Spectroscopy and Chemometrics/Machine-Learning News Weekly #19, 2023

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NIR Calibration-Model Services

CalibrationModel is a service that provides the development of customized calibrations from NIR and laboratory data. It allows the use of NIR with your own customized models without the need for chemometric software! LINK

CalibrationModel simplifies the process of training machinelearning models for NIRS data while also providing the opportunity to try out different algorithms and applied knowledge from near-infrared spectroscopy (NIRS) . LINK

With the free NIR-Predictor software, you can use your NIRS calibration files locally and offline. This means you can predict as many NIR data as you want, at full speed without waiting and at no extra cost. LINK

Spectroscopy and Chemometrics News Weekly 18, 2023 | 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 18, 2023 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 18, 2023 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK

Near-Infrared Spectroscopy (NIRS)

“Quantitative and qualitative prediction of sulfur content in diesel by near infrared spectroscopy” LINK

“Near-infrared spectroscopy for early selection of waxy cassava clones via seed analysis” | LINK

“Near infrared spectroscopy discriminates glutinous and non-glutinous sorghum using an approach based on typical samples and direct calibration” LINK

“Classification for GM and Non-GM Maize Kernels Based on NIR Spectra and Deep Learning” | LINK

“Data fusion strategy for rapid prediction of moisture content during drying of black tea based on micro-NIR spectroscopy and machine vision” LINK

“Rapid Classification of Coffee Origin Using Near-Infrared (Nir) Spectroscopy and (Non) Linear Machine Learning” LINK

“A feasibility study on nondestructive classification of frozen Atlantic salmon (Salmo salar) fillets based on temperature history at the logistics using NIR spectroscopy” LINK

“Potential of Near-Infrared Spectroscopy for the Determination of OliveOil quality ” LINK

“Variasi Kualitas Dedak Padi dalam Ransum Sapi Perah dan Pendeteksian Pemalsuan Menggunakan Near Infrared Reflectance Spectroscopy (NIRS).” LINK

“In-Situ Compositional Analysis of Tomato Plants and Cell Wall Using Fiber Optic Fourier Transform Near-Infrared Spectroscopy” LINK

“Prediction models of the nutritional quality of fresh and dry Brachiaria brizantha cv. Piatã grass by near infrared spectroscopy” LINK

“Changes in transcranial near-infrared spectroscopy (NIRS) values reflect changes in cardiac index during cardiac surgery.” LINK

“Geographical Origin Identification and Adulteration Quantification of Ziziphi Spinosae Semen by Using Near Infrared Spectroscopy with Gwo-Svm” LINK

“Development of a CH2-dependent analytical method using Near-Infrared spectroscopy via the integration of two algorithms: Non-dominated Sorting Genetic-II and competitive adaptive reweighted sampling (NSGAII-CARS)” LINK

Raman Spectroscopy

“Biosensors : High-Precision Detection of Cellular Drug Response Based on SERS Spectrum and Multivariate Statistical Analysis” | LINK

Hyperspectral Imaging (HSI)

“Sensors : Single Seed Near-Infrared Hyperspectral Imaging for Classification of Perennial Ryegrass Seed” | LINK

Chemometrics and Machine Learning

“Understanding the compositional changes of organic matter in torrefied olive mill pomace compost using infrared spectroscopy and chemometrics” LINK

” Using a global diversity panel of Cannabis sativa L. to develop a near InfraRed-based chemometric application for cannabinoid quantification” | LINK

“Development of ANN Models for Prediction of Physical and Chemical Characteristics of Oil-in-Aqueous Plant Extract Emulsions Using Near-Infrared Spectroscopy” LINK

“Study of the suitable climate factors and geographical origins traceability of Panax notoginseng based on correlation analysis and spectral images combined with machine learning” | LINK

“Remote Sensing : PSSA: PCA-Domain Superpixelwise Singular Spectral Analysis for Unsupervised Hyperspectral Image Classification” | LINK

“Predicting leaf traits across functional groups using reflectance spectroscopy” LINK

Optics for Spectroscopy

“Analytical Methods for the Identification and Quantitative Determination of Wool and Fine Animal Fibers: A Review” LINK

“Polymeric Photonic Crystal Fibers for Textile Tracing and Sorting” LINK

Facts

“Sensors : UAV Multisensory Data Fusion and Multi-Task Deep Learning for High-Throughput Maize Phenotyping” LINK

Environment NIR-Spectroscopy Application

“Salinity and high pH reduce denitrification rates by inhibiting denitrifying gene abundance in a saline-alkali soil” | LINK

“Remote Sensing : Multi-Angle Detection of Spatial Differences in Tea Physiological Parameters” | LINK

Agriculture NIR-Spectroscopy Usage

“Large-scale screening of diverse barely lignocelluloses for simultaneously upgrading biomass enzymatic saccharification and plant lodging resistance coupled with …” | LINK

“Agriculture : Identification of Constructive Species and Degraded Plant Species in the Temperate Typical Grassland of Inner Mongolia Based on Hyperspectral Data” | LINK

Food & Feed Industry NIR Usage

” Rapid Nondestructive Testing Technology-Based Biosensors for FoodAnalysis” LINK

“Sensors : Spatiotemporal Winter Wheat Water Status Assessment Improvement Using a Water Deficit Index Derived from an Unmanned Aerial System in the North China Plain” | LINK

“Foods : Food Intake of Macro and Trace Elements from Different Fresh Vegetables Taken from Timisoara Market, Romania—Chemometric Analysis of the Results” | LINK

Medicinal Spectroscopy

“Antibiotics : Induction of Endogenous Antimicrobial Peptides to Prevent or Treat Oral Infection and Inflammation” | LINK

Other

“Non-Destructive Study of Egyptian Emeralds Preserved in the Collection of the Museum of the Ecole des Mines” | LINK

Spectroscopy and Chemometrics/Machine-Learning News Weekly #22, 2022Spektroskopie und Chemometrie/Machine-Learning News Wöchentlich #22, 2022Spettroscopia e Chemiometria/Machine-Learning Weekly News #22, 2022

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 21, 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 21, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 21, 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)

"NIRSCAM: A Mobile Near-Infrared Sensing System for Food Calorie Estimation" LINK

"Nutritional Components of Beverage Granules by Near-Infrared Spectroscopy Based on PLS Model" | LINK

"A new concept of acousto-optic tunable filter-based near-infrared hyperspectral imager for planetary surface exploration" LINK

"Supplementary Materials Determination of the Geographical Origin of Walnuts (Juglans regia L.) Using Near-Infrared Spectroscopy and Chemometrics" LINK

"Characteristic wavelengths optimization improved the predictive performance of near-infrared spectroscopy models for determination of aflatoxin B1 in maize" LINK

"DETERMINATION OF QUALITY AND RIPENING STAGES OF 'PACOVAN'BANANAS USING VIS-NIR SPECTROSCOPY AND MACHINE LEARNING" LINK

"Molecules : Identification of Stingless Bee Honey Adulteration Using Visible-Near Infrared Spectroscopy Combined with Aquaphotomics" LINK

"A review of visible and near-infrared (Vis-NIR) spectroscopy application in plant stress detection" LINK

"Predicting the performance of handheld near-infrared photonic sensors from a master benchtop device" LINK

"A novel handheld FT-NIR spectroscopic approach for real-time screening of major cannabinoids content in hemp" LINK

"Chemometric studies of hops degradation at different storage forms using UV-Vis, NIRS and UPLC analyses" LINK

"Comparison of VIS/NIR spectral curves plus RGB images with hyperspectral images for the identification of Pterocarpus species" | LINK

"Etruscan Fine Ware Pottery: Near-Infrared (NIR) Spectroscopy as a Tool for the Investigation of Clay Firing Temperature and Atmosphere" LINK

"Penilaian Sejawat: Fast and contactless assessment of intact mango fruit quality attributes using near infrared spectroscopy (NIRS). IOP EES." | EES Mango Kusumiyati (Gabungan).pdf LINK

"Segregation of 'Hayward'kiwifruit for storage potential using Vis-NIR spectroscopy" LINK

"Portable Near-Infrared Spectroscopy as a Screening Test of Corrosive Solutions Concealed in Plastic Containers" | LINK

"General model of multi-quality detection for apple from different origins by Vis/NIR transmittance spectroscopy" | LINK

"Analytical Chemistry Strategies in the Use of Miniaturised NIR Instruments: An Overview" LINK

"Application of near-infrared spectroscopy to agriculture and forestry" | LINK




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

"NearInfrared LightDriven ThreeDimensional Soft Photonic Crystals Loaded with Upconversion Nanoparticles" LINK

"Gaming behavior and brain activation using functional nearinfrared spectroscopy, Iowa gambling task, and machine learning techniques" LINK

