the property type (Quantitative) – it’s range (min – max) and – the number of unique values and – if the Lab-values are enough diverse to get calibrated.

First select the folder with the PropertiesBySamples.csv.txt and measured spectra files of samples you have Lab-values. The data is checked and you get notified what is missing or might be wrong. If something needs to be changed, edit the PropertiesBySamples.csv.txt and do Create Calibration Request again. Your last selected folder is remembered, so you can press return in the folder selection dialog.

Hint: The keyboard shortcuts for redoing it after you edited some entries is : F7 Return – that allows you to get the property information quickly.

Hint: If you open the PropertiesBySamples.csv.txt in a spreadsheet program, you can create Histogram plots of the entered Lab-values, to see in which range are to less samples measurements.

When all is fine

When all is fine the “CalibrationRequest.zip” file is created for that data.

The ZIP file contains:

your PropertiesBySamples.csv.txt
your personal REQuest file for your computer system, that looks like
e.g. “337dcdc06b2d6dfb0b5c4bba578642312edf2ae84d909281624d7e26283e8b07 WIN-GB0PB48GSK4.req”
the spectra data files

Note: If the CalibrationRequest.zip file is already created and you change the PropertiesBySamples.csv.txt make sure to delete the old CalibrationRequest.zip file first! In the dialog it states if it was successfully created or NOT because it already exist. So you are always on the safe side.

Note: CalibrationRequest.zip file name contains the property names to know what would be calibrated and at the end an identification number for referencing the file. E.g. “CalibrationRequest ‘Prop1’ – ‘Prop2’ h31T3wOH.zip”

Program Settings

The users program settings are stored in UserSettings.json
The program counters are stored in GlobalCounters.json

Further References

Data File Formats : NIR-Predictor supported Spectral Data File Formats
Release Notes : NIR-Predictor – Release Notes History
Frequently Asked Questions: NIR-Predictor – FAQ