Spectroscopy and Chemometrics Machine-Learning News Weekly #31, 2022

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 30, 2022 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 30, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 30, 2022 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK




Near-Infrared Spectroscopy (NIRS)

“Peatlands spectral data influence in global spectral modelling of soil organic carbon and total nitrogen using visible-near-infrared spectroscopy” LINK

“A NIRS Based Device for Identification of Acute Ischemic Stroke by Using a Novel Organic Dye in the Human Blood Serum” | LINK

“Interlacing the evaluation of mechanical properties of mortar cement with near-infrared spectroscopy using multivariate data analysis” LINK

“A Preliminary Study to Classify Corn Silage for High or Low Mycotoxin Contamination by Using near Infrared Spectroscopy” | LINK

“Scalable, NanometerAccurate Fabrication of AllDielectric Metasurfaces with Narrow Resonances Tunable from Near Infrared to Visible Wavelengths” LINK

“A Combined Near-Infrared and Mid-Infrared Spectroscopic Approach for the Detection and Quantification of Glycine in Human Serum” | LINK

“Sensors : Determination of Quality Parameters in Mangetout (Pisum sativum L. ssp. arvense) by Using Vis/Near-Infrared Reflectance Spectroscopy” LINK

“Study on the Effect of Apple Size Difference on Soluble Solids Content Model Based on Near-Infrared (NIR) Spectroscopy” | LINK

“Canopy VIS-NIR spectroscopy and self-learning artificial intelligence for a generalised model of predawn leaf water potential in Vitis vinifera” LINK

“Chemical composition of Andropogon gayanus cv. planaltina predicted through nirs and analyzed through wet chemistry” LINK

“A Preliminary Study to Classify Corn Silage for High or Low Mycotoxin Contamination by Using near Infrared Spectroscopy” LINK

“Model robustness in estimation of blueberry SSC using NIRS” LINK

“Non-invasive Measurement of Blood Sugar Using Near-Infrared Spectroscopy” | LINK

“Investigating the Utility of Near Infrared Reflectance (NIR) Imaging for Diabetic Retinopathy Screening” LINK

“Fourier transform near infrared spectroscopy as a tool to predict spawning status in Alaskan fishes with variable reproductive strategies” LINK

“Prediction of dry matter, carbon and ash contents and identification of Calycophyllum spruceanum (Benth) organs by Near-Infrared Spectrophotometry” LINK

“Determination of aflatoxin B1 value in corn based on Fourier transform near-infrared spectroscopy: Comparison of optimization effect of characteristic …” LINK

“Combining different pre-processing and multivariate methods for prediction of soil organic matter by near infrared spectroscopy (NIRS) in Southern Brazil” LINK

“Evaluation of coating uniformity for the digestion-aid tablets by portable near-infrared spectroscopy” LINK

“Novel strategies in near infrared spectroscopy (NIRS) and multivariate analysis (MVA) for detecting and profiling pathogens and diseases of agricultural importance.” LINK




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

“A highly efficient colloidal quantum dot imager that operates at near-infrared wavelengths” LINK

“Green tea grades identification via Fourier transform near‐infrared spectroscopy and weighted global fuzzy uncorrelated discriminant transform” LINK

“Investigation of oxygen saturation in regions of skin by near infrared spectroscopy” LINK

“Spectral variable selection for estimation of soil organic carbon content using midinfrared spectroscopy” LINK

“Plants : Uptake and Presence Evaluation of Nanoparticles in Cicer arietinum L. by Infrared Spectroscopy and Machine Learning Techniques” LINK

“Electric-field-resolved near-infrared microscopy” LINK




Raman Spectroscopy

“A comparative study based on serum SERS spectra in and on the coffee ring for high precision breast cancer detection” LINK

“Raman spectroscopy and multivariate analysis for identification and classification of pharmaceutical pain reliever tablets” LINK

“Foods : High Precisive Prediction of Aflatoxin B1 in Pressing Peanut Oil Using Raman Spectra Combined with Multivariate Data Analysis” LINK




Hyperspectral Imaging (HSI)

” Identification of pesticide residues on black tea by fluorescence hyperspectral technology combined with machine learning” LINK

“Combining hyperspectral imaging and electrochemical sensing for detection of Pseudomonas aeruginosa through pyocyanin production” LINK




Spectral Imaging

“Open-source mobile multispectral imaging system and its applications in biological sample sensing” LINK




