Spectroscopy and Chemometrics/Machine-Learning News Weekly #2, 2022Spektroskopie und Chemometrie/Machine-Learning News Wöchentlich #2, 2022Spettroscopia e Chemiometria/Machine-Learning Weekly News #2, 2022

NIR Calibration-Model Services

NIR Spectrometry Custom Applications for chemical analysis | laboratory analyzer analyser QA QC Testing QAQC LINK

Protip: For NIR Spectroscopy Data Analysis use a Data Analytics Service that is NIR Domain related LINK

Spectroscopy and Chemometrics News Weekly 1, 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 1, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 1, 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)

"Minerals : VIS-NIR/SWIR Spectral Properties of H2O Ice Depending on Particle Size and Surface Temperature" LINK

"AKURASI KESAMAAN KELOMPOK DATA BERDASARKAN FCM DAN PCA-FCM PADA DATA GULA DARAH HASIL PEMINDAIAN NIRS TERHADAP DATA GULA ..." LINK

"Prediksi Kehilangan Hara Pada Tanah Tererosi Menggunakan Near Infrared Reflectance Spectroscopy (NIRS)" LINK

"Aplikasi Teknologi Near Infrared Reflectance Spectroscopy Dengan Metode Partial Least Square Untuk Prediksi Kadar Patchouli Alkohol Minyak Nilam" LINK

"Near infrared spectroscopy and aquaphotomics evaluation of the efficiency of solar dehydration processes in pineapple slices" LINK

"Comparisons of commercially available NIRS-based analyte predictions of haylage quality for equid nutrition" LINK

"Rapid discrimination of wood species from native forest and plantations using near infrared spectroscopy" LINK

"Identification of cocoa bean quality by near infrared spectroscopy and multivariate modeling" LINK

"The Influence of Ingredients, Corn Particle Size, and Sample Preparation on the Predictability of the Near Infrared Reflectance Spectroscopy" LINK

"Machine Learning Approach Using a Handheld Near-Infrared (NIR) Device to Predict the Effect of Storage Conditions on Tomato Biomarkers" LINK

"Solid Physical State Transformation in Hot Melt Extrusion Revealed by Inline Near-Infrared (NIR) Spectroscopy and Offline Terahertz (THz) Raman Imaging" LINK

"Thermal Insulation Performance of Novel Coated Fabrics Based on Fe-Doped BaSnO3 Near-Infrared Reflectance Pigments" LINK

"Non-destructive method for discrimination of weedy rice using near infrared spectroscopy and modified self-organizing maps (SOMs)" LINK

"Potential of VIS/NIR spectroscopy to detect and predict bitter pit in 'Golden Smoothee'apples" LINK

"Litterbag-NIRS to Forecast Yield: a Horticultural Case with Biofertilizer Effectors" | LINK

"Determination of SSC and TA content of pear by Vis-NIR spectroscopy combined CARS and RF algorithm" LINK

"Evaluation of the robustness of a novel NIR-based technique to measure the residual moisture in freeze-dried products" LINK

"Comparison of Partial Least Square, Artificial Neural Network and Support Vector Regressions for real time monitoring of CHO cell culture processes using in situ Near Infrared spectroscopy" LINK

"Evaluating the impact of NIR pre-processing methods via multiblock partial least-squares" LINK

"Differentiation of Organic Cocoa Beans and Conventional Ones by Using Handheld NIR Spectroscopy and Multivariate Classification Techniques" | LINK

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

"NearInfrared II Plasmonic Phototheranostics with Glutathione Depletion for Multimodal ImagingGuided HypoxiaTolerant ChemodynamicPhotocatalyticPhotothermal Cancer Therapy Triggered by a Single Laser" LINK

"Nearinfrared spectroscopy aids ecological restoration by classifying variation of taxonomy and phenology of a native shrub" LINK

"Optimization of sweet basil harvest time and cultivar characterization using nearinfrared spectroscopy, liquid and gas chromatography, and chemometric statistical methods" LINK

Hyperspectral Imaging (HSI)

"Prediction and Distribution Visualization of Salmon Quality Based on Hyperspectral Imaging Technology" LINK

"A data fusion method of electronic nose and hyperspectral to identify the origin of rice" LINK

"Plants : Hyperspectral Reflectance Response of Wild Rocket (Diplotaxis tenuifolia) Baby-Leaf to Bio-Based Disease Resistance Inducers Using a Linear Mixed Effect Model" LINK

"Prediction of moisture content in steamed and dried purple sweet potato using hyperspectral imaging analysis" | LINK

"Integration of textural and spectral features of Raman hyperspectral imaging for quantitative determination of a single maize kernel mildew coupled with chemometrics" LINK

Chemometrics and Machine Learning

"Near infrared spectroscopy combined with chemometrics for quantitative analysis of corn oil in edible blend oil" LINK

