Spectroscopy and Chemometrics/Machine-Learning News Weekly #8, 2023

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

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

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 7, 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 7, 2023 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 7, 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)

“Foods : Investigating Changes in pH and Soluble Solids Content of Potato during the Storage by Electronic Nose and Vis/NIR Spectroscopy” LINK

” The influence of water of crystallization in NIR-based MDMA∙ HCl detection” LINK

“Study on the secondary structure and hydration effect of human serum albumin under acidic pH and ethanol perturbation with IR/NIR spectroscopy” | LINK

“Application of the Combination Method Based on RF and LE in Near Infrared Spectral Modeling” LINK

“A chemometric method for the viability analysis of spinach seeds by near infrared spectroscopy with variable selection using successive projections algorithm” LINK

“Application of Near-Infrared Spectroscopy to characterize volatile phenols and sensory profile of aged wine spirits” | et al.pdf LINK

“A novel fast method for identifying the origin of Maojian using NIR spectroscopy with deep learning algorithms” | LINK

“Highly efficient and thermally stable broadband NIR phosphors by rationally bridging Cr 3+-Yb 3+ in LiScGe 2 O 6 for optical bioimaging” | LINK

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

“Quantitative and convenient protocol for analysis of surfacemodified silica nanoparticles using 29SiNMR and nearinfrared diffuse reflection spectroscopy” LINK

Hyperspectral Imaging (HSI)

“Prediction of TVB-N content in beef with packaging films using visible-near infrared hyperspectral imaging” LINK

“Hyperspectral Imaging and Analysis” LINK

“Non-destructive Detection of Fatty Acid Content of Camellia Seed Based on Hyperspectral” LINK

Chemometrics and Machine Learning

“Overview of Cocaine Identification by Vibrational Spectroscopy and Chemometrics” LINK

“Remote Sensing : VIS-NIR-SWIR Hyperspectroscopy Combined with Data Mining and Machine Learning for Classification of Predicted Chemometrics of Green Lettuce” | LINK

Optics for Spectroscopy

“Highly Sensitive TinLead Perovskite Photodetectors with Over 450 Days Stability Enabled by Synergistic Engineering for Pulse Oximetry System” LINK

Research on Spectroscopy

“Methodologies based on ASCA to elucidate the influence of a subprocess: vinification as a case of study” LINK

Environment NIR-Spectroscopy Application

“Satellite imagery dataset of manure application on pasture fields” LINK

“Remote Sensing : Exploring the Best-Matching Plant Traits and Environmental Factors for Vegetation Indices in Estimates of Global Gross Primary Productivity” LINK

“Remote Sensing : Multispectral Characteristics of Glacier Surface Facies (Chandra-Bhaga Basin, Himalaya, and Ny-Ålesund, Svalbard) through Investigations of Pixel and Object-Based Mapping Using Variable Processing Routines” LINK

“Remote Sensing : Estimation of the Key Water Quality Parameters in the Surface Water, Middle of Northeast China, Based on Gaussian Process Regression” LINK

Agriculture NIR-Spectroscopy Usage

“Recent advances in the ultrasound-assisted osmotic dehydration of agricultural products: A review” LINK

“Miniaturized NearInfrared Spectroscopy The Ultimate Analytical Tool in Food and Agriculture” LINK

“Remote Sensing : UAV-Based Estimation of Grain Yield for Plant Breeding: Applied Strategies for Optimizing the Use of Sensors, Vegetation Indices, Growth Stages, and Machine Learning Algorithms” | LINK

“Agriculture : Ripeness Evaluation of Achacha Fruit Using Hyperspectral Image Data” LINK

“A review of the opportunities for spectral‐based technologies in post‐harvest testing of pulse grains” LINK

Food & Feed Industry NIR Usage

“Nutritional labelling of food products purchased from online retail outlets: screening of compliance with European Union tolerance limits by near infrared spectroscopy” LINK

“Sensors : Non-Destructive Detection of Abnormal Chicken Eggs by Using an Optimized Spectral Analysis System” | LINK

Chemical Industry NIR Usage

“Polymers : A Tissue Paper/Hydrogel Composite Light-Responsive Biomimetic Actuator Fabricated by In Situ Polymerization” | LINK

Petro Industry NIR Usage

“Prospects for the utilization of the prairie cordgrass spartina pectinata for bioenergy production in Moldova” LINK

Medicinal Spectroscopy

“Noninvasive Monitoring of Glucose Using Near-Infrared Reflection Spectroscopy of Skin—Constraints and Effective Novel Strategy in Multivariate Calibration” LINK

Other

“Applied Sciences : Verification of Convolutional Neural Network Cephalometric Landmark Identification” | LINK

“Multi-Dimensional Self Attention based Approach for Remaining Useful Life Estimation. (arXiv:2212.05772v1 [cs.LG])” LINK

.