Chemometrics and Machine Learning

“Sensors : A Model for Predicting Cervical Cancer Using Machine Learning Algorithms” LINK

“Application of miniature fiber near infrared spectroscopy combined with chemometrics in predicting antioxidant activity of Sagittaria sagittifolia L …” LINK

“Comparison of Calibration Models for Rapid Prediction of Lignin Content in Lignocellulosic Biomass Based on Infrared and Near-Infrared Spectroscopy” LINK

“Foods : Shelf-Life Prediction and Critical Value of Quality Index of Sichuan Sauerkraut Based on Kinetic Model and Principal Component Analysis” LINK




Spectroscopy

“Giorgia Stocco Rapid and non-destructive determination of Ca and P in milk using WDXRF” LINK




Facts

” A Review of Machine Learning Techniques for Identifying Weeds in Corn” LINK




Research on Spectroscopy

“Syntheses, Structures, and Properties of Coordination Polymers with 2,5-Dihydroxy-1,4-Benzoquinone and 4,4′-Bipyridyl Synthesized by In Situ Hydrolysis Method” LINK




Equipment for Spectroscopy

“Polymers : Combined Strategy of Wound Healing Using Thermo-Sensitive PNIPAAm Hydrogel and CS/PVA Membranes: Development and In-Vivo Evaluation” LINK




Future topics in Spectroscopy

“The Effect of Task Performance and Partnership on Interpersonal Brain Synchrony during Cooperation” LINK




Process Control and NIR Sensors

“Monitoring of dromedary milk clotting process by Urtica dioica extract using fluorescence, near infrared and rheology measurements” LINK




Environment NIR-Spectroscopy Application

“Remote Sensing : Combination of Hyperspectral and Machine Learning to Invert Soil Electrical Conductivity” LINK

“Sensors : Comparative Study on Recognition Models of Black-Odorous Water in Hangzhou Based on GF-2 Satellite Data” LINK




Agriculture NIR-Spectroscopy Usage

“Vis-NIR Spectroscopy and Machine Learning Methods to Diagnose Chemical Properties in Colombian Sugarcane Soils” LINK

“Nutrients : Long-Term Dietary Patterns Are Reflected in the Plasma Inflammatory Proteome of Patients with Inflammatory Bowel Disease” LINK

“Remote Sensing : Hyperspectral UAV Images at Different Altitudes for Monitoring the Leaf Nitrogen Content in Cotton Crops” LINK

“Plants : Integrated Starches and Physicochemical Characterization of Sorghum Cultivars for an Efficient and Sustainable Intercropping Model” LINK

“Remote Sensing : Estimation of Canopy Structure of Field Crops Using Sentinel-2 Bands with Vegetation Indices and Machine Learning Algorithms” LINK




Horticulture NIR-Spectroscopy Applications

“Foods : Physico-Chemical, Textural and Sensory Evaluation of Spelt Muffins Supplemented with Apple Powder Enriched with Sugar Beet Molasses” LINK




Food & Feed Industry NIR Usage

“Warming increase the N2O emissions from wheat fields but reduce the wheat yield in a rice-wheat rotation system” LINK

“Biochemical study of rapid discolouration mechanisms in bison meat” LINK

“Emerging Nondestructive Techniques for the Quality and Safety Evaluation of Pork and Beef: Recent Advances, Challenges and Future Perspectives” LINK




Pharma Industry NIR Usage

“The Conservation of Cloud Pattern-painted Boots (1800-1600 BP) Excavated in Yingpan, Xinjiang” | LINK




Other

“基于 WOS 的高光谱技术在农业方面应用的计量分析” LINK

“Modified Hybrid Strategy Integrating Online Adjustable Oil Property Characterization and Data-Driven Robust Optimization under Uncertainty: Application in Gasoline …” LINK

“Insights into the Effect of Sludge Retention Times on System Performance, Microbial Structure and Quorum Sensing in an Activated Sludge Bioreactor” | LINK

“Diclofenac Ion Hydration: Experimental and Theoretical Search for Anion Pairs” LINK

“Aort cerrahisinde derin ve ılımlı hipotermik antegrad serebral perfüzyonun nörolojik etkileri” LINK

“Vibrational spectroscopic evaluation of hydrophilic or hydrophobic properties of oxide surfaces” LINK




Spectroscopy and Chemometrics/Machine-Learning News Weekly #23, 2022

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 22, 2022 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 22, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 22, 2022 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK




