Spectroscopy and Chemometrics News Weekly #19, 2019Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #19, 2019Spettroscopia e Chemiometria Weekly News #19, 2019

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Spectroscopy and Chemometrics News Weekly 18, 2019 | NIRS NIR Spectroscopy Chemometrics Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality Checking LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 18, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse Labor LINK

Spettroscopia e Chemiometria Weekly News 18, 2019 | NIRS NIR Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem prediction models LINK

This week's NIR news Weekly is sponsored by YourCompanyNameHere - BestNIRinstruments. Check out their product page ... link

Chemometrics

"Correlation between the composition of green Arabica coffee beans and the sensory quality of coffee brews" LINK

"High accuracy deternimation of Angelica dahurica origin based on near infrared spectroscopy and random forest pruning algorithm" LINK

"Rapid analysis of the Tanreqing injection by near-infrared spectroscopy combined with least squares support vector machine and Gaussian process modeling techniques." LINK

"Classification and Identification of Pesticide Residues in Cucumber Based on Near Infrared Spectroscopy" LINK

"Analytical strategies based on near infrared spectroscopy and multivariate calibration for rapid quantification of florfenicol at low-concentrations in medicated-feed pellets" LINK

"Lighting the Ivory Track: Are Near Infrared and Chemometrics Up to the Job? A Proof of Concept" LINK

"NIR spectroscopy-multivariate analysis for discrimination and bioactive compounds prediction of different Citrus species peels" | /> LINK

"Fast and Non-Destructive Prediction of Moisture Content and Chologenic Acid of Intact Coffee Beans Using Near Infrared Reflectance Spectroscopy" LINK

"Characterization of Edible Oils Using NIR Spectroscopy and Chemometric Methods" LINK

"A diffuse reflectance NIR spectroscopy method for determine drug concentration in pharmaceutical production tablets based on a PLS calibration model from manufactured tablets" LINK

Near Infrared (NIR) Spectroscopy

"Estimating forest soil organic carbon content using vis-NIR spectroscopy: Implications for large-scale soil carbon spectroscopic assessment" LINK

"Multivariate data analysis of near-infrared spectra of cultivation medium powders for mammalian cells" LINK

"Rapid-Detection Sensor for Rice Grain Moisture Based on NIR Spectroscopy" LINK

"REC-NIR-BLACK carbon-black free masterbatch provides a second life for black plastic packaging by allowing scanning by near-infrared technology for automated sorting at recovery facilities." LINK

"Near-infrared spectroscopy for food quality evaluation" LINK

"Near infrared spectroscopy as an alternative method for rapid determination of the solidification point of 2,4,6-trinitrotoluene in production" TNT LINK

"Spectral noise-to-signal ratio priority method with application for visible and near-infrared analysis of whole blood viscosity" LINK

Spectral Imaging

"Multispectral Approach for Identifying Invasive Plant Species Based on Flowering Phenology Characteristics" Remote Sensing LINK

Equipment

"Comparative performance of bench and portable near infrared spectrometers for measuring wood samples of two Eucalyptus species (E. pellita and E. benthamii)" LINK

"Non-destructive determination of silymarin in Silybum marianum extracts with a handheld near infrared spectrometer" LINK

Food & Feed

"A rapid classification of wheat flour protein content using artificial neural network model based on bioelectrical properties" LINK

Laboratory

"Non-destructive Methods to Determine Ripening Quality of Intact Muskmelon" LINK

.

CalibrationModel.com

Chemometrics

Near Infrared (NIR) Spectroscopy

Spectral Imaging

"Multispectral Approach for Identifying Invasive Plant Species Based on Flowering Phenology Characteristics" Remote Sensing LINK

Equipment

Food & Feed

"A rapid classification of wheat flour protein content using artificial neural network model based on bioelectrical properties" LINK

Laboratory

"Non-destructive Methods to Determine Ripening Quality of Intact Muskmelon" LINK

.

CalibrationModel.com

Chemometrics

Near Infrared (NIR) Spectroscopy

Spectral Imaging

"Multispectral Approach for Identifying Invasive Plant Species Based on Flowering Phenology Characteristics" Remote Sensing LINK

Equipment

Food & Feed

"A rapid classification of wheat flour protein content using artificial neural network model based on bioelectrical properties" LINK

Laboratory

"Non-destructive Methods to Determine Ripening Quality of Intact Muskmelon" LINK

.

May 6, 2019

Spectroscopy and Chemometrics News Weekly #18, 2019Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #18, 2019Spettroscopia e Chemiometria Weekly News #18, 2019

CalibrationModel.com

Spectroscopy and Chemometrics News Weekly 17, 2019 | NIRS NIR Spectroscopy Chemometrics Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality Checking LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 17, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 17, 2019 | NIRS Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità LINK

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

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

Chemometrics

"Comparison and rapid prediction of lignocellulose and organic elements of a wide variety of rice straw based on near infrared spectroscopy" LINK

"Rapid Determination of Green Tea Origins by Near-Infrared Spectroscopy and Multi-Wavelength Statistical Discriminant Analysis" LINK

"Automated Chinese medicinal plants classification based on machine learning using leaf morpho-colorimetry, fractal dimension and visible/near infrared spectroscopy" LINK

"Monitoring model for predicting maize moisture content at the grain-filling stage using near-infrared spectroscopy and a small sample size" LINK

"Near-infrared-based models for lignin syringyl/guaiacyl ratio of Eucalyptus benthamii and E. pellita using a streamlined thioacidolysis procedure as the reference method" LINK

"Arthroscopic Near-Infrared Spectroscopic Prediction of Human Meniscus Properties" LINK

"变量优选补正算法的鲜枣可溶性固形物检测模型传递方法研究" 变量优选补正算法的鲜枣可溶性固形物检测模型传递方法研究 Model Transfer Method of Fresh Jujube Soluble Solids Detection Using Variables Optimization and Correction Algorithms LINK

New software article published in | No excuse for not using realistic noise when evaluating proposed algorithms anymore! chemometrics machinelearning statistics LINK

"Fine root lignin content is well predictable with near-infrared spectroscopy." LINK

Near Infrared

"Abundance and composition of kaolinite on Mars: Information from NIR spectra of rocks from acid-alteration environments, Riotinto, SE Spain" LINK

"Distinct Difference in Sensitivity of NIR vs. IR Bands of Melamine to Inter-Molecular Interactions with Impact on Analytical Spectroscopy Explained by Anharmonic Quantum Mechanical Study" LINK

" Association Between Near Infrared Spectroskopy (NIRS) and Normobaric and Hyperbaric Oxygen Treatment in Acute Carbon Monoxide Poisoning" LINK

"Sensors, Vol. 19, Pages 2076: Towards Integrated Mid-Infrared Gas Sensors" LINK

"Detection of Acrylamide in Food Using Near Infrared Spectroscopy" LINK

"Determination of natural rubber and resin content of guayule fresh biomass by near infrared spectroscopy" LINK

"Automated Preprocessing of Near Infrared Spectroscopic Data" LINK

"Evaluation of a low-cost portable near-infrared spectrophotometer for in situ cocaine profiling." LINK

"Application of a Fourier transformnear infrared reflectance spectroscopy method for the rapid proximate analysis of the greenshell mussel (Perna canaliculus) and king (Chinook) salmon (Oncorhynchus tshawytscha)" LINK

" Assessment of the chemical change in heat treated pine wood by near infrared spectroscopy" LINK

"Characterisation of organic colourants in ukiyo-e prints by Fourier transform near infrared fibre optics reflectance spectroscopy" LINK

" Plastic Solid Waste identification system based on Near Infrared Spectroscopy in combination with support vector machine" LINK

"Development and application of Fourier transform infrared spectroscopy for detection of milk adulteration in practice" FTIR LINK

"Near-Infrared Light Emitting Diode Based Non-Invasive Glucose Detection System." LINK

"Determination of cellulose, hemicellulose and lignin content using near-infrared spectroscopy in flax fiber" LINK

Raman

"Raman spectroscopic discrimination of normal and cancerous lung tissues." LINK

Spectral Imaging

"A new low-cost portable multispectral optical device for precise plant status assessment" LINK

"Evaluation of Fire Severity Indices Based on Pre- and Post-Fire Multispectral Imagery Sensed from UAV" Remote Sensing LINK