Spectroscopy and Chemometrics/Machine-Learning News Weekly #14, 2022Spektroskopie und Chemometrie/Machine-Learning News Wöchentlich #14, 2022Spettroscopia e Chemiometria/Machine-Learning Weekly News #14, 2022

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 13, 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 13, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 13, 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)

"NIR Spectroscopy and Aquaphotomics Approach to Identify Soil Characteristics as a Function of the Sampling Depth" LINK

"Improving the multi-class classification of Alzheimer's disease with machine learning-based techniques: An EEG-fNIRS hybridization study" LINK

"A novel methodology for determining effectiveness of preprocessing methods in reducing undesired spectral variability in near infrared spectra" LINK

"NEAR INFRARED SPECTROSCOPY AS IN-LINE PAT TOOL FOR A ROBUST MOISTURE CONTENT DETERMINATION OF SPIN FREEZE-DRIED SAMPLES" LINK

"Near infrared‐based process analytical technology module for estimating gelatinization optimal point" LINK

"Near Infrared Technology in Agricultural Sustainability: Rapid Prediction of Nitrogen Content from Organic Fertilizer" LINK

"Gasoline octane number prediction from near-infrared spectroscopy with an ANN-based model" LINK

"Rapid On-site Identification of Geographical Origin and Storage Age of Tangerine Peel by Near-infrared Spectroscopy" LINK

"Empirical mode decomposition of near-infrared spectroscopy signals for predicting oil content in palm fruits" LINK

"Miniaturization in NIR Spectroscopy Reshapes Chemical Analysis" LINK

"Unscrambling spectral interference and matrix effects in Vitis vinifera Vis-NIR spectroscopy: Towards analytical grade 'in vivo'sugars and acids quantification" LINK

"Research Progress of Bionic Materials Simulating Vegetation Visible-Near Infrared Reflectance Spectra" LINK

"Latent Variable Machine Learning Methods Applied for NIR Quantitative Analysis of Coffee" LINK

"Identification of informative spectral ranges for predicting major chemical constituents in corn using NIR spectroscopy" LINK

"Vis-NIR Spectroscopy and Machine Learning Methods for the Discrimination of Transgenic Brassica napus L. and Their Hybrids with B. juncea" LINK

"Applied Sciences : Hidden Information in Uniform Design for Visual and Near-Infrared Spectrum and for Inkjet Printing of Clothing on Canvas to Enhance Urban Security" LINK

"LIONirs: flexible Matlab toolbox for fNIRS data analysis" LINK




Raman Spectroscopy

"Raman Spectroscopic Detection and Quantification of Macro- and Microhematuria in Human Urine" LINK




Hyperspectral Imaging (HSI)

"Prediction of total carotenoids, color and moisture content of carrot slices during hot air drying using noninvasive hyperspectral imaging technique" LINK

"Growth simulation of Pseudomonas fluorescens in pork using hyperspectral imaging" LINK

"Estimation of Leaf Water Content of Different Leaves from Different Species Using Hyperspectral Reflectance Data" LINK




Chemometrics and Machine Learning

"Automation : Predictive Performance of Mobile Vis-NIR Spectroscopy for Mapping Key Fertility Attributes in Tropical Soils through Local Models Using PLS and ANN" LINK

"Prediction of South American Leaf Blight and Disease-Induced Photosynthetic Changes in Rubber Tree, Using Machine Learning Techniques on Leaf Hyperspectral ..." LINK

"Proximal spectroscopy sensing for sugarcane quality prediction and spatial variability mapping" LINK

"Variable Selection Based on Gray Wolf Optimization Algorithm for the Prediction of Saponin Contents in Xuesaitong Dropping Pills Using NIR Spectroscopy" | LINK

"Prediction of soil organic matter content based on characteristic band selection method" LINK

"Sensors : Algorithm of Stability-Analysis-Based Feature Selection for NIR Calibration Transfer" LINK

"Modelling soil water retention and water‐holding capacity with visible-near infrared spectra and machine learning" LINK

