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 #20, 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 19, 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 19, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 19, 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)

” RAPID EVALUATION OF DRY WHITE KIDNEY BEANS COOKING CHARACTERISTICS BY NEAR-INFRARED (NIR) SPECTROSCOPY” LINK

“Potential of Vis-NIR spectroscopy for detection of chilling injury in kiwifruit” LINK

“The application of NIR spectroscopy in moisture determining of vegetable seeds” LINK

“Detection and quantification of active pharmaceutical ingredients as adulterants in Garcinia cambogia slimming preparations using NIR spectroscopy combined with …” LINK

“Comparison of the Potential Abilities of Three Spectroscopy Methods: Near-Infrared, Mid-Infrared, and Molecular Fluorescence, to Predict Carotenoid, Vitamin and Fatty Acid Contents in Cow Milk ” LINK




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

” Machine Learning Classification of Articular Cartilage Integrity 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

“Non-destructive assessment of moisture content and modulus of rupture of sawn timber Hevea wood using near infrared spectroscopy technique” LINK

“Accurate prediction of glucose concentration and identification of major contributing features from hardly distinguishable near-infrared spectroscopy” LINK

“Determination of in situ ruminal degradation of phytate phosphorus from single and compound feeds in dairy cows using chemical analysis and near-infrared spectroscopy” LINK

” RAPID, NONDESTRUCTIVE AND SIMULTANEOUS PREDICTIONS OF SOIL CONTENT IN WULING MOUNTAIN AREA USING NEAR INFRARED …” LINK

” Multiblock PLS-DA on fecal and plasma visible-near-infrared spectra for discriminating young bulls according to their efficiency. Preliminary results” LINK

“Developing deep learning based regression approaches for determination of chemical compositions in dry black goji berries (Lycium ruthenicum Murr.) using near-infrared hyperspectral …” LINK

“Near-infrared wavelength-selection method based on joint mutual information and weighted bootstrap sampling” LINK

“Rapid and simultaneous analysis of direct and indirect bilirubin indicators in serum through reagent-free visible-near-infrared spectroscopy combined with …” LINK

“Sensors, Vol. 20, Pages 1472: Fusion of Mid-Wave Infrared and Long-Wave Infrared Reflectance Spectra for Quantitative Analysis of Minerals” LINK

“Near-infrared spectroscopy as a quantitative spasticity assessment tool: A systematic review.” LINK




Raman Spectroscopy

“Surfaceenhanced Raman spectroscopy for onsite analysis: A review of recent developments” LINK




Hyperspectral Imaging (HSI)

“Comparative Study on Hyperspectral and Satellite Image for the Estimation of Chlorophyll a Concentration on Coastal Areas” LINK

“Performance of Fluorescence and Diffuse Reflectance Hyperspectral Imaging for Characterization of Lutefisk: A Traditional Norwegian Fish Dish” LINK

“Dual-camera design for hyperspectral and panchromatic imaging, using a wedge shaped liquid crystal as a spectral multiplexer” LINK




Spectral Imaging

“Functional Imaging of the Ocular Fundus Using an 8-Band Retinal Multispectral Imaging System” LINK

“Multispectral imaging for predicting the water status in mushroom during hotair dehydration” LINK




Chemometrics and Machine Learning

“Development of spectral signatures and classification using hyperspectral face recognition” LINK

The Google Cloud Developer’s Cheat Sheet. BigData Analytics DataScience AI MachineLearning CyberSecurity IoT IIoT Python RStats TensorFlow Java JavaScript ReactJS CloudComputing Serverless Linux Programming Coding 100DaysofCode LINK

“Vibrational spectroscopy and chemometrics for quantifying key bioactive components of various plum cultivars grown in New Zealand” LINK

“ATR-MIR spectroscopy to predict commercial milk major components: A comparison between a handheld and a benchtop instrument” LINK

“Chemometrics as a Green Analytical Tool” LINK




Facts

“Systematic review of deep learning techniques in plant disease detection” LINK

“Machine learning estimators for the quantity and quality of grass swards used for silage production using drone-based imaging spectrometry and photogrammetry” LINK




Environment NIR-Spectroscopy Application

“Remote Sensing, Vol. 12, Pages 931: Optical Water Type Guided Approach to Estimate Optical Water Quality Parameters” LINK

“Estimation of total nitrogen and organic carbon contents in mine soils with NIR reflectance spectroscopy and various chemometric methods” LINK

“Improved mapping of soil heavy metals using a Vis-NIR spectroscopy index in an agricultural area of eastern China” LINK