Near-Infrared Spectroscopy (NIRS)

“Sensors : Potential of Near-Infrared Spectroscopy for the Determination of Olive Oil Quality” LINK

“Physiological variable predictions using VIS-NIR spectroscopy for water stress detection on grapevine: Interest in combining climate data using multiblock method” LINK

“SpectraNet-53: A deep residual learning architecture for predicting soluble solids content with VIS-NIR spectroscopy” LINK

“Measurement of water-holding capacity in fermented milk using near-infrared spectroscopy combined with chemometric methods” LINK

“Investigating the water structures in reverse micelles by temperature-dependent near infrared spectroscopy combined with independent component analysis” LINK

“Chemosensors : Digital Detection of Olive Oil Rancidity Levels and Aroma Profiles Using Near-Infrared Spectroscopy, a Low-Cost Electronic Nose and Machine Learning Modelling” LINK

“A new variant position of head-up CPR may be associated with improvement in the measurements of cranial near-infrared spectroscopy suggestive of an increase in …” LINK

“Design of an Integrated Near-Infrared Spectroscopy Module for Sugar Content Estimation of Apples” | LINK

“Comparison of several strategies for the deployment of a multivariate regression model on several handheld NIR instruments. Application to the Quality Control of …” LINK

“Cross-Modal Transfer Learning From EEG to Functional Near-Infrared Spectroscopy for Classification Task in Brain-Computer Interface System” | |(08)70223-0 LINK

“Novel Application of NIR Spectroscopy for Non-Destructive Determination of ‘Maratina’ Wine Parameters” LINK

“Effects of degraded speech processing and binaural unmasking investigated using functional near-infrared spectroscopy (fNIRS)” LINK

“Rapid monitoring of flavonoid content in sweet tea (Lithocarpus litseifolius (Hance) Chun) leaves using NIR spectroscopy” | LINK

“Simultaneous determination of apparent amylose, amylose and amylopectin content and classification of waxy rice using near-infrared spectroscopy (NIRS)” LINK

“Design of an Integrated Near-Infrared Spectroscopy Module for Sugar Content Estimation of Apples” LINK

“Nondestructive Testing of Pear Based on Fourier Near-Infrared Spectroscopy” | LINK

“NIRSCAM: A Mobile Near-Infrared Sensing System for Food Calorie Estimation” LINK

“Potential of Near-Infrared Spectroscopy for the Determination of Olive Oil Quality” | LINK

“A new concept of acousto-optic tunable filter-based near-infrared hyperspectral imager for planetary surface exploration” LINK

“Multivariety and multimanufacturer drug identification based on near-infrared spectroscopy and recurrent neural network” | LINK

“Rapid identification of lamb freshness grades using visible and near-infrared spectroscopy (Vis-NIR)” LINK

“Blended Fabric with Integrated Neural Network based on Attention Mechanism Qualitative Identification Method of Near Infrared Spectroscopy” LINK

“ex type determination in papaya seeds and leaves using near infrared spectroscopy combined with multivariate techniques and machine learnin” LINK

“Enhancing count of Aspergillus colony in wheat based on nanoparticles modified chemo-responsive dyes combined with visible/near-infrared spectroscopy” LINK




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

“Physicochemical Properties and Detection of Glucose Syrup Adulterated Kelulut (Heterotrigona Itama) Honey Using Near‐Infrared Spectroscopy” LINK

“Applied Sciences : Use of Fourier-Transform Infrared Spectroscopy for DNA Identification on Recycled PET Composite Substrate” LINK

“Identification of Five Similar Cinnamomum Wood Species Using Portable Near-Infrared Spectroscopy” LINK

“Rapid identification of the geographic origin of Taiping Houkui green tea using nearinfrared spectroscopy combined with a variable selection method” LINK

“A Fast Method to Sparse Reconstruction for Near-infrared Spectroscopy” LINK

“Thermal-Infrared Spectral Feature Analysis and Spectral Identification of Monzonite Using Feature-Oriented Principal Component Analysis” LINK

“Nondestructive quality assessment of longans using near infrared hyperspectral imaging” LINK




Raman Spectroscopy

“Biomedicines : Lung Cancer: Spectral and Numerical Differentiation among Benign and Malignant Pleural Effusions Based on the Surface-Enhanced Raman Spectroscopy” LINK

