Spectroscopy and Chemometrics/Machine-Learning News Weekly #43, 2021

NIR Calibration-Model Services

Espectroscopia e Quimiometria/Máquina-Aprendizagem Semanal 42, 2021 | NIRS NIR Spectroscopia MaquinaLearning Espectrometria Analítica Química Análise Lab Labs Laboratórios Laboratório Software IoT Sensores QA QC Teste Qualidad LINK

Noticias semanales sobre espectroscopia y quimiometría 42, 2021 | NIRS NIR Espectroscopia AprendizajeMáquina Espectrómetro Espectrométrico Analítica Química Análisis Laboratorio Laboratorios Software IoT Sensores QA QC Testing Calidad LINK

Spectroscopy and Chemometrics News Weekly 42, 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 42, 2021 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 42, 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

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Еженедельник новостей спектроскопии и хемометрии/машинного обучения LINK

光谱学和化学计量学/机器学习新闻周刊 | 近红外光谱 机器学习光谱仪 光谱分析化学 化学分析实验室 实验室 实验室软件 物联网传感器 QA QC 测试质量 LINK

分光法とケモメトリックス/機械学習ニュースウィークリー | NIR-分光法機械学習分光計分光分析化学化学分析ラボラボラボラボラボソフトウェアIoTセンサーQAQCテスト品質 LINK




Near-Infrared Spectroscopy (NIRS)

“Rapid prediction of soil available sulphur using visible near-infrared reflectance spectros copy” LINK

“Multispectral and Hyperspectral Reflectance Imaging Spectrometry (VIS, VNIR, SWIR) in Painting Analyses: Undergraduate Teaching and Interfacial Undergraduate …” LINK

“The effectiveness of drug-coated balloons for two dissimilar calcific lesions assessed by near-infrared spectroscopy intravascular ultrasound and optical coherence …” LINK

“The visible and near-infrared optical absorption coefficient spectrum of Parylene C measured by transmitting light through thin films in liquid filled cuvettes” thinfilms LINK

“Predicting heavy metals in dark sun-cured tobacco by near-infrared spectroscopy modeling based on the optimized variable selections” LINK

“Penentuan Indeks Panen Buah Jambu Kristal secara Non Destruktif dengan Spektroskopi NIR” LINK

“In vivo non-invasive near-infrared spectroscopy distinguishes normal, post-stroke, and botulinum toxin treated human muscles” LINK

“Soil Classification Based on Deep Learning Algorithm and Visible Near-Infrared Spectroscopy” | LINK

“… SERAT KASAR DEDAK PADI MENGGUNAKAN JARINGAN SYARAF TIRUAN (JST) BERDASARKAN DATA ABSORBAN NIRS (NEAR INFRARED REFLECTANCE …” LINK

“Correlation of Near-Infrared Spectroscopy Oximetry and Corresponding Venous Oxygen Saturations in Children with Congenital Heart Disease” | LINK

“High Near-Infrared Reflectance Orange Pigments of Fe-Doped La2W2O9: Preparation, Characterization, and Energy Consumption Simulation” LINK




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

“On the Limit of Detection in Infrared Spectroscopic Imaging” LINK

“Minerals : Coupled Substitutions in Natural MnO(OH) Polymorphs: Infrared Spectroscopic Investigation” LINK

“Sensors : Application of High-Speed Quantum Cascade Detectors for Mid-Infrared, Broadband, High-Resolution Spectroscopy” LINK

“Infrared Spectroscopy and Chemometric Applications for the Qualitative and Quantitative Investigation of Grapevine Organs” | LINK

“Aging Pacific cod (Gadus macrocephalus) from otoliths using Fourier‐transformed near‐infrared spectroscopy” LINK




Hyperspectral Imaging (HSI)

“CHEMOMETRIC STRATEGIES FOR NEAR INFRARED HYPERSPECTRAL IMAGING ANALYSIS: CLASSIFICATION OF SEED GENOTYPES” LINK

“Near-infrared hyperspectral imaging technology combined with deep convolutional generative adversarial network to predict oil content of single maize kernel” LINK

“Detecting total acid content quickly and accurately by combining hyperspectral imaging and an optimized algorithm method” LINK