"Metaheuristic algorithms in visible and near infrared spectra to detect excess nitrogen content in tomato plants" LINK




Hyperspectral Imaging (HSI)

"Non-destructive age estimation of biological fluid stains: An integrated analytical strategy based on near-infrared hyperspectral imaging and multivariate regression" LINK

"Prediction of peroxidase activity using near infrared hyperspectral imaging in red delicious apple fruit during storage time" LINK

"Remote Sensing : Detection of Apple Valsa Canker Based on Hyperspectral Imaging" LINK




Spectral Imaging

"Sensors : Sugarcane Nitrogen Concentration and Irrigation Level Prediction Based on UAV Multispectral Imagery" LINK




Chemometrics and Machine Learning

"PENGEMBANGAN MODEL PARTIAL LEAST SQUARE REGRESSION (PLSR) UNTUK MEMPREDIKSI KEASAMAN (pH) DAN KADAR AIR BIJI KAKAO (Theobroma ..." LINK

"Unsupervised detection of ash dieback disease (Hymenoscyphus fraxineus) using diffusion-based hyperspectral image clustering" LINK

"IAI SPECIAL EDITION: Infrared spectroscopy chemometric model for determination of phenolic content of plant leaf powder" LINK

"Sensors : Accuracy and Reproducibility of Laboratory Diffuse Reflectance Measurements with Portable VNIR and MIR Spectrometers for Predictive Soil Organic Carbon Modeling" LINK

"Coatings : Nondestructive Evaluation of Thermal Barrier Coatings Thickness Using Terahertz Technique Combined with PCA-GA-ELM Algorithm" LINK

"Prediction of topsoil organic carbon content with Sentinel-2 imagery and spectroscopic measurements under different conditions using an ensemble model approach ..." LINK




Optics for Spectroscopy

"Artificial Intelligence in Classical and Quantum Photonics" LINK




Research on Spectroscopy

" A dataset for spectral radiative properties of black poly (methyl methacrylate)" LINK




Process Control and NIR Sensors

"Pharmaceutics : Tailoring Rational Manufacturing of Extemporaneous Compounding Oral Dosage Formulations with a Low Dose of Minoxidil" LINK




Environment NIR-Spectroscopy Application

"Polymers : Antioxidant and Anti-Aging Activity of Freeze-Dried Alcohol-Water Extracts from Common Nettle (Urtica dioica L.) and Peppermint (Mentha piperita L.) in Elastomer Vulcanizates" LINK

"Particle densities of cultivated south greenlandic soils can be explained by a threecompartment model, pedotransfer functions, and a visNIR spectroscopy model" LINK




Agriculture NIR-Spectroscopy Usage

"Influence of ingredient quality and diet formulation on amino acid digestibility and growth performance of poultry and swine" LINK

"Guidelines for Optimal Use of NIRSC Forage and Feed Calibrations in Membership Laboratories" LINK

"Linear Support Vector Machine Classification of Plant Stress From Soybean Aphid (Hemiptera: Aphididae) Using Hyperspectral Reflectance" LINK

"Goat milk authentication by one-class classification of digital image-based fingerprint signatures: detection of adulteration with cow milk" LINK

"Agronomy : Crop Monitoring Strategy Based on Remote Sensing Data (Sentinel-2 and Planet), Study Case in a Rice Field after Applying Glycinebetaine" LINK

"Estimation of Vertisols Soil Nutrients by Hyperion Satellite Data: Case Study in Deccan Plateau of India" | LINK

"Real-time milk analysis integrated with stacking ensemble learning as a tool for the daily prediction of cheese-making traits in Holstein cattle" LINK

"The effect of nitrogen fertility rate and seeding rate on yield, nutritive value and economics of forage corn in a low corn heat unit region of Western Canada" LINK




Food & Feed Industry NIR Usage

"Near-infrared techniques for fraud detection in dairy products: A review" | LINK




Laboratory and NIR-Spectroscopy

"Digital technologies to assess yoghurt quality traits and consumers acceptability" LINK




Other

"Tantalum - 2D Light Transport" | optics physically simulation spectroscopy spectrum prism lens mirror light lighttransport multiple scattering LINK

"Characterizing tourniquet induced hemodynamics during total knee arthroplasty using diffuse optical spectroscopy" LINK





.

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 21, 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 21, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 21, 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)

"NIRSCAM: A Mobile Near-Infrared Sensing System for Food Calorie Estimation" LINK

"Nutritional Components of Beverage Granules by Near-Infrared Spectroscopy Based on PLS Model" | LINK

"A new concept of acousto-optic tunable filter-based near-infrared hyperspectral imager for planetary surface exploration" LINK

"Supplementary Materials Determination of the Geographical Origin of Walnuts (Juglans regia L.) Using Near-Infrared Spectroscopy and Chemometrics" LINK

"Characteristic wavelengths optimization improved the predictive performance of near-infrared spectroscopy models for determination of aflatoxin B1 in maize" LINK

"DETERMINATION OF QUALITY AND RIPENING STAGES OF 'PACOVAN'BANANAS USING VIS-NIR SPECTROSCOPY AND MACHINE LEARNING" LINK

"Molecules : Identification of Stingless Bee Honey Adulteration Using Visible-Near Infrared Spectroscopy Combined with Aquaphotomics" LINK

"A review of visible and near-infrared (Vis-NIR) spectroscopy application in plant stress detection" LINK

"Predicting the performance of handheld near-infrared photonic sensors from a master benchtop device" LINK

"A novel handheld FT-NIR spectroscopic approach for real-time screening of major cannabinoids content in hemp" LINK

"Chemometric studies of hops degradation at different storage forms using UV-Vis, NIRS and UPLC analyses" LINK

"Comparison of VIS/NIR spectral curves plus RGB images with hyperspectral images for the identification of Pterocarpus species" | LINK

"Etruscan Fine Ware Pottery: Near-Infrared (NIR) Spectroscopy as a Tool for the Investigation of Clay Firing Temperature and Atmosphere" LINK

"Penilaian Sejawat: Fast and contactless assessment of intact mango fruit quality attributes using near infrared spectroscopy (NIRS). IOP EES." | EES Mango Kusumiyati (Gabungan).pdf LINK

"Segregation of 'Hayward'kiwifruit for storage potential using Vis-NIR spectroscopy" LINK

"Portable Near-Infrared Spectroscopy as a Screening Test of Corrosive Solutions Concealed in Plastic Containers" | LINK

"General model of multi-quality detection for apple from different origins by Vis/NIR transmittance spectroscopy" | LINK

"Analytical Chemistry Strategies in the Use of Miniaturised NIR Instruments: An Overview" LINK

"Application of near-infrared spectroscopy to agriculture and forestry" | LINK




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

"NearInfrared LightDriven ThreeDimensional Soft Photonic Crystals Loaded with Upconversion Nanoparticles" LINK

"Gaming behavior and brain activation using functional nearinfrared spectroscopy, Iowa gambling task, and machine learning techniques" LINK

"Metaheuristic algorithms in visible and near infrared spectra to detect excess nitrogen content in tomato plants" LINK




Hyperspectral Imaging (HSI)

"Non-destructive age estimation of biological fluid stains: An integrated analytical strategy based on near-infrared hyperspectral imaging and multivariate regression" LINK

"Prediction of peroxidase activity using near infrared hyperspectral imaging in red delicious apple fruit during storage time" LINK

"Remote Sensing : Detection of Apple Valsa Canker Based on Hyperspectral Imaging" LINK




Spectral Imaging

"Sensors : Sugarcane Nitrogen Concentration and Irrigation Level Prediction Based on UAV Multispectral Imagery" LINK




Chemometrics and Machine Learning

"PENGEMBANGAN MODEL PARTIAL LEAST SQUARE REGRESSION (PLSR) UNTUK MEMPREDIKSI KEASAMAN (pH) DAN KADAR AIR BIJI KAKAO (Theobroma ..." LINK

"Unsupervised detection of ash dieback disease (Hymenoscyphus fraxineus) using diffusion-based hyperspectral image clustering" LINK

"IAI SPECIAL EDITION: Infrared spectroscopy chemometric model for determination of phenolic content of plant leaf powder" LINK

"Sensors : Accuracy and Reproducibility of Laboratory Diffuse Reflectance Measurements with Portable VNIR and MIR Spectrometers for Predictive Soil Organic Carbon Modeling" LINK

"Coatings : Nondestructive Evaluation of Thermal Barrier Coatings Thickness Using Terahertz Technique Combined with PCA-GA-ELM Algorithm" LINK

"Prediction of topsoil organic carbon content with Sentinel-2 imagery and spectroscopic measurements under different conditions using an ensemble model approach ..." LINK




Optics for Spectroscopy

"Artificial Intelligence in Classical and Quantum Photonics" LINK




Research on Spectroscopy

" A dataset for spectral radiative properties of black poly (methyl methacrylate)" LINK