"Applications of NIR spectroscopy and chemometrics to illicit drug analysis: an example from inhalant drug screening tests" LINK

"Remote Sensing : Extraction of Kenyan Grassland Information Using PROBA-V Based on RFE-RF Algorithm" LINK

"Monitoring Molecular Weight Changes during Technical Lignin Depolymerization by Operando Attenuated Total Reflectance Infrared Spectroscopy and Chemometrics" LINK

"Modification of the effect of maturity variation on nondestructive detection of apple quality based on the compensation model" LINK

"Foods : Rapid Detection of Thermal Treatment of Honey by Chemometrics-Assisted FTIR Spectroscopy" LINK

"Applied Sciences : Dual Image-Based CNN Ensemble Model for Waste Classification in Reverse Vending Machine" LINK

Optics for Spectroscopy

Five highly cited papers in the fields of biosensors materials sensors (a thread) LINK

Facts

"Remote Sensing : Towards a Deep-Learning-Based Framework of Sentinel-2 Imagery for Automated Active Fire Detection" LINK

Research on Spectroscopy

"Residence Time Distribution as a Traceability Method for Lot Changes in A Pharmaceutical Continuous Manufacturing System" LINK

Environment NIR-Spectroscopy Application

"Remote Sensing : Inversion Evaluation of Rare Earth Elements in Soil by Visible-Shortwave Infrared Spectroscopy" LINK

"Heavy rainfall in peak growing season had larger effects on soil nitrogen flux and pool than in the late season in a semiarid grassland" LINK

"Rachis browning and water loss description during postharvest storage of 'Krissy'and 'Thompson Seedless' table grapes" LINK

"Retrieving zinc concentrations in topsoil with reflectance spectroscopy at Opencast Coal Mine sites" | LINK

"Remote Sensing : Soil Organic Carbon Content Prediction Using Soil-Reflected Spectra: A Comparison of Two Regression Methods" LINK

Agriculture NIR-Spectroscopy Usage

"The Promise of Hyperspectral Imaging for the Early Detection of Crown Rot in Wheat" LINK

"Ecological effects on the nutritional value of bromeliads, and its influence on Andean bears' diet selection" LINK

"Agronomy : Complex Spectroscopic Study for Fusarium Genus Fungi Infection Diagnostics of “Zalp” Cultivar Oat" LINK

"Predicting Protein Content in Grain Using Hyperspectral Deep Learning" LINK

"Genome-Wide Association Studies of Soybean Yield-Related Hyperspectral Reflectance Bands Using Machine Learning-Mediated Data Integration Methods" | LINK

Horticulture NIR-Spectroscopy Applications

"Determination of Sugar Adulteration in Honey Using Conductivity Meter and pH Meter" LINK

"A Comparative Analysis of Hybrid SVM and LS-SVM Classification Algorithms to Identify Dried Wolfberry Fruits Quality Based on Hyperspectral Imaging Technology" LINK

Chemical Industry NIR Usage

"Polymers : Hybrid Proton-Exchange Membrane Based on Perfluorosulfonated Polymers and Resorcinol-Formaldehyde Hydrogel" LINK

Laboratory and NIR-Spectroscopy

"Improving Quality Inspection of Textiles by an Augmented RGB-IR-HS-AI Approach" LINK

Other

"External beam irradiation angle measurement using Cerenkov emission I: Signal dependencies consideration" LINK

"Applications of Sensing for Disease Detection" LINK

"Functionalized Tris (anilido) triazacyclononanes as Hexadentate Ligands for the Encapsulation of U (III), U (IV) And La (III) Cations" LINK

"การ ประยุกต์ ใช้ เทคนิค สเปก โทร ส โค ปี อินฟราเรด ย่าน ใกล้ สำหรับ ทำนาย ปริมาณ แค โร ที น อย ด์ ใน เชื้อ พันธุกรรม ข้าวโพด หวาน" LINK

"抑郁症的近红外光谱研究进展" LINK

"高光谱成像技术在医药领域中的应用进展研究" LINK

NIR Calibration-Model Services

Near-Infrared Spectroscopy (NIRS)

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

Hyperspectral Imaging (HSI)

Chemometrics and Machine Learning

Optics for Spectroscopy

Five highly cited papers in the fields of biosensors materials sensors (a thread) LINK

Facts

"Remote Sensing : Towards a Deep-Learning-Based Framework of Sentinel-2 Imagery for Automated Active Fire Detection" LINK

Research on Spectroscopy

"Residence Time Distribution as a Traceability Method for Lot Changes in A Pharmaceutical Continuous Manufacturing System" LINK

Environment NIR-Spectroscopy Application

Agriculture NIR-Spectroscopy Usage

Horticulture NIR-Spectroscopy Applications

Chemical Industry NIR Usage

"Polymers : Hybrid Proton-Exchange Membrane Based on Perfluorosulfonated Polymers and Resorcinol-Formaldehyde Hydrogel" LINK