“Hyperspectral-enhanced dark field analysis of individual and collective photo-responsive gold-copper sulfide nanoparticles” LINK

“Ripeness evaluation of kiwifruit by hyperspectral imaging” LINK

“Hyperspectral reflectance imaging for water content and firmness prediction of potatoes by optimum wavelengths” | LINK

“Soluble solid content and firmness index assessment and maturity discrimination of Malus micromalus Makino based on near-infrared hyperspectral imaging” LINK




Chemometrics and Machine Learning

“Comparison of variable selection methods in predictive models applied to near-infrared and genomic data” LINK

“Building kinetic models to determine moisture content in apples and predicting shelf life based on spectroscopy” LINK

“Applied Sciences : Sample Reduction for Physiological Data Analysis Using Principal Component Analysis in Artificial Neural Network” LINK

“MultiTempLSTM: prediction and compression of multitemporal hyperspectral images using LSTM networks” LINK




Facts

“Stop Sending Samples” Off to the Lab” for Analysis: A Machine Learning Solution” LINK




Research on Spectroscopy

“Research on the online rapid sensing method of moisture content in famous green tea spreading” LINK




Process Control and NIR Sensors

“Microcirculatory Monitoring to Assess Cardiopulmonary Status” | LINK

“Advanced Process Analytical Tools for Identification of Adulterants in Edible Oils-A Review” LINK




Environment NIR-Spectroscopy Application

“Remote Sensing : Fine-Scale Sea Ice Segmentation for High-Resolution Satellite Imagery with Weakly-Supervised CNNs” LINK

“Plants : Water Spectral Patterns Reveals Similarities and Differences in Rice Germination and Induced Degenerated Callus Development” LINK

“Remote Sensing : Combining Remote Sensing and Meteorological Data for Improved Rice Plant Potassium Content Estimation” LINK




Agriculture NIR-Spectroscopy Usage

“Nutrients : Plant-Derived and Dietary Hydroxybenzoic AcidsA Comprehensive Study of Structural, Anti-/Pro-Oxidant, Lipophilic, Antimicrobial, and Cytotoxic Activity in MDA-MB-231 and MCF-7 Cell Lines” LINK




Horticulture NIR-Spectroscopy Applications

“Biology : Phylogenetic Analysis and Genetic Diversity of Colletotrichum falcatum Isolates Causing Sugarcane Red Rot Disease in Bangladesh” LINK




Food & Feed Industry NIR Usage

“Feasibility study on quantification and authentication of the cassava starch content in wheat flour for bread-making using NIR spectroscopy and digital images” LINK

“Technological innovations or advancement in detecting frozen and thawed meat quality: A review” LINK




Laboratory and NIR-Spectroscopy

“Separations : Quality Assessment of Camellia oleifera Oil Cultivated in Southwest China” LINK




Other

“A Strategy to Detect and Monitor Coca Production in Colombia, Peru, and Bolivia” LINK

“Measuring Nd(III) Solution Concentration in the Presence of Interfering Er(III) and Cu(II) Ions: A Partial Least Squares Analysis of UltravioletVisible Spectra” UVvis Ultraviolet LINK

“Spectral Properties of Anhydrous Carbonates and Nitrates” LINK

“การจำแนกสายพันธุ์อ้อยด้วยการตรวจวัดลำอ้อยโดยใช้เครื่องอินฟาเรดย่านใกล้สเปกโทรมิเตอร์แบบพกพา” LINK





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 #41, 2020

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 40, 2020 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality LINK

NIR-Spectroscopy and Chemometrics News Weekly 40, 2020 Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 40, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 40, 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)

“Comparison of four mobile, non‐invasive diagnostic techniques for differentiating glass types in historical leaded windows: MA‐XRF, UV–Vis–NIR, Raman …” LINK

“NIR associated to PLS and SVM for fast and non-destructive determination of C, N, P, and K contents in poultry litter” LINK

“Feasibility of FT-NIR spectroscopy and Vis/NIR hyperspectral imaging for sorting unsound chestnuts” LINK

“Estimating purple-soil moisture content using Vis-NIR spectroscopy” | LINK




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

“Classification approaches for sorting maize (Zea mays subsp. mays) haploids using single‐kernel near‐infrared spectroscopy” LINK