“Robust Encapsulation of Biocompatible Gold Nanosphere Assemblies for Bioimaging via Surface Enhanced Raman Scattering” LINK




Hyperspectral Imaging (HSI)

“Detecting aggressive papillary thyroid carcinoma using hyperspectral imaging and radiomic features” LINK

“Quantitative Detection of Myoglobin Content in Tan Mutton During Cold Storage by Near-infrared Hyperspectral Imaging” | LINK

“Rapid and non-destructive detection of natural mildew degree of postharvest Camellia oleifera fruit based on hyperspectral imaging” LINK

“A new quantitative index for the assessment of tomato quality using Vis-NIR hyperspectral imaging” LINK




Chemometrics and Machine Learning

“Authenticity green coffee bean species and geographical origin using near‐infrared spectroscopy combined with chemometrics” LINK

“Advanced process control for salvianolic acid A conversion reaction based on data-driven and mechanism-driven model” LINK

“A comparison of benchtop and micro NIR spectrometers for infant milk formula powder storage time discrimination and particle size prediction using chemometrics and …” LINK

“Origin identification of foxtail millet (Setaria italica) by using green spectral imaging coupled with chemometrics” LINK

“A two-dimensional sample screening method based on data quality and variable correlation” LINK




Research on Spectroscopy

“Novel regularization method for diffuse optical tomography inverse problem” LINK




Equipment for Spectroscopy

“Advances in costeffective integrated spectrometers” IoT miniature sensors applications LINK




Environment NIR-Spectroscopy Application

“Particle densities of cultivated south greenlandic soils can be explained by a three‐compartment model, pedotransfer functions, and a vis-NIR spectroscopy model” LINK




Agriculture NIR-Spectroscopy Usage

“Polymers : Preparation of a Novel Nanocomposite and Its Antibacterial Effectiveness against Enterococcus faecalis—An In Vitro Evaluation” LINK

“Synthesis of a mixedvalent europium(II, III)borate and its optical and magnetic behavior” LINK

“Performance of analytical techniques (SWIR imaging, XRD, EPMA) for the identification of minerals frequently formed during natural and technological geothermal …” LINK

“Functional N-cycle genes in soil and N2O emissions in tropical grass-maize intercropping systems” LINK

“Agriculture : Forever Young? Late Shoot Pruning Affects Phenological Development, Physiology, Yield and Wine Quality of Vitis vinifera cv. Malbec” LINK

“Aquaphotomic, E-Nose and Electrolyte Leakage to Monitor Quality Changes during the Storage of Ready-to-Eat Rocket” LINK

“Investigation of physicochemical properties, photoluminescence, laser damage threshold, antimicrobial, NLO activity of L-proline manganese chloride monohydrate …” | LINK




Horticulture NIR-Spectroscopy Applications

“Consensual Regression of Soluble Solids Content in Peach by Near Infrared Spectrocopy” | LINK




Food & Feed Industry NIR Usage

“Quantitative assessment of wheat quality using nearinfrared spectroscopy: A comprehensive review” LINK

“Calculation of the Mixing Time as a Function of the Dairy Cow Diet Chemical Homogeneity Inside the Mixing Hopper” | LINK

“Discrimination of centre composition in panned chocolate goods using nearinfrared spectroscopy” LINK

“Advanced Spectroscopic Techniques for Food Quality” FoodQuality FoodSecurity FoodSafety Spectroscopy LINK

“CONCISE REVIEWS AND HYPOTHESES IN FOOD SCIENCE” LINK

“Adulteration detection technologies used for halal/kosher food products: an overview” | LINK

“Synthesis and characterization of theJapanese rice-ball’-shaped Molybdenum Blue Na4 [Mo2O2 (OH) 4 (C6H4NO2) 2] 2 [Mo120Ce6O366H12 (OH) 2 (H2O) 76]∼ …” LINK




Pharma Industry NIR Usage

“Detection of low numbers of bacterial cells in pharmaceutical drug product using Raman Spectroscopy and PLS-DA multivariate analysis” LINK




Laboratory and NIR-Spectroscopy

“Multifunctional superhydrophobic and cool coating surfaces of the blue ceramic nanopigments based on the heulandite zeolite” LINK




Other

“Influence of anisotropy on heterogeneous nucleation of gold nanorod assemblies” LINK

“Phenomic selection: A new and efficient alternative to genomic selection” | LINK