Equipment

"On site monitoring of Grana Padano cheese production using portable spectrometers" LINK

Agriculture

"Assessing the potential of two customized fiber-optic probes for on-site analysis of bulk feed grains" LINK

"A Cost Effective and Field Deployable System for Soil Macronutrient Analysis Based on Near-Infrared Reflectance Spectroscopy" LINK

Food & Feed

"Freshness Evaluation in Chub Mackerel (Scomber japonicus) Using Near-Infrared Spectroscopy Determination of the Cadaverine Content." Fish Fisheries FoodSafety FoodProtection LINK

Pharma

"An update on contribution of hot-melt extrusion technology to novel drug delivery in the 21st century: part I" LINK

Other

" Evaluación de dos atributos de calidad críticos en la producción de formas farmacéuticas sólidas utilizando la espectroscopia de infrarrojo cercano" LINK

CalibrationModel.com

Chemometrics

Near Infrared

Raman

"Raman spectroscopic discrimination of normal and cancerous lung tissues." LINK

Spectral Imaging

Equipment

"On site monitoring of Grana Padano cheese production using portable spectrometers" LINK

Agriculture

Food & Feed

"Freshness Evaluation in Chub Mackerel (Scomber japonicus) Using Near-Infrared Spectroscopy Determination of the Cadaverine Content." Fish Fisheries FoodSafety FoodProtection LINK

Pharma

"An update on contribution of hot-melt extrusion technology to novel drug delivery in the 21st century: part I" LINK

Other

" Evaluación de dos atributos de calidad críticos en la producción de formas farmacéuticas sólidas utilizando la espectroscopia de infrarrojo cercano" LINK

CalibrationModel.com

Chemometrics

Near Infrared

Raman

"Raman spectroscopic discrimination of normal and cancerous lung tissues." LINK

Spectral Imaging

Equipment

"On site monitoring of Grana Padano cheese production using portable spectrometers" LINK

Agriculture

Food & Feed

"Freshness Evaluation in Chub Mackerel (Scomber japonicus) Using Near-Infrared Spectroscopy Determination of the Cadaverine Content." Fish Fisheries FoodSafety FoodProtection LINK

Pharma

"An update on contribution of hot-melt extrusion technology to novel drug delivery in the 21st century: part I" LINK

Other

" Evaluación de dos atributos de calidad críticos en la producción de formas farmacéuticas sólidas utilizando la espectroscopia de infrarrojo cercano" LINK

April 29, 2019

Spectroscopy and Chemometrics News Weekly #17, 2019Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #17, 2019Spettroscopia e Chemiometria Weekly News #17, 2019

CalibrationModel.com

"Automated Analytical Method Development for NIRS. Software/Service Solution for Automation of Machine Learning for the NIR-Spectroscopy Domain." LINK

Develop near infrared spectroscopy applications & freeing up hours of analysts time QAQC QualityManager QualityAssurance LINK

Do you use NIR Spectroscopy for Quality Control? You need to know | GLP GMP QbD PAT OQ PQ pauto testing labs LINK

Increase Your Profit with optimized NIR Accuracy QA QC Food Feed Lab Agriculture crop grain soybean LINK

NIR Machine Learning as a Service, a Game Changer for Productivity and Accuracy/Precision! ( NIRS Spectroscopy AI MLaaS ) LINK

Spectroscopy and Chemometrics News Weekly 16, 2019 | NIRS NIR Spectroscopy Chemometrics Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QC Testing Quality Checking LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 16, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse Lab LINK

Spettroscopia e Chemiometria Weekly News 16, 2019 | NIRS Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità LINK

These are the "pigments" we have in our NIR application database LINK

We develop Near-Infrared (NIR) Spectroscopy Calibration Models and Software for Chemical Physical Parameter Analysis of Food, Feed, Process ... IoT Sensors | NIRS Analytical Laboratory Lab Analysis QC LINK

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

Chemometrics

"Study on identification of different producing areas of Gastrodia elata using multivariable selection and two-dimensional correlation spectroscopy of near infrared spectroscopy." LINK

"Evaluating matcha tea quality index using portable NIR spectroscopy coupled chemometric algorithms" LINK

"A transferable spectroscopic diagnosis model for predicting arsenic contamination in soil." LINK

"Evaluating matcha tea quality index using portable NIR spectroscopy coupled chemometric algorithms." LINK

"Cultivar Classification of Single Sweet Corn Seed Using Fourier Transform Near-Infrared Spectroscopy Combined with Discriminant Analysis" LINK

"Comparative nondestructive classification of partial waxy wheats using near-infrared (NIR) and Raman spectroscopy" LINK

Near Infrared

"Cr3+Doped Broadband NIR Garnet Phosphor with Enhanced Luminescence and its Application in NIR Spectroscopy" LINK

"In-line Application of Visible and Near-Infrared Diffuse Reflectance Spectroscopy to Identify Apple Varieties" LINK

"High-Throughput Biochemical Fingerprinting of Oleaginous Aurantiochytrium sp. Strains by Fourier Transform Infrared Spectroscopy (FT-IR) for Lipid and Carbohydrate Productions" LINK

"On-line detection of toxigenic fungal infection in wheat by visible/near infrared spectroscopy" LINK

"Shortwave Near-Infrared Spectroscopy for Rapid Detection of Aflatoxin B1 Contamination in Polished Rice." LINK

"Detection of cracked shell in intact aromatic young coconut using near infrared spectroscopy and acoustic response methods" LINK

"ASSESSMENT OF THE CHEMICAL CHANGE IN HEAT TREATED PINE WOOD BY NEAR INFRARED SPECTROSCOPY " LINK

Raman

Microscope-less lab-on-a-chip Raman spectroscopy of cell membranes | TW05 LINK

"Analysis of Cellulose and Lignocellulose Materials by Raman Spectroscopy: A Review of the Current Status" Molecules LINK

Hyperspectral

Simultaneous Hyperspectral Imaging & LiDAR Sensing Platform LINK

Process Control

"Feedforward and Feedback Control of a Pharmaceutical Coating Process" LINK

Agriculture

"Evaluation of the Optimum Harvesting Maturity of Makhwaen Fruit for the Perfumery Industry" Agriculture LINK

"Foods, Vol. 8, Pages 126: Physicochemical Properties and Pollen Profile of Oak Honeydew and Evergreen Oak Honeydew Honeys from Spain: A Comparative Study" LINK

"Early Visual Detection of Wheat Stripe Rust Using Visible/Near-Infrared Hyperspectral Imaging." LINK

"Foods, Vol. 8, Pages 137: Influence of Supplemental Feed Choice for Pasture-Based Cows on the Fatty Acid and Volatile Profile of Milk" LINK

Food & Feed

"Grape and juice handling: Assessing the use of visible and near infrared spectroscopy to rapidly evaluate the health status of grapes entering wineries" LINK

Pharma

"A rapid and non-destructive method for simultaneous determination of aflatoxigenic fungus and aflatoxin contamination on corn kernels." LINK

Laboratory

"A Strategy to Assess Quality Consistency of Drug Products." LINK

"Outsourcing Spectroscopic Analysis?" laboratory spectrometer Lab LINK

Other

"Classifying with confidence using Bayes rule and kernel density estimation" LINK

"Reestablishment of Protium cordatum (Burseraceae) based on integrative taxonomy" LINK

AI Trained on Decades of Food Research Is Making Brand-New Foods | by MachineLearning DeepLearning Cc LINK

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

CalibrationModel.com

Chemometrics

Near Infrared

Raman

Hyperspectral

Simultaneous Hyperspectral Imaging & LiDAR Sensing Platform LINK

Process Control

"Feedforward and Feedback Control of a Pharmaceutical Coating Process" LINK

Agriculture

Food & Feed

"Grape and juice handling: Assessing the use of visible and near infrared spectroscopy to rapidly evaluate the health status of grapes entering wineries" LINK

Pharma

"A rapid and non-destructive method for simultaneous determination of aflatoxigenic fungus and aflatoxin contamination on corn kernels." LINK