Process Control and NIR Sensors

"Pharmaceutics : Tailoring Rational Manufacturing of Extemporaneous Compounding Oral Dosage Formulations with a Low Dose of Minoxidil" LINK




Environment NIR-Spectroscopy Application

"Polymers : Antioxidant and Anti-Aging Activity of Freeze-Dried Alcohol-Water Extracts from Common Nettle (Urtica dioica L.) and Peppermint (Mentha piperita L.) in Elastomer Vulcanizates" LINK

"Particle densities of cultivated south greenlandic soils can be explained by a threecompartment model, pedotransfer functions, and a visNIR spectroscopy model" LINK




Agriculture NIR-Spectroscopy Usage

"Influence of ingredient quality and diet formulation on amino acid digestibility and growth performance of poultry and swine" LINK

"Guidelines for Optimal Use of NIRSC Forage and Feed Calibrations in Membership Laboratories" LINK

"Linear Support Vector Machine Classification of Plant Stress From Soybean Aphid (Hemiptera: Aphididae) Using Hyperspectral Reflectance" LINK

"Goat milk authentication by one-class classification of digital image-based fingerprint signatures: detection of adulteration with cow milk" LINK

"Agronomy : Crop Monitoring Strategy Based on Remote Sensing Data (Sentinel-2 and Planet), Study Case in a Rice Field after Applying Glycinebetaine" LINK

"Estimation of Vertisols Soil Nutrients by Hyperion Satellite Data: Case Study in Deccan Plateau of India" | LINK

"Real-time milk analysis integrated with stacking ensemble learning as a tool for the daily prediction of cheese-making traits in Holstein cattle" LINK

"The effect of nitrogen fertility rate and seeding rate on yield, nutritive value and economics of forage corn in a low corn heat unit region of Western Canada" LINK




Food & Feed Industry NIR Usage

"Near-infrared techniques for fraud detection in dairy products: A review" | LINK




Laboratory and NIR-Spectroscopy

"Digital technologies to assess yoghurt quality traits and consumers acceptability" LINK




Other

"Tantalum - 2D Light Transport" | optics physically simulation spectroscopy spectrum prism lens mirror light lighttransport multiple scattering LINK

"Characterizing tourniquet induced hemodynamics during total knee arthroplasty using diffuse optical spectroscopy" LINK





.

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 21, 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 21, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 21, 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)

"NIRSCAM: A Mobile Near-Infrared Sensing System for Food Calorie Estimation" LINK

"Nutritional Components of Beverage Granules by Near-Infrared Spectroscopy Based on PLS Model" | LINK

"A new concept of acousto-optic tunable filter-based near-infrared hyperspectral imager for planetary surface exploration" LINK

"Supplementary Materials Determination of the Geographical Origin of Walnuts (Juglans regia L.) Using Near-Infrared Spectroscopy and Chemometrics" LINK

"Characteristic wavelengths optimization improved the predictive performance of near-infrared spectroscopy models for determination of aflatoxin B1 in maize" LINK

"DETERMINATION OF QUALITY AND RIPENING STAGES OF 'PACOVAN'BANANAS USING VIS-NIR SPECTROSCOPY AND MACHINE LEARNING" LINK

"Molecules : Identification of Stingless Bee Honey Adulteration Using Visible-Near Infrared Spectroscopy Combined with Aquaphotomics" LINK

"A review of visible and near-infrared (Vis-NIR) spectroscopy application in plant stress detection" LINK

"Predicting the performance of handheld near-infrared photonic sensors from a master benchtop device" LINK

"A novel handheld FT-NIR spectroscopic approach for real-time screening of major cannabinoids content in hemp" LINK

"Chemometric studies of hops degradation at different storage forms using UV-Vis, NIRS and UPLC analyses" LINK

"Comparison of VIS/NIR spectral curves plus RGB images with hyperspectral images for the identification of Pterocarpus species" | LINK

"Etruscan Fine Ware Pottery: Near-Infrared (NIR) Spectroscopy as a Tool for the Investigation of Clay Firing Temperature and Atmosphere" LINK

"Penilaian Sejawat: Fast and contactless assessment of intact mango fruit quality attributes using near infrared spectroscopy (NIRS). IOP EES." | EES Mango Kusumiyati (Gabungan).pdf LINK

"Segregation of 'Hayward'kiwifruit for storage potential using Vis-NIR spectroscopy" LINK

"Portable Near-Infrared Spectroscopy as a Screening Test of Corrosive Solutions Concealed in Plastic Containers" | LINK

"General model of multi-quality detection for apple from different origins by Vis/NIR transmittance spectroscopy" | LINK

"Analytical Chemistry Strategies in the Use of Miniaturised NIR Instruments: An Overview" LINK

"Application of near-infrared spectroscopy to agriculture and forestry" | LINK




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

"NearInfrared LightDriven ThreeDimensional Soft Photonic Crystals Loaded with Upconversion Nanoparticles" LINK

"Gaming behavior and brain activation using functional nearinfrared spectroscopy, Iowa gambling task, and machine learning techniques" LINK

"Metaheuristic algorithms in visible and near infrared spectra to detect excess nitrogen content in tomato plants" LINK




Hyperspectral Imaging (HSI)

"Non-destructive age estimation of biological fluid stains: An integrated analytical strategy based on near-infrared hyperspectral imaging and multivariate regression" LINK

"Prediction of peroxidase activity using near infrared hyperspectral imaging in red delicious apple fruit during storage time" LINK

"Remote Sensing : Detection of Apple Valsa Canker Based on Hyperspectral Imaging" LINK




Spectral Imaging

"Sensors : Sugarcane Nitrogen Concentration and Irrigation Level Prediction Based on UAV Multispectral Imagery" LINK




Chemometrics and Machine Learning

"PENGEMBANGAN MODEL PARTIAL LEAST SQUARE REGRESSION (PLSR) UNTUK MEMPREDIKSI KEASAMAN (pH) DAN KADAR AIR BIJI KAKAO (Theobroma ..." LINK

"Unsupervised detection of ash dieback disease (Hymenoscyphus fraxineus) using diffusion-based hyperspectral image clustering" LINK

"IAI SPECIAL EDITION: Infrared spectroscopy chemometric model for determination of phenolic content of plant leaf powder" LINK

"Sensors : Accuracy and Reproducibility of Laboratory Diffuse Reflectance Measurements with Portable VNIR and MIR Spectrometers for Predictive Soil Organic Carbon Modeling" LINK

"Coatings : Nondestructive Evaluation of Thermal Barrier Coatings Thickness Using Terahertz Technique Combined with PCA-GA-ELM Algorithm" LINK

"Prediction of topsoil organic carbon content with Sentinel-2 imagery and spectroscopic measurements under different conditions using an ensemble model approach ..." LINK




Optics for Spectroscopy

"Artificial Intelligence in Classical and Quantum Photonics" LINK




Research on Spectroscopy

" A dataset for spectral radiative properties of black poly (methyl methacrylate)" LINK




Process Control and NIR Sensors

"Pharmaceutics : Tailoring Rational Manufacturing of Extemporaneous Compounding Oral Dosage Formulations with a Low Dose of Minoxidil" LINK




Environment NIR-Spectroscopy Application

"Polymers : Antioxidant and Anti-Aging Activity of Freeze-Dried Alcohol-Water Extracts from Common Nettle (Urtica dioica L.) and Peppermint (Mentha piperita L.) in Elastomer Vulcanizates" LINK

"Particle densities of cultivated south greenlandic soils can be explained by a threecompartment model, pedotransfer functions, and a visNIR spectroscopy model" LINK




Agriculture NIR-Spectroscopy Usage

"Influence of ingredient quality and diet formulation on amino acid digestibility and growth performance of poultry and swine" LINK

"Guidelines for Optimal Use of NIRSC Forage and Feed Calibrations in Membership Laboratories" LINK

"Linear Support Vector Machine Classification of Plant Stress From Soybean Aphid (Hemiptera: Aphididae) Using Hyperspectral Reflectance" LINK

"Goat milk authentication by one-class classification of digital image-based fingerprint signatures: detection of adulteration with cow milk" LINK

"Agronomy : Crop Monitoring Strategy Based on Remote Sensing Data (Sentinel-2 and Planet), Study Case in a Rice Field after Applying Glycinebetaine" LINK

"Estimation of Vertisols Soil Nutrients by Hyperion Satellite Data: Case Study in Deccan Plateau of India" | LINK

"Real-time milk analysis integrated with stacking ensemble learning as a tool for the daily prediction of cheese-making traits in Holstein cattle" LINK

"The effect of nitrogen fertility rate and seeding rate on yield, nutritive value and economics of forage corn in a low corn heat unit region of Western Canada" LINK




Food & Feed Industry NIR Usage

"Near-infrared techniques for fraud detection in dairy products: A review" | LINK




Laboratory and NIR-Spectroscopy

"Digital technologies to assess yoghurt quality traits and consumers acceptability" LINK




Other

"Tantalum - 2D Light Transport" | optics physically simulation spectroscopy spectrum prism lens mirror light lighttransport multiple scattering LINK

"Characterizing tourniquet induced hemodynamics during total knee arthroplasty using diffuse optical spectroscopy" LINK





.

