Spectroscopy and Chemometrics News Weekly #25, 2019

CalibrationModel.com

Spectroscopy and Chemometrics News Weekly 24, 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 24, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 24, 2019 | NIRS NIR Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem prediction models LINK




Chemometrics

“Classification of hybrid seeds using near-infrared hyperspectral imaging technology combined with deep learning” LINK

“Multivariate Discriminant Analysis of Single Seed Near Infrared Spectra for Sorting Dead-Filled and Viable Seeds of Three Pine Species: Does One Model Fit All Species?” forests LINK

“Development of near infrared spectroscopic methods to predict and understand dissolution of solid oral dosage forms” LINK

” Replication Data for: Towards a global arctic-alpine model for Near-infrared reflectance spectroscopy (NIRS) predictions of foliar nitrogen, phosphorus and …” LINK

” Genetic parameters for cow-specific digestibility predicted by near infrared reflectance spectroscopy” LINK

“Classification of Glycyrrhiza Seeds by Near Infrared Hyperspectral Imaging Technology” LINK

“Comprehensive comparison of multiple quantitative near-infrared spectroscopy models for Aspergillus flavus contamination detection in peanut.” LINK

“Non-Destructive Classification of Fruits Based on Vis-nir Spectroscopy and Principal Component Analysis” LINK




Near Infrared

“Assessment of applied microwave power of intermittent microwave-dried carrot powders from Colour and NIRS” LINK

“Soil Quality Analysis Using Modern Statistics and NIR spectroscopy Procedure” LINK

“Near-infrared diffusereflectance spectroscopy for discriminating fruit and vegetable products preserved in glass containers” LINK




Infrared

“A review of the application of near-infrared spectroscopy to rare traditional Chinese medicine” LINK

“Near-infrared spectroscopy as a tool for in vivo analysis of human muscles” LINK

“Surface Functionality and Water Adsorption Studies of a-Aluminium (III) Oxide Nanoparticles by near Infrared Spectroscopy” LINK

“A comparative study of mango solar drying methods by visible and near-infrared spectroscopy coupled with ANOVA-simultaneous component analysis (ASCA)” LINK

“High throughput phenotyping of Camelina sativa seeds for crude protein, total oil, and fatty acids profile by near infrared spectroscopy” LINK

“Near-infrared spectroscopic study of molecular interaction in ethanol-water mixtures” LINK




Hyperspectral

“Potential of hyperspectral imaging for nondestructive determination of chlorogenic acid content in Flos Lonicerae” LINK

“Thickness estimation of crude oil slicks by hyperspectral data based on partial least square regression method” LINK

“Development of a polarized hyperspectral imaging system for investigation of absorption and scattering properties” LINK

“Hyperspectral Imaging Retrieval Using MODIS Satellite Sensors Applied to Volcanic Ash Clouds Monitoring” LINK




Facts

“Sensor Fusion and Machine Learning for Soil Characterization from Farm to National Scale” LINK




Equipment

“Extension of the Measurable Wavelength Range for a Near-Infrared Spectrometer Using a Plasmonic Au Grating on a Si Substrate.” LINK




Environment

“Application of PROSPECT for estimating Total Petroleum Hydrocarbons in contaminated soils from leaf optical properties” LINK




Agriculture

“Ensemble Identification of Spectral Bands Related to Soil Organic Carbon Levels over an Agricultural Field in Southern Ontario, Canada” LINK

“Saving Old Bones: a non-destructive method for bone collagen prescreening” LINK

“Nondestructive On-site Detection of Soybean Contents Based on An Electrothermal MEMS Fourier Transform Spectrometer” LINK

“Remote Sensing Extraction of Crop Disaster Information Based on Support Vector Machine” LINK

“Remote Sensing, Vol. 11, Pages 1331: Evaluation of Leaf N Concentration in Winter Wheat Based on Discrete Wavelet Transform Analysis” LINK