Spectroscopy and Chemometrics/Machine-Learning News Weekly #6, 2022

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 5, 2022 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 5, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 5, 2022 | 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)

“Heat impact control in flash pasteurization by estimation of applied pasteurization units using near infrared spectroscopy” LINK

“Rapid and real-time detection of moisture in black tea during withering using micro-near-infrared spectroscopy” LINK

“Rapid Quality Discrimination of Grape Seed Oil Using an Extreme Machine Learning Approach with Near-Infrared (NIR) Spectroscopy” LINK

“Non-destructive prediction of the hotness of fresh pepper with a single scan using portable near infrared spectroscopy and a variable selection strategy” LINK

“Hyperspectral remote sensing for foliar nutrient detection in forestry: A near-infrared perspective” LINK

“High Near-Infrared Reflective Zn1-xAxWO4 Pigments with Various Hues Facilely Fabricated by Tuning Doped Transition Metal Ions (A = Co, Mn, and Fe)” LINK

“Identifying the main drivers of the seasonal decline of near-infrared reflectance of a temperate deciduous forest” LINK




Hyperspectral Imaging (HSI)

“Estimation of soil organic matter content using selected spectral subset of hyperspectral data” LINK

“Applied Sciences : Detection of Foreign Materials on Broiler Breast Meat Using a Fusion of Visible Near-Infrared and Short-Wave Infrared Hyperspectral Imaging” LINK

“Feasibility Study of Wood-leaf Separation Based on Hyperspectral LiDAR Technology in Indoor Circumstances” LINK

“Calibration of Short-Wave InfraRed (SWIR) hyperspectral imaging using Diffuse Reflectance infrared Fourier Transform spectroscopy (DRIFTS) to obtain continuous …” LINK




Chemometrics and Machine Learning

“Remote Sensing : Estimation of Salinity Content in Different Saline-Alkali Zones Based on Machine Learning Model Using FOD Pretreatment Method” LINK




Research on Spectroscopy

“Portable vibrational spectroscopic methods can discriminate between grass-fed and grain-fed beef” LINK

“Dataanalysis method for material optimization by forecasting longterm chemical stability” LINK




Process Control and NIR Sensors

“Gaussian Process Inspired Neural Networks for Spectral Unmixing Dataset Augmentation” LINK

“Copper (I) selenocyanate (CuSeCN): Eco-friendly solution-processable deposition of hole transport layer for organic solar cells” LINK




Environment NIR-Spectroscopy Application

“Soil erodibility prediction by Vis-NIR spectra and environmental covariates coupled with GIS, regression and PLSR in a watershed scale, Iran” LINK

“Remote Sensing : Retrieval of Phytoplankton Pigment Composition from Their In Vivo Absorption Spectra” LINK




Agriculture NIR-Spectroscopy Usage

“Remote Sensing : Using Sentinel-2 Images for Soil Organic Carbon Content Mapping in Croplands of Southwestern France. The Usefulness of Sentinel-1/2 Derived Moisture Maps and Mismatches between Sentinel Images and Sampling Dates” LINK

“Rapid Directed Molecular Evolution of Fluorescent Proteins in Mammalian Cells” LINK

“First identification of sudoite in Caribbean Ceramic-Age lapidary craftsmanship” LINK

“Elevated carbon dioxide stimulates nitrous oxide emission in agricultural soils: A global meta-analysis”LINK




Food & Feed Industry NIR Usage

“Photonics : Raman Spectroscopy Enables Non-Invasive Identification of Mycotoxins р. Fusarium of Winter Wheat Seeds” LINK




Pharma Industry NIR Usage

“The relationship between renal oxygen saturation and renal function in patients with and without diabetes following coronary artery bypass grafting surgery” LINK




Medicinal Spectroscopy

“Evaluation of Functional Capacity and Muscle Metabolism in Individuals with Peripheral Arterial Disease with and without Diabetes” | LINK




Other

“Global meta-analysis of terrestrial nitrous oxide emissions and associated functional genes under nitrogen addition” LINK

“CATCH the Wave of Coronary Atherosclerotic Plaque MRI” LINK

“Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture. (arXiv:2112.08534v1 [cs.LG])” LINK

“The Biologically Relevant Coordination Chemistry of Iron and Nitric Oxide: Electronic Structure and Reactivity” 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 #34, 2020

NIR Calibration-Model Services

Got a NIRspectrometer and need help for application development? chemometrics multivariate prediction NIRS LINK

Spectroscopy and Chemometrics News Weekly 33, 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 33, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 33, 2020 | 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 Chemometrics and Spectroscopy News in real time on Twitter @ CalibModel and follow us.