Digitization in the field of NIR spectroscopy (smart sensors) / Digitalisierung im Bereich der NIR-Spektroskopie / Digitalizzazione nel campo della spettroscopia NIR (sensori intelligenti)

Digitalization is advancing, also in NIR spectroscopy, which enables trainable miniature smart sensors e.g. for analyses in the food&feed, chemical and pharmaceutical sectors.

The calibration is the core of a NIR spectroscopy sensor, it enables the numerous applications and should therefore not be the weakest link in the measurement chain.

The development of calibrations that turn NIR spectrometers into smart sensors is done manually by experts (NIR specialist, chemometrician, data scientist) with so-called chemometrics software.

This is very time-consuming (time to market) and the result is person-dependent and thus suboptimal, because each expert has his own preferred way of proceeding.
In addition, the calibrations have to be maintained, as new data has been collected in the meantime, which can be used to extend and improve the calibrations.

This is where our automated service comes in, combining the knowledge and good practices of NIR spectroscopy and chemometrics collected in one software and using machine learning to generate optimal calibrations.

Based on this, we have developed a complete technology platform (Time to Market) that covers the entire process from sending NIR + Lab data, to NIR Calibration as a Service, from online purchase of calibrations, to NIR Predictor software that directly evaluates newly measured NIR data locally and generates result reports.

Besides the free desktop version with user interface, the NIR Predictor can also be integrated (OEM). This can be integrated in parallel as a complement to your current Predictor, allowing the user to choose how they want to calibrate.
And give them the advantage in NIR feasibility studies and NIR spectrometer evaluations to quickly provide the customer with a solid and accurate calibration that will make their NIR system deliver better results.

Advantages for your NIR users (internal or external)

  • no initial costs (no chemometrics software license required),
  • calculable operating costs (fixed amount instead of time and hourly rate) (calibration development, calibration maintenance)
  • easy to use (no chemometrics and software training),
  • quicker to use (no calibration development work) and
  • better calibrations (precision, accuracy, robustness, ...)

Our chargeable service is based on the calibration development and the annual calibration use.
Calibration development and calibration use can also be carried out separately (manufacturer / user).

For you as a spectrometer manufacturer, this means that you can deliver your system pre-calibrated for certain applications without incurring software license costs. And without your application specialists having to provide additional calibration services.

The unique advantages of our calibration service together with the free NIR Predictor are:

  • no software license costs (chemometrics software, predictor software, OEM integration)
  • no chemometrics know-how necessary
  • no time needed to develop optimal NIR calibrations.

If interested in using/evaluating the service :

About CalibrationModel.com : Time and knowledge intensive creation and optimization of chemometric evaluation methods for spectrometers as a service to enable more accurate analysis and measurement results.

see also

Paradigm Change in NIR

Five Mistakes to avoid on Digitalization in NIR

NIR - Total cost of ownership (TCO)

OEM / White Label Software

White Paper


Die Digitalisierung schreitet voran, so auch in der NIR-Spektroskopie, die trainierbare miniatur Smart-Sensors ermöglicht z.B. für Analysen im Bereich Food&Feed, Chemie und Pharma.

Die Kalibration ist das Kernstück eines NIR-Spektroskopie Sensors, sie ermöglicht die zahlreichen Applikationen und sollte darum nicht das schwächste Glied in der Messkette sein.

Das Entwickeln von Kalibrationen die NIR-Spektrometer zu Smart-Sensoren macht, wird bis an hin von Experten (NIR-Spezialist, Chemometriker, Data Scientist) manuell gemacht mit sogenannter Chemometrie Software.

Das ist sehr zeitintensiv (Time to Market) und das Ergebnis ist personenabhängig und somit suboptimal, denn jeder Experte hat seine eigene bevorzugte Weise wie er vorgeht.
Dazu kommt, dass die Kalibrationen gewartet werden müssen, da in der Zwischenzeit neue Daten gesammelt wurden, die zur Erweiterung und Verbesserung der Kalibrationen genutzt werden kann.

Hier setzt unser automatisierter Service an, der das Wissen und Good-Practices der NIR-Spektroskopie und Chemometrie gesammelt in einer Software vereint und mittels Machine-Learning optimale Kalibrationen erzeugt.

Wir haben darauf aufbauend eine komplette Technologie-Plattform entwickelt (Time to Market), die den ganzen Ablauf vom Senden der NIR + Lab Daten, zu NIR-Kalibration as a Service, vom Online-Kauf der Kalibrationen, bis hin zur NIR-Predictor Software die neu gemessene NIR Daten direkt lokal auswertet und Ergebnis Reports erstellt.

Nebst der freien Desktop Variante mit User Interface kann der NIR-Predictor auch integriert werden (OEM). Das kann parallel als Ergänzung zu ihrem jetzigen Predictor integriert werden und so dem Anwender die Wahl ermöglichen, wie er Kalibrieren möchte.
Und ihnen so den Vorteil verschaffen, bei NIR Feasibility Studies und NIR-Spektrometer Evaluationen, dem Kunden rasch eine solide und genaue Kalibration bereitzustellen, die ihr NIR System bessere Ergebnisse liefern lässt.

Vorteile für ihre NIR-Anwender (intern oder extern)

  • keine Initial-Kosten (keine Chemometrie Software Lizenz nötig),
  • kalkulierbare Betriebs Kosten (fix Betrag statt nach Aufwand und Stundensatz) (Kalibrationsentwicklung, Kalibrations-Pflege)
  • einfach Anwendbar (keine Chemometrie- und Software-Trainings),
  • schneller Einsatzbereit (keine Kalibrations-Entwicklungs Arbeit) und
  • bessere Kalibrationen (precision, accuracy, robustness, …)

Unsere kostenpflichtige Serviceleistung beruht auf der Kalibrationsentwicklung und der jährlichen Kalibrationsnutzung.
Dabei kann die Kalibrationsentwicklung und Kalibrationsnutzung auch getrennt voneinander (Hersteller / User) erfolgen.

Für Sie als Spektrometer Hersteller kommt so die Möglichkeit hinzu, dass Sie für bestimmte Applikationen ihr System Vorkalibriert ausliefern können, ohne dass Software-Lizenz-Kosten fällig werden. Und ohne dass ihre Applikations-Spezialisten zusätzliche Kalibrationsleistung erbringen müssen.

Die einzigartigen Vorteile unseres Calibrations-Service zusammen mit dem free NIR-Predictor sind:

  • keine Software Lizenz Kosten (Chemometrie Software, Predictor Software, OEM integration)
  • kein Chemometrie Know-How nötig
  • kein Zeitaufwand nötig um optimale NIR-Kalibrationen zu entwickeln.

Bei Interesse zur Nutzung/Evaluation des Services :

Über CalibrationModel.com : Zeit- und Wissens-intensive Erstellung und Optimierung von chemometrischen Auswertemethoden für Spektrometer als Service, um präzisere Analysen- und Messergebnisse zu ermöglichen.

see also

Paradigm Change in NIR

Five Mistakes to avoid on Digitalization in NIR

NIR - Total cost of ownership (TCO)

OEM / White Label Software

White Paper


La digitalizzazione sta progredendo, anche nella spettroscopia NIR, che consente l'uso di sensori intelligenti in miniatura addestrabili, ad esempio per analisi nei settori alimentare e dei mangimi, chimico e farmaceutico.

La calibrazione è il cuore di un sensore di spettroscopia NIR, consente le numerose applicazioni e non dovrebbe quindi essere l'anello più debole della catena di misura.

Lo sviluppo delle calibrazioni che trasformano gli spettrometri NIR in sensori intelligenti viene effettuato manualmente da esperti (specialista NIR, chemiometrista, scienziato dei dati) con il cosiddetto software di chemiometria.

Ciò richiede molto tempo (time to market) e il risultato dipende dalla persona ed è quindi subottimale, perché ogni esperto ha il suo modo di procedere preferito.
Inoltre, le calibrazioni devono essere mantenute, poiché nel frattempo sono stati raccolti nuovi dati che possono essere utilizzati per ampliare e migliorare le calibrazioni.

Qui entra in gioco il nostro servizio automatizzato, che combina le conoscenze e le buone pratiche della spettroscopia NIR e della chemiometria in un unico software e genera calibrazioni ottimali mediante l'apprendimento automatico.