Laboratory

"A Strategy to Assess Quality Consistency of Drug Products." LINK

"Outsourcing Spectroscopic Analysis?" laboratory spectrometer Lab LINK

Other

CalibrationModel.com

Chemometrics

Near Infrared

Raman

Hyperspectral

Simultaneous Hyperspectral Imaging & LiDAR Sensing Platform LINK

Process Control

"Feedforward and Feedback Control of a Pharmaceutical Coating Process" LINK

Agriculture

Food & Feed

"Grape and juice handling: Assessing the use of visible and near infrared spectroscopy to rapidly evaluate the health status of grapes entering wineries" LINK

Pharma

"A rapid and non-destructive method for simultaneous determination of aflatoxigenic fungus and aflatoxin contamination on corn kernels." LINK

Laboratory

"A Strategy to Assess Quality Consistency of Drug Products." LINK

"Outsourcing Spectroscopic Analysis?" laboratory spectrometer Lab LINK

Other

April 8, 2019April 8, 2019

Spectroscopy and Chemometrics News Weekly #14, 2019Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #14, 2019Spettroscopia e Chemiometria Weekly News #14, 2019

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

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

CalibrationModel.com

Spectroscopy and Chemometrics News Weekly 13, 2019 | NIRS NIR Spectroscopy Chemometrics analysis Spectral Spectrometer Spectrometric Analytical Sensors QC Lab Labs Laboratories Laboratory LabServices Software Testing Quality Checking LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 13, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Spektral Sensor Nahinfrarot Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse Qualitätslabor LINK

Spettroscopia e Chemiometria Weekly News 13, 2019 | NIRS Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Sensore Attrezzatura analitica Laboratorio analisi prova qualità LINK

Chemometrics

"Fraud detection in hen housing system declared on the eggs' label: An accuracy method based on UV-VIS-NIR spectroscopy and chemometrics." LINK

"Use of near infrared reflectance spectroscopy to predict chemical composition of some pastoral species appeased by the dromedaryin southern Tunisia" LINK

"On-line vis-NIR spectroscopy prediction of soil organic carbon using machine learning" LINK

" Kısmi En Küçük Kareler Regresyonu (KEKKR) ve Yapay Sinir Ağı (YSA) Modelleri Kullanarak, Kanopi Kızılötesi Spektroskopisi (KS) ile Kış Buğdayında …" LINK

"Application of invasive weed optimization and least square support vector machine for prediction of beef adulteration with spoiled beef based on visible near-infrared (Vis-NIR) hyperspectral imaging." LINK

"Comparison of multivariate models and variable selection algorithms for rapid analysis of the chemical composition of field crops" NIRS NIR LINK

Near Infrared

Near-infrared spectroscopy could improve flu vaccine manufacturing NIR virus cell near infrared spectroscopy |rld/magazine/article/707/near-infrared-spectroscopy-could-improve-flu-vaccine-manufacturin.XKcA_t2OuwY.twitter LINK

"Calibration development for nutritional evaluation of Yam (Dioscorea sp.) using Near-Infrared Reflectance Spectrophotometry (NIRS)" LINK

"DETERMINATION OF CAROTENOIDS AND DOBI CONTENT IN CRUDE PALM OIL BY SPECTROSCOPY TECHNIQUES: COMPARISON OF RAMAN AND FT-NIR SPECTROSCOPY" FTNIR NIRS LINK

"Feedforward and Feedback Control of a Pharmaceutical Coating Process." NIRS LINK

"Development of Portable Non-Invasive Blood Glucose Measuring Device Using NIR Spectroscopy" LINK

"Akurasi Metode NIRS dalam Prediksi Kandungan Kimia Bubuk Green Coffee Bondowoso dengan Model Kubelka-Munk" LINK

"Identification of fiber added to semolina by near infrared (NIR) spectral techniques" LINK

Infrared

"Comparing the Potential of Near-and Mid-Infrared Spectroscopy in Determining the Freshness of Strawberry Powder from Freshly Available and Stored Strawberry" LINK

"Near-Infrared Imaging of Artificial Enamel Caries Lesions with a Scanning Fiber Endoscope" Sensors LINK

"Near-infrared imaging of diseases: A nanocarrier approach." LINK

"N-Linked Glycosylation and Near-Infrared Spectroscopy in the Diagnosis of Prostate Cancer." LINK

"Identification of Coal Geographical Origin Using Near Infrared Sensor Based on Broad Learning" LINK

"Online determination of chemical and physical properties of Poly(ethylene vinyl acetate) pellets using a novel method of Near-Infrared spectroscopy combined with angle transform" LINK

"Study on the Processing Technology of Calamine Calcination by Near-Infrared Spectroscopy" LINK

"A new approach to vibrational sum frequency generation spectroscopy using near infrared pulse shaping." LINK

"Fourier transform near-infrared spectroscopy coupled to a long fibre optic head for the quality control of IBERIAN pork loins: Intact versus minced" LINK

Raman

"Recent Advancement in the Surface-Enhanced Raman Spectroscopy-Based Biosensors for Infectious Disease Diagnosis" LINK

Facts

"A Machine Learning Approach for Biomass Characterization" LINK

Equipment

"Classification of Food Powders with Open Set using Portable VIS-NIR Spectrometer" LINK

Future

"The 2019 Spectroscopy Salary Survey: A Surprising Downtrend" TL;DR : "The 2019 Spectroscopy salary survey results showed a 14% decrease in average base salaries compared to 2018. " LINK

Environment

" Predicting bioavailability change of complex chemical mixtures in contaminated soils using visible and near-infrared spectroscopy and random forest regression" LINK

"Remote Sensing Techniques for Soil Organic Carbon Estimation: A Review" LINK

Agriculture

1000ogs project on regulated deficit irrigation in orchards of apple blueberry cherry considering the actual fruit developmental stage based on its size & brightening of ground colour (healthy chlorophyll, pheophytin_a) to save water. LINK

"Influence of moisture and grain sizes on the analysis of nutrients in German agricultural soils using DP-LIBS" LINK

"Change in the Microviscosity of Erythrocyte Membranes and Proteins in Blood Plasma after Graphene Oxide Addition: The ESR Spectroscopy Study" LINK

Pharma

"Spectral interval combination optimization (ICO) on rapid quality assessment of Solanaceae plant: a validation study" LINK

Laboratory

"On-farm instant quality analysis" by Cherney Jerry and Cherney Debbie (Progressive Dairyman ) forage laboratory NIR NIRS handheld LINK

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

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

CalibrationModel.com

Chemometrics

Near Infrared

Infrared

Raman

"Recent Advancement in the Surface-Enhanced Raman Spectroscopy-Based Biosensors for Infectious Disease Diagnosis" LINK

Facts

"A Machine Learning Approach for Biomass Characterization" LINK

Equipment

"Classification of Food Powders with Open Set using Portable VIS-NIR Spectrometer" LINK

Future

"The 2019 Spectroscopy Salary Survey: A Surprising Downtrend" TL;DR : "The 2019 Spectroscopy salary survey results showed a 14% decrease in average base salaries compared to 2018. " LINK

Environment

Agriculture

Pharma

"Spectral interval combination optimization (ICO) on rapid quality assessment of Solanaceae plant: a validation study" LINK

Laboratory

CalibrationModel.com

Chemometrics

Near Infrared

Infrared

Raman

"Recent Advancement in the Surface-Enhanced Raman Spectroscopy-Based Biosensors for Infectious Disease Diagnosis" LINK

Facts

"A Machine Learning Approach for Biomass Characterization" LINK

Equipment

"Classification of Food Powders with Open Set using Portable VIS-NIR Spectrometer" LINK

Future

"The 2019 Spectroscopy Salary Survey: A Surprising Downtrend" TL;DR : "The 2019 Spectroscopy salary survey results showed a 14% decrease in average base salaries compared to 2018. " LINK

Environment

Agriculture

Pharma

"Spectral interval combination optimization (ICO) on rapid quality assessment of Solanaceae plant: a validation study" LINK

Laboratory

"On-farm instant quality analysis" by Cherney Jerry and Cherney Debbie (Progressive Dairyman ) forage laboratory NIR NIRS handheld LINK

April 1, 2019

Spectroscopy and Chemometrics News Weekly #13, 2019Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #13, 2019Spettroscopia e Chemiometria Weekly News #13, 2019

Laboratory Automation with NIRS Lab Software for Near-Infrared Spectroscopy Analysis Predictions for QA/QC Testing Checking Labs #Food #LabServices #NIRS LINK