“Near Infrared and Aquaphotomic analysis of water absorption in lactate containing media” LINK

“Classification of Imbalanced Near-infrared Spectroscopy Data” LINK

“Meat freshness revealed by visible to near-infrared spectroscopy and principal component analysis” LINK

“Measurement of the diffusion coefficient and hydrogen bonds of water in a dry-protective solution by microscopic near-infrared spectroscopy” LINK

“Authentication of Antibiotics Using Portable Near-Infrared Spectroscopy and Multivariate Data Analysis” LINK

“Infrared spectroscopy approaches support soil organic carbon estimations to evaluate land degradation” LINK

“Assessment of some wood properties by near infrared spectroscopy” LINK

“Impact of spectroscopic information on total column water vapor retrieval in the near-infrared spectral region” LINK

“Prediction of intramuscular fat in lamb by visible and near-infrared spectroscopy in an abattoir environment” LINK




Raman Spectroscopy

“Principal Component Regression for Forensic Age Determination Using the Raman Spectra of Teeth” LINK




Hyperspectral Imaging (HSI)

“Rapid and nondestructive evaluation of hygroscopic behavior changes of thermally modified softwood and hardwood samples using near-infrared hyperspectral imaging (NIR-HSI)” LINK

“Differentiation of Environmental Bacteria Using Hyperspectral Imaging Technology And Multivariate Analysis” LINK




Chemometrics and Machine Learning

“Comprehensive chemometric classification of snack products based on their near infrared spectra” LINK

“Adulteration detection of corn oil, rapeseed oil and sunflower oil in camellia oil by in situ diffuse reflectance near-infrared spectroscopy and chemometrics” LINK

“Near-Infrared Spectroscopy Coupled Chemometric Algorithms for Rapid Origin Identification and Lipid Content Detection of Pinus Koraiensis Seeds” Sensors LINK

“Application of Generative Adversarial Network for the Prediction of Gasoline Properties” LINK

“Near Infrared Reflectance Spectroscopy Coupled to Chemometrics as a Cost-Effective, Rapid and Non-Destructive Tool for Fish Fraud Control: Monitoring Source …” LINK

“Using chemometrics to characterise and unravel the near infra-red spectral changes induced in aubergine fruit by chilling injury as influenced by storage time and …” LINK




Equipment for Spectroscopy

“Water as a probe to understand the traditional Chinese medicine extraction process with near infrared spectroscopy: a case of Danshen (Salvia miltiorrhiza Bge) …” LINK




Process Control and NIR Sensors

“Sample Mass Estimate for the Use of Near-Infrared and Raman Spectroscopy to Monitor Content Uniformity in a Tablet Press Feed Frame of a Drug Product Continuous Manufacturing Process” LINK




Environment NIR-Spectroscopy Application

“ESTIMATION OF SOIL HEAVY METAL COMBINING FRACTIONAL ORDER DERIVATIVE” LINK

“Metabolomics approaches for analysing effects of geographic and environmental factors on the variation of root essential oils of Ferula assa-foetida L.” LINK




Agriculture NIR-Spectroscopy Usage

“Principles and Applications of Vibrational Spectroscopic Imaging in Plant Science: A Review.” LINK




Food & Feed Industry NIR Usage

“Multi-block classification of chocolate and cocoa samples into sensory poles” LINK




Pharma Industry NIR Usage

“Rapid quantification of active pharmaceutical ingredient for sugar-free Yangwei granules in commercial production using FT-NIR spectroscopy based on machine …” LINK




Laboratory and NIR-Spectroscopy

“Resin and volatile content of melamine-impregnated paper assessed by near infrared spectroscopy, a simulation of the industrial process using a laboratory-scale …” | LINK




Other

“Development of an automatic sorting robot for construction and demolition waste” LINK

“SEASONAL SPECTRAL SEPARABILITY OF SELECTED GRASSES: CASE STUDY FROM THE KRKONOŠE MTS. TUNDRA ECOSYSTEM” LINK

“Polymer types ingested by northern fulmars (Fulmarus glacialis) and southern hemisphere relatives.” LINK

“High-sensitive spectroscopy for remote sensing of concrete structures” LINK