Su questa base, abbiamo sviluppato una piattaforma tecnologica completa (Time to Market), che copre l'intero processo dall'invio dei dati NIR + Lab, alla calibrazione NIR come servizio, dall'acquisto online delle calibrazioni, al software NIR Predictor, che valuta direttamente i dati NIR appena misurati a livello locale e genera rapporti sui risultati.

Oltre alla versione desktop gratuita con interfaccia utente, il NIR Predictor può essere integrato (OEM). Questo può essere integrato in parallelo come complemento al vostro Predictor attuale, permettendo all'utente di scegliere come vuole calibrare.
Questo vi offre il vantaggio negli studi di fattibilità NIR e nelle valutazioni degli spettrometri NIR per fornire rapidamente al cliente una calibrazione solida e accurata che farà sì che il vostro sistema NIR fornisca risultati migliori.

Vantaggi per i vostri utenti NIR (interni o esterni)

  • nessun costo iniziale (non è necessaria la licenza del software di chemiometria),
  • costi operativi calcolabili (importo fisso anziché tariffa oraria) (sviluppo della taratura, manutenzione della taratura)
  • facile da usare (nessuna chemiometria e formazione software),
  • più veloce da usare (nessun lavoro di sviluppo di calibrazione) e
  • calibrazioni migliori (precisione, accuratezza, robustezza, ...)

Il nostro servizio a pagamento si basa sullo sviluppo della taratura e sull'utilizzo annuale della taratura.
Lo sviluppo della taratura e l'uso della taratura possono essere effettuati anche separatamente (produttore/utente).

Per voi, in qualità di produttori di spettrometri, ciò significa che potete fornire il vostro sistema pre-calibrato per determinate applicazioni senza incorrere in costi di licenza del software. E senza che i vostri specialisti delle applicazioni debbano fornire ulteriori servizi di taratura.

I vantaggi unici del nostro servizio di calibrazione insieme al predittore NIR Predictor gratuito sono:

  • nessun costo di licenza software (software di chemiometria, software di previsione, integrazione OEM)
  • non è necessario alcun know-how in chemiometria
  • non c'è bisogno di tempo per sviluppare calibrazioni NIR ottimali.

Se interessati all'uso/valutazione del servizio :

Informazioni su CalibrationModel.com : Creazione e ottimizzazione dei metodi di valutazione chemiometrica per gli spettrometri come servizio per consentire analisi e risultati di misura più precisi.

see also

Paradigm Change in NIR

Five Mistakes to avoid on Digitalization in NIR

NIR - Total cost of ownership (TCO)

OEM / White Label Software

White Paper

Spectroscopy and Chemometrics News Weekly #49, 2020Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #49, 2020Spettroscopia e Chemiometria Weekly News #49, 2020

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 48, 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 48, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 48, 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 of natural medicines supported by novel instrumentation and methods for data analysis and interpretation" LINK

"A fast determination of insecticide deltamethrin by spectral data fusion of UV-vis and NIR based on extreme learning machine" LINK

"Assessing Laser Cleaning of a Limestone Monument by Fiber Optics Reflectance Spectroscopy (FORS) and Visible and Near-Infrared (VNIR) Hyperspectral Imaging …" LINK

"Near infrared spectroscopy combined with chemometrics to detect and quantify adulteration of maca powder " LINK

"Potential of smartphone-coupled micro NIR spectroscopy for quality control of green tea" LINK

"APPLICATION OF VIS–NIR HYPERSPECTRAL IMAGING FOR PREDICTION OF FLAVONOIDS, ANTHOCYANINS AND SOLUBLE SOLIDS CONTENT IN ..." LINK




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

"Determination of Adenosine and Cordycepin Concentrations in Cordyceps militaris Fruiting Bodies Using Near-Infrared Spectroscopy." LINK

"… : Prediction of α-Lactalbumin and β-Lactoglobulin Composition of Aqueous Whey Solutions Using Fourier Transform Mid-Infrared and Near-Infrared Spectroscopy" LINK

"The Effect of Freeze-Drying Pretreatment on the Accuracy of Near Infrared Spectroscopic Food Analysis to Predict the Nutritive Values of Japanese Cooked Foods" LINK

"Estimating hardness and density of wood and charcoal by near-infrared spectroscopy" LINK

"Assessing the interaction between drying and addition of maltodextrin to Kakadu plum powder samples by two dimensional and near infrared spectroscopy" LINK

"Near-infrared Spectroscopy and Hyperspectral Imaging for Sugar Content Evaluation in Potatoes over Multiple Growing Seasons" LINK

"Determination of radial profiles of wood properties using a near infrared scanning system" LINK

"FTIR combined with chemometric tools (Fingerprinting spectroscopy) in comparison to HPLC; Which strategy offers more opportunities as a green analytical chemistry technique for the pharmaceutical analysis" LINK

"Prediction of high-biomass sorghum quality using near infrared spectroscopy to monitoring calorific value, moisture, and ash content." LINK




Raman Spectroscopy

"Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy" LINK




Hyperspectral Imaging (HSI)

"Hyperspectral Imaging for Minced Meat Classification Using Nonlinear Deep Features" LINK

"Monitoring microstructural changes and moisture distribution of dry-cured pork-A combined confocal laser scanning microscopy and hyperspectral imaging study." LINK

"Monitoring Urban Black-Odorous Water by Using Hyperspectral Data and Machine Learning" LINK


Chemometrics and Machine Learning

"Development of multi-product calibration models of various root and tuber powders by fourier transform near infra-red (FT-NIR) spectroscopy for the quantification of polysaccharide contents." LINK


Research on Spectroscopy

"Extraction of rheological-optical characteristics of rice single kernel, in order to develop an instrumental method for determining grain quality" LINK




Equipment for Spectroscopy

"Near-infrared spectroscopy in quality control of Piper nigrum: A Comparison of performance of benchtop and handheld spectrometers" Pepper LINK




Process Control and NIR Sensors

"De-risking excipient particle size distribution variability with automated robust mixing: Integrating quality by design and process analytical technology." LINK

"Evaluation of IoT-Enabled Monitoring and Electronic Nose Spoilage Detection for Salmon Freshness During Cold Storage" Foods LINK




Agriculture NIR-Spectroscopy Usage

"Impact of Goji Berries (Lycium barbarum) Supplementation on the Energy Homeostasis of Rabbit Does: Uni- and Multivariate Approach" Animals LINK

"Chemometrics in NIR Hyperspectral Imaging: Theory and Applications in the Agricultural Crops and Products Sector" LINK




Horticulture NIR-Spectroscopy Applications

"Watermelon ripeness detector using near infrared spectroscopy" LINK




Food & Feed Industry NIR Usage

"Portable NIR spectrometer for quick identification of fat bloom in chocolates." LINK

"Non-destructive identification of slightly sprouted wheat kernels using hyperspectral data on both sides of wheat kernels" LINK




Pharma Industry NIR Usage

"Application of Process Analytical Technology in Active Pharmaceutical Ingredient Production (PAT)" LINK




Medicinal Spectroscopy

"Microwave Ablation Efficacy Evaluation of Bone Tissue Based on Near Infrared Spectrum" LINK




Laboratory and NIR-Spectroscopy

"Simultaneous prediction of several soil properties related to engineering uses based on laboratory Vis-NIR reflectance spectroscopy" LINK




Other

"ニューラルネットワークを用いた近赤外ハイパースペクトル画像におけるプラーク検出" Dental Plaque Detection LINK

"Preparation and characterization of triamterene complex with ascorbic acid derivatives" LINK

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 48, 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 48, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 48, 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 of natural medicines supported by novel instrumentation and methods for data analysis and interpretation" LINK

"A fast determination of insecticide deltamethrin by spectral data fusion of UV-vis and NIR based on extreme learning machine" LINK

"Assessing Laser Cleaning of a Limestone Monument by Fiber Optics Reflectance Spectroscopy (FORS) and Visible and Near-Infrared (VNIR) Hyperspectral Imaging …" LINK

"Near infrared spectroscopy combined with chemometrics to detect and quantify adulteration of maca powder " LINK

"Potential of smartphone-coupled micro NIR spectroscopy for quality control of green tea" LINK

"APPLICATION OF VIS–NIR HYPERSPECTRAL IMAGING FOR PREDICTION OF FLAVONOIDS, ANTHOCYANINS AND SOLUBLE SOLIDS CONTENT IN ..." LINK




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

"Determination of Adenosine and Cordycepin Concentrations in Cordyceps militaris Fruiting Bodies Using Near-Infrared Spectroscopy." LINK

"… : Prediction of α-Lactalbumin and β-Lactoglobulin Composition of Aqueous Whey Solutions Using Fourier Transform Mid-Infrared and Near-Infrared Spectroscopy" LINK

