Spectroscopy and Chemometrics News Weekly #12, 2020

CalibrationModel.com

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

Do you work with Near Infra-red Reflectance Spectrometry (NIRS) and need better Accuracy? NIR Spectroscopy | mill agriculture LINK

Spectroscopy and Chemometrics News Weekly 11, 2020 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical foodprocessing foodsafety Analysis Lab Labs Laboratories Laboratory Software IoT Sensors Testing Quality LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 11, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor nearinfrared Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 11, 2020 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK




Near Infrared

“Characterization of the Fruits and Seeds of Alpinia Oxyphylla Miq by High-Performance Liquid Chromatography (HPLC) and near-Infrared Spectroscopy (NIRS) with Partial Least …” LINK

“Yenidoğan Yoğun Bakım Ünitesinde Yeni Bir Yaklaşım: Hemşirelik Bakımında Yakın Kızılötesi Spektroskopisi (Near-Infrared Spectroscopy-NIRS) Kullanımı” LINK

“Individual Wheat Kernels Vigor Assessment Based on NIR Spectroscopy Coupled with Machine Learning Methodologies” LINK

“Characteristion of Hydrogen Bond of L–Methionium Hydrogen Selenite by Temperature Dependent Two-dimensional Correlation FT-NIR Spectroscopy” LINK

“Authentication of Iberian pork official quality categories using a portable near infrared spectroscopy (NIRS) instrument.” LINK

“Determination of grated hard cheeses adulteration by near infrared spectroscopy (NIR) and multivariate analysis” LINK

“Prekalibrasi Rumput Gajah Menggunakan NIRS dan Perbandingannya dengan Pengujian Kimia” LINK

“Near‐infrared spectroscopy (NIRS) for taxonomic entomology: A brief review” LINK

“NIR spectroscopy can detect acrylamide” Visible Spectrophotometer H2020 LINK

“Evaluation and classification of five cereal fungi on culture medium using Visible/Near-Infrared (Vis/NIR) hyperspectral imaging” LINK

“APLIKASI NEAR INFRARED SPECTROSCOPY (NIRS) UNTUK MENDETEKSI PENCEMARAN TANAH” LINK

“Near-Infrared Hyperspectral Imaging Combined with Deep Learning to Identify Cotton Seed Varieties.” LINK

“Structural and visible-near infrared optical properties of (Fe, Mo)-co-doped TiO2 for colored cool pigments” LINK

“Rapid Evaluation of Biomass Properties Used for Energy Purposes Using Near-Infrared Spectroscopy” DOI: 10.5772/intechopen.90828 LINK

“Visible/near infrared spectroscopy and machine learning for predicting polyhydroxybutyrate production cultured on alkaline pretreated liquor from corn stover” LINK

“Kernel functions embedded in support vector machine learning models for rapid water pollution assessment via near-infrared spectroscopy.” LINK

“Determination of the viability of retinispora (Hinoki cypress) seeds using shortwave infrared hyperspectral imaging spectroscopy” LINK

“PREDIKSI KADAR SALINITAS, PH DAN C-ORGANIK TANAH MENGGUNAKAN NEAR INFRARED KECAMATAN BAITUSSALAM KABUPATEN ACEH BESAR” LINK

“Determination of pH and acidity in green coffee by near infrared spectroscopy and multivariate regression” LINK




Chemometrics

“Prediction of soil properties with machine learning models based on the spectral response of soil samples in the near infrared range” LINK

The statistics mantra “Correlation does NOT mean Causation” explained with an example. LINK

“Evaluation of aroma styles in flue-cured tobacco by near infrared spectroscopy combined with chemometric algorithms” LINK

“Sensors, Vol. 20, Pages 686: Fuzzy Evaluation Output of Taste Information for Liquor Using Electronic Tongue Based on Cloud Model” LINK

“Modelos de calibración para la cuantificación nutricional de praderas frescas mediante espectroscopía de infrarojo cercano” LINK