“Predicting coefficient of linear extensibility and Atterberg limits of fine-grained soils using vis-NIR spectra” LINK




Other

“Effect of external compression on femoral retrograde shear and microvascular oxygenation in exercise trained and recreationally active young men” LINK





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Spectroscopy and Chemometrics News Weekly #1, 2019

CalibrationModel.com

Develop customized NIRS applications and freeing up hours of spectroscopy analysts time | spectroscopist chemist laboratory LINK

Increase Your Profit with optimized NIR Accuracy Beverage Processing Dairy LINK

Neue Möglichkeiten in der Entwicklung von Applikationen für die NIR-Analytik | Labor NIRS Analytik LaborAnalytik LINK

New : FREE NIR Predictor Software, drag&drop spectral data to plug&play calibrations, for any NIRS Analysis sensor type. | Chemometrics Prediction LINK

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

Spectroscopy and Chemometrics News Weekly 52, 2018 | NIRS Spectroscopy Chemometrics analysis Spectral Spectrometer Sensors Spectrometry LINK




HAPPY NEW YEAR

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Chemometrics

“Nocturnal Hypoglycemic Alarm Based on Near-Infrared Spectroscopy: In Vivo Studies with a Rat Animal Model.” LINK

“Hydrolysis kinetics of silane coupling agents studied by near-infrared spectroscopy plus partial least squares model” LINK

“Utilizing visible and near infrared spectroscopy based on multi-class support vector machines classification to characterize olive oil adulteration” LINK

“Analysis of Near-Infrared (NIR) Spectroscopy for Chlorophyll Prediction in Oil Palm Leaves” LINK

“基于卷积神经网络的烟叶近红外光谱分类建模方法研究” “The Study of Classification Modeling Method for Near Infrared Spectroscopy of Tobacco Leaves Based on Convolution Neural Network” LINK




Near Infrared

“Determination of the geographical origin of green coffee beans using NIR spectroscopy and multivariate data analysis” LINK

“Acton Optics & Coatings Develops New UV-NIR Neutral Density Filters That Offer Unmatched Broadband Performance” LINK

“The Influence of Packaging on Cosmetic Emulsion during Storage Assessed by FT-NIR Spectroscopy and Color Measurements” – Society of Cosmetic Chemists LINK

The Influence of Packaging on Cosmetic Emulsion during Storage Assessed by FT-NIR Spectroscopy and Color Measurements – Society of Cosmetic Chemists LINK

“Measurement of pesticide residues in peppers by near-infrared reflectance spectroscopy” NIRS LINK

“Near infrared reflectance spectroscopy of pasticceria foodstuff as protein content predicting method” NIRS NIR LINK

“Application of portable micro near infrared spectroscopy to the screening of extractable polyphenols in grape skins: A complex challenge.” vineyard NIR LINK

“Qualitative Identification of Pesticide Residues in Pakchoi Based on Near Infrared Spectroscopy” NIRS LINK

“稻谷有害霉菌侵染的近红外光谱快速检测” “Rapid Detection of Harmful Mold Infection in Rice by Near Infrared Spectroscopy” LINK

“Quantitative Characterization of Arnicae flos by RP-HPLC-UV and NIR Spectroscopy.” LINK




Infrared

“Fast detection of cocoa shell in cocoa powders by Near Infrared Spectroscopy and multivariate analysis” LINK

“SDAE-BP Based Octane Number Soft Sensor Using Near-infrared Spectroscopy in Gasoline Blending Process” LINK

“Differentiating between bottled water from different sources using near-infrared spectroscopy” LINK

“Nondestructive Detection of Pesticide Residue on Banana Surface Based on Near Infrared Spectroscopy” LINK

“Raman spectroscopy of a near infrared absorbing proteorhodopsin: Similarities to the bacteriorhodopsin O photointermediate.” LINK

“Determination of Total Polysaccharides and Total Flavonoids in Chrysanthemum morifolium Using Near-Infrared Hyperspectral Imaging and Multivariate Analysis.” LINK