"The Effect of Freeze-Drying Pretreatment on the Accuracy of Near Infrared Spectroscopic Food Analysis to Predict the Nutritive Values of Japanese Cooked Foods" LINK

"Estimating hardness and density of wood and charcoal by near-infrared spectroscopy" LINK

"Assessing the interaction between drying and addition of maltodextrin to Kakadu plum powder samples by two dimensional and near infrared spectroscopy" LINK

"Near-infrared Spectroscopy and Hyperspectral Imaging for Sugar Content Evaluation in Potatoes over Multiple Growing Seasons" LINK

"Determination of radial profiles of wood properties using a near infrared scanning system" LINK

"FTIR combined with chemometric tools (Fingerprinting spectroscopy) in comparison to HPLC; Which strategy offers more opportunities as a green analytical chemistry technique for the pharmaceutical analysis" LINK

"Prediction of high-biomass sorghum quality using near infrared spectroscopy to monitoring calorific value, moisture, and ash content." LINK




Raman Spectroscopy

"Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy" LINK




Hyperspectral Imaging (HSI)

"Hyperspectral Imaging for Minced Meat Classification Using Nonlinear Deep Features" LINK

"Monitoring microstructural changes and moisture distribution of dry-cured pork-A combined confocal laser scanning microscopy and hyperspectral imaging study." LINK

"Monitoring Urban Black-Odorous Water by Using Hyperspectral Data and Machine Learning" LINK


Chemometrics and Machine Learning

"Development of multi-product calibration models of various root and tuber powders by fourier transform near infra-red (FT-NIR) spectroscopy for the quantification of polysaccharide contents." LINK


Research on Spectroscopy

"Extraction of rheological-optical characteristics of rice single kernel, in order to develop an instrumental method for determining grain quality" LINK




Equipment for Spectroscopy

"Near-infrared spectroscopy in quality control of Piper nigrum: A Comparison of performance of benchtop and handheld spectrometers" Pepper LINK




Process Control and NIR Sensors

"De-risking excipient particle size distribution variability with automated robust mixing: Integrating quality by design and process analytical technology." LINK

"Evaluation of IoT-Enabled Monitoring and Electronic Nose Spoilage Detection for Salmon Freshness During Cold Storage" Foods LINK




Agriculture NIR-Spectroscopy Usage

"Impact of Goji Berries (Lycium barbarum) Supplementation on the Energy Homeostasis of Rabbit Does: Uni- and Multivariate Approach" Animals LINK

"Chemometrics in NIR Hyperspectral Imaging: Theory and Applications in the Agricultural Crops and Products Sector" LINK




Horticulture NIR-Spectroscopy Applications

"Watermelon ripeness detector using near infrared spectroscopy" LINK




Food & Feed Industry NIR Usage

"Portable NIR spectrometer for quick identification of fat bloom in chocolates." LINK

"Non-destructive identification of slightly sprouted wheat kernels using hyperspectral data on both sides of wheat kernels" LINK




Pharma Industry NIR Usage

"Application of Process Analytical Technology in Active Pharmaceutical Ingredient Production (PAT)" LINK




Medicinal Spectroscopy

"Microwave Ablation Efficacy Evaluation of Bone Tissue Based on Near Infrared Spectrum" LINK




Laboratory and NIR-Spectroscopy

"Simultaneous prediction of several soil properties related to engineering uses based on laboratory Vis-NIR reflectance spectroscopy" LINK




Other

"ニューラルネットワークを用いた近赤外ハイパースペクトル画像におけるプラーク検出" Dental Plaque Detection LINK

"Preparation and characterization of triamterene complex with ascorbic acid derivatives" LINK

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 48, 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 48, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 48, 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 of natural medicines supported by novel instrumentation and methods for data analysis and interpretation" LINK

"A fast determination of insecticide deltamethrin by spectral data fusion of UV-vis and NIR based on extreme learning machine" LINK

"Assessing Laser Cleaning of a Limestone Monument by Fiber Optics Reflectance Spectroscopy (FORS) and Visible and Near-Infrared (VNIR) Hyperspectral Imaging …" LINK

"Near infrared spectroscopy combined with chemometrics to detect and quantify adulteration of maca powder " LINK

"Potential of smartphone-coupled micro NIR spectroscopy for quality control of green tea" LINK

"APPLICATION OF VIS–NIR HYPERSPECTRAL IMAGING FOR PREDICTION OF FLAVONOIDS, ANTHOCYANINS AND SOLUBLE SOLIDS CONTENT IN ..." LINK




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

"Determination of Adenosine and Cordycepin Concentrations in Cordyceps militaris Fruiting Bodies Using Near-Infrared Spectroscopy." LINK

"… : Prediction of α-Lactalbumin and β-Lactoglobulin Composition of Aqueous Whey Solutions Using Fourier Transform Mid-Infrared and Near-Infrared Spectroscopy" LINK

"The Effect of Freeze-Drying Pretreatment on the Accuracy of Near Infrared Spectroscopic Food Analysis to Predict the Nutritive Values of Japanese Cooked Foods" LINK

"Estimating hardness and density of wood and charcoal by near-infrared spectroscopy" LINK

"Assessing the interaction between drying and addition of maltodextrin to Kakadu plum powder samples by two dimensional and near infrared spectroscopy" LINK

"Near-infrared Spectroscopy and Hyperspectral Imaging for Sugar Content Evaluation in Potatoes over Multiple Growing Seasons" LINK

"Determination of radial profiles of wood properties using a near infrared scanning system" LINK

"FTIR combined with chemometric tools (Fingerprinting spectroscopy) in comparison to HPLC; Which strategy offers more opportunities as a green analytical chemistry technique for the pharmaceutical analysis" LINK

"Prediction of high-biomass sorghum quality using near infrared spectroscopy to monitoring calorific value, moisture, and ash content." LINK




Raman Spectroscopy

"Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy" LINK




Hyperspectral Imaging (HSI)

"Hyperspectral Imaging for Minced Meat Classification Using Nonlinear Deep Features" LINK

"Monitoring microstructural changes and moisture distribution of dry-cured pork-A combined confocal laser scanning microscopy and hyperspectral imaging study." LINK

"Monitoring Urban Black-Odorous Water by Using Hyperspectral Data and Machine Learning" LINK


Chemometrics and Machine Learning

"Development of multi-product calibration models of various root and tuber powders by fourier transform near infra-red (FT-NIR) spectroscopy for the quantification of polysaccharide contents." LINK


Research on Spectroscopy

"Extraction of rheological-optical characteristics of rice single kernel, in order to develop an instrumental method for determining grain quality" LINK




Equipment for Spectroscopy

"Near-infrared spectroscopy in quality control of Piper nigrum: A Comparison of performance of benchtop and handheld spectrometers" Pepper LINK




Process Control and NIR Sensors

"De-risking excipient particle size distribution variability with automated robust mixing: Integrating quality by design and process analytical technology." LINK

"Evaluation of IoT-Enabled Monitoring and Electronic Nose Spoilage Detection for Salmon Freshness During Cold Storage" Foods LINK




Agriculture NIR-Spectroscopy Usage

"Impact of Goji Berries (Lycium barbarum) Supplementation on the Energy Homeostasis of Rabbit Does: Uni- and Multivariate Approach" Animals LINK

"Chemometrics in NIR Hyperspectral Imaging: Theory and Applications in the Agricultural Crops and Products Sector" LINK




Horticulture NIR-Spectroscopy Applications

"Watermelon ripeness detector using near infrared spectroscopy" LINK




Food & Feed Industry NIR Usage

"Portable NIR spectrometer for quick identification of fat bloom in chocolates." LINK

"Non-destructive identification of slightly sprouted wheat kernels using hyperspectral data on both sides of wheat kernels" LINK




Pharma Industry NIR Usage

"Application of Process Analytical Technology in Active Pharmaceutical Ingredient Production (PAT)" LINK




Medicinal Spectroscopy

"Microwave Ablation Efficacy Evaluation of Bone Tissue Based on Near Infrared Spectrum" LINK




Laboratory and NIR-Spectroscopy

"Simultaneous prediction of several soil properties related to engineering uses based on laboratory Vis-NIR reflectance spectroscopy" LINK




Other

"ニューラルネットワークを用いた近赤外ハイパースペクトル画像におけるプラーク検出" Dental Plaque Detection LINK

"Preparation and characterization of triamterene complex with ascorbic acid derivatives" LINK

Spectroscopy and Chemometrics News Weekly #42, 2020Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #42, 2020Spettroscopia e Chemiometria Weekly News #42, 2020

NIR Calibration-Model Services

Stop Paying Too Much Time and Effort for NIRS Chemometrics Calibration Method Development! Use a Service | accuracy measure predictive analytics NIR spectroscopy analysis outsourcing Lab laboratory QA QC QAQC LINK

Spectroscopy and Chemometrics News Weekly 41, 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 41, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 41, 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

Get the Chemometrics and Spectroscopy News in real time on Twitter @ CalibModel and follow us.