Near-Infrared Spectroscopy (NIRS)

“Using visible near-infrared reflectance spectroscopy (VNIRS) of lake sediments to estimate historical changes in cyanobacterial production: potential and challenges” LINK

“Inversion of soil heavy metals in Guanzhong area of Shaanxi based on VIS-NIR spectroscopy” LINK




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

“In-field measurement of starch content of cassava tubers using handheld vis-near infrared spectroscopy implemented for breeding programmes” LINK

“Near-infrared reflectance spectroscopy-based fast versicolorin A detection in maize for early aflatoxin warning and safety sorting.” LINK

“Egg freshness prediction using a comprehensive analysis based on visible near infrared spectroscopy” LINK

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

“Signal-to-Noise Ratio Contributors and Effects in Proximal Near-Infrared Spectral Reflectance Measurement on Plant Leaves” LINK

“Non-destructive analysis of Japanese table grape qualities using near-infrared spectroscopy” LINK

“Classifying Cannabis Sativa Flowers, Stems and Leaves using Statistical Machine Learning with Near-Infrared Hyperspectral Reflectance Imaging” LINK

“Near infrared spectroscopy to evaluate change in color and chemical composition in heat-treated bamboo” LINK

“Mid-Infrared Reflectance Spectroscopy of Oil Sands Minerals Based on Tunable Quantum Cascade Lasers” LINK

“Accurate Prediction of Sensory Attributes of Cheese Using Near-Infrared Spectroscopy Based on Artificial Neural Network.” LINK

“Near-Infrared Reflectance Spectroscopy-based Fast Versicolorin A Detection in Maize for Early Aflatoxin Warning and Safety Sorting” LINK

“Near-Infrared Spectroscopy in Bio-Applications” LINK




Raman Spectroscopy

“Sensors, Vol. 20, Pages 3723: High-Throughput Phenotyping Approach for Screening Major Carotenoids of Tomato by Handheld Raman Spectroscopy Using Chemometric Methods” LINK

“Chemical Bleaching to Minimize Fluorescence Interference in Raman Spectroscopic Measurements for Sulfonated Polystyrene Solutions” LINK




Hyperspectral Imaging (HSI)

“Comparison between Hyperspectral Imaging and Chemical Analysis of Polyphenol Oxidase Activity on Fresh-Cut Apple Slices” LINK




Chemometrics and Machine Learning

“Food Quality Assessed by Chemometrics” LINK

“Foods, Vol. 9, Pages 880: HPLC-Based Chemometric Analysis for Coffee Adulteration” LINK

“Foods, Vol. 9, Pages 876: Non-Targeted Detection of Adulterants in Almond Powder Using Spectroscopic Techniques Combined with Chemometrics” LINK

“Model-Based Process Optimization for the Production of Macrolactin D by Paenibacillus polymyxa” LINK

“Rapid detection model of Bacillus subtilis in solid-state fermentation of rapeseed meal” LINK

“Machine Learning Modeling of Wine Sensory Profiles and Color of Vertical Vintages of Pinot Noir Based on Chemical Fingerprinting, Weather and Management Data.” LINK

“Comparison of Individual and Integrated Inline Raman, Near-Infrared, and Mid-Infrared Spectroscopic Models to Predict the Viscosity of Micellar Liquids” LINK

“Identification and Quantification of Adulterants in Coffee (Coffea arabica L.) Using FT-MIR Spectroscopy Coupled with Chemometrics” Foods LINK




Equipment for Spectroscopy

“Rapid and Robust OnScene Detection of Cocaine in Street Samples using a Handheld Near Infrared Spectrometer and Machine Learning Algorithms” LINK

“Micro-Electro-Mechanical System Fourier Transform Infrared (MEMS FT-IR) Spectrometer Under Modulated–Pulsed Light Source Excitation” LINK




Agriculture NIR-Spectroscopy Usage

“RobHortic: A Field Robot to Detect Pests and Diseases in Horticultural Crops by Proximal Sensing” Agriculture LINK

“… Agriculture Technology and Farm Data: A Case Study on Swedish Grain Farmers and On-Combine Near-Infrared Spectroscopy for Quality Measurement” LINK