Raman

“Surface Chemistry of Oil-Filled Organic Nanoparticle Coated Papers Analyzed Using Micro-Raman Mapping” LINK




Agriculture

“Spectroscopy and Spectral Imaging Techniques for Non-destructive Food Microbial Assessment” LINK

“Evaluating Soybean Cultivars for Low- and High-Temperature Tolerance During the Seedling Growth Stage” Agronomy NIRS LINK




Pharma

to acquire Celgene to create a leading innovative biopharma company LINK




Other

“The nutritive value of hay from the family farms of northwestern Croatia” LINK

“A comparison study of five different methods to measure carotenoids in biofortified yellow cassava (Manihot esculenta)” LINK

“大気中光電子収量分光分析による有機薄膜半導体のエネルギー準位の測定” LINK




Spectroscopy and Chemometrics News Weekly #49, 2018

CalibrationModel.com

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

Spectroscopy and Chemometrics News Weekly 48, 2018 | NIRS Spectroscopy Chemometrics analysis Spectral Spectrometer Sensors Spectrometry LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 48, 2018 | NIRS Spektroskopie Chemometrie analyse Spektral Spektrometer Sensor LINK

Spettroscopia e Chemiometria Weekly News 48, 2018 | NIRS Spettroscopia Chemiometria analisi Spettrale Spettrometro Sensore LINK






Chemometrics

“Using deep learning to predict soil properties from regional spectral data” LINK

“Determination of Pesticide in Banana by Infrared Spectroscopy Using Partial Least Square-Discriminant Analysis” LINK

“Quantification of Different Forms of Iron from Intact Soil Cores of Paddy Fields with Vis-NIR Spectroscopy” LINK

“A Vis-NIR spectral library to predict clay in Australian cotton growing soil” LINK




Near Infrared

“Water spectral pattern as a marker for studying apple sensory texture” aquaphotomics crispness juiciness mealiness NIR LINK

“Near-Infrared (NIR) Spectrometry as a Fast and Reliable Tool for Fat and Moisture Analyses in Olives” LINK

“A New Statistical Approach to Describe the Quality of Extra Virgin Olive Oils Using Near Infrared Spectroscopy (NIR) and Traditional Analytical Parameters” LINK

“Olive oil nutritional labeling by using Vis/NIR spectroscopy and compositional statistical methods” LINK

“Sparse NIR Optimization method (SNIRO) to quantify analyte composition with visible (VIS)/near infrared (NIR) spectroscopy (350nm-2500nm)” LINK

“Monitoring the growth and maturation of apple fruit on the tree with handheld Vis/NIR devices” LINK




Infrared

“Direct Determination of Ni2+-Capacity of IMAC Materials Using Near-Infrared Spectroscopy” LINK

“Quantitative analysis of quality for marian plum (Bouea burmanica Griff.) by transmittance near infrared spectroscopy” LINK

“Variable selection for the determination of total polar materials in fried oils by near infrared spectroscopy” LINK

“Biodiesel Synthesis Monitoring using Near Infrared Spectroscopy” LINK

“Non-destructive chemical analysis of water and chlorine content in cement paste using near-infrared spectroscopy” LINK




Hyperspectral

“Identification of Maize Kernel Vigor under Different Accelerated Aging Times Using Hyperspectral Imaging” LINK




Environment

“Interval Multiple-output Soft sensors Development with Capacity Control for Wastewater Treatment Applications: A Comparative Study” LINK




Other

“Nondestructive measurements of postharvest changes in lamb’s lettuce” LINK





Spectroscopy and Chemometrics News Weekly #41, 2018

CalibrationModel.com

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

Near Infrared (NIR) Analysis Software, work smart with all NIR Spectrometers for quantitative sensing & detection. | AnalyticalChemistry LabManger Chemical Analysis Equipment ChemicalAnalysis Analytical Instruments Laboratory LabEquipment LINK