"Machine learning for atherosclerotic tissue component classification in combined near-infrared spectroscopy intravascular ultrasound imaging: Validation against ..." LINK

"Modelling soil water retention and waterholding capacity with visiblenear infrared spectra and machine learning" LINK

"Cancers : Novel Non-Invasive Quantification and Imaging of Eumelanin and DHICA Subunit in Skin Lesions by Raman Spectroscopy and MCR Algorithm: Improving Dysplastic Nevi Diagnosis" LINK




Spectroscopy

"Evaluation of portable vibrational spectroscopy for identifying plasticizers in dairy tubing" LINK




Optics for Spectroscopy

"Chemosensors : Carbocyanine-Based Fluorescent and Colorimetric Sensor Array for the Discrimination of Medicinal Compounds" LINK

"Platinum(II)Acetylide Conjugated Polymer Containing AzaBODIPY Moieties for Panchromatic Photodetectors" LINK




Equipment for Spectroscopy

"Polymers : Role of Macrodiols in the Synthesis and Thermo-Mechanical Behavior of Anti-Tack Water Borne Polyurethane Dispersions" LINK




Process Control and NIR Sensors

"A Perfect Pair: Stabilized Black Phosphorous Nanosheets Engineering with Antimicrobial Peptides for Robust Multidrug Resistant Bacteria Eradication" LINK




Environment NIR-Spectroscopy Application

"Long-Term Liming Reduces the Emission and Temperature Sensitivity of N2o Via Altering Denitrification Functional Gene Ratio in Acidic Soil" LINK

"Environmental metabolomics approaches to identify and enhance secondary compounds in medicinal plants for bio-based plant protection" LINK

"Soil moisture determines nitrous oxide emission and uptake" LINK

"Remote Sensing : Evaluating the Capability of Satellite Hyperspectral Imager, the ZY1-02D, for Topsoil Nitrogen Content Estimation and Mapping of Farmlands in Black Soil Area, China" LINK

"Remote Sensing : Extending the GOSAILT Model to Simulate Sparse Woodland Bi-Directional Reflectance with Soil Reflectance Anisotropy Consideration" LINK




Agriculture NIR-Spectroscopy Usage

"Evaluation of Near-Infrared Reflectance and Transflectance Sensing System for Predicting Manure Nutrients" LINK

"Ecoenzymatic stoichiometry reflects the regulation of microbial carbon and nitrogen limitation on soil nitrogen cycling potential in arid agriculture ecosystems" | LINK

"Remote Sensing : Phenotypic Traits Estimation and Preliminary Yield Assessment in Different Phenophases of Wheat Breeding Experiment Based on UAV Multispectral Images" LINK

"Agronomy : Evaluation of Methods for Measuring Fusarium-Damaged Kernels Wheat" LINK

"Agriculture : Non-Destructive Detection of pH Value of Kiwifruit Based on Hyperspectral Fluorescence Imaging Technology" LINK

"Agronomy : Optical Spectrometry to Determine Nutrient Concentrations and other Physicochemical Parameters in Liquid Organic Manures: A Review" LINK

"Agriculture : The Effect of Tytanit on Fibre Fraction Content in Medicago x varia T. Martyn and Trifolium pratense L. Cell Walls" LINK




Horticulture NIR-Spectroscopy Applications

"Redefining the impact of preharvest factors on peach fruit quality development and metabolism: A review" LINK

"Accurate nondestructive prediction of soluble solids content in citrus by nearinfrared diffuse reflectance spectroscopy with characteristic variable selection" LINK




Forestry and Wood Industry NIR Usage

"Spectrometric Prediction of Nitrogen Content in Different Tissues of Slash Pine Trees" LINK




Food & Feed Industry NIR Usage

"Effects of Irrigation Strategy and Plastic Film Mulching on Soil N 2 O Emissions and Fruit Yields of Greenhouse Tomato" LINK

"Mini shortwave Spectroscopic Techniques and Multivariate Statistical Analysis as a Tool for Testing intact Cocoa beans at farmgate for Quality Control in Ghana" LINK

"Foods : Gluten Conformation at Different Temperatures and Additive Treatments" LINK




Pharma Industry NIR Usage

"Revealing the Effect of Heat Treatment on the Spectral Pattern of Unifloral Honeys Using Aquaphotomics" LINK

"Biomedicines : Pathophysiological Response to SARS-CoV-2 Infection Detected by Infrared Spectroscopy Enables Rapid and Robust Saliva Screening for COVID-19" LINK