Near-Infrared Spectroscopy (NIRS)

"Modelling potentially toxic elements in forest soils with vis–NIR spectra and learning algorithms" LINK

"ANALYSIS OF ROBUSTA COFFEE CULTIVATED IN AGROFORESTRY SYSTEMS (AFS) BY ESI-FT-ICR MS AND PORTABLE NIR ASSOCIATED WITH SENSORY ..." LINK

"In 30 years of near-infrared spectroscopy, I haven't seen too many drugs that look like that," said Robert Lodder, PhD, of the UK College of Pharmacy . By . medtwitter medstudenttwitter LINK

"Chemometric strategies for nondestructive and rapid assessment of nitrate content in harvested spinach using VisNIR spectroscopy" LINK

"ANALYSIS OF ROBUSTA COFFEE CULTIVATED IN AGROFORESTRY SYSTEMS (AFS) BY ESI-FT-ICR MS AND PORTABLE NIR ASSOCIATED WITH SENSORY …" LINK

Using Near-infrared reflectance spectroscopy (NIRS) to predict glucobrassicin concentrations in cabbage and brussels sprout leaf tissue LINK

"Age estimation of red snapper (Lutjanus campechanus) using FT-NIR spectroscopy: feasibility of application to production ageing for management" LINK

"Rapid Assessment of Exercise State through Athlete's Urine Using Temperature-Dependent NIRS Technology" LINK

"Multivariate calibration: Identification of phenolic compounds in PROPOLIS using FTNIR" LINK

"FT-NIR spectroscopy and RP-HPLC combined with multivariate analysis reveals differences in plant cell suspension cultures of Thevetia peruviana treated with salicylic acid and methyl jasmonate." LINK




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

"Non-destructive detection of foreign contaminants in toast bread with near infrared spectroscopy and computer vision techniques" LINK

"Knowledge-based genetic algorithm for resolving the near-infrared spectrum and understanding the water structures in aqueous solution" LINK

"Estimation of heavy metals using deep neural network with visible and infrared spectroscopy of soil." LINK

"Lipid Core Plaque Distribution Using Near-infrared Spectroscopy Is Consistent with Pathological Evaluation in Carotid Artery Plaques" LINK

"Elucidation of the Molecular Mechanism of Wet Granulation for Pharmaceutical Standard Formulations in a High-Speed Shear Mixer Using Near-Infrared Spectroscopy" LINK

"Nearinfrared spectroscopy and data analysis for predicting milk powder quality attributes" LINK

"Near Infrared Reflectance Spectroscopy and Multivariate Analyses for Fast and Non-Destructive Prediction of Corn Seed Germination" LINK

"Effect of Sample Preparation Methods on the Prediction Performances of Near Infrared Reflectance Spectroscopy for Quality Traits of Fresh Yam (Dioscorea spp.)" LINK

"Comparison of artificial neural networks and multiple regression tools applied to near infrared spectroscopy for predicting sensory properties of products from Quality …" LINK




Raman Spectroscopy

Raman spectra‐based deep learning: A tool to identify microbial contamination LINK

"Temperature-Induced Chemical Changes in Lubricant Automotive Oils Evaluated Using Raman Spectroscopy" LINK

"Study of Blood Serum in Rats with Transplanted Cholangiocarcinoma Using Raman Spectroscopy" LINK




Hyperspectral Imaging (HSI)

"Early detection of black Sigatoka in banana leaves using hyperspectral images" LINK




Chemometrics and Machine Learning

"Weights or measures for better calibration" spectroscopy LINK

"Feasibility of rapid piperine quantification in whole and black pepper using near infrared spectroscopy and chemometrics" LINK

"Rethinking AI talent strategy as automated machine learning comes of age" | employment MachineLearning automated AutoML LINK

"Developing Calibration Model for Prediction of Malt Barley Genotypes Quality Traits using Fourier Transform near Infrared Spectroscopy" LINK




Equipment for Spectroscopy

"Discriminant analysis of pyrrolizidine alkaloid contamination in bee pollen based on near-infrared data from lab-stationary and portable spectrometers" | LINK




Future topics in Spectroscopy

"Journal of Global Trends in Pharmaceutical Sciences" LINK




Agriculture NIR-Spectroscopy Usage

"Evaluation of soybean condition under various fertilizer application by the relationship of the red and near-infrared bands reflectance in scatter plot" LINK

"Nutrient Prediction for Tef (Eragrostis tef) Plant and Grain with Hyperspectral Data and Partial Least Squares Regression: Replicating Methods and Results across Environments" LINK

"A spectral parameter for the estimation of soil total nitrogen and nitrate nitrogen of winter wheat growth period" LINK

"Animal species identification in parchments by light." LINK




Food & Feed Industry NIR Usage

"Intrinsic and Extrinsic Quality Attributes of Fresh and Semi-Hard Goat Cheese from Low- and High-Input Farming Systems" LINK

"Non-Invasive Characterization of Single-, Double- and Triple-Viral Diseases of Wheat With a Hand-Held Raman Spectrometer" | LINK




Other

"Physicochemical Fingerprint of "Pera Rocha do Oeste". A PDO Pear Native from Portugal." LINK

"Polymer types ingested by northern fulmars (Fulmarus glacialis) and southern hemisphere relatives" LINK





.

NIR Calibration-Model Services

Stop Paying Too Much Time and Effort for NIRS Chemometrics Calibration Method Development! Use a Service | accuracy measure predictive analytics NIR spectroscopy analysis outsourcing Lab laboratory QA QC QAQC LINK

Spectroscopy and Chemometrics News Weekly 41, 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 41, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 41, 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

Get the Chemometrics and Spectroscopy News in real time on Twitter @ CalibModel and follow us.





Near-Infrared Spectroscopy (NIRS)

"Modelling potentially toxic elements in forest soils with vis–NIR spectra and learning algorithms" LINK

"ANALYSIS OF ROBUSTA COFFEE CULTIVATED IN AGROFORESTRY SYSTEMS (AFS) BY ESI-FT-ICR MS AND PORTABLE NIR ASSOCIATED WITH SENSORY ..." LINK

"In 30 years of near-infrared spectroscopy, I haven't seen too many drugs that look like that," said Robert Lodder, PhD, of the UK College of Pharmacy . By . medtwitter medstudenttwitter LINK

"Chemometric strategies for nondestructive and rapid assessment of nitrate content in harvested spinach using VisNIR spectroscopy" LINK

"ANALYSIS OF ROBUSTA COFFEE CULTIVATED IN AGROFORESTRY SYSTEMS (AFS) BY ESI-FT-ICR MS AND PORTABLE NIR ASSOCIATED WITH SENSORY …" LINK

Using Near-infrared reflectance spectroscopy (NIRS) to predict glucobrassicin concentrations in cabbage and brussels sprout leaf tissue LINK

"Age estimation of red snapper (Lutjanus campechanus) using FT-NIR spectroscopy: feasibility of application to production ageing for management" LINK

"Rapid Assessment of Exercise State through Athlete's Urine Using Temperature-Dependent NIRS Technology" LINK

"Multivariate calibration: Identification of phenolic compounds in PROPOLIS using FTNIR" LINK

"FT-NIR spectroscopy and RP-HPLC combined with multivariate analysis reveals differences in plant cell suspension cultures of Thevetia peruviana treated with salicylic acid and methyl jasmonate." LINK




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

"Non-destructive detection of foreign contaminants in toast bread with near infrared spectroscopy and computer vision techniques" LINK

"Knowledge-based genetic algorithm for resolving the near-infrared spectrum and understanding the water structures in aqueous solution" LINK

"Estimation of heavy metals using deep neural network with visible and infrared spectroscopy of soil." LINK

"Lipid Core Plaque Distribution Using Near-infrared Spectroscopy Is Consistent with Pathological Evaluation in Carotid Artery Plaques" LINK

"Elucidation of the Molecular Mechanism of Wet Granulation for Pharmaceutical Standard Formulations in a High-Speed Shear Mixer Using Near-Infrared Spectroscopy" LINK

"Nearinfrared spectroscopy and data analysis for predicting milk powder quality attributes" LINK

"Near Infrared Reflectance Spectroscopy and Multivariate Analyses for Fast and Non-Destructive Prediction of Corn Seed Germination" LINK

"Effect of Sample Preparation Methods on the Prediction Performances of Near Infrared Reflectance Spectroscopy for Quality Traits of Fresh Yam (Dioscorea spp.)" LINK

"Comparison of artificial neural networks and multiple regression tools applied to near infrared spectroscopy for predicting sensory properties of products from Quality …" LINK




Raman Spectroscopy

Raman spectra‐based deep learning: A tool to identify microbial contamination LINK