Increase Your Profit with optimized NIR Accuracy QA QC Food Feed Lab Agriculture crop grain soybean LINK

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

CalibrationModel.com

Spectroscopy and Chemometrics News Weekly 12, 2019 | NIRS NIR Spectroscopy Chemometrics analysis Spectral Spectrometer Spectrometric Analytical Sensors Laboratory Analysis Testing Quality Checking QC QA LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 12, 2019 | NIRS NIR Spektroskopie Chemometrie Analyse Spektrometer Spektral Sensor Nahinfrarot Analysengeräte Labs Analysemethode Analyzer Nahinfrarotspektroskopie LINK

Spettroscopia e Chemiometria Weekly News 12, 2019 | NIRS Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Sensore Attrezzatura analitica Laboratorio analisi prova qualità LINK

Chemometrics

"Fast Inline Tobacco Classification by Near-Infrared Hyperspectral Imaging and Supporting Vector Machines-Discriminant Analysis" LINK

"Optimized Prediction of Reducing Sugars and Dry Matter of Potato Frying by FT-NIR Spectroscopy on Peeled Tubers" LINK

"Identification of phenolic and alcoholic compounds in wine spirits and their classification by use of multivariate analysis" LINK

"Editorial: Chemometrics-based Spectroscopy for Pharmaceutical and Biomedical Analysis" LINK

"End‐to‐end quantitative analysis modeling of near‐infrared spectroscopy based on convolutional neural network" LINK

"Using interpretable fuzzy rule-based models for the estimation of soil organic carbon from VNIR/SWIR spectra and soil texture" LINK

"Fraud detection in hen housing system declared on the eggs' label: An accuracy method based on UV-VIS-NIR spectroscopy and chemometrics" LINK

"In vivo characterization of cervical remodeling throughout gestation using photoacoustic near-infrared spectra (Conference Presentation)" PANIR LINK

" Classification Method for Viability Screening of Naturally Aged Watermelon Seeds Using FT-NIR Spectroscopy" LINK

Near Infrared

"Potential of fourier transformed near-infrared (FT-NIR) spectroscopy for rapid analysis of elderberry (Sambucus nigra L.) fruits" LINK

NIRS quantification of lake sediment composition by multiple regression using end-member spectra | just published novel approach interpreting Near Infrared Spectra applied to lake sediments LINK

"Interferometric near-infrared spectroscopy (iNIRS) of human tissues in the presence of motion (Conference Presentation)" LINK

"玉米秸秆纤维素和半纤维素 NIRS 特征波长优选" "Optimization of Characteristic Wavelength Variables of Near Infrared Spectroscopy for Detecting Contents of Cellulose and Hemicellulose in Corn Stover" LINK

"可见-近红外光谱的古陶瓷断代分类识别" "Visible-Near Infrared Spectroscopy Based Chronological Classification and Identification of Ancient Ceramic" UV VIS NIRS LINK

"近红外光谱的古筝面板用木材等级识别研究" "A Method for Identifying Wood Grades of Chinese Zither Panel Based on Near Infrared Spectroscopy" NIRS LINK

"特征分层结合改进粒子群算法的近红外光谱特征选择方法研究" "Study on Feature Selection of Near Infrared Spectra Based on Feature Hierarchical Combining Improved Particle Swarm Optimization" LINK

"Application of vibrational spectroscopy for classification, authentication and quality analysis of mushroom: A concise review" NIRS LINK

Infrared

"Effect of the chain length on near-infrared spectra of 1-alcohols from methanol to 1-decanol" LINK

"Study of Bismuth-Containing Composites Based on Thermally Modified Porous Glass with Low Additions of P2O5 and Fluorine Ions by the Near Infrared Spectroscopy Method" LINK

"Quality evaluation of flue-cured tobacco by near infrared spectroscopy and spectral similarity method" LINK

"Using Near Infrared Spectroscopy to Quickly Analyze Different Nitrogens during the Shortcut Biological Removal of Nitrogen from a Polluted River" LINK

"Real-Time Release Testing of Herbal Extract Powder by Near-Infrared Spectroscopy considering the Uncertainty around Specification Limits" LINK

"Potential of near infrared spectroscopy as a rapid method to detect aflatoxins in brown rice" LINK

"木材种类的近红外光谱和模式识别" "Identification of Wood Species Based on Near Infrared Spectroscopy and Pattern Recognition Method" LINK

"Near infrared spectrometry of humic acid content in fertilizers at different levels of granularity" LINK

"Near infrared optical biosensor based on peptide functionalized single-walled carbon nanotubes hybrids for 2,4,6-trinitrotoluene (TNT) explosive detection." LINK

Equipment

"Development of a low cost SWIR spectrometer for low resource settings (Conference Presentation)" LINK

Food & Feed

"Using near-infrared (NIR) spectroscopy for rapid, quantitative detection of kojic acid in wheat flour." LINK

Chemical

"Conjugated Polymers with Benzothiadiazole and Benzotriazole Moieties for Polymer Solar Cells" LINK

Laboratory

"A strategy to assess quality consistency of drug products" LINK

"Advances in Nondestructive Methods for Meat Quality and Safety Monitoring" LINK

Other

"ウンシュウミカンでの β-クリプトキサンチンの可視・近赤外分光法による非破壊計測法" LINK

Laboratory Automation with NIRS Lab Software for Near-Infrared Spectroscopy Analysis Predictions for QA/QC Testing Checking Labs #Food #LabServices #NIRS LINK

Increase Your Profit with optimized NIR Accuracy QA QC Food Feed Lab Agriculture crop grain soybean LINK

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

CalibrationModel.com

Chemometrics

Near Infrared

Infrared

Equipment

"Development of a low cost SWIR spectrometer for low resource settings (Conference Presentation)" LINK

Food & Feed

"Using near-infrared (NIR) spectroscopy for rapid, quantitative detection of kojic acid in wheat flour." LINK

Chemical

"Conjugated Polymers with Benzothiadiazole and Benzotriazole Moieties for Polymer Solar Cells" LINK

Laboratory

"A strategy to assess quality consistency of drug products" LINK

"Advances in Nondestructive Methods for Meat Quality and Safety Monitoring" LINK

Other

CalibrationModel.com

Chemometrics

Near Infrared

Infrared

Equipment

"Development of a low cost SWIR spectrometer for low resource settings (Conference Presentation)" LINK

Food & Feed

"Using near-infrared (NIR) spectroscopy for rapid, quantitative detection of kojic acid in wheat flour." LINK

Chemical

"Conjugated Polymers with Benzothiadiazole and Benzotriazole Moieties for Polymer Solar Cells" LINK

Laboratory

"A strategy to assess quality consistency of drug products" LINK

"Advances in Nondestructive Methods for Meat Quality and Safety Monitoring" LINK

Other

"ウンシュウミカンでの β-クリプトキサンチンの可視・近赤外分光法による非破壊計測法" LINK

Spectroscopy and Chemometrics News Weekly #13, 2019Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #13, 2019Spettroscopia e Chemiometria Weekly News #13, 2019

CalibrationModel.com

Chemometrics

Near Infrared

Infrared

Equipment

"Development of a low cost SWIR spectrometer for low resource settings (Conference Presentation)" LINK

Food & Feed

"Using near-infrared (NIR) spectroscopy for rapid, quantitative detection of kojic acid in wheat flour." LINK

Chemical

"Conjugated Polymers with Benzothiadiazole and Benzotriazole Moieties for Polymer Solar Cells" LINK

Laboratory

"A strategy to assess quality consistency of drug products" LINK

"Advances in Nondestructive Methods for Meat Quality and Safety Monitoring" LINK

Other

CalibrationModel.com

Chemometrics

Near Infrared

Infrared

Equipment

"Development of a low cost SWIR spectrometer for low resource settings (Conference Presentation)" LINK

Food & Feed

"Using near-infrared (NIR) spectroscopy for rapid, quantitative detection of kojic acid in wheat flour." LINK

Chemical

"Conjugated Polymers with Benzothiadiazole and Benzotriazole Moieties for Polymer Solar Cells" LINK

Laboratory

"A strategy to assess quality consistency of drug products" LINK

"Advances in Nondestructive Methods for Meat Quality and Safety Monitoring" LINK

Other

CalibrationModel.com

Chemometrics

Near Infrared

Infrared

Equipment

"Development of a low cost SWIR spectrometer for low resource settings (Conference Presentation)" LINK

Food & Feed

"Using near-infrared (NIR) spectroscopy for rapid, quantitative detection of kojic acid in wheat flour." LINK

Chemical

"Conjugated Polymers with Benzothiadiazole and Benzotriazole Moieties for Polymer Solar Cells" LINK

Laboratory

"A strategy to assess quality consistency of drug products" LINK

"Advances in Nondestructive Methods for Meat Quality and Safety Monitoring" LINK

Other

"ウンシュウミカンでの β-クリプトキサンチンの可視・近赤外分光法による非破壊計測法" LINK

NIR-PredictorNIR-PrädiktorNIR-Predittore

New: NIR-Predictor V2.6 with new features

The new Version of the free NIR-Predictor
supports GRAMS .SPC, CSV, JCAMP and multiple native file formats
of miniature, mobile and desktop spectrometers
get your spectra analyced as easy as Drag’n’Drop.

