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




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

Reduce Operating Costs and Total Cost of Ownership (TCO) of NIR-Spectroscopy (NIRS) in the Digitalization Age.
NIR-Spectroscopy (NIRS) - Reduce cost, Increase revenue
Reduce Cost by automated NIR development.
Increase Revenue by higher accuracy NIR results.


CalibrationModel.com (CM) versus Others

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

CM fix € pricing (approx.) 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

Spectroscopy and Chemometrics News Weekly #33, 2019

CalibrationModel.com

SAFE COST IN MAINTAINING NIR-SPECTROSCOPY METHODS | NIRSpectroscopy NIRS Spectroscopy DigitalTransformation Analysis Lab Laboratory Application Quantitative Analysis Methods Measurements Analytical Parameters Spectrometer Quality Accuracy LINK

Spectroscopy and Chemometrics News Weekly 32, 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 32, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LaborNIR LINK

Spettroscopia e Chemiometria Weekly News 32, 2019 | NIRS NIR Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem prediction NIRmodels LINK

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




Chemometrics

“Predicting the dry matter intake of grazing dairy cows using infrared reflectance spectroscopy analysis.” LINK

“Simultaneous determination of food colorants in liquid samples by UVVisible spectroscopy and multivariate data analysis using a reduced calibration matrix” LINK

“Coupling MicroNIR / Chemometrics for the on-site detection of cannabinoids in hemp flours” LINK

“Calibration and Characterization of Hyperspectral Imaging Systems Used for Natural Scene Imagery” LINK

“Analysis of wood thermal degradation using 2D correlation of near infrared and visible-light spectroscopy” LINK

“Rapid method for the quantification and identification of emerging compounds in wastewater based in nir spectroscopy and chemometrics” LINK

“Predicting the dry matter intake of grazing dairy cows using infrared reflectance spectroscopy analysis” |(19)30642-3/fulltext LINK




Near Infrared

“Application of Artificial Neural Networks (ANN) Coupled with Near-InfraRed (NIR) Spectroscopy for Detection of Adulteration in Honey” LINK

“Statistical Analysis of Amylose and Protein Content in Landrace Rice Germplasm Collected from East Asian Countries Based on Near-Infrared Reflectance Spectroscopy (NIRS)” LINK

“Identification of wheat kernels by fusion of RGB, SWIR, and VNIR samples.” LINK

“Purity analysis of multi-grain rice seeds with non-destructive visible and near-infrared spectroscopy” LINK

“Development of a methodology to analyze leaves from Prunus dulcis varieties using near infrared spectroscopy.” LINK

“Analysis of hydration water around human serum albumin using near-infrared spectroscopy” LINK

“Real-time Biomass Characterization in Energy Conversion Processes using Near Infrared Spectroscopy-A Machine Learning Approach” LINK

“Support vector machine regression on selected wavelength regions for quantitative analysis of caffeine in tea leaves by near infrared spectroscopy” LINK

“Near Infrared Reflectance Spectroscopy to analyze texture related characteristics of sous vide pork loin.” LINK

“Estimation of the Alcoholic Degree in Beers through Near Infrared Spectrometry Using Machine Learning” LINK

“The quantitative detection of botanical impurities contained in seed cotton with near infrared spectroscopy method” LINK




Raman

New post: Raman spectroscopy may make thyroid cancer diagnosis less invasive | Raman spectroscopy thyroid cancer LINK




Optics

“A multi-pixel diffuse correlation spectroscopy system based on a single photon avalanche diode array.” LINK




Agriculture

“The acute influence of sucrose consumption with and without vitamin C co-ingestion on microvascular reactivity in healthy young adults” vitaminC LINK

“Identification and characterization of a fast-neutron-induced mutant with elevated seed protein content in soybean” LINK

“Quantitative analysis and hyperspectral remote sensing of the nitrogen nutrition index in winter wheat” LINK




Food & Feed

“Multidimensional scaling assisted Fourier-transform Infrared spectroscopic analysis of fruit wine samples: Introducing a novel analytical approach” 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 (white-label)
    Customer <————————> CalibrationModel
                            or
    Customer <–>
Middleman <–> CalibrationModel
                        NIR Company
                        NIR Sales, Consultancy


Riskless Predictor OEM integration (white label) (in NIR-Vendors Instrument Software)
    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
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