“Determination of Total Phenolic Content and NIR-Chemometrics Classification Model of Queen and Local Varieties of Soursop (Annonamuricata L.) Leaf Powder” LINK

“Recognition of different Longjing fresh tea varieties using hyperspectral imaging technology and chemometrics” LINK




Facts

“Visualizing the History of Pandemics” #infoGrafics LINK




Equipment

“Development of Low-Cost Portable Spectrometers for Detection of Wood Defects.” LINK




Process Control

“Preparation of Celecoxib Tablet by Hot Melt Extrusion Technology and Application of Process Analysis Technology to Discriminate Solubilization Effect” LINK

“Internet of Things — Leap towards a hyper-connected world” IoT Spectral Sensors SpectralSensing qualitycontrol analysis Production ProcessControl foodprocessing foodsafety foodproduction AI BigData DataScience #INFOGRAPHICS LINK




Agriculture

“Estimating fatty acid content and related nutritional indexes in ewe milk using different near infrared instruments” LINK

“Indirect measures of methane emissions of Sahelian zebu cattle in West Africa, role of environment and management” LINK

“Detection of mycotoxins and toxigenic fungi in cereal grains using vibrational spectroscopic techniques: a review” LINK

“NIR spectroscopy and management of bioactive components, antioxidant activity, and macronutrients in fruits” LINK

“Scald-Cold: Joint Austrian-Italian consortium in the Euregio project for the comprehensive dissection of the superficial scald in apples” postharvest food LINK

“Both genetic and environmental conditions affect wheat grain texture: Consequences for grain fractionation and flour properties” LINK

“A phenotyping tool for water status determination in soybean by vegetation indexes and NIR-SWIR spectral bands.” LINK




Pharma

“Non-destructive dose verification of two drugs within 3D printed polyprintlets” LINK




Laboratory

“Forward and Backward Interval Partial Least Squares Method for Quantitative Analysis of Frying Oil Quality” LINK




Other

“Study of simple detection of gasoline fuel contaminants contributing to increase Particulate Matter Emissions” LINK

“COVID-19 Open Research Dataset (CORD-19)” LINK







.

Spectroscopy and Chemometrics News Weekly #8, 2020

CalibrationModel.com

Knowledge-Based Variable Selection and Model Selection for near infrared spectroscopy NIRS LINK

Stop wasting too much time for NIRS Chemometrics Method development | foodanalyticaltechnologies analytic qualitycontrol foodindustry beverageindustry materialsensing LINK

Spectroscopy and Chemometrics News Weekly 7, 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 7, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 7, 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)

“Determination of Glucose by NIR Spectroscopy Under Magnetic Field” LINK

“Sensors, Vol. 20, Pages 230: The Effect of Light Intensity, Sensor Height, and Spectral Pre-Processing Methods when using NIR Spectroscopy to Identify Different Allergen-Containing Powdered Foods” LINK

“Quantum mechanical modeling of NIR spectra of thymol” LINK

“Using a handheld near-infrared spectroscopy (NIRS) scanner to predict meat quality” LINK

“NIR spectroscopy in simulation–a new way for augmenting near-infrared phytoanalysis” LINK

“Using visible-near-infrared spectroscopy to classify lichens at a Neotropical Dry Forest” LINK

“Near infrared spectroscopy as a rapid method for detecting paprika powder adulteration with corn flour” LINK

“Application of deep learning and near infrared spectroscopy in cereal analysis” LINK

“Using near infrared spectroscopy to determine the scots pine place of growth” LINK

“Chagas disease vectors identification using visible and near-infrared spectroscopy” LINK

“Ensemble of extreme learning machines for multivariate calibration of near-infrared spectroscopy” LINK

“Quantification of Silymarin in Silybum marianum with near-infrared spectroscopy: a comparison of benchtop vs. handheld devices” LINK

“N-way partial least squares combined with new self-construction strategy—A promising approach of using near infrared spectral data for quantitative determination of …” LINK