Chemical Industry NIR Usage

“Benzothiadiazole Bridged EDOT Based Donor-Acceptor Polymers With Tunable Optical, Electrochemical, Morphological and Electrochromic Performance: Effects of …” LINK




Pharma Industry NIR Usage

“Validation and comparison of different near-infrared quantitative methods to rapid determination of the total content of anthraquinones in Rhubarb based on accuracy …” LINK

“Feature Selection and Rapid Characterization of Bloodstains on Different Substrates” LINK




Other

“Application of Optical Technologies in the US Poultry Slaughter Facilities for the Detection of Poultry Carcass Condemnation.” LINK





How to start building a NIR Calibration (a NIR prediction model)?

With at least 60-100 different NIR measured samples with different Lab values
we can develop a quantitative NIR Calibration for you!

You don’t need to operate with expensive Chemometric Software.
Don’t worry, prices are inexpensive for that and all software you need is included.
Price comparison

The free NIR-Predictor software allows to combine your measured NIR-Spectra with the Lab values of the samples. And checks your data and creates a Calibration Request file for you. NIR-Predictor Info

With that you can order your individual customized calibration, by sending the Calibration Request file to info@CalibrationModel.com.

After processing you will get an Email with a link to access your customize calibrations in our WebShop where you can purchase and download the calibration file immediately
for use in the included free NIR-Predictor software to get results predicted out of spectra files. NIR-Predictor software

For your Calibration start-up cycle we provide low-price short living calibrations, that work for e.g. 3 or 6 months. Pricing

During that Calibration usage time you have measured more samples and collected more NIR and Lab data to build a bigger and better calibration.
E.g. you got samples that extend the range of the constituents.
Or you have collected the Lab values of additional constituents.

Yes out of an measured NIR-Spectrum you can get multiple constituents predicted at the same time (a quantitative calibration per constituent is needed).

And NIR-Predictor does handle this with ease and creates NIR Prediction Reports (printable, archive-able) of all the calibrations you have in folder named with e.g. “MyFruitApplication”.

And having multiple such applications, in NIR-Predictor you can easily switch between the applications for analyzing new NIR spectra files.

The NIR spectra files are found from the stored or exported folder from your NIR-Spectrometer software. supported File Formats



NIR Calibration Service explained


Start Calibrate

NIR-Predictor Download

The free NIR-Predictor software
  • comes with demo data, so you can predict sample spectra with demo calibrations.
  • has no functional limitations, no nagging, no ads and needs no license-key.
  • you need no account and no registration to download and use.
  • runs on Microsoft Windows 10/8/7 (Starter, Basic, Professional) (32 bit / 64 bit).
  • no data is ever transmitted from your local machine. We don’t even collect usage data.
See more Videos



Beside the free NIR-Predictor software with Windows user interface,
the real-time Predictor Engine is also available
  • for embedded integration in application, cloud and instrument-software (ICT).
  • As a light-weigt single library file (DLL)
    with application programming interface (API),
    documentation and software development kit (SDK)
    including sample source code (C#).
  • Easy integration and deployment,
    no software license protection (no serial key, no dongle).
  • Put your spectrum as an array into the multivariate predictor,
    no specific file format needed.
  • Fast prediction speed and low latency
    because of compiled code library (direct call, no cloud API).
  • Protected prediction results with outlier detection information.
See NIR Method Development Service for Labs and NIR-Vendors (OEM, White-Label)



Software Size Date Comment
NIR-Predictor V2.6.0.2 (download)

What’s new, see Release Notes

By downloading and/or using the software
you accept the Software License Agreement (EULA)
3.7 MB 18.08.2021 public release

Minimal System Requirements
Windows 7 Starter 32Bit, 1.6 GHz, 2 GB RAM, non-Administrator account

Installation
There are no administrator rights required, unpack the zip file to a folder “NIR-Predictor” in your documents or on your desktop.
Read the ReadMe.txt and double click the NIR-Predictor.exe file.

Upgrade
If you have installed an older version of NIR-Predictor then unpack into a different folder named e.g. “NIR-PredictorVx.y”. All versions can run side-by-side. Copy the Calibrations in use to the new version into the “Calibration” folder. That’s all.

Uninstall
Make sure to backup your reports and calibrations inside your “NIR-Predictor” folder. Delete the “NIR-Predictor” folder.


Start Calibrate

See also: