Spectroscopy and Chemometrics/Machine Learning News Weekly #35, 2021

NIR Calibration-Model Services

With CM Service you can have customized optimized NIR calibrations developed without subscription. | NIRS NIR Spectroscopy ModelDevelopment MachineLearning Chemometrics LINK

How to develop near-infrared spectroscopy calibrations in the 21st Century? | transmission reflectance absorbance LINK

Spectroscopy and Chemometrics News Weekly 34, 2021 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 34, 2021 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 34, 2021 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK

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

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




Near-Infrared Spectroscopy (NIRS)

“Minerals : The Role of Solar Energy (UV-VIS-NIR) as an Assistant for Sulfide Minerals Leaching and Its Potential Application for Metal Extraction” LINK

“Development of Attenuated Total Reflectance Mid-Infrared (ATR-MIR) and Near-Infrared (NIR) Spectroscopy for the Determination of Resistant Starch Content …” | LINK

“Particle Swarm Optimization and Multiple Stacked Generalizations to Detect Nitrogen and Organic-Matter in Organic-Fertilizer Using Vis-NIR” | LINK

“Inversion Method for Cellulose Content of Rice Stem in Northeast Cold Region Based on Near Infrared Spectroscopy” LINK

“Sensors : Particle Swarm Optimization and Multiple Stacked Generalizations to Detect Nitrogen and Organic-Matter in Organic-Fertilizer Using Vis-NIR” LINK




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

“Smart Detection of Faults in Beers Using Near-Infrared Spectroscopy, a Low-Cost Electronic Nose and Artificial Intelligence” LINK

“Fault Isolation for Desalting Processes Using Near-Infrared Measurements” | LINK

“Temporal Changes in Near-Infrared Spectroscopy Signals in Recurrent In-Stent Restenosis Attributable to Calcified Nodule” LINK




Raman Spectroscopy

“Multivariate Analysis Aided Surface-Enhanced Raman Spectroscopy (MVA-SERS) Multiplex Quantitative Detection of Trace Fentanyl in Illicit Drug Mixtures Using a Handheld Raman Spectrometer” LINK




Hyperspectral Imaging (HSI)

“SWiVIA-Sliding Window Variographic Image Analysis for real-time assessment of heterogeneity indices in blending processes monitored with hyperspectral …” LINK

“Assessing produce freshness using hyperspectral imaging and machine learning” LINK

“Nondestructive prediction and visualization of total flavonoids content in Cerasus Humilis fruit during storage periods based on hyperspectral imaging technique” LINK

“Altered mineral mapping based on ground-airborne hyperspectral data and wavelet spectral angle mapper tri-training model: Case studies from Dehua-Youxi …” LINK




Chemometrics and Machine Learning

“Artificial bionic taste sensors coupled with chemometrics for rapid detection of beef adulteration” LINK

“Identification and Classification of Technical Lignins by means of Principle Component Analysis and kNearest Neighbor Algorithm” LINK

“A 50-year personal journey through time with principal component analysis. Ian Jolliffe. Journal of Multivariate Analysis.” LINK

“A feasibility quantitative analysis of free fatty acids in polished rice by fourier transform near‐infrared spectroscopy and chemometrics” LINK

“Forensics Applications of Raman Spectroscopy, ATR FT-IR, and Chemometrics” LINK

“Fast and non-destructive near infrared spectroscopic analysis associated with chemometrics: an efficient tool in assisting breeding programs” LINK

“Chemosensors : Environmental Odour Quantification by IOMS: Parametric vs. Non-Parametric Prediction Techniques” LINK

“ACD/Labs Partners with Science Data Experts to Aid Life Sciences Companies in Accelerating Their Implementation of Machine Learning and Artificial Intelligence Technologies” | MachineLearning ArtificialIntelligence Partnership LINK

“Remote Sensing : UCalib: Cameras Autocalibration on Coastal Video Monitoring Systems” LINK

“Medical urine analysis method based on Vis-NIR optical spectroscopy using machine learning algorithms.” LINK

“A feasibility quantitative analysis of free fatty acids in polished rice by fourier transform nearinfrared spectroscopy and chemometrics” LINK

“Diffuse reflectance spectroscopy based rapid coal rank estimation: A machine learning enabled framework” LINK

“Remote Sensing : Mapping Plastic Greenhouses with Two-Temporal Sentinel-2 Images and 1D-CNN Deep Learning” LINK




Research on Spectroscopy

“Polymers : Role of the Anilinium Ion on the Selective Polymerization of Anilinium 2-Acrylamide-2-methyl-1-propanesulfonate” LINK




Environment NIR-Spectroscopy Application

“A knowledge-based, validated classifier for the identification of aliphatic and aromatic plastics by WorldView-3 satellite data” LINK

“Sustainability : Assessment of Soil Pollution Levels in North Nile Delta, by Integrating Contamination Indices, GIS, and Multivariate Modeling” LINK

“Sensing and data fusion opportunities for raw material characterisation in mining: Technology and data-driven approach” LINK




Agriculture NIR-Spectroscopy Usage

“Evaluation of non-invasive bioforensic techniques for determining the age of hot-iron brand burn scars in cattle” LINK

“Nutrients : Diet and Leukocyte Telomere Length in a Population with Extended Longevity: The Costa Rican Longevity and Healthy Aging Study (CRELES)” LINK

“Spectral and lifetime resolution of fundus autofluorescence in advanced age‐related macular degeneration revealing different signal sources” LINK

“Linking insect herbivory with plant traits: phylogenetically structured trait syndromes matter” LINK

“An in vitro Propagation of Aspilia africana (Pers.) C. D. Adams, and Evaluation of Its Anatomy and Physiology of Acclimatized Plants” | LINK

“Urban Science : Effects of Urbanization on Ecosystem Services in the Shandong Peninsula Urban Agglomeration, in China: The Case of Weifang City” LINK

“Binding to Amyloid Protein by Photothermal BloodBrain BarrierPenetrating Nanoparticles for Inhibition and Disaggregation of Fibrillation” LINK




Food & Feed Industry NIR Usage

“Molecules : The Effect of Fat Content and Fatty Acids Composition on Color and Textural Properties of Butter” LINK

“Nondestructive identification of barley seeds variety using nearinfrared hyperspectral imaging coupled with convolutional neural network” LINK

“Effect of Weather Conditions on the Fatty Acid Composition of Medium-Growth Chicken Reared in Organic Production System” LINK




Beverage and Drink Industry NIR Usage

“Chemosensors : Multi-Sensor Characterization of Sparkling Wines Based on Data Fusion” LINK

“コーヒー生豆の品質基準に関する研究” “Coffee flavor is considerably influenced by the quality of green coffee beans. ” LINK




Other

AI computers can’t patent their own inventions …. LINK



“Rape Variety Identification Based on Canopy Spectral Parameters” LINK

“Critical Review of LASSO and Its Derivatives for Variable Selection Under Dependence Among Covariates.” LINK

“近红外光谱法快速测定养生酒的酒精度方法研究” LINK

“全球食品领域近红外光谱应用研究文献计量分析” LINK

“Photochemical Synthesis of Nonplanar Small Molecules with Ultrafast Nonradiative Decay for Highly Efficient Phototheranostics” LINK

“Fluorescent Silicon Carbide Nanoparticles” LINK





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Digitization in the field of NIR spectroscopy (smart sensors)

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

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

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

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

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

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

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

Advantages for your NIR users (internal or external)
  • no initial costs (no chemometrics software license required),
  • calculable operating costs (fixed amount instead of time and hourly rate) (calibration development, calibration maintenance)
  • easy to use (no chemometrics and software training),
  • quicker to use (no calibration development work) and
  • better calibrations (precision, accuracy, robustness, …)


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

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

The unique advantages of our calibration service together with the free NIR Predictor are:
  • no software license costs (chemometrics software, predictor software, OEM integration)
  • no chemometrics know-how necessary
  • no time needed to develop optimal NIR calibrations.


If interested in using/evaluating the service :

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



see also

Paradigm Change in NIR

Five Mistakes to avoid on Digitalization in NIR

NIR – Total cost of ownership (TCO)

OEM / White Label Software

White Paper



Spectroscopy and Chemometrics News Weekly #21, 2020

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

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


NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 20, 2020 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 20, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 20, 2020 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK




Near-Infrared Spectroscopy (NIRS)

“New applications of visnir spectroscopy for the prediction of soil properties” LINK

“Simultaneous determination of quality parameters in yerba mate (Ilex paraguariensis) samples by application of near-infrared (NIR) spectroscopy and partial least …” LINK

“Fault detection with moving window PCA using NIRS spectra for the monitoring of anaerobic digestion process” LINK

“Control of ascorbic acid in fortified powdered soft drinks using near-infrared spectroscopy (NIRS) and multivariate analysis.” LINK