Agriculture NIR-Spectroscopy Usage

“Remote Sensing, Vol. 12, Pages 940: Editorial for the Special Issue Estimation of Crop Phenotyping Traits using Unmanned Ground Vehicle and Unmanned Aerial Vehicle Imagery”” LINK

“Predicting grain protein content of field-grown winter wheat with satellite images and partial least square algorithm.” LINK

“The development of models to predict the nutritional value of feedstuffs and feed mixture using NIRS” LINK

“Permafrost soil complexity evaluated by laboratory imaging Vis‐NIR spectroscopy” LINK

“Agriculture, Vol. 10, Pages 164: Chemical Variation and Implications on Repellency Activity of Tephrosia vogelii (Hook f.) Essential Oils Against Sitophilus zeamais Motschulsky” LINK

“The Use of Multi-temporal Spectral Information to Improve the Classification of Agricultural Crops in Landscapes” LINK




Horticulture NIR-Spectroscopy Applications

“Recent advances in imaging techniques for bruise detection in fruits and vegetables” LINK




Food & Feed Industry NIR Usage

“Beef Nutritional Quality Testing and Food Packaging” LINK

“Foods, Vol. 9, Pages 619: Evaluation of the Physicochemical and Sensory Characteristics of Different Fig Cultivars for the Fresh Fruit Market” LINK




Laboratory and NIR-Spectroscopy

“Laboratory-Scale Preparation and Characterization of Dried Extract of Muirapuama (Ptychopetalumolacoides Benth) by Green Analytical Techniques” LINK




Other

“Sony releases industrial SWIR sensors with 5m pixels” LINK





NIR Calibration Service explained

Our Service is different

  • We build the optimal quantitative prediction models for your NIR analytical needs (No need for mathematical/statistical model building software usage at your site).
  • The NIR-Predictor software and the calibration models are at your site. No internet connection needed to our service. You can do unlimited predictions, that allows fast measurement cycles with no extra cost (Not payed per prediction).
  • You own your data and the calibrations. You can have access to the detailed Calibration Report with all the settings and statistics (No Black-Box Models).

Get NIR Calibrations

Get NIR Calibrations - Workflow
Your 4 steps to the applicable NIR calibration:
  1. Download free NIR-Predictor here
  2. Combine NIR-Spectra with Lab-Reference values, see Video for 2. and 3. (manual)
  3. Create a Calibration Request and sent it to info@CalibrationModel.com (CM)
  4. After processing you will get a link to the Web Shop to download the calibrations.



Use NIR Calibrations

Use NIR Calibrations Workflow
see more Videos


In other words

Calibration Model simplifies the process of training machine learning models for NIRS data while providing an opportunity to trying different algorithms and applied near-infrared spectroscopy (NIRS) knowledge. It’s more than an AutoML platform, it’s a full service where you can download the optimal model and its describing Calibration Report that provide insights into the data preparation, feature engineering, model training, and hyperparameter tuning.

Start Calibrate

Spectroscopy and Chemometrics News Weekly #50, 2019

CalibrationModel.com

Total cost of ownership (TCO) of NIR-Spectroscopy Systems in the Age of Digitalization – Compare Operating Costs of NIRS LINK

Spectroscopy and Chemometrics News Weekly 49, 2019 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 49, 2019 | NIRS NIR Spektroskopie MachineLearning Spektrometer Sensor Nahinfrarot LaborAnalytik Analysengeräte Analysentechnik Analysemethode Labor Nahinfrarotspektroskopie Qualitätslabor LINK

Spettroscopia e Chemiometria Weekly News 49, 2019 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem prediction models LINK

This week’s NIR news Weekly is sponsored by 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

” Raman Spectroscopy and NIR Spectroscopy as Possible AID in Localisation of Solitary Pulmonary Nodules” LINK

NIR spectroscopy has potential for rapid on farm analysis of slurry nutrient content. Wouter Saeys, IFSConf LINK

“Modeling for SSC and Firmness Detection of Persimmon Based on NIR Hyperspectral Imaging by Sample Partitioning and Variables Selection” LINK

” Application of the NIR Spectroscopy in the Researches of Orthopedics Diseases” LINK

“FT-NIR による油脂の迅速な品質管理” LINK

“Accuracy improvement of quantitative analysis in VIS-NIR spectroscopy using the GKF-WTEF algorithm.” LINK

“Rapid determination of the content of digestible energy and metabolizable energy in sorghum fed to growing pigs by near-infrared reflectance spectroscopy.” LINK