Spectra Plots and Histograms on the Prediction Report

NIR-Predictor is an easy to use NIR software for all NIR devices
to produce quantitative results out of NIR data.
CalibrationModel Service provides development of
customized calibrations out of NIR and Lab data.
It allows to use NIR with your own customized
models without the need of Chemometric Software!
We do the Machine Leraning for your NIR-Spectrometer
and with the free NIR-Predictor you are
able to analyze new measured samples.
For NIR-Vendors we also offer the
Software Development Kit (SDK) for OEM Predictor use
via the Application Programming Interface (API).
Think of a sencod predictor engine,
as a second heart in your system.

NIR-Predictor with Demo Calibrations and supported NIR Vendors

Download

Key Features of NIR-Predictor

Super flexible prediction with automatic file format detection
Support for many mobile and desktop NIR Spectrometers file format
Application concept allows to group multiple Calibrations together for an Application
Prediction Report shows Histogram Charts of the tabulated prediction results
Sample based Properties File Creator for combining NIR and Lab reference data
Checked creation of a single file Calibration Request

Super flexible prediction

Loads multiple files at once in

different file-formats and …
different wave-ranges and wave-resolutions and …
predicts each spectrum with all compatible calibrations and …
merges the results in a report and …
saves the report as HTML.

It allows you to

comparing measurements
compare different calibrations
compare different spectrometers,
carry out your own round-robin amongst the vendors’ instruments.
compare different spectra file formats

With no configuration and no special menu command,
just drag & drop your data files.

Videos

Properties File Creator

A tool for the NIR-User to create the property file easily. It helps to create a CSV file from the measured spectra files with sample names and properties to edit in Spreadsheet/EXCEL software. Lets you enter Lab-Reference-Values in a sample-based manner, corresponding to your sample spectra for calibration. It contains clever automatic analysis mechanisms of inconsistencies in your raw-data to increase the data quality for calibration. Provides detailed analyzer information for manual data cleanup when needed.

It’s time saving and less error prone because you DON’T need to open each spectrum file separately in an editor and copy the spectral values into a table grid beside the Lab-values.

Properties File Creator saves you from:

manually error prone and boring tasks
importing multiple data files and combining it’s content manually into a single data file to append the lab reference values (aka properties)
programming and writing scripts to transform the data into the shape needed
no trouble with data handling of
- Wavelength / Wavenumber information (x-axis)
- Absorbance / Reflectance labeling (y-axis)
- checking compatibility of the raw data before merging
- Averaging Spectral Intensities of a Sample
- coping, flipping and transposing rows and colums to get the X-Block and Y-Block data sets ready for calibration modeling
- limited and error prone table grid functionality

Because it’s all automatic and you can check the results and get the analysis information!

Properties File Creator provides you - a individual template based on your raw-data for combining NIR and Lab-values - analysis and checks for better data quality for calibration

Top 8 Reasons why you should use
Automated NIR Calibration Service

No subjective model selection
No variation in results and interpretation
No overfitting model
Better accuracy
Better precision
Time saving!
No software cost (no need for Chemometric software and training)
One free prediction software for all your NIR systems

Reduce Total Cost of Ownership (TCO) of your NIR

To be ahead of competitors

by not owning a chemometric software
by not struggling days with these complicated software
by not deep dive into chemometrics theory

It takes significant know-how and continous investment to develop calibrations

You need to have the relevant skill sets in your organization.
That means salaries (the biggest expense in most organizations)

To get most out of it, start now!

use the free NIR-Predictor together with your NIR-Instrument software
as an NIR-Vendor, integrate the free NIR-Predictor OEM into your NIR-Instrument software
don’t delay time-to-market

About the included Demo-Spectra and Demo-Calibrations

The demo calibrations for the spectrometers from

Si-Ware Systems
Spectral Engines
Texas Instruments
VIAVI

are built with the raw data, thankfully provided from Prof. Heinz W Siesler, from this publication

“Hand-held near-infrared spectrometers:
State-of-the-art instrumentation and practical applications”
Hui Yan, Heinz W Siesler
First Published August 20, 2018 Research Article
https://doi.org/10.1177/0960336018796391

The demo calibrations for the FOSS are built with the

ANSIG Kaji Competition 2014 shootout data
http://www.anisg.com.au/the-kaji-competition

References

Quickstart: NIR-Predictor - Manual

Features and Version History: NIR-Predictor - Release Notes History

Supported NIR Spectra Formats: NIR-Predictor supported Spectral Data File Formats

Frequently Asked Questions: NIR-Predictor - FAQ

WebShop : CalibrationModel WebShop

New: NIR-Predictor V2.6 with new features

NIR-Predictor is an easy to use NIR software for all NIR devices
to produce quantitative results out of NIR data.
CalibrationModel Service provides development of
customized calibrations out of NIR and Lab data.
It allows to use NIR with your own customized
models without the need of Chemometric Software!
We do the Machine Leraning for your NIR-Spectrometer
and with the free NIR-Predictor you are
able to analyze new measured samples.
For NIR-Vendors we also offer the
Software Development Kit (SDK) for OEM Predictor use
via the Application Programming Interface (API).
Think of a sencod predictor engine,
as a second heart in your system.

Download

Key Features of NIR-Predictor

Super flexible prediction with automatic file format detection
Support for many mobile and desktop NIR Spectrometers file format
Application concept allows to group multiple Calibrations together for an Application
Prediction Report shows Histogram Charts of the tabulated prediction results
Sample based Properties File Creator for combining NIR and Lab reference data
Checked creation of a single file Calibration Request

Super flexible prediction

Loads multiple files at once in

different file-formats and …
different wave-ranges and wave-resolutions and …
predicts each spectrum with all compatible calibrations and …
merges the results in a report and …
saves the report as HTML.

It allows you to

comparing measurements
compare different calibrations
compare different spectrometers,
carry out your own round-robin amongst the vendors’ instruments.
compare different spectra file formats

With no configuration and no special menu command,
just drag & drop your data files.

Videos

Properties File Creator

It’s time saving and less error prone because you DON’T need to open each spectrum file separately in an editor and copy the spectral values into a table grid beside the Lab-values.

Properties File Creator saves you from:

manually error prone and boring tasks
importing multiple data files and combining it’s content manually into a single data file to append the lab reference values (aka properties)
programming and writing scripts to transform the data into the shape needed
no trouble with data handling of
- Wavelength / Wavenumber information (x-axis)
- Absorbance / Reflectance labeling (y-axis)
- checking compatibility of the raw data before merging
- Averaging Spectral Intensities of a Sample
- coping, flipping and transposing rows and colums to get the X-Block and Y-Block data sets ready for calibration modeling
- limited and error prone table grid functionality

Because it’s all automatic and you can check the results and get the analysis information!