New : FREE NIR Predictor Software, drag&drop spectral data to plug&play calibrations, for any NIRS Analysis sensor type. | Chemometrics Prediction LINK

Spectroscopy and Chemometrics News Weekly 40, 2018 | NIRS Spectroscopy Chemometrics analysis Spectral Spectrometer Sensors LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 40, 2018 | NIRS Spektroskopie Chemometrie analyse Spektral Spektrometer Sensor LINK

Spettroscopia e Chemiometria Weekly News 40, 2018 | NIRS Spettroscopia Chemiometria analisi Spettrale Spettrometro Sensore LINK




Chemometrics

“Classification of different animal fibers by near infrared spectroscopy and chemometric models” LINK

“Discrimination of organic and conventional rice by chemometric analysis of NIR spectra: a pilot study” LINK

“Discrimination between conventional and omega-3 fatty acids enriched eggs by FT-Raman spectroscopy and chemometric tools” omega3 LINK

“Quantification of mineral composition of Brazilian bee pollen by near infrared spectroscopy and PLS regression.” LINK

“Sex determination of silkworm pupae using VIS-NIR hyperspectral imaging combined with chemometrics.” LINK




Near Infrared

“Spinning-disc confocal microscopy in the second near-infrared window (NIR-II)” Fluorescence LINK

“Measuring the brain’s fast optical signal could speed up Brain–computer interfaces (BCI) response” NIRS LINK

“Bioprofiling for the quality control of Egyptian propolis using an integrated NIR-HPTLC-image analysis strategy.” LINK

“lab for the pocket” hertzstueck NIRS LINK

“NIR gas phase spectroscopy – Pressure broadening effects” LINK

“Near-infrared Band Used for Permanent, Wireless Self-charging System – R & D Magazine” LINK

“Non-Destructive NIR Spectral Imaging Assessment of Bone Water: Comparison to MRI Measurements” – NIRS vs. Magnetic Resonance Imaging LINK




Infrared

“Near-infrared spectroscopy could improve flu vaccine manufacturing” LINK

“Detection of Alone Stress and Combined Stress by CU and NI in Wheat Using Visible to Near-Infrared Spectroscopy” LINK

“A Novel Method for Classifying Driver Cognitive Distraction under Naturalistic Conditions with Information from Near-Infrared Spectroscopy” LINK




Agriculture

“Quality evaluation of fried soybean oil base on near infrared spectroscopy” LINK

Curious about new developments in various fields of spectroscopy and their application in plant sciences? Register now for the International Plant Spectroscopy Conference (IPSC) organised by our colleagues in Berlin, March 24-28th, 2019: LINK

“Application of Vibrational Spectroscopy and Imaging to Point-of-Care Medicine: A Review” LINK




Food & Feed

“From NIR spectra to singular wavelengths for the estimation of the oil and water contents in olive fruits” LINK




Medicinal

“New, noninvasive blood glucose test as effective as finger prick test – Clinical Innovation + Technology” Raman spectroscopy LINK




Laboratory

so, spent some time down the hardware rabbit hole. the core sensors, | is available in a number of combos, on a number of boards; e.g. | LINK










Spectroscopy and Chemometrics News Weekly #34, 2018

CalibrationModel.com

New : FREE NIR Predictor Software, drag&drop spectral data to plug&play calibrations, for any NIRS Analysis sensor type. | Chemometrics Prediction LINK

Spectroscopy and Chemometrics News Weekly 33, 2018 | NIRS Spectroscopy Chemometrics analysis Spectral Spectrometer Sensors LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 33, 2018 | NIRS Spektroskopie Chemometrie analyse Spektral Spektrometer Sensor LINK

Spettroscopia e Chemiometria Weekly News 33, 2018 | NIRS Spettroscopia Chemiometria analisi Spettrale Spettrometro Sensore LINK