Other

"Unraveling the potential of phenomic selection within and among diverse breeding material of maize (Zea mays L.)" LINK

"Applied Sciences : Impact of Pheidole fallax (Hymenoptera: Formicidae) as an Ecosystem Engineer in Rehabilitated Coal Mine Areas" LINK

"The Spectral Mixture Residual: A Source of LowVariance Information to Enhance the Explainability and Accuracy of Surface Biology and Geology Retrievals" LINK

"Glycosylated MoS2 Sheets for Capturing and Deactivating E. coli Bacteria: Combined Effects of Multivalent Binding and Sheet Size" LINK




NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 13, 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 13, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 13, 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)

"NIR Spectroscopy and Aquaphotomics Approach to Identify Soil Characteristics as a Function of the Sampling Depth" LINK

"Improving the multi-class classification of Alzheimer's disease with machine learning-based techniques: An EEG-fNIRS hybridization study" LINK

"A novel methodology for determining effectiveness of preprocessing methods in reducing undesired spectral variability in near infrared spectra" LINK

"NEAR INFRARED SPECTROSCOPY AS IN-LINE PAT TOOL FOR A ROBUST MOISTURE CONTENT DETERMINATION OF SPIN FREEZE-DRIED SAMPLES" LINK

"Near infrared‐based process analytical technology module for estimating gelatinization optimal point" LINK

"Near Infrared Technology in Agricultural Sustainability: Rapid Prediction of Nitrogen Content from Organic Fertilizer" LINK

"Gasoline octane number prediction from near-infrared spectroscopy with an ANN-based model" LINK

"Rapid On-site Identification of Geographical Origin and Storage Age of Tangerine Peel by Near-infrared Spectroscopy" LINK

"Empirical mode decomposition of near-infrared spectroscopy signals for predicting oil content in palm fruits" LINK

"Miniaturization in NIR Spectroscopy Reshapes Chemical Analysis" LINK

"Unscrambling spectral interference and matrix effects in Vitis vinifera Vis-NIR spectroscopy: Towards analytical grade 'in vivo'sugars and acids quantification" LINK

"Research Progress of Bionic Materials Simulating Vegetation Visible-Near Infrared Reflectance Spectra" LINK

"Latent Variable Machine Learning Methods Applied for NIR Quantitative Analysis of Coffee" LINK

"Identification of informative spectral ranges for predicting major chemical constituents in corn using NIR spectroscopy" LINK

"Vis-NIR Spectroscopy and Machine Learning Methods for the Discrimination of Transgenic Brassica napus L. and Their Hybrids with B. juncea" LINK

"Applied Sciences : Hidden Information in Uniform Design for Visual and Near-Infrared Spectrum and for Inkjet Printing of Clothing on Canvas to Enhance Urban Security" LINK

"LIONirs: flexible Matlab toolbox for fNIRS data analysis" LINK




Raman Spectroscopy

"Raman Spectroscopic Detection and Quantification of Macro- and Microhematuria in Human Urine" LINK




Hyperspectral Imaging (HSI)

"Prediction of total carotenoids, color and moisture content of carrot slices during hot air drying using noninvasive hyperspectral imaging technique" LINK

"Growth simulation of Pseudomonas fluorescens in pork using hyperspectral imaging" LINK

"Estimation of Leaf Water Content of Different Leaves from Different Species Using Hyperspectral Reflectance Data" LINK




Chemometrics and Machine Learning

"Automation : Predictive Performance of Mobile Vis-NIR Spectroscopy for Mapping Key Fertility Attributes in Tropical Soils through Local Models Using PLS and ANN" LINK

"Prediction of South American Leaf Blight and Disease-Induced Photosynthetic Changes in Rubber Tree, Using Machine Learning Techniques on Leaf Hyperspectral ..." LINK

"Proximal spectroscopy sensing for sugarcane quality prediction and spatial variability mapping" LINK

"Variable Selection Based on Gray Wolf Optimization Algorithm for the Prediction of Saponin Contents in Xuesaitong Dropping Pills Using NIR Spectroscopy" | LINK

"Prediction of soil organic matter content based on characteristic band selection method" LINK

"Sensors : Algorithm of Stability-Analysis-Based Feature Selection for NIR Calibration Transfer" LINK

"Modelling soil water retention and water‐holding capacity with visible-near infrared spectra and machine learning" LINK