“Characterization of the Processing Conditions upon Textural Profile Analysis (TPA) Parameters of Processed Cheese Using Near-Infrared Hyperspectral Imaging” LINK

“Total aromatics of diesel fuels analysis by deep learning and near-infrared spectroscopy” LINK

“Rapid Assessment of Soil Quality Indices Using Infrared Reflectance Spectroscopy” LINK

“Quantitative Determination of the Fiber Components in Textiles by Near-Infrared Spectroscopy and Extreme Learning Machine” LINK

“Non-Destructive Method for Predicting Sapodilla Fruit Quality Using Near Infrared Spectroscopy” LINK

“Qualitative analysis for sweetness classification of longan by near infrared hyperspectral imaging” LINK

” MENGUKUR BERAT VOLUME TANAH DI LAPANGAN MENGGUNAKAN NEAR INFRARED SPECTROSCOPY MEASUREMENT OF SOIL BULK DENSITY IN …” LINK

“Hyperspectral Characteristics of Coastal Saline Soil with Visible/near Infrared Spectroscopy” LINK

“Monitoring Soil Surface Mineralogy at Different Moisture Conditions Using Visible Near-Infrared Spectroscopy Data” LINK

“Near infrared spectroscopy for assessing mechanical properties of Castanea sativa wood samples” Modulus of elasticity LINK

” Development of near-infrared spectroscopic sensing system for online real-time monitoring of milk quality during milking” LINK

” Advances in Near-Infrared Spectroscopy and Related Computational Methods” LINK

“Morphological, Physicochemical and FTIR Spectroscopic Properties of Bee Pollen Loads from Different Botanical Origin” LINK

“Fourier transform infrared imaging and quantitative analysis of pre-treated wood fibers: A comparison between partial least squares and multivariate curve resolution with alternating least squares methods in a case study” LINK

“Antioxidant Activity of Blueberry (Vaccinium spp.) Cultivar Leaves: Differences Across the Vegetative Stage and the Application of Near Infrared Spectroscopy.” LINK




Hyperspectral

“Development of Simplified Models for Nondestructive Testing of Rice with Husk Starch Content Using Hyperspectral Imaging Technology” LINK




Spectral Imaging

“Model for estimation of total nitrogen content in sandalwood leaves based on nonlinear mixed effects and dummy variables using multispectral images” LINK

“Sources of Variation in Assessing Canopy Reflectance of Processing Tomato by Means of Multispectral Radiometry” LINK




Chemometrics

“Sampling for spectroscopic analysis: consequences for multivariate calibration” LINK

“Combination of hyperspectral sensing images and chemometrics for measuring tensile strength indices of organic plastic sheeting in the field” LINK

” Comparison of prediction power of three multivariate calibrations for estimation of leaf anthocyanin content with visible spectroscopy in Prunus cerasifera” LINK

” Prediction of quality parameters of food residues using NIR spectroscopy and PLS models based on proximate analysis” LINK

“Pre-processing spectroscopic data: for good or ill?” LINK




Process Control

“Optimization of pickled herring production-Approaches for process and quality control-DTU Orbit (26/09/2019)” LINK




Environment

“Response surface methodology for optimizing LIBS testing parameters: A case to conduct the elemental contents analysis in soil” LINK




Pharma

“Rapid detection of cAMP content in red jujube using near-infrared spectroscopy” LINK

“Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning.” LINK




Other

“Determination of Carvacrol Content in Alaska Yellow Cedar (Callitropsis nootkatensis) Extractives” LINK





Cost comparision / Price comparison of Chemometrics / Machine Learning / Data Science for NIR-Spectroscopy

CalibrationModel.com (CM) versus Others

Costs are not everything, there are other important factors listed in the table.

CM fix € pricing Others € Price Range (approx.)
Software
included
Chemometric Package not‑needed
€3500 – €6500 per user
Chemometric Predictor
free‑software
€1500 – €2500 per NIR device
Knowledge
included
Chemometric Training not‑needed
€1500 – €2500 per user
Chemometrician* Salary not‑needed
1 years Salary / year
(+ risk of Employee Turnover)
Computation
included
Powerful Computer (many Processors, lot of RAM for big data) not‑needed
€1500 – €4500 per computer
Development and Usage
Development of a Calibration
€128
€80 – €150 / hour
of Chemometrician* using a Chemometric Software (click and wait) and applying it’s knowledge
Usage of a Calibration
€60 / year
Total €178 in first year
€60 in second year
initial (min €8000 , max €15500)
+ 2 * (2 – 4)(hour to cost same! as CM service) * (€80 – €150) Chemometrician* work
no initial cost
very high initial costs
no personnel cost
high personnel* costs
constant CM services
risk of Employee Turnover
global knowledge
risk of only use personal knowledge
easy to calculate fix cost on demand
difficult to calculate variable cost on demand plus Chemometrician* Recruitment needed
Results :
calibration prediction performance
always reproducible highly optimized
only as good as your Chemometrician* daily condition
better prediction performance, due to best-of 10’000x calibrations
small size of experiments, non-optimal calibrations

See also: pricing

Start Calibrate

*) Personnel / Chemometrician / Data Scientist / Data Analyst / Machine Learning Engineer : We are not against it, we are one of them a long time ago, but the way the work is done is changing (see below).

2019 Digitalization and the Future of Work: Macroeconomic Consequences
2019 The Digitalization of the American Workforce
2017 Digitalization and the American workforce , full-report

Start Calibrate – NIR Quick Guide

Quick Start NIR Workflow: step by step

1. Check if your NIR-Device Data Format is directly supported (anyway you can convert to JCAMP) : NIR-Predictor supported Spectral Data File Formats

2. Download the free NIR-Predictor Software that contains demo data so you can play with it to see if it is the way you want analyse your NIR spectra (no registration needed) : NIR-Predictor Download

3. With your “NIR device” measurement software:

  • measure samples with NIR, that gets you spectra files,
  • label them with a proper sample name, so you know which is which,
  • and determine quantitative reference values by Laboratory reference method.
  • at least 60 samples with different contents is needed for a minimal calibration.
  • NIR-Predictor helps to create a template file (.csv) to enter the Lab values.

4. Creating your own Calibrations with NIR-Predictor to combine your NIR and Lab data for a calibration request : watch Video read Manual



Videos


Spectroscopy and Chemometrics News Weekly #40, 2019

CalibrationModel.com

“Food quality digitized at the “speed of light” ” : Food Sample -> measured with a NIRS spectrometer -> spectral data -> ⚖️ predicted with a NIRPredictor & CalibrationModel -> % quantitative results -> quality decision -> LINK

Spectroscopy and Chemometrics News Weekly 39, 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 39, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 39, 2019 | NIRS NIR Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem predictionmodel HSI LINK




Chemometrics

“Near-infrared spectroscopy to determine residual moisture in freeze-dried products: model generation by statistical design of experiments LINK

“制浆材木质素含量近红外分析模型传递研究” “Study on Near-infrared Calibration Model Transfer for Lignin Content in Pulpwood” LINK

“Prediction of Mineral Composition in Commercial Extruded Dry Dog Food by Near-Infrared Reflectance Spectroscopy” LINK




Near Infrared

“Influence of Particles Size on NIR Spectroscopic Estimations of Charcoal Properties” LINK

“Measurement of refractive index of hemoglobin in the visible/NIR spectral range.” LINK

“Feasibility on using NIR spectroscopy for the measurement of the textural parameters in mango” LINK

“NIR Spectroscopy as a Suitable Tool for the Investigation of the Horticultural Field” LINK

“Handheld Near-Infrared Spectroscopy for Distinction of Extra Virgin Olive Oil from Other Olive Oil Grades Substantiated by Compositional Data” LINK




Infrared

“Short-wave near infrared spectroscopy for the quality control of milk” LINK

“Rapid detection of infrared inactive sodium chloride content in frozen tuna fish for determining commercial value using short wavelengths” LINK




Equipment

Visible/near Infrared Reflection Spectrometer and Electronic Nose Data Fusion as an Accuracy Improvement Method for Portable Total Soluble Solid Content Detection of Orange” LINK




Environment

“Prediction of soil available water-holding capacity from visible near-infrared reflectance spectra.” LINK




Agriculture

“Local anomaly detection and quantitative analysis of contaminants in soybean meal using near infrared imaging: The example of non-protein nitrogen.” LINK

“Challenges and opportunities in clinical translation of biomedical optical spectroscopy and imaging.” LINK

“The potential of CIELAB colour scores to gauge the quality of sorghum as a feed grain for chicken-meat production” LINK




Food & Feed

“Control and Monitoring of Milk Renneting Using FT-NIR Spectroscopy as a Process Analytical Technology Tool” Foods LINK

Food quality digitized at the “speed of light” This shows how using spectroscopy for measuring food quality can become the future for many businesses – With the speed of light LINK

“A Study on the use of Spectroscopic Techniques to Identify Food Adulteration” LINK