We updated the Near Infrared (NIR) Spectrometer Directory of Suppliers / Manufacturers / Vendors. The list includes now also mobile miniature NIR spectrometer sensors. | NIRS NIR FTNIR NIT NearInfrared MEMS Spectral Sensor IoT LINK




Chemometrics

“Enhancing near infrared spectroscopy models to identify omega-3 fish oils used in the nutraceutical industry by means of calibration range extension” omega3 LINK

“Near infrared spectroscopy coupled with chemometric algorithms for predicting chemical components in black goji berries (Lycium ruthenicum Murr.)” LINK

“Towards innovation in paper dating: a MicroNIR analytical platform and chemometrics” nondestructive diagnostic forensic LINK

“Least-squares support vector machine and successive projection algorithm for quantitative analysis of cotton-polyester textile by near infrared spectroscopy” LINK

“Direct calibration transfer to principal components via canonical correlation analysis” NIRS corn tobacco LINK

“Collaborative representation based classifier with partial least squares regression for the classification of spectral data” LINK




Near Infrared

“Rapid and non-destructive discrimination of special-grade flat green tea using Near-infrared spectroscopy.” LINK

“HOW DID SCIENTISTS DISCOVER WATER ON THE SURFACE OF THE MOON? …. used near-infrared reflectance spectroscopy (NIRS) to find surface water at the moon’s polar regions. …. electromagnetic spectrum, from about 700 to 2,500 manometers.” LINK




Infrared

“DSC, FTIR and Raman Spectroscopy Coupled with Multivariate Analysis in a Study of Co-Crystals of Pharmaceutical Interest” LINK




Equipment

“Calibration transfer of near infrared spectrometers for the assessment of plasma ethanol precipitation process” LINK




Laboratory

“ILS: An R package for statistical analysis in Interlaboratory Studies” | outliers ANOVA LINK




Other

“Spectral Identification of Disease in Weeds Using Multilayer Perceptron with Automatic Relevance Determination” LINK





Spectroscopy and Chemometrics News Weekly #33, 2018

Near Infrared

“Accurate and rapid detection of soil and fertilizer properties based on visible/near-infrared spectroscopy.” LINK

“Authenticity Detection of Black Rice by Near-Infrared Spectroscopy and Support Vector Data Description.” NIRS LINK

“MicroNIR™ PAT-W for Blend Endpoint Analysis in a High Dosage Product” LINK




Chemometrics

“Which regression method to use? Making informed decisions in “data-rich/knowledge poor” scenarios – The Predictive Analytics Comparison framework (PAC)” LINK

“Determination of salvianolic acid B and borneol in compound Danshen tablet by near-infrared spectroscopy and establishment of dependency model” LINK

“Error propagation of partial least squares for parameters optimization in NIR modeling.” LINK

“Rapid quantification of the adulteration of fresh coconut water by dilution and sugars using Raman spectroscopy and chemometrics” LINK

“Predicting pork freshness using multi-index statistical information fusion method based on near infrared spectroscopy.” LINK

“Validation of short wave near infrared calibration models for the quality and ripening of ‘Newhall’ orange on tree across years and orchards” fruits SWNIRS LINK

“Fault detection based on time series modeling and multivariate statistical process control.” LINK




CalibrationModel.com

Near Infrared (NIR) Analysis Software, work smart with all NIR Spectrometers for quantitative sensing & detection. | AnalyticalChemistry LabManger Chemical Analysis Equipment ChemicalAnalysis Analytical Instruments Laboratory LabEquipment LINK

New : FREE NIR Predictor Software, drag&drop spectral data to plug&play calibrations, for any NIRS Analysis sensor type. | Chemometrics Prediction LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 32, 2018 | NIRS Spektroskopie Chemometrie analyse Spektral Spektrometer Sensor LINK

Spettroscopia e Chemiometria Weekly News 32, 2018 | NIRS Spettroscopia Chemiometria analisi Spettrale Spettrometro Sensore LINK