"Temperature-Induced Chemical Changes in Lubricant Automotive Oils Evaluated Using Raman Spectroscopy" LINK

"Study of Blood Serum in Rats with Transplanted Cholangiocarcinoma Using Raman Spectroscopy" LINK




Hyperspectral Imaging (HSI)

"Early detection of black Sigatoka in banana leaves using hyperspectral images" LINK




Chemometrics and Machine Learning

"Weights or measures for better calibration" spectroscopy LINK

"Feasibility of rapid piperine quantification in whole and black pepper using near infrared spectroscopy and chemometrics" LINK

"Rethinking AI talent strategy as automated machine learning comes of age" | employment MachineLearning automated AutoML LINK

"Developing Calibration Model for Prediction of Malt Barley Genotypes Quality Traits using Fourier Transform near Infrared Spectroscopy" LINK




Equipment for Spectroscopy

"Discriminant analysis of pyrrolizidine alkaloid contamination in bee pollen based on near-infrared data from lab-stationary and portable spectrometers" | LINK




Future topics in Spectroscopy

"Journal of Global Trends in Pharmaceutical Sciences" LINK




Agriculture NIR-Spectroscopy Usage

"Evaluation of soybean condition under various fertilizer application by the relationship of the red and near-infrared bands reflectance in scatter plot" LINK

"Nutrient Prediction for Tef (Eragrostis tef) Plant and Grain with Hyperspectral Data and Partial Least Squares Regression: Replicating Methods and Results across Environments" LINK

"A spectral parameter for the estimation of soil total nitrogen and nitrate nitrogen of winter wheat growth period" LINK

"Animal species identification in parchments by light." LINK




Food & Feed Industry NIR Usage

"Intrinsic and Extrinsic Quality Attributes of Fresh and Semi-Hard Goat Cheese from Low- and High-Input Farming Systems" LINK

"Non-Invasive Characterization of Single-, Double- and Triple-Viral Diseases of Wheat With a Hand-Held Raman Spectrometer" | LINK




Other

"Physicochemical Fingerprint of "Pera Rocha do Oeste". A PDO Pear Native from Portugal." LINK

"Polymer types ingested by northern fulmars (Fulmarus glacialis) and southern hemisphere relatives" LINK





.

NIR Calibration-Model Services

Stop Paying Too Much Time and Effort for NIRS Chemometrics Calibration Method Development! Use a Service | accuracy measure predictive analytics NIR spectroscopy analysis outsourcing Lab laboratory QA QC QAQC LINK

Spectroscopy and Chemometrics News Weekly 41, 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 41, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 41, 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

Get the Chemometrics and Spectroscopy News in real time on Twitter @ CalibModel and follow us.





Near-Infrared Spectroscopy (NIRS)

"Modelling potentially toxic elements in forest soils with vis–NIR spectra and learning algorithms" LINK

"ANALYSIS OF ROBUSTA COFFEE CULTIVATED IN AGROFORESTRY SYSTEMS (AFS) BY ESI-FT-ICR MS AND PORTABLE NIR ASSOCIATED WITH SENSORY ..." LINK

"In 30 years of near-infrared spectroscopy, I haven't seen too many drugs that look like that," said Robert Lodder, PhD, of the UK College of Pharmacy . By . medtwitter medstudenttwitter LINK

"Chemometric strategies for nondestructive and rapid assessment of nitrate content in harvested spinach using VisNIR spectroscopy" LINK

"ANALYSIS OF ROBUSTA COFFEE CULTIVATED IN AGROFORESTRY SYSTEMS (AFS) BY ESI-FT-ICR MS AND PORTABLE NIR ASSOCIATED WITH SENSORY …" LINK

Using Near-infrared reflectance spectroscopy (NIRS) to predict glucobrassicin concentrations in cabbage and brussels sprout leaf tissue LINK

"Age estimation of red snapper (Lutjanus campechanus) using FT-NIR spectroscopy: feasibility of application to production ageing for management" LINK

"Rapid Assessment of Exercise State through Athlete's Urine Using Temperature-Dependent NIRS Technology" LINK

"Multivariate calibration: Identification of phenolic compounds in PROPOLIS using FTNIR" LINK

"FT-NIR spectroscopy and RP-HPLC combined with multivariate analysis reveals differences in plant cell suspension cultures of Thevetia peruviana treated with salicylic acid and methyl jasmonate." LINK




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

"Non-destructive detection of foreign contaminants in toast bread with near infrared spectroscopy and computer vision techniques" LINK

"Knowledge-based genetic algorithm for resolving the near-infrared spectrum and understanding the water structures in aqueous solution" LINK

"Estimation of heavy metals using deep neural network with visible and infrared spectroscopy of soil." LINK

"Lipid Core Plaque Distribution Using Near-infrared Spectroscopy Is Consistent with Pathological Evaluation in Carotid Artery Plaques" LINK

"Elucidation of the Molecular Mechanism of Wet Granulation for Pharmaceutical Standard Formulations in a High-Speed Shear Mixer Using Near-Infrared Spectroscopy" LINK

"Nearinfrared spectroscopy and data analysis for predicting milk powder quality attributes" LINK

"Near Infrared Reflectance Spectroscopy and Multivariate Analyses for Fast and Non-Destructive Prediction of Corn Seed Germination" LINK

"Effect of Sample Preparation Methods on the Prediction Performances of Near Infrared Reflectance Spectroscopy for Quality Traits of Fresh Yam (Dioscorea spp.)" LINK

"Comparison of artificial neural networks and multiple regression tools applied to near infrared spectroscopy for predicting sensory properties of products from Quality …" LINK




Raman Spectroscopy

Raman spectra‐based deep learning: A tool to identify microbial contamination LINK

"Temperature-Induced Chemical Changes in Lubricant Automotive Oils Evaluated Using Raman Spectroscopy" LINK

"Study of Blood Serum in Rats with Transplanted Cholangiocarcinoma Using Raman Spectroscopy" LINK




Hyperspectral Imaging (HSI)

"Early detection of black Sigatoka in banana leaves using hyperspectral images" LINK




Chemometrics and Machine Learning

"Weights or measures for better calibration" spectroscopy LINK

"Feasibility of rapid piperine quantification in whole and black pepper using near infrared spectroscopy and chemometrics" LINK

"Rethinking AI talent strategy as automated machine learning comes of age" | employment MachineLearning automated AutoML LINK

"Developing Calibration Model for Prediction of Malt Barley Genotypes Quality Traits using Fourier Transform near Infrared Spectroscopy" LINK




Equipment for Spectroscopy

"Discriminant analysis of pyrrolizidine alkaloid contamination in bee pollen based on near-infrared data from lab-stationary and portable spectrometers" | LINK




Future topics in Spectroscopy

"Journal of Global Trends in Pharmaceutical Sciences" LINK




Agriculture NIR-Spectroscopy Usage

"Evaluation of soybean condition under various fertilizer application by the relationship of the red and near-infrared bands reflectance in scatter plot" LINK

"Nutrient Prediction for Tef (Eragrostis tef) Plant and Grain with Hyperspectral Data and Partial Least Squares Regression: Replicating Methods and Results across Environments" LINK

"A spectral parameter for the estimation of soil total nitrogen and nitrate nitrogen of winter wheat growth period" LINK

"Animal species identification in parchments by light." LINK




Food & Feed Industry NIR Usage

"Intrinsic and Extrinsic Quality Attributes of Fresh and Semi-Hard Goat Cheese from Low- and High-Input Farming Systems" LINK

"Non-Invasive Characterization of Single-, Double- and Triple-Viral Diseases of Wheat With a Hand-Held Raman Spectrometer" | LINK




Other

"Physicochemical Fingerprint of "Pera Rocha do Oeste". A PDO Pear Native from Portugal." LINK

"Polymer types ingested by northern fulmars (Fulmarus glacialis) and southern hemisphere relatives" LINK





.

NIR-Predictor – Manual


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:

  1. Open the demo Spectra folder by using the Menu > Open Demo Spectra or press F8.
    There are files with spectra from different Vendors.
  2. Drag & drop a spectra file onto the NIR-Predictor window (or press Ctrl+O as for ’Open some files).
  3. 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

  1. 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

  2. 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!

  3. 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.
  4. 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.

  5. Email the CalibrationRequest.zip file
    to info@CalibrationModel.com to develop the calibrations.
  6. 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:

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

Usage:

  1. in NIR-Predictor : open the Application drop down list, and select your application by name
  2. if all is fine, the calibration file is valid and not expired, it shows : Calibration “1 valid calibation”
  3. the NIR-Predictor is now ready to predict
  4. 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

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.
Spectra Plot

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.

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

  1. 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
  2. Use your favorite editor or spreadsheet program to enter and copy&paste the Lab Values into the columns and save the file.
  3. 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.
  4. 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