Laboratory and NIR-Spectroscopy

"Improving Quality Inspection of Textiles by an Augmented RGB-IR-HS-AI Approach" LINK

Other

NIR Calibration-Model Services

Near-Infrared Spectroscopy (NIRS)

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

Hyperspectral Imaging (HSI)

Chemometrics and Machine Learning

Optics for Spectroscopy

Five highly cited papers in the fields of biosensors materials sensors (a thread) LINK

Facts

"Remote Sensing : Towards a Deep-Learning-Based Framework of Sentinel-2 Imagery for Automated Active Fire Detection" LINK

Research on Spectroscopy

"Residence Time Distribution as a Traceability Method for Lot Changes in A Pharmaceutical Continuous Manufacturing System" LINK

Environment NIR-Spectroscopy Application

Agriculture NIR-Spectroscopy Usage

Horticulture NIR-Spectroscopy Applications

Chemical Industry NIR Usage

"Polymers : Hybrid Proton-Exchange Membrane Based on Perfluorosulfonated Polymers and Resorcinol-Formaldehyde Hydrogel" LINK

Laboratory and NIR-Spectroscopy

"Improving Quality Inspection of Textiles by an Augmented RGB-IR-HS-AI Approach" LINK

Other

Digitization in the field of NIR spectroscopy (smart sensors) / Digitalisierung im Bereich der NIR-Spektroskopie / Digitalizzazione nel campo della spettroscopia NIR (sensori intelligenti)

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 :

Start

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.

NIR Analysis in Laboratory and Laboratories – aka NIR Labs and NIR testingNIR-Analyse im Labor und in Laboratorien – aka NIR-Labore und NIR-TestsAnalisi NIR in laboratorio e nei laboratori – noti anche come laboratori NIR e test NIR

Do you have a NIR spectrometer in your Lab?

How many other analytics you do in the Lab could be done faster and cheaper with NIR?

Is this possible and precise enough?

Try, we have the solution for you!
You have the NIR, scan the samples, you have the lab values and the spectra, we calibrate for you!

To see if the application is possible and how precise it can be due to knowledge based intensive model optimizations.

We do the NIR feasibility study with data for you. Fixed prices

NIR has huge application potentials and it's a Green analytical method, that's fast and easy to use. And has today the possibility to scale out with inexpensive mobile NIR spectrometers.

Bring the Lab to the sample. To avoid sample transport and get immediate results for decision at the place or in the process.

Just try the NIR application, use the NIR daily, collect data in parallel, we develop, optimize and maintain the calibration models for you.

How do you think?

Start Calibrate

What is possible today with NIR?
The number of different Applications exploded in the last 2-3 years!
See NIR research papers news daily on @CalibModel or the 7-day summaries "NIR News Weekly" here.

Haben Sie ein NIR-Spektrometer in Ihrem Labor?

Wie viele andere Analysen, die Sie im Labor durchführen, könnten mit NIR schneller und billiger durchgeführt werden?

Ist dies möglich und präzise genug?

Versuchen Sie es, wir haben die Lösung für Sie!
Sie haben das NIR, scannen sie Proben, Sie haben die Laborwerte und die Spektren, wir kalibrieren für Sie!

Um zu sehen, ob die Anwendung möglich ist und wie präzise sie aufgrund von wissensbasierten intensiven Modelloptimierungen sein kann.

Wir führen die NIR-Machbarkeitsstudie mit Daten für Sie durch. Fixpreise

NIR hat ein riesiges Anwendungspotential und ist eine grüne Analysemethode, die schnell und einfach anzuwenden ist. Und hat heute die Möglichkeit, mit kostengünstigen mobilen NIR-Spektrometern zu skalieren.

Bringen Sie das Labor zu der Probe. So vermeiden Sie den Probentransport und erhalten sofortige Ergebnisse zur Entscheidung am Ort oder im Prozess.

Probieren Sie einfach die NIR-Anwendung aus, nutzen Sie das NIR täglich, sammeln Sie parallel dazu Daten, wir entwickeln, optimieren und warten die Kalibriermodelle für Sie.

Wie denken Sie darüber?

Start Calibrate

Was ist heute mit NIR möglich?
Die Zahl der verschiedenen Anwendungen ist in den letzten 2-3 Jahren explodiert!
Sehen Sie hier die täglichen NIR-Forschungsberichte über @CalibModel oder die 7-Tage-Zusammenfassungen "NIR News Weekly".

Avete uno spettrometro NIR nel vostro laboratorio?

Quante altre analisi si possono fare in laboratorio in modo più veloce ed economico con il NIR?

È possibile e sufficientemente preciso?