Properties File Creator provides you - a individual template based on your raw-data for combining NIR and Lab-values - analysis and checks for better data quality for calibration

Top 8 Reasons why you should use
Automated NIR Calibration Service

No subjective model selection
No variation in results and interpretation
No overfitting model
Better accuracy
Better precision
Time saving!
No software cost (no need for Chemometric software and training)
One free prediction software for all your NIR systems

Reduce Total Cost of Ownership (TCO) of your NIR

To be ahead of competitors

by not owning a chemometric software
by not struggling days with these complicated software
by not deep dive into chemometrics theory

It takes significant know-how and continous investment to develop calibrations

You need to have the relevant skill sets in your organization.
That means salaries (the biggest expense in most organizations)

To get most out of it, start now!

use the free NIR-Predictor together with your NIR-Instrument software
as an NIR-Vendor, integrate the free NIR-Predictor OEM into your NIR-Instrument software
don’t delay time-to-market

About the included Demo-Spectra and Demo-Calibrations

The demo calibrations for the spectrometers from

Si-Ware Systems
Spectral Engines
Texas Instruments
VIAVI

are built with the raw data, thankfully provided from Prof. Heinz W Siesler, from this publication

“Hand-held near-infrared spectrometers:
State-of-the-art instrumentation and practical applications”
Hui Yan, Heinz W Siesler
First Published August 20, 2018 Research Article
https://doi.org/10.1177/0960336018796391

The demo calibrations for the FOSS are built with the

ANSIG Kaji Competition 2014 shootout data
http://www.anisg.com.au/the-kaji-competition

References

Quickstart: NIR-Predictor - Manual

Features and Version History: NIR-Predictor - Release Notes History

Supported NIR Spectra Formats: NIR-Predictor supported Spectral Data File Formats

Frequently Asked Questions: NIR-Predictor - FAQ

WebShop : CalibrationModel WebShop

New: NIR-Predictor V2.6 with new features

NIR-Predictor is an easy to use NIR software for all NIR devices
to produce quantitative results out of NIR data.
CalibrationModel Service provides development of
customized calibrations out of NIR and Lab data.
It allows to use NIR with your own customized
models without the need of Chemometric Software!
We do the Machine Leraning for your NIR-Spectrometer
and with the free NIR-Predictor you are
able to analyze new measured samples.
For NIR-Vendors we also offer the
Software Development Kit (SDK) for OEM Predictor use
via the Application Programming Interface (API).
Think of a sencod predictor engine,
as a second heart in your system.

Download

Key Features of NIR-Predictor

Super flexible prediction with automatic file format detection
Support for many mobile and desktop NIR Spectrometers file format
Application concept allows to group multiple Calibrations together for an Application
Prediction Report shows Histogram Charts of the tabulated prediction results
Sample based Properties File Creator for combining NIR and Lab reference data
Checked creation of a single file Calibration Request

Super flexible prediction

Loads multiple files at once in

different file-formats and …
different wave-ranges and wave-resolutions and …
predicts each spectrum with all compatible calibrations and …
merges the results in a report and …
saves the report as HTML.

It allows you to

comparing measurements
compare different calibrations
compare different spectrometers,
carry out your own round-robin amongst the vendors’ instruments.
compare different spectra file formats

With no configuration and no special menu command,
just drag & drop your data files.

Videos

Properties File Creator

It’s time saving and less error prone because you DON’T need to open each spectrum file separately in an editor and copy the spectral values into a table grid beside the Lab-values.

Properties File Creator saves you from:

manually error prone and boring tasks
importing multiple data files and combining it’s content manually into a single data file to append the lab reference values (aka properties)
programming and writing scripts to transform the data into the shape needed
no trouble with data handling of
- Wavelength / Wavenumber information (x-axis)
- Absorbance / Reflectance labeling (y-axis)
- checking compatibility of the raw data before merging
- Averaging Spectral Intensities of a Sample
- coping, flipping and transposing rows and colums to get the X-Block and Y-Block data sets ready for calibration modeling
- limited and error prone table grid functionality

Because it’s all automatic and you can check the results and get the analysis information!

Properties File Creator provides you - a individual template based on your raw-data for combining NIR and Lab-values - analysis and checks for better data quality for calibration

Top 8 Reasons why you should use
Automated NIR Calibration Service

No subjective model selection
No variation in results and interpretation
No overfitting model
Better accuracy
Better precision
Time saving!
No software cost (no need for Chemometric software and training)
One free prediction software for all your NIR systems

Reduce Total Cost of Ownership (TCO) of your NIR

To be ahead of competitors

by not owning a chemometric software
by not struggling days with these complicated software
by not deep dive into chemometrics theory

It takes significant know-how and continous investment to develop calibrations

You need to have the relevant skill sets in your organization.
That means salaries (the biggest expense in most organizations)

To get most out of it, start now!

use the free NIR-Predictor together with your NIR-Instrument software
as an NIR-Vendor, integrate the free NIR-Predictor OEM into your NIR-Instrument software
don’t delay time-to-market

About the included Demo-Spectra and Demo-Calibrations

The demo calibrations for the spectrometers from

Si-Ware Systems
Spectral Engines
Texas Instruments
VIAVI

are built with the raw data, thankfully provided from Prof. Heinz W Siesler, from this publication

“Hand-held near-infrared spectrometers:
State-of-the-art instrumentation and practical applications”
Hui Yan, Heinz W Siesler
First Published August 20, 2018 Research Article
https://doi.org/10.1177/0960336018796391

The demo calibrations for the FOSS are built with the

ANSIG Kaji Competition 2014 shootout data
http://www.anisg.com.au/the-kaji-competition

References

Quickstart: NIR-Predictor - Manual

Features and Version History: NIR-Predictor - Release Notes History

Supported NIR Spectra Formats: NIR-Predictor supported Spectral Data File Formats

Frequently Asked Questions: NIR-Predictor - FAQ

WebShop : CalibrationModel WebShop

Procedures for NIR calibration – Creation of NIRS spectroscopy calibration curvesArbeitsweisen zur NIR Kalibrierung – Erstellung von NIRS-Spektroskopie Kalibrierungskurven Le procedure di calibrazione NIR – Realizzazione di curve di calibrazione NIRS spettroscopia

Do you know the effect that you prefer to try out their favorite data pretreatments in combination and often try the same wavelength selections based spectra of the visualized?

You try as six to ten combinations until one of them selects his favorite calibration model, to then continue to optimize. Since then suddenly fall to outliers, because it goes in depth, so is familiar with the data, we know now the spectra of numbers of outliers and is familiar with the extreme values.

Now, the focus is on the major components (principal components, Latent Variables, factors) and makes sure not to over-fit and under-fit not to. The whole takes a few hours and finally one is content with the model found.

So what would happen if you all in the beginning tried variants found outliers removed and re-evaluated and compared? The results would be better than that of the previous model choice? One does not try out? Because it is cumbersome and takes hours again?

We have developed a software which simplifies this so that also the number of model variations can be increased as desired. The variants generation is automated with an intelligent control system, as well as the optimization and comparing the models and finally the final selection of the best calibration model.

Our software includes all the usual known data pretreatment methods (data pre-processing) and can combine them useful. Since many Preteatments are directly dependent on the wavelength selection, such as the normalization the determined within a wavelength range of the scaling factors to normalize the spectra so that pretreatments with the wavelength ranges may be combined. So a variety of settings sensible model comes together that are all calculated and optimized. For the automatic selection of the relevant wavelength ranges, different methods are used, which are based on the spectral intensities. Thus, for example, regions with total absorption is not used, and often interfering water bands removed or retained.

Over all the calculated model variations as a summary outlier analysis can be made. Are there any new outliers (hidden outlier) discovered, all previous models can be automatically recalculated, optimized and compared without these outliers.

From this great number of calculated models with the statistical quality reviews (prediction performance) the optimum calibration can now be selected. For this purpose, not simply sorting by the prediction error (prediction error, SEP RMSEP) or the coefficient of determination (coefficient of determination r²), but by several statistical and test values are used jointly toward the final assessment of optimal calibration.

Thus we have created a platform that allows the highly automated work what a man can never do with a commercial software.

We therefore offer the largest number of matched to your application problem modeling calculations and choose the best calibration for you!

This means that our results are faster, more accurate, robust and objective basis (person independent) and quite easy for you to apply.

You have the full control of the models supplied by us, because we provide a clearly structured and detailed blueprint of the complete calibration, with all settings and parameters, with all necessary statistical characteristics and graphics.

Using this blueprint, you can adjust the quantitative calibration model itself in the software you use, understand and compare. You have everything under control form model creation, model validation and model refinement.

Your privacy is very important to us. The NIR data that you briefly provide us for the custom calibration development will remain of course your property. Your NIR data will be deleted after the job with us.