The non-destructive technique such as Near Infrared Spectroscopy NIRS along with Chemometrics can predict quality parameters of measurements by using the free NIR-Predictor Software. QualityControl QualityAssurance foodsafety productinspection LINK




Infrared

“Estimating soil heavy metals concentration at large scale using visible and near-infrared reflectance spectroscopy.” LINK

“Overall uncertainty measurement for near infrared analysis of cryptotanshinone in tanshinone extract.” LINK




Hyperspectral

“Hyperspectral imaging reveals wound problems” LINK




Research

“Sensoren machen guten Wein – Mit Hilfe von Sensoren können Winzer Informationen zu Reife, Qualität, Ertragsaussichten und Krankheitsrisiken ihrer Reben erhalten.” LINK




Equipment

“Fourier transform infrared spectrometer based on an electrothermal MEMS mirror.” LINK




Agriculture

“Discrimination of Milks with a Multisensor System Based on Layer-by-Layer Films” LINK




Other

“Watch out, birders: Artificial intelligence has learned to spot birds from their songs” LINK





Spectroscopy and Chemometrics News Weekly #31, 2018

Chemometrics

How to Configure the Number of Layers and Nodes in NeuralNetworks: BigData DataScience AI MachineLearning DeepLearning Algorithms by Source for graphic: | abdsc (2018.08.02) LINK

“Visible-Near-Infrared Spectroscopy can predict Mass Transport of Dissolved Chemicals through Intact Soil.” (2018.08.02) LINK

“Classification and compositional characterization of different varieties of cocoa beans by near infrared spectroscopy and multivariate statistical analyses.” (2018.08.02) LINK

“Classification of Chicken Parts Using a Portable Near-Infrared (NIR) Spectrophotometer and Machine Learning.” (2018.08.02) LINK

“Rapid Prediction of Low (<1%) trans Fat Content in Edible Oils and Fast Food Lipid Extracts by Infrared Spectroscopy and Partial Least Squares Regression” (2018.07.31) LINK

“Evaluating the performance of a consumer scale SCiO™ molecular sensor to predict quality of horticultural products” (2018.07.30) LINK

“Estimation of Total Phenols, Flavanols and Extractability of Phenolic Compounds in Grape Seeds Using Vibrational Spectroscopy and Chemometric Tools” (2018.07.26) LINK



Near Infrared

“FT-NIR, MicroNIR and LED-MicroNIR for Detection of Adulteration in Palm Oil via PLS and LDA” FTNIR NIRS (2018.08.03) LINK

“Long-Length Fiber Optic Near-Infrared (NIR) Spectroscopy Probes for On-Line Quality Control of Processed Land Animal Proteins” (2018.08.03) LINK

“Near-infrared spectroscopy for rapid and simultaneous determination of five main active components in rhubarb of different geographical origins and processing.” (2018.08.02) LINK

“Marktech Optoelectronics Introduces Silicon Avalanche Photodiodes for Low-Level Light and Short Pulse Detection” UV NIR NIRS SWIR (2018.08.02) LINK

“Innovative Technology Promises Fast, Cost-Efficient Age Data for Fisheries Management” FTNIR (2018.07.31) LINK

“Rapid qualitative and quantitative analysis of methamphetamine, ketamine, heroin, and cocaine by near-infrared spectroscopy.” (2018.07.31) LINK

We (led by ) have been independently assessing thew value of consumer scale NIR devices for horticultural quality assessment. Here is our published work assessing (2018.07.30) LINK



Infrared

“Fault Detection Based on Near-Infrared Spectra for the Oil Desalting Process” (2018.08.05) LINK

“Common Infrared Optical Materials and Coatings: A Guide to Properties, Performance and Applications” (2018.08.04) LINK



Raman

SpectraBase – FREE, fast text access to hundreds of thousands of NMR, IR, Raman, UV-Vis, and mass spectra! spectroscopy (2018.08.02) LINK