"Machine learning for atherosclerotic tissue component classification in combined near-infrared spectroscopy intravascular ultrasound imaging: Validation against ..." LINK

"Modelling soil water retention and waterholding capacity with visiblenear infrared spectra and machine learning" LINK

"Cancers : Novel Non-Invasive Quantification and Imaging of Eumelanin and DHICA Subunit in Skin Lesions by Raman Spectroscopy and MCR Algorithm: Improving Dysplastic Nevi Diagnosis" LINK




Spectroscopy

"Evaluation of portable vibrational spectroscopy for identifying plasticizers in dairy tubing" LINK




Optics for Spectroscopy

"Chemosensors : Carbocyanine-Based Fluorescent and Colorimetric Sensor Array for the Discrimination of Medicinal Compounds" LINK

"Platinum(II)Acetylide Conjugated Polymer Containing AzaBODIPY Moieties for Panchromatic Photodetectors" LINK




Equipment for Spectroscopy

"Polymers : Role of Macrodiols in the Synthesis and Thermo-Mechanical Behavior of Anti-Tack Water Borne Polyurethane Dispersions" LINK




Process Control and NIR Sensors

"A Perfect Pair: Stabilized Black Phosphorous Nanosheets Engineering with Antimicrobial Peptides for Robust Multidrug Resistant Bacteria Eradication" LINK




Environment NIR-Spectroscopy Application

"Long-Term Liming Reduces the Emission and Temperature Sensitivity of N2o Via Altering Denitrification Functional Gene Ratio in Acidic Soil" LINK

"Environmental metabolomics approaches to identify and enhance secondary compounds in medicinal plants for bio-based plant protection" LINK

"Soil moisture determines nitrous oxide emission and uptake" LINK

"Remote Sensing : Evaluating the Capability of Satellite Hyperspectral Imager, the ZY1-02D, for Topsoil Nitrogen Content Estimation and Mapping of Farmlands in Black Soil Area, China" LINK

"Remote Sensing : Extending the GOSAILT Model to Simulate Sparse Woodland Bi-Directional Reflectance with Soil Reflectance Anisotropy Consideration" LINK




Agriculture NIR-Spectroscopy Usage

"Evaluation of Near-Infrared Reflectance and Transflectance Sensing System for Predicting Manure Nutrients" LINK

"Ecoenzymatic stoichiometry reflects the regulation of microbial carbon and nitrogen limitation on soil nitrogen cycling potential in arid agriculture ecosystems" | LINK

"Remote Sensing : Phenotypic Traits Estimation and Preliminary Yield Assessment in Different Phenophases of Wheat Breeding Experiment Based on UAV Multispectral Images" LINK

"Agronomy : Evaluation of Methods for Measuring Fusarium-Damaged Kernels Wheat" LINK

"Agriculture : Non-Destructive Detection of pH Value of Kiwifruit Based on Hyperspectral Fluorescence Imaging Technology" LINK

"Agronomy : Optical Spectrometry to Determine Nutrient Concentrations and other Physicochemical Parameters in Liquid Organic Manures: A Review" LINK

"Agriculture : The Effect of Tytanit on Fibre Fraction Content in Medicago x varia T. Martyn and Trifolium pratense L. Cell Walls" LINK




Horticulture NIR-Spectroscopy Applications

"Redefining the impact of preharvest factors on peach fruit quality development and metabolism: A review" LINK

"Accurate nondestructive prediction of soluble solids content in citrus by nearinfrared diffuse reflectance spectroscopy with characteristic variable selection" LINK




Forestry and Wood Industry NIR Usage

"Spectrometric Prediction of Nitrogen Content in Different Tissues of Slash Pine Trees" LINK




Food & Feed Industry NIR Usage

"Effects of Irrigation Strategy and Plastic Film Mulching on Soil N 2 O Emissions and Fruit Yields of Greenhouse Tomato" LINK

"Mini shortwave Spectroscopic Techniques and Multivariate Statistical Analysis as a Tool for Testing intact Cocoa beans at farmgate for Quality Control in Ghana" LINK

"Foods : Gluten Conformation at Different Temperatures and Additive Treatments" LINK




Pharma Industry NIR Usage

"Revealing the Effect of Heat Treatment on the Spectral Pattern of Unifloral Honeys Using Aquaphotomics" LINK

"Biomedicines : Pathophysiological Response to SARS-CoV-2 Infection Detected by Infrared Spectroscopy Enables Rapid and Robust Saliva Screening for COVID-19" LINK