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




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

“ripening stages monitoring of Lamuyo pepper using a new‐generation near‐infrared spectroscopy sensor” LINK

“Modeling bending strength of oil-heat-treated wood by near-infrared spectroscopy” LINK

“Performance Improvement of Near-Infrared Spectroscopy-Based Brain-Computer Interface Using Regularized Linear Discriminant Analysis Ensemble Classifier Based on Bootstrap Aggregating.” LINK

“Continuously measurement of the dry matter content using near-infrared spectroscopy” LINK

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

“Rapid identification of Lilium species and polysaccharide contents based on near infrared spectroscopy and weighted partial least square method.” LINK

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

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

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

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

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




Raman Spectroscopy

“Differentiating cancer cells using Raman spectroscopy (Conference Presentation)” LINK




Hyperspectral Imaging (HSI)

“A deep learning based regression method on hyperspectral data for rapid prediction of cadmium residue in lettuce leaves” LINK

“Detection of fish fillet substitution and mislabeling using multimode hyperspectral imaging techniques” LINK

“Deep learning applied to hyperspectral endoscopy for online spectral classification” DOI:10.1038/s41598-020-60574-6 LINK

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

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




Chemometrics and Machine Learning

“Identification of invisible biological traces in forensic evidences by hyperspectral NIR imaging combined with chemometrics” LINK

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

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




Equipment for Spectroscopy

“Determination of soluble solids content in Prunus avium by Vis/NIR equipment using linear and non-linear regression methods” LINK

“Characterization of Deep Green Infection in Tobacco Leaves Using a Hand-Held Digital Light Projection Based Near-Infrared Spectrometer and an Extreme Learning …” LINK




Environment NIR-Spectroscopy Application

“An Evaluation of Citizen Science Smartphone Apps for Inland Water Quality Assessment” LINK




Agriculture NIR-Spectroscopy Usage

“Robustness of visible/near and midinfrared spectroscopic models to changes in the quantity and quality of crop residues in soil” LINK

“Complex Food Recognition using Hyper-Spectral Imagery” LINK

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




Horticulture NIR-Spectroscopy Applications

” The Effect of Spent Mushroom Substrate and Cow Slurry on Sugar Content and Digestibility of Alfalfa Grass Mixtures” LINK




Laboratory and NIR-Spectroscopy

“The influence analysis of reflectance anisotropy of canopy on the prediction accuracy of Cu stress based on laboratory multi-directional measurement” LINK

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









Spectroscopy and Chemometrics News Weekly #13, 2020

CalibrationModel.com

We have updated the free NIR-Predictor-Software Spectral Data format support list for many mobile and benchtop NIR Spectroscopy Sensors. | Used in QualityControl for Food Fruits Milk Meat LINK

CalibrationModel.com has changed the pricing structure and NIRS-Calibration licensing options (including new perpetual and unlimited systems). NIR Spectroscopy Chemometric AutoML Calibration Development Service milk meet food qualitycontrol LINK

“NIR-Spectroscopy Cost & Price Comparison of Chemometrics, MachineLearning and DataScience for NIRS Application Development” | HomeOffice Laboratory Spectroscopy TimeSaving BetterResults TCO LINK

Do you want better NIRS prediction results? Use your Near-Infrared Analysis data and do recalibration adjustment LINK

Spectroscopy and Chemometrics News Weekly 12, 2020 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 12, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot FoodTech Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie LINK

Spettroscopia e Chemiometria Weekly News 12, 2020 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK




Near Infrared

The journal Sensors (ISSN 1424-8220) is currently running a Special Issue  “Using Vis-NIR Spectroscopy for Predicting Quality Compounds in Foods” LINK

“Application of NIRS in Nutrient Composition Evaluation of Lathyrus sativus” LINK

“Forecasting the potential of apple fruitlet drop by in-situ Vis-NIR spectroscopy” LINK

“Near infrared spectroscopy (NIRS) data analysis for a rapid and simultaneous prediction of feed nutritive parameters” LINK

“Evaluation by NIRS technology of curing process of ham with low sodium content” LINK

“Optical transmission spectra study in visible and near-infrared spectral range for identification of rough transparent plastics in aquatic environments.” LINK

“Sensors, Vol. 20, Pages 874: Improved Deep CNN with Parameter Initialization for Data Analysis of Near-Infrared Spectroscopy Sensors” LINK

“Terahertz Time of Flight Spectroscopy as a Coating Thickness Reference Method for Partial Least Squares Near Infrared Spectroscopy Models.” LINK