“Identification of rice flour types with near-infrared spectroscopy associated with PLS-DA and SVM methods” LINK

” Multivariate Classification of Prunus Dulcis Varieties using Leaves of Nursery Plants and Near Infrared Spectroscopy” LINK




Hyperspectral

“Frost damage to maize in northeast India: assessment and estimated loss of yield by hyperspectral proximal remote sensing” LINK

“Identification of authenticity, quality and origin of saffron using hyperspectral imaging and multivariate spectral analysis” LINK




Chemometrics

“Early detection of chilling injury in green bell peppers by hyperspectral imaging and chemometrics” LINK

“Evaluating photosynthetic pigment contents of maize using UVE-PLS based on continuous wavelet transform” LINK

“Near-infrared spectroscopy coupled with chemometrics algorithms for the quantitative determination of the germinability of Clostridium perfringens in four different …” LINK

“Analysis of residual moisture in a freeze-dried sample drug using a multivariate fitting regression model” LINK

“Spectroscopy based novel spectral indices, PCA-and PLSR-coupled machine learning models for salinity stress phenotyping of rice” LINK

“Standardisation of near infrared hyperspectral imaging for quantification and classification of DON contaminated wheat samples” LINK

“Vibrational spectroscopy and chemometric data analysis: the principle components of rapid quality control of herbal medicines” LINK

“A Model for Yellow Tea Polyphenols Content Estimation Based on Multi-Feature Fusion” LINK




Process Control

“Review of near-infrared spectroscopy as a process analytical technology for real-time product monitoring in dairy processing” LINK




Environment

“POTENTIAL OF SENSOR-BASED SORTING IN ENHANCED LANDFILL MINING” LINK

“Characterization of the salt marsh soils and visible-near-infrared spectroscopy along a chronosequence of Spartina alterniflora invasion in a coastal wetland of …” LINK




Agriculture

“Remote Sensing, Vol. 12, Pages 126: Predicting Forage Quality of Grasslands Using UAV-Borne Imaging Spectroscopy” LINK

“Novel implementation of laser ablation tomography as an alternative technique to assess grain quality and internal insect development in stored products” LINK

“Comparative Study of Two Different Strategies for Determination of Soluble Solids Content of Apples From Multiple Geographical Regions by Using FT-NIR Spectroscopy” LINK




Food & Feed

“Adulteration of Olive Oil” LINK




Laboratory

“Laboratory Raman and VNIR spectroscopic studies of jarosite and other secondary mineral mixtures relevant to Mars” LINK




Other

“Combining analytical tools to identify adulteration: some practical examples” LINK

“… questioned whether the growth and sustainability of AI technology will lead to the need for two copyright systems — one to address human creation and one to address machine creation.” 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 #26, 2019

CalibrationModel.com

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

Spectroscopy and Chemometrics News Weekly 25, 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 25, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensoren Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Qualitätslabor LINK

Spettroscopia e Chemiometria Weekly News 25, 2019 | NIRS NIR Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem prediction models LINK




Chemometrics

“X-ray fluorescence and visible near infrared sensor fusion for predicting soil chromium content” LINK

“Staling of white wheat bread crumb and effect of maltogenic a-amylases. Part 2: Monitoring the staling process by using near infrared spectroscopy and chemometrics” LINK

“Rapid and Nondestructive Quantification of Trimethylamine by FT-NIR Coupled with Chemometric Techniques” Fish quality LINK

“Prediction of yerba mate caffeine content using near infrared spectroscopy” LINK

“Journal Highlight: A new flow cell and chemometric protocol for implementing inline Raman spectroscopy in chromatography” LINK

Teaching Machine Learning at the moment and a student asks whether “PCA” stands for “Pretty Cool Algorithm” after I apparently used that phrase… That should really have been deliberate (it wasn’t). I will never use “Principal Component Analysis” again. PrettyCoolAlgorithm LINK

“A screening method based on Visible-NIR spectroscopy for the identification and quantification of different adulterants in high-quality honey.” LINK