Other

"Unraveling the potential of phenomic selection within and among diverse breeding material of maize (Zea mays L.)" LINK

"Applied Sciences : Impact of Pheidole fallax (Hymenoptera: Formicidae) as an Ecosystem Engineer in Rehabilitated Coal Mine Areas" LINK

"The Spectral Mixture Residual: A Source of LowVariance Information to Enhance the Explainability and Accuracy of Surface Biology and Geology Retrievals" LINK

"Glycosylated MoS2 Sheets for Capturing and Deactivating E. coli Bacteria: Combined Effects of Multivalent Binding and Sheet Size" LINK




NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 13, 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 13, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 13, 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)

"NIR Spectroscopy and Aquaphotomics Approach to Identify Soil Characteristics as a Function of the Sampling Depth" LINK

"Improving the multi-class classification of Alzheimer's disease with machine learning-based techniques: An EEG-fNIRS hybridization study" LINK

"A novel methodology for determining effectiveness of preprocessing methods in reducing undesired spectral variability in near infrared spectra" LINK

"NEAR INFRARED SPECTROSCOPY AS IN-LINE PAT TOOL FOR A ROBUST MOISTURE CONTENT DETERMINATION OF SPIN FREEZE-DRIED SAMPLES" LINK

"Near infrared‐based process analytical technology module for estimating gelatinization optimal point" LINK

"Near Infrared Technology in Agricultural Sustainability: Rapid Prediction of Nitrogen Content from Organic Fertilizer" LINK

"Gasoline octane number prediction from near-infrared spectroscopy with an ANN-based model" LINK

"Rapid On-site Identification of Geographical Origin and Storage Age of Tangerine Peel by Near-infrared Spectroscopy" LINK

"Empirical mode decomposition of near-infrared spectroscopy signals for predicting oil content in palm fruits" LINK

"Miniaturization in NIR Spectroscopy Reshapes Chemical Analysis" LINK

"Unscrambling spectral interference and matrix effects in Vitis vinifera Vis-NIR spectroscopy: Towards analytical grade 'in vivo'sugars and acids quantification" LINK

"Research Progress of Bionic Materials Simulating Vegetation Visible-Near Infrared Reflectance Spectra" LINK

"Latent Variable Machine Learning Methods Applied for NIR Quantitative Analysis of Coffee" LINK

"Identification of informative spectral ranges for predicting major chemical constituents in corn using NIR spectroscopy" LINK

"Vis-NIR Spectroscopy and Machine Learning Methods for the Discrimination of Transgenic Brassica napus L. and Their Hybrids with B. juncea" LINK

"Applied Sciences : Hidden Information in Uniform Design for Visual and Near-Infrared Spectrum and for Inkjet Printing of Clothing on Canvas to Enhance Urban Security" LINK

"LIONirs: flexible Matlab toolbox for fNIRS data analysis" LINK




Raman Spectroscopy

"Raman Spectroscopic Detection and Quantification of Macro- and Microhematuria in Human Urine" LINK




Hyperspectral Imaging (HSI)

"Prediction of total carotenoids, color and moisture content of carrot slices during hot air drying using noninvasive hyperspectral imaging technique" LINK

"Growth simulation of Pseudomonas fluorescens in pork using hyperspectral imaging" LINK

"Estimation of Leaf Water Content of Different Leaves from Different Species Using Hyperspectral Reflectance Data" LINK




Chemometrics and Machine Learning

"Automation : Predictive Performance of Mobile Vis-NIR Spectroscopy for Mapping Key Fertility Attributes in Tropical Soils through Local Models Using PLS and ANN" LINK

"Prediction of South American Leaf Blight and Disease-Induced Photosynthetic Changes in Rubber Tree, Using Machine Learning Techniques on Leaf Hyperspectral ..." LINK

"Proximal spectroscopy sensing for sugarcane quality prediction and spatial variability mapping" LINK

"Variable Selection Based on Gray Wolf Optimization Algorithm for the Prediction of Saponin Contents in Xuesaitong Dropping Pills Using NIR Spectroscopy" | LINK

"Prediction of soil organic matter content based on characteristic band selection method" LINK

"Sensors : Algorithm of Stability-Analysis-Based Feature Selection for NIR Calibration Transfer" LINK

"Modelling soil water retention and water‐holding capacity with visible-near infrared spectra and machine learning" LINK