Start Calibrate

Interested, then do not hesitate to contact us.

Kennen Sie den Effekt, dass Sie bevorzugt ihre Lieblings-Datenvorbehandlungen in Kombination durchprobieren und oft die gleichen Wellenlängen-Selektionen anhand der visualisierten Spektren ausprobieren?

Man probiert z.B. sechs bis zehn Kombinationen aus, bis man davon sein favorisiertes Kalibrationsmodell auswählt, um es dann weiter zu optimieren. Da fallen dann plötzlich Ausreisser (Outlier) auf, weil man in die Tiefe geht, also mit den Daten vertraut ist, man kennt mittlerweile die Spektren-Nummern der Ausreisser und ist mit den Extremwerten vertraut.

Jetzt fokussiert man sich auf die Hauptkomponenten (Principal Components, Latent Variables, Faktoren) und achtet darauf nicht zu über-fitten und nicht zu unter-fitten. Das ganze dauert ein paar Stunden und schliesslich begnügt man sich mit dem gefundenen Modell.

Was wäre nun, wenn man in all den zu Beginn ausprobierten Varianten, die gefundenen Ausreisser entfernt und nochmals berechnet und vergleicht? Wären die Ergebnisse besser als die von der bisherigen Modell Wahl? Man probiert es nicht aus? Weil es mühsam ist und wieder Stunden dauert?

Wir haben eine Software entwickelt die dies so vereinfacht, dass auch die Anzahl der Modell Variationen beliebig erhöht werden kann. Die Varianten Erzeugung läuft automatisiert mit einem intelligenten Regelsystem, so auch die Optimierung und das Vergleichen der Modelle und schliesslich die finale Auswahl des Besten Kalibrations Modell.

Unsere Software beinhaltet alle üblichen bekannten Datenvorbehandlungs Methoden (Preteatments) und kann diese sinnvoll kombinieren. Da viele Preteatments direkt abhängig sind von der Wellenlängen Selektion, so z.B. die Normalisierungen die innerhalb eines Wellenlängen-Bereiches die Skalierungsfaktoren ermittelt, um die Spektren damit zu normieren, werden die Pretreatments mit dem Wellenlängen-Bereichen kombiniert. So kommt eine Vielzahl von sinnvollen Modell Einstellungen zusammen die alle berechnet und optimiert werden.

Für die automatische Auswahl der relevanten Wellenlängen Bereiche kommen verschiedene Methoden zum Einsatz, die sich an den Spektren Intensitäten orientieren. So werden z.B. Bereiche mit Totalabsorption nicht verwendet, oftmals störende Wasserbanden entfernt oder beibehalten.

Über all die berechneten Modell Variationen können so zusammenfassende Outlier Analysen gemacht werden. Werden durch die gefahrenen Versuche neue Outlier (Hidden Outlier) entdeckt, können alle bisherigen Modelle automatisch ohne diese Ausreisser nachberechnet, optimiert und verglichen werden.

Aus dieser Vielzahl berechneter Modelle mit deren Statistischen Güte Bewertungen (Prediction Performance) kann nun die optimale Kalibration ausgewählt werden. Dazu wird nicht einfach nach dem Vorhersage Fehler (Prediction Error, SEP, RMSEP) oder nach dem Bestimmtheitsmaß (Coefficient of Determination r²) sortiert, sondern mehrere Statistik- und Testwerte gemeinsam zur umfänglichen Beurteilung der optimalen Kalibration herangezogen.

Somit haben wir eine Plattform geschaffen, die es ermöglicht hochgradig automatisiert das zu tun, was ein Mensch niemals mit einer handelsüblichen Software tun kann.

Wir bieten damit die grösste Anzahl auf Ihr Applikations-Problem angepasste Modellierungs-Berechnungen und wählen die beste Kalibration für Sie aus!

Das heisst, unsere Ergebnisse sind schneller, genauer, robuster und objektiv ausgewählt (Personen unabhängig) und für Sie ganz einfach anzuwenden.

Die Kontrolle über die von uns gelieferten Modelle haben Sie vollumfänglich, denn wir liefern einen klar strukturierten und detaillierten Bauplan der kompletten Kalibration, mit allen Einstellungen und Parametern, mit allen notwendigen Statistischen Kenngrössen und Grafiken.

Anhand dieses Bauplans können Sie das quantitative Kalibrations Modell selbst in der von Ihnen verwendeten Software nachstellen, nachvollziehen und vergleichen. Sie haben so alles im Griff, für die Modell-Validierung und die Modellpflege.

Der Datenschutz ist uns sehr wichtig. Die NIR Daten, die Sie uns für die Kalibrations-Erstellung kurzzeitig zu Verfügung stellen bleiben selbstverständlich Ihr Eigentum. Ihre NIR Daten werden nach Abschluss des Auftrags bei uns gelöscht.

Start Calibrate

Interessiert, dann zögern Sie nicht uns zu kontaktieren.

Do you know the effect that you prefer to try out their favorite data pretreatments in combination and often try the same wavelength selections based spectra of the visualized?

You try as six to ten combinations until one of them selects his favorite calibration model, to then continue to optimize. Since then suddenly fall to outliers, because it goes in depth, so is familiar with the data, we know now the spectra of numbers of outliers and is familiar with the extreme values.

Now, the focus is on the major components (principal components, Latent Variables, factors) and makes sure not to over-fit and under-fit not to. The whole takes a few hours and finally one is content with the model found.

So what would happen if you all in the beginning tried variants found outliers removed and re-evaluated and compared? The results would be better than that of the previous model choice? One does not try out? Because it is cumbersome and takes hours again?

We have developed a software which simplifies this so that also the number of model variations can be increased as desired. The variants generation is automated with an intelligent control system, as well as the optimization and comparing the models and finally the final selection of the best calibration model.

Our software includes all the usual known data pretreatment methods (data pre-processing) and can combine them useful. Since many Preteatments are directly dependent on the wavelength selection, such as the normalization the determined within a wavelength range of the scaling factors to normalize the spectra so that pretreatments with the wavelength ranges may be combined. So a variety of settings sensible model comes together that are all calculated and optimized. For the automatic selection of the relevant wavelength ranges, different methods are used, which are based on the spectral intensities. Thus, for example, regions with total absorption is not used, and often interfering water bands removed or retained.

Over all the calculated model variations as a summary outlier analysis can be made. Are there any new outliers (hidden outlier) discovered, all previous models can be automatically recalculated, optimized and compared without these outliers.

From this great number of calculated models with the statistical quality reviews (prediction performance) the optimum calibration can now be selected. For this purpose, not simply sorting by the prediction error (prediction error, SEP RMSEP) or the coefficient of determination (coefficient of determination r²), but by several statistical and test values are used jointly toward the final assessment of optimal calibration.

Thus we have created a platform that allows the highly automated work what a man can never do with a commercial software.

We therefore offer the largest number of matched to your application problem modeling calculations and choose the best calibration for you!

This means that our results are faster, more accurate, robust and objective basis (person independent) and quite easy for you to apply.

You have the full control of the models supplied by us, because we provide a clearly structured and detailed blueprint of the complete calibration, with all settings and parameters, with all necessary statistical characteristics and graphics.

Using this blueprint, you can adjust the quantitative calibration model itself in the software you use, understand and compare. You have everything under control form model creation, model validation and model refinement.

Your privacy is very important to us. The NIR data that you briefly provide us for the custom calibration development will remain of course your property. Your NIR data will be deleted after the job with us.

Start Calibrate

Interested, then do not hesitate to contact us.

March 7, 2012December 15, 2020

What is JCAMP-DX ?Was ist JCAMP-DX ?Cos’è JCAMP-DX?

New: the free NIR-Predictor software supports many other native and simple text formats like CSV, please see supported data file formats.

JCAMP-DX is a Electronic Data Standards for long-term storage and transfer of chemometric information. The standard is development by the International Union of Pure and Applied Chemistry (IUPAC).

JCAMP-DX is an abreviation for the Joint Committee on Atomic and Molecular Physical data - Data eXchange.

It is an human readable file format that is used to store near infrared spectrometry data (and others like Raman, UV, NMR, mass, x-ray, chromatograms, thermograms) and related chemical and physical information and is used since the late 80s.