“Chemometric studies of the effects of milk fat replacement with different proportions of vegetable oils in the formulation of fat-filled milk powders: Implications for quality assurance.” LINK

“Comparison of Bayesian and partial least squares regression methods for mid-infrared prediction of cheese-making properties in Montbéliarde cows” LINK

“NIR model transfer of alkali-soluble polysaccharides in Poria cocos with piecewise direct standardization” LINK

“Comparison of three different classification methods performance for the determination of biofuel quality by means of NIR spectroscopy” LINK

“Application of hierarchical classification models and reliability estimation by bootstrapping, for authentication and discrimination of wine vinegars by UV-vis spectroscopy” LINK

“Geographical origin traceability of Cabernet Sauvignon wines based on Infrared fingerprint technology combined with chemometrics.” LINK

“Determination of Adulteration Content in Extra Virgin Olive Oil Using FT-NIR Spectroscopy Combined with the BOSSPLS Algorithm” LINK




Near Infrared

“NIR-based Sudan I to IV and Para-Red food adulterants screening.” Paprika adulteration LINK

“Nondestructive detection of rape leaf chlorophyll level based on Vis-NIR spectroscopy.” LINK

“High-throughput analysis of leaf physiological and chemical traits with VIS–NIR–SWIR spectroscopy: a case study with a maize diversity panel” | New phenomics paper from Ge, Schnable, Sigmon and Yang labs of & LINK

High-throughput analysis of leaf physiological and chemical traits with VIS–NIR–SWIR spectroscopy: a case study with a maize diversity panel LINK

“Estimating dry matter and fat content in blocks of Swiss cheese during production using on-line near infrared spectroscopy” LINK

“Temperature-dependent near-infrared spectroscopy for studying the interactions in protein aqueous solutions” LINK

” 滑皮金桔糖度的近红外光谱无损检测技术.” “Non-destructive testing technology of sugar content in Huapikumquat by near infrared spectroscopy” LINK

“Grading and Sorting of Grape Berries Using Visible-Near Infrared Spectroscopy on the Basis of Multiple Inner Quality Parameters” LINK

“Modified silver nanoparticles enhanced single drop micro extraction of tartrazine in food samples coupled with diffuse reflectance Fourier transform infrared spectroscopic analysis” LINK

“Multicolor lanthanide-doped CaS and SrS near-infrared stimulated luminescent nanoparticles with bright emission: application in broad-spectrum lighting, information coding, and bio-imaging.” LINK

“The use of mid-infrared spectra to map genes affecting milk composition” |(19)30485-0/fulltext?rss=yes LINK




Raman

“Semi-Automated Heavy-Mineral Analysis by Raman Spectroscopy” Minerals LINK




Hyperspectral

“Discrimination of astringent and deastringed hard Rojo Brillante persimmon fruit using a sensory threshold by means of hyperspectral imaging” LINK

“Remote Sensing, Vol. 11, Pages 1485: Tensor Based Multiscale Low Rank Decomposition for Hyperspectral Images Dimensionality Reduction” LINK




Agriculture

“Applied Sciences, Vol. 9, Pages 2472: Comparison of Raman and Mid-Infrared Spectroscopy for Real-Time Monitoring of Yeast Fermentations: A Proof-of-Concept for Multi-Channel Photometric Sensors” LINK

“Agronomy, Vol. 9, Pages 293: Field Spectroscopy to Determine Nutritive Value Parameters of Individual Ryegrass Plants” LINK




Pharma

“Quantification of Inkjet-Printed Pharmaceuticals on Porous Substrates Using Raman Spectroscopy and Near-Infrared Spectroscopy” LINK




Laboratory

“Adapted-Consumer-Technology Approach to Making Near-Infrared-Reflectography Visualization of Paintings and Murals Accessible to a Wider Audience” – Journal of Chemical Education 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


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 format
    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 V2.4 with new features

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

  • 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