"Machine learning for atherosclerotic tissue component classification in combined near-infrared spectroscopy intravascular ultrasound imaging: Validation against ..." LINK

"Modelling soil water retention and waterholding capacity with visiblenear infrared spectra and machine learning" LINK

"Cancers : Novel Non-Invasive Quantification and Imaging of Eumelanin and DHICA Subunit in Skin Lesions by Raman Spectroscopy and MCR Algorithm: Improving Dysplastic Nevi Diagnosis" LINK




Spectroscopy

"Evaluation of portable vibrational spectroscopy for identifying plasticizers in dairy tubing" LINK




Optics for Spectroscopy

"Chemosensors : Carbocyanine-Based Fluorescent and Colorimetric Sensor Array for the Discrimination of Medicinal Compounds" LINK

"Platinum(II)Acetylide Conjugated Polymer Containing AzaBODIPY Moieties for Panchromatic Photodetectors" LINK




Equipment for Spectroscopy

"Polymers : Role of Macrodiols in the Synthesis and Thermo-Mechanical Behavior of Anti-Tack Water Borne Polyurethane Dispersions" LINK




Process Control and NIR Sensors

"A Perfect Pair: Stabilized Black Phosphorous Nanosheets Engineering with Antimicrobial Peptides for Robust Multidrug Resistant Bacteria Eradication" LINK




Environment NIR-Spectroscopy Application

"Long-Term Liming Reduces the Emission and Temperature Sensitivity of N2o Via Altering Denitrification Functional Gene Ratio in Acidic Soil" LINK

"Environmental metabolomics approaches to identify and enhance secondary compounds in medicinal plants for bio-based plant protection" LINK

"Soil moisture determines nitrous oxide emission and uptake" LINK

"Remote Sensing : Evaluating the Capability of Satellite Hyperspectral Imager, the ZY1-02D, for Topsoil Nitrogen Content Estimation and Mapping of Farmlands in Black Soil Area, China" LINK

"Remote Sensing : Extending the GOSAILT Model to Simulate Sparse Woodland Bi-Directional Reflectance with Soil Reflectance Anisotropy Consideration" LINK




Agriculture NIR-Spectroscopy Usage

"Evaluation of Near-Infrared Reflectance and Transflectance Sensing System for Predicting Manure Nutrients" LINK

"Ecoenzymatic stoichiometry reflects the regulation of microbial carbon and nitrogen limitation on soil nitrogen cycling potential in arid agriculture ecosystems" | LINK

"Remote Sensing : Phenotypic Traits Estimation and Preliminary Yield Assessment in Different Phenophases of Wheat Breeding Experiment Based on UAV Multispectral Images" LINK

"Agronomy : Evaluation of Methods for Measuring Fusarium-Damaged Kernels Wheat" LINK

"Agriculture : Non-Destructive Detection of pH Value of Kiwifruit Based on Hyperspectral Fluorescence Imaging Technology" LINK

"Agronomy : Optical Spectrometry to Determine Nutrient Concentrations and other Physicochemical Parameters in Liquid Organic Manures: A Review" LINK

"Agriculture : The Effect of Tytanit on Fibre Fraction Content in Medicago x varia T. Martyn and Trifolium pratense L. Cell Walls" LINK




Horticulture NIR-Spectroscopy Applications

"Redefining the impact of preharvest factors on peach fruit quality development and metabolism: A review" LINK

"Accurate nondestructive prediction of soluble solids content in citrus by nearinfrared diffuse reflectance spectroscopy with characteristic variable selection" LINK




Forestry and Wood Industry NIR Usage

"Spectrometric Prediction of Nitrogen Content in Different Tissues of Slash Pine Trees" LINK




Food & Feed Industry NIR Usage

"Effects of Irrigation Strategy and Plastic Film Mulching on Soil N 2 O Emissions and Fruit Yields of Greenhouse Tomato" LINK

"Mini shortwave Spectroscopic Techniques and Multivariate Statistical Analysis as a Tool for Testing intact Cocoa beans at farmgate for Quality Control in Ghana" LINK

"Foods : Gluten Conformation at Different Temperatures and Additive Treatments" LINK




Pharma Industry NIR Usage

"Revealing the Effect of Heat Treatment on the Spectral Pattern of Unifloral Honeys Using Aquaphotomics" LINK

"Biomedicines : Pathophysiological Response to SARS-CoV-2 Infection Detected by Infrared Spectroscopy Enables Rapid and Robust Saliva Screening for COVID-19" LINK