Agriculture

“Three-Dimensional Reconstruction of Soybean Canopies Using Multisource Imaging for Phenotyping Analysis” (2018.08.03) LINK

“Smartphone Spectroscopy Promises a Data-Rich Future – An upsurge of portable, consumer-facing devices at the intersection of smartphone computing and spectroscopy is now leveraging integration. ” (2018.08.02) LINK

Innovative Technology Promises Fast, Cost-Efficient Age Data for Fisheries Management (2018.07.31) LINK

“Smartphone-Based Food Diagnostic Technologies: A Review” (2018.07.30) LINK



Petro

“Detection, Purity Analysis, and Quality Assurance of Adulterated Peanut (Arachis Hypogaea) Oils” (2018.08.02) LINK



Pharma

“Potential of near infrared spectroscopy and pattern recognition for rapid discrimination and quantification of Gleditsia sinensis thorn powder with adulterants.” (2018.08.02) LINK



Medicinal

A micro-spectrometer fit for a smartphone: Could the power to measure things like CO2, food freshness, and blood sugar levels soon be in the palm of our hands? |rld/magazine/article/323/micro-spectrometer-opens-door-to-a-wealth-of-new-smartphone-functions?utm_source=twitter.com/CalibModel health safety medicine spectroscopy (2018.02.25) LINK

“Near-infrared spectroscopy detects age-related differences in skeletal muscle oxidative function: promising implications for geroscience.” (2018.02.08) LINK




Other

69% of decision makers say industrial analytics will be crucial for business in 2020. | IoT IIoT MT LINK





CalibrationModel.com

Free Chemometric NIR Predictor Software! Simple plug&play calibrations, drag&drop spectral data, for any NIRS sensor device. Easy to use software for off-line and real-time prediction without limits. offline realtime (2018.08.04) LINK

Automated NIRS spectroscopy chemometrics method development with MachineLearning for spectrometer Spectral IoT sensor SmartSensor SmartSensors (2018.07.25) LINK

Automatic NIR Spectroscopy Calibration-Development as a Service. Applicable with free NIR-Predictor software or via OEM API. | NIRSpectroscopy NearInfrared NIRanalysis spectrometers DataAnalytics Regression Spectral Sensors QualityControl Lab (2018.07.26) LINK

Increase Your Profit with optimized NIRS Accuracy with Calibration as a Service (CaaS) and the new free NIR-Predictor software. | foodsafety Feed Lab QC QA testing (2018.08.03) LINK

New : FREE NIR Predictor Software, drag&drop spectral data to plug&play calibrations, for any NIRS Analysis sensor type. | Chemometrics Prediction (2018.07.24) LINK

Spectroscopy and Chemometrics News (KW 11-30 2018) | NIRS Spectroscopy Chemometrics analysis Spectral Spectrometer Sensors (2018.07.25) LINK

Spektroskopie und Chemometrie Neuigkeiten (KW 11-30 2018) | NIRS Spektroskopie Chemometrie analyse Spektral Spektrometer Sensor (2018.07.25) LINK

Spettroscopia e Chemiometria Weekly (KW 11-30 2018) | NIRS Spettroscopia Chemiometria analisi Spettrale Spettrometro Sensore (2018.07.25) LINK

光谱学和化学计量学新闻(KW#11-#30 2018) | 近红外光谱化学计量学分析光谱仪传感器 (2018.07.26) LINK

分光法とケモメトリックスニュース(KW#11-#30 2018) | 赤外分光法・ケモメトリックスの分光センサーの近く (2018.07.26) LINK




Procedures for NIR calibration – Creation of NIRS spectroscopy calibration curves

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.

NIR Calibration Modeling

The majority of NIR calibrations are generated using a small number of different parameter settings and all too often are restricted to the time a user has available, their spectroscopic and chemometric knowledge and their ability (tedious use of the software) to choose and combine all the possible parameter settings required for good calibrations.