Almost all NIR-software packages can export the spectra including the reference values as JCAMP-DX. A single file can contain multiple spectra and reference values. A JCAMP file name looks like "sample.dx", "sample.jdx" or "sample.jcm".

For a software tool to predict JCAMP spectra, see NIR-Predictor JCAMP.
For a software tool to anonymize your JCAMP data, see JCAMP-Anonymizer Software

All data are stored as labeled fields of variable length using printable ASCII characters. Such files can be loaded in an text editor to check the content:

##TITLE= Indene (FILE: AFIR2.DX)
$$ FILE AFIR2.DX ( derived from TFIR2.DX)
$$ ABSORBANCE
$$ FIXED FORM
$$ INCREASING ABSCISSA
$$ RATIONAL ABSCISSA SPACING
##JCAMP-DX= 4.24 $$ Encoded by INTTODX 1.04 (RS McDonald)
##DATA TYPE= INFRARED SPECTRUM
##ORIGIN= JCAMP-DX Test Disk 1.04
R.S.McDonald, 9 Woodside Dr., Burnt Hills, NY 12027, 518-399-5145
##OWNER= Public Domain
##RESOLUTION= 2.0
##DELTAX=1.00000000
##XUNITS= 1/CM
##YUNITS= ABSORBANCE
##XFACTOR= 1.000000000
##YFACTOR= 0.000100000
##FIRSTX= 400.000
##LASTX= 4.000E+03
##NPOINTS= 3601
##FIRSTY= 3.487E-1
##XYDATA= (X++(Y..Y))
400 3487 3355 3264 3198 3153 3143 3182 3298 3520 3845 4262
411 4783 5449 6304 7383 8684 10209 12041 14123 16003 16162 14191
422 11791 9674 7943 6540 5406 4528 3874 3397 3045 2780 2584
433 2446 2354 2290 2246 2212 2187 2165 2135 2087 2022 1945
444 1865 1786 1713 1649 1596 1550 1512 1478 1448 1422 1401
:

The standard can be downloaded here: "JCAMP-DX: A Standard Form for the Exchange of Infrared Spectra in Computer Readable Form", ROBERT S. McDONALD and PAUL A. WILKS, JR., Appl. Spectrosc. 42(1), pp151-162, 1988

Neu: die kostenlose NIR-Predictor-Software unterstützt viele andere native und einfache Textformate wie CSV, siehe unterstützte Dateiformate.

JCAMP-DX ist ein elektronischer Daten Standard für die langfristige Speicherung und Übertragung von chemometrischen Informationen. Der Standard ist die Entwicklung von der International Union of Pure and Applied Chemistry (IUPAC)

JCAMP-DX ist eine Abkürzung für Joint Committee on Atomic and Molecular Physical data - Data eXchange.

Es ist ein von Menschen lesbares Dateiformat, das Nah-Infrarot-Spektrometrie Daten (und andere wie Raman, UV, NMR, Massen, Röntgen, Chromatogramme, Thermogramme) und zugehörige chemische und physikalische Informationen speichert und wird seit den späten 80er Jahren verwendet.

Fast alle NIR-Software-Pakete können die Spektren einschließlich der Referenzwerte als JCAMP-DX exportieren. Eine einzelne Datei kann mehrere Spektren und Referenzwerte enthalten. Ein JCAMP Dateiname sieht aus wie "sample.dx", "sample.jdx" oder "sample.jcm".

Ein Software-Tool zum predicten von JCAMP spectra ist der NIR-Predictor JCAMP.
Ein Software-Tool zur Anonymisierung Ihrer JCAMP-Daten finden Sie unter JCAMP-Anonymizer Software

Alle Daten werden als markierte Felder variabler Länge mit druckbaren ASCII-Zeichen gespeichert. Solche Dateien können in einem Text-Editor geladen werden, um den Inhalt zu überprüfen:

##TITLE= Indene (FILE: AFIR2.DX)
$$ FILE AFIR2.DX ( derived from TFIR2.DX)
$$ ABSORBANCE
$$ FIXED FORM
$$ INCREASING ABSCISSA
$$ RATIONAL ABSCISSA SPACING
##JCAMP-DX= 4.24 $$ Encoded by INTTODX 1.04 (RS McDonald)
##DATA TYPE= INFRARED SPECTRUM
##ORIGIN= JCAMP-DX Test Disk 1.04
R.S.McDonald, 9 Woodside Dr., Burnt Hills, NY 12027, 518-399-5145
##OWNER= Public Domain
##RESOLUTION= 2.0
##DELTAX=1.00000000
##XUNITS= 1/CM
##YUNITS= ABSORBANCE
##XFACTOR= 1.000000000
##YFACTOR= 0.000100000
##FIRSTX= 400.000
##LASTX= 4.000E+03
##NPOINTS= 3601
##FIRSTY= 3.487E-1
##XYDATA= (X++(Y..Y))
400 3487 3355 3264 3198 3153 3143 3182 3298 3520 3845 4262
411 4783 5449 6304 7383 8684 10209 12041 14123 16003 16162 14191
422 11791 9674 7943 6540 5406 4528 3874 3397 3045 2780 2584
433 2446 2354 2290 2246 2212 2187 2165 2135 2087 2022 1945
444 1865 1786 1713 1649 1596 1550 1512 1478 1448 1422 1401
:

Der Standard kann hier heruntergeladen werden: "JCAMP-DX: A Standard Form for the Exchange of Infrared Spectra in Computer Readable Form", ROBERT S. McDONALD and PAUL A. WILKS, JR. , Appl. Spectrosc. 42(1), pp151-162, 1988

New: the free NIR-Predictor software supports many other native and simple text formats like CSV, please see supported data file formats.

JCAMP-DX is a Electronic Data Standards for long-term storage and transfer of chemometric information. The standard is development by the International Union of Pure and Applied Chemistry (IUPAC).

JCAMP-DX is an abreviation for the Joint Committee on Atomic and Molecular Physical data - Data eXchange.

It is an human readable file format that is used to store near infrared spectrometry data (and others like Raman, UV, NMR, mass, x-ray, chromatograms, thermograms) and related chemical and physical information and is used since the late 80s.

Almost all NIR-software packages can export the spectra including the reference values as JCAMP-DX. A single file can contain multiple spectra and reference values. A JCAMP file name looks like "sample.dx", "sample.jdx" or "sample.jcm".

For a software tool to predict JCAMP spectra, see NIR-Predictor JCAMP.
For a software tool to anonymize your JCAMP data, see JCAMP-Anonymizer Software

All data are stored as labeled fields of variable length using printable ASCII characters. Such files can be loaded in an text editor to check the content:

##TITLE= Indene (FILE: AFIR2.DX)
$$ FILE AFIR2.DX ( derived from TFIR2.DX)
$$ ABSORBANCE
$$ FIXED FORM
$$ INCREASING ABSCISSA
$$ RATIONAL ABSCISSA SPACING
##JCAMP-DX= 4.24 $$ Encoded by INTTODX 1.04 (RS McDonald)
##DATA TYPE= INFRARED SPECTRUM
##ORIGIN= JCAMP-DX Test Disk 1.04
R.S.McDonald, 9 Woodside Dr., Burnt Hills, NY 12027, 518-399-5145
##OWNER= Public Domain
##RESOLUTION= 2.0
##DELTAX=1.00000000
##XUNITS= 1/CM
##YUNITS= ABSORBANCE
##XFACTOR= 1.000000000
##YFACTOR= 0.000100000
##FIRSTX= 400.000
##LASTX= 4.000E+03
##NPOINTS= 3601
##FIRSTY= 3.487E-1
##XYDATA= (X++(Y..Y))
400 3487 3355 3264 3198 3153 3143 3182 3298 3520 3845 4262
411 4783 5449 6304 7383 8684 10209 12041 14123 16003 16162 14191
422 11791 9674 7943 6540 5406 4528 3874 3397 3045 2780 2584
433 2446 2354 2290 2246 2212 2187 2165 2135 2087 2022 1945
444 1865 1786 1713 1649 1596 1550 1512 1478 1448 1422 1401
:

The standard can be downloaded here: "JCAMP-DX: A Standard Form for the Exchange of Infrared Spectra in Computer Readable Form", ROBERT S. McDONALD and PAUL A. WILKS, JR., Appl. Spectrosc. 42(1), pp151-162, 1988