Other

"Unraveling the potential of phenomic selection within and among diverse breeding material of maize (Zea mays L.)" LINK

"Applied Sciences : Impact of Pheidole fallax (Hymenoptera: Formicidae) as an Ecosystem Engineer in Rehabilitated Coal Mine Areas" LINK

"The Spectral Mixture Residual: A Source of LowVariance Information to Enhance the Explainability and Accuracy of Surface Biology and Geology Retrievals" LINK

"Glycosylated MoS2 Sheets for Capturing and Deactivating E. coli Bacteria: Combined Effects of Multivalent Binding and Sheet Size" 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

Start Calibrate – NIR Quick Guide / Kalibrierung starten – NIR Kurzanleitung / Avvio della calibrazione – Guida rapida NIR


More Details

Quick Start NIR Workflow: step by step

1.
Check if your NIR-Device Data Format is directly supported (anyway you can convert to JCAMP) :
NIR-Predictor supported Spectral Data File Formats

2.
Download the free NIR-Predictor Software that contains demo data so you can play with it to see if it is the way you want analyse your NIR spectra (no registration needed) :
NIR-Predictor Download

3.
With your "NIR device" measurement software:

  • measure samples with NIR, that gets you spectra files,
  • label them with a proper sample name, so you know which is which,
  • and determine quantitative reference values by Laboratory reference method.
  • at least 60 samples with different contents is needed for a minimal calibration.
  • NIR-Predictor helps to create a template file (.csv) to enter the Lab values.

4.
Creating your own Calibrations with NIR-Predictor to combine your NIR and Lab data for a calibration request :
watch Video
read Manual

Videos



Mehr Details

Schnellstart NIR-Workflow: Schritt für Schritt

1.
Überprüfen Sie, ob Ihr NIR-Geräte-Datenformat direkt unterstützt wird (sonst können Sie nach JCAMP konvertieren). :
NIR-Predictor supported Spectral Data File Formats

2.
Laden Sie die kostenlose NIR-Predictor Software herunter, die Demo-Daten enthält, damit Sie mit ihr spielen können, um zu sehen, ob es die Art und Weise ist, wie Sie Ihre NIR-Spektren analysieren wollen (keine Registrierung erforderlich): :
NIR-Predictor Download

3.
Mit Ihrer "NIR Instrument" Messsoftware :

  • Proben mit NIR messen, das liefert Ihnen Spektrendateien,
  • kennzeichnen Sie sie mit einem richtigen Probennamen, damit Sie wissen, was was was ist.
  • Bestimmung der quantitativen Referenzwerte durch die Laborreferenzmethode.
  • Für eine Minimalkalibrierung werden mindestens 60 vermessene Proben mit unterschiedlichem Inhalt benötigt.
  • Der NIR-Predictor hilft bei der Erstellung einer Vorlagendatei (.csv) zur Eingabe der Lab-Werte.

4.
Erstellen Sie Ihre eigenen Kalibrierungen mit dem NIR-Predictor, um Ihre NIR- und Lab-Daten für eine Kalibrierungsanforderung zu kombinieren :
siehe Video
lese Handbuch

Videos



Maggiori dettagli

Avvio rapido del flusso di lavoro NIR: passo dopo passo

1.
Controlla se il tuo NIR-Device Data Format è supportato direttamente (in ogni caso puoi convertirlo in JCAMP) :
NIR-Predictor supported Spectral Data File Formats

2.
Scarica il software gratuito NIR-Predictor che contiene i dati dimostrativi per poter giocare con esso per vedere se è il modo in cui vuoi analizzare i tuoi spettri NIR (non è necessaria la registrazione) :
NIR-Predictor Download

3.
Con il software di misura "NIR device" :

  • misurare i campioni con il NIR, in modo da ottenere i file degli spettri,
  • etichettarli con un nome di esempio corretto, in modo da sapere qual è quale,
  • e determinare i valori quantitativi di riferimento con il metodo di riferimento di laboratorio.
  • sono necessari almeno 60 campioni con contenuti diversi per una calibrazione minima.
  • NIR-Predictor aiuta a creare un file modello (.csv) per inserire i valori di laboratorio.

4.
Creazione di calibrazioni personalizzate con NIR-Predictor per combinare i dati NIR e di laboratorio per una richiesta di calibrazione :
vedi il Video
leggi il manuale

Videos