“Quantitative detection of apple watercore and soluble solids content by near infrared transmittance spectroscopy” LINK

“Glucose Monitoring in Cell Culture with Online Ultrasound-Assisted Near-Infrared Spectroscopy.” LINK

“Development of nearinfrared online grading device for long jujube” LINK

“Nearinfrared reflectance spectroscopy based online moisture measurement in copra” LINK

“Remote Sensing, Vol. 12, Pages 469: Repaid Identification and Prediction of CadmiumLead Cross-Stress of Different Stress Levels in Rice Canopy Based on Visible and Near-Infrared Spectroscopy” LINK

“In vivo relationship between near-infrared spectroscopy-detected lipid-rich plaques and morphological plaque characteristics by optical coherence tomography and …” LINK

“The Kinetic Model of the Peel Brittleness of Stored Cucumis Melons Based on Visible/Near-Infrared Spectroscopy” LINK




Hyperspectral Imaging

“Applied Sciences, Vol. 10, Pages 1173: Rapid and Nondestructive Discrimination of Geographical Origins of Longjing Tea using Hyperspectral Imaging at Two Spectral Ranges Coupled with Machine Learning Methods” LINK

“Remote Sensing, Vol. 12, Pages 537: Detecting the Sources of Methane Emission from Oil Shale Mining and Processing Using Airborne Hyperspectral Data” LINK

“Comparative analysis of mineral mapping for hyperspectral and multispectral imagery” LINK




Chemometrics

“Comparison of the performance of partial least squares and support vector regressions for predicting fatty acids/fatty acid classes in marine oil dietary supplements using vibrational spectroscopic data.” LINK

“Prediction of water contents in biscuits using near infrared hyperspectral imaging spectroscopy and chemometrics” LINK

“Vis-NIR Hyperspectral Imaging for the Classification of Bacterial Foodborne Pathogens based on pixel-wise analysis and a novel CARS-PSO-SVM model” LINK

“Using the random forest model and validated MODIS with the field spectrometer measurement promote the accuracy of estimating aboveground biomass and …” LINK




Research

“A spatially resolved transmittance spectroscopy system for detecting internal rots in onions” LINK




Equipment

“Use of a handheld near infrared spectrometer and partial least squares regression to quantify metanil yellow adulteration in turmeric powder” LINK




Agriculture

“Remote Sensing, Vol. 12, Pages 574: Advancing High-Throughput Phenotyping of Wheat in Early Selection Cycles” LINK

“Evaluation of analytical and statistical approaches for predicting in vitro nitrogen solubility and in vivo pre-caecal crude protein digestibility of cereal grains in growing pigs.” LINK

“Detecting Frost Stress in Wheat: A Controlled Environment Hyperspectral Study on Wheat Plant Components and Implications for Multispectral Field Sensing” LINK

“Sensors, Vol. 20, Pages 867: Predicting Forage Quality of Warm-Season Legumes by Near Infrared Spectroscopy Coupled with Machine Learning Techniques” LINK

On their page, they offer a “Purchase Instant Access”. Or contact the author. LINK

“Detection of Invisible Damage of Kiwi Fruit Based on Hyperspectral Technique” LINK

“Nondestructive detection of storage time of strawberries using visible/near-infrared hyperspectral imaging” LINK

“Scaling up of NIRS facility in Mali for analysis of biomass quality for GLDC crops Final Technical Report” LINK




Food & Feed

“Comparison of various pharmaceutical properties of clobetasol propionate cream formulations – considering stability of mixture with moisturizer.” LINK

“Foods, Vol. 9, Pages 154: Rapid Identification and Visualization of Jowl Meat Adulteration in Pork Using Hyperspectral Imaging” LINK




Laboratory

What Lab Manager need to know about NIRSpectroscopy total cost of ownership (TCO) and DataScience. LabManagers LabManager FoodQuality Automate QualityControl foodtech foodtechnologies Laboratory LINK





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NIR Method Development Service for Labs and NIR-Vendors (OEM)


CalibrationModel.com ia a perfect match for
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    Before
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    with
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    DATA = exported
Spectra and (Lab-)reference values as JCAMP-DX or other data formats
    CALIB = single quantitative property


Sending DATA
    DATA is sent by email, 2-3 days later, receive email with link to
      WebShop to purchase CALIB with PayPal/CreditCard
    DATA is
deleted after processing (Terms of Service TOS)
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    owner can
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Re-Calibration
    DATA + DATA -> CALIB    same easy workflow as    DATA -> CALIB
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NIR-Predictor Software
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