There are many published standards and guidelines (protocols) available for developing NIR calibrations from Standards Consortium such as ASTM, EMEA, ICH, IUPAC, ISO, USP, PASG etc. as well as many good recommendations and guidelines found in various textbooks and papers.

The difficulty with so many ‘Protocols’ for the NIR user is to have them all available and in their thought processes during calibration work and in addition to execute, check and challenge all calibrations generated manually. This is time consuming and sometimes boring repetitive work.

To simplify this for the person generating the NIR Calibrations, we have collected the good practices protocols and integrated them into our service that automates the calibration building and evaluation procedures.

to part 2

What are pre-developed NIR pre-calibrations?

There are a lot of terms that means the same, pre-calibration or NIR starter calibration or pre-built calibration or pre-installed calibration orcalibration package or pre-developed calibrations or pre-calibrated NIR or global calibrations or nir global calibration package or factory calibrations or universal near-infrared (NIR) calibrations or local calibrations or ready-to-use NIR calibrations or off-the-shelf calibrations or factory-calibrated or pre calculated model or start-up calibrations or calibration equations or prefabricated nir calibrations or calibration library or mathematical model. That are Calibration models that are prepared and developed by a calibration specialist. They have collected a lot of samples over years and measured them with NIR and analyced it with reference methods. The NIR spectra are then calibrated against the reference values. This is called a NIR calibration or calibration model or sometimes calibration curve or calibration equation. Normally a precalibration is delivered as a file that is compatible to the used NIR analysis software. Such a calibration file does not contain the spectra nor the reference values.

So how can that work?

The only thing that is in the file is a description what it is for (e.g. protein in feed) and the chemometric model that is represented and stored as list of vectors and matrices. You can’t visualize them, it’s a black-box file. You have no insight of how the calibration is done, how are the settings, how is the prediction performance. You can not extend the calibration with your data to adjust it to your purpose or specialty. Most often the pre calibration files are protected, so you can use it only with a paid license to your software or even to your instrument serials number. These are some (not well known) limitations you will discover if you got one. But such starter calibrations are very useful to have a fast and easy start with a new NIR spectrometer. That’s the main reason why pre-calibrations are available. The second reason is that a collection of spectra can be reused to build such pre calibrations.

Predicting the future?

Are very old spectra useful to predict the future? To adjust a calibration model with newly collected data, the calibrations grows and contains more and more redundancy. That means there are very similar spectra with the same concentration range. So which spectra can be removed to make the calibration better? You maybe never ask this because often you hear, that the more spectra you put into a model the better it will be. Why to remove some spectra?
  • reduce not needed redundancy
  • makes the calibration smaller and less complex
  • makes the calibration better fit to the current situation of now and the near future
  • remove long past seasonal data if you have natural products because nature is changing
  • and of course bad outliers should be removed

Custom NIR calibrations

Build your own calibrations that perfectly fit to your specific sample matrix of your products and your preferred raw materials from your local suppliers. Nature grows differently depending on the geographical region, by seasons and year by year. As you know that NIR-Spectroscopy is not an absolute method, then you have to think about to calibrate these current changing effects into your models. If you own the spectra and the reference values then your are able to build your own calibration models and re-calibrate them when needed. So you have the full control on Calibration updates (also known as moving models).

Conclusion

A NIR-instrument can only measure NIR spectra. So the usefulness of NIR comes in with calibrations. That is very important to know when buying such an instrument. For a fast start you can use pre-built calibrations. Good reliably calibrations are offered from third party to quite high prices that level is similar to a cheaper NIR-Instrument! To continue successfully it is highly recommended to develop your own customized calibration (multivariate calibration model) with your own data from your own products, especially with the use of natural resources. Therefore you need knowledge about chemometrics and multivariate analysis (MVA), spectroscopy and the software used to get the calibration optimized. It is worthwhile to create your own calibrations, because you can calibrate product characteristics that are not covered by the proposed pre-calibrations.