“Recent advances in micro-level experimental investigation in food drying technology” LINK




Laboratory

“In situ reaction monitoring using spectroscopy can be very useful in an industrial laboratory, but there are many factors to take into account.” Click Here for Seven Essential Steps for In Situ Reaction Monitoring: LINK





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


CalibrationModel.com ia a perfect match for
    – NIR Vendors    , selling NIR            , with limited capacity for NIR method development
    – Labs                , using NIR            , with limited capacity for NIR method development
    – small Labs        , starting with NIR , with no or less Chemometric knowledge


The Triple to success :
faster better analytics
    LAB Reference Analytics + NIR Spectroscopy + ChemoMetrics
    LAB + NIR +
CM
    => use CM as a Service : CalibrationModel


NIR Method Development : Before / After
    Before
    – The
need of a chemometric software ($$)
    – The
need of expert training courses (time,$$)
    – The
need of manual expert work (time,$$$)
    with
CalibrationModel
    – The
freedom without a chemometric software
    – The
freedom without being an expert
    – The
freedom of using a Service ($)
    =>
work smart, not hard
See Cost Comparision

Workflow:
    Cloud Service
        DATA ->
CalibrationModel -> CALIB
                    fix cost, pay per CALIB development and usage

    Local Usage (no internet connection)
        DATA -> CALIB +
Predictor -> RESULT
                                included, no extra cost

    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)
    optional: JCAMP
Anonymizer (removes sensitive information) before sending DATA


As Middleman you can
hide/cover the Service
    Customer <————————> CalibrationModel
                            or
    Customer <–>
Middleman <–> CalibrationModel
                        NIR Company
                        NIR Sales, Consultancy


Riskless Predictor OEM integration (in NIR-Vendors Instrument Software)
    Predictor is included at
no extra cost (for software licenses and development kit (SDK))
    Predictor as a
hidden second engine (second Heart)
    Windows .NET, easy programming interface (API)


Ownership
    
DATA owner -> CALIB owner ==> use as your Pre-CALIB
    CALIB is licensed to owner and so copy protected
    The owner can Re-License a CALIB to others
    owner can
re-sell CALIBs in its own WebShop with own prices


Re-Calibration
    DATA + DATA -> CALIB    same easy workflow as    DATA -> CALIB
    optimize from scratch, benefit from complete optimization possibilities
    
learn more
NIR-Predictor Software

NIR-Predictor

New: NIR-Predictor V2.6 with new features

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

Spectra Plots and Histograms on the Prediction Report
  • NIR-Predictor is an easy to use NIR software for all NIR devices
    to produce quantitative results out of NIR data.

  • CalibrationModel Service provides development of
    customized calibrations out of NIR and Lab data.

  • It allows to use NIR with your own customized
    models without the need of Chemometric Software!

  • We do the Machine Leraning for your NIR-Spectrometer
    and with the free NIR-Predictor you are
    able to analyze new measured samples.

  • For NIR-Vendors we also offer the
    Software Development Kit (SDK) for OEM Predictor use
    via the Application Programming Interface (API).
    Think of a sencod predictor engine,
    as a second heart in your system.



Download

Key Features of NIR-Predictor

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

Super flexible prediction

Loads multiple files at once in

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

It allows you to

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

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

Videos


Properties File Creator

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

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

Properties File Creator saves you from:

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

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

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

Top 8 Reasons why you should use
Automated NIR Calibration Service

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

Reduce Total Cost of Ownership (TCO) of your NIR

To be ahead of competitors
  • by not owning a chemometric software
  • by not struggling days with these complicated software
  • by not deep dive into chemometrics theory
It takes significant know-how and continous investment to develop calibrations
  • You need to have the relevant skill sets in your organization.
  • That means salaries (the biggest expense in most organizations)
To get most out of it, start now!
  • use the free NIR-Predictor together with your NIR-Instrument software
  • as an NIR-Vendor, integrate the free NIR-Predictor OEM into your NIR-Instrument software
  • don’t delay time-to-market
Read more about NIR Total cost of ownership (TCO)

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About the included Demo-Spectra and Demo-Calibrations

The demo calibrations for the spectrometers from

  • Si-Ware Systems
  • Spectral Engines
  • Texas Instruments
  • VIAVI

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

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

The demo calibrations for the FOSS are built with the

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


References

Quickstart: NIR-Predictor – Manual

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

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

Frequently Asked Questions: NIR-Predictor – FAQ

WebShop : CalibrationModel WebShop