Provate, abbiamo la soluzione per voi!
Avete il NIR, scansionate i campioni, avete i valori di laboratorio e gli spettri, noi calibriamo per voi!

Per vedere se l'applicazione è possibile e quanto precisa può essere grazie all'ottimizzazione intensiva del modello basata sulla conoscenza.
Facciamo lo studio di fattibilità NIR con i dati per voi. Prezzi fissi

Il NIR ha enormi potenzialità applicative ed è un metodo analitico Green, veloce e facile da usare. E ha oggi la possibilità di scalare con gli economici spettrometri mobili NIR.
Portate il laboratorio al campione. Per evitare il trasporto del campione e ottenere risultati immediati per la decisione sul posto o nel processo.

Basta provare l'applicazione NIR, usare il NIR quotidianamente, raccogliere dati in parallelo, noi sviluppiamo, ottimizziamo e manteniamo i modelli di calibrazione per voi.

Come pensate di fare?

Inizia a calibrare

Cosa è possibile oggi con il NIR?
Il numero di diverse Applicazioni è esploso negli ultimi 2-3 anni!
Vedi le notizie dei giornali di ricerca NIR su @CalibModel o i riassunti di 7 giorni "NIR News Weekly" qui.
________________________________________________

Análise NIR no laboratório e laboratórios - também conhecidos como laboratórios NIR e testes NIR

Tem um espectrómetro NIR no seu laboratório?

Quantas outras análises que faz no Laboratório poderiam ser feitas mais rapidamente e mais baratas com o NIR? Será isto possível e suficientemente preciso?

Tente, nós temos a solução para si!

Tem o NIR, digitaliza as amostras, tem os valores de laboratório e os espectros, nós calibramos para si! Para ver se a aplicação é possível e quão precisa pode ser devido a optimizações de modelos intensivas baseadas no conhecimento.
Fazemos o estudo de viabilidade do NIR com dados para si. Preços fixos

NIR tem um enorme potencial de aplicação e é um método analítico Verde, que é rápido e fácil de usar. E tem hoje a possibilidade de ser escalado com espectrómetros NIR móveis de baixo custo.

Traga o Laboratório para a amostra. Para evitar o transporte de amostras e obter resultados imediatos para decisão no local ou no processo.

Basta experimentar a aplicação NIR, utilizar o NIR diariamente, recolher dados em paralelo, nós desenvolvemos, optimizamos e mantemos os modelos de calibração para si.

Como pensa?

Iniciar a calibração

O que é possível hoje com o NIR?
O número de diferentes Aplicações explodiu nos últimos 2-3 anos!
Ver os jornais de investigação NIR diariamente sobre @CalibModel ou os resumos de 7 dias "NIR News Weekly" aqui.
________________________________________________

El análisis NIR en el laboratorio y los laboratorios - también conocidos como laboratorios NIR y pruebas NIR

Tiene un espectrómetro NIR en su laboratorio?

Cuántos análisis más haces en el laboratorio podrían hacerse más rápido y más barato con el NIR? Es esto posible y suficientemente preciso?

¡Inténtelo, tenemos la solución para usted!
Tienes el NIR, escaneas las muestras, tienes los valores del laboratorio y los espectros, ¡calibramos para ti!

Para ver si la aplicación es posible y cuán precisa puede ser gracias a las optimizaciones intensivas de modelos basadas en el conocimiento.

Hacemos el estudio de viabilidad del NIR con los datos para usted. Precios fijos

El NIR tiene un enorme potencial de aplicación y es un método analítico verde, que es rápido y fácil de usar. Y tiene hoy la posibilidad de escalar con espectrómetros NIR móviles baratos.
Trae el laboratorio a la muestra. Para evitar el transporte de la muestra y obtener resultados inmediatos para la decisión en el lugar o en el proceso.

Pruebe la aplicación NIR, utilice el NIR diariamente, recoja los datos en paralelo, nosotros desarrollamos, optimizamos y mantenemos los modelos de calibración para usted.

Cómo cree usted?

Comenzar a calibrar

Qué es posible hoy en día con el NIR?
¡El número de aplicaciones diferentes explotó en los últimos 2-3 años!
Vea las noticias diarias de los trabajos de investigación del NIR en @CalibModel o los resúmenes de 7 días "NIR News Weekly" aquí.

June 22, 2020

Spectroscopy and Chemometrics News Weekly #25, 2020Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #25, 2020Spettroscopia e Chemiometria Weekly News #25, 2020

NIR Calibration-Model Services

Using cost saving NIR-Spectroscopy Analysis? You can Save even more Costs and Time! How? Read here | VIS NIR NIRS Spectroscopy LabManager Labs QualityControl CostSaving foodindustry foodproduct Spectrometer Sensor Analytics LINK

Machine Learning for NIR Spectroscopy as a Service, a Game Changer for Productivity and Accuracy/Precision! Use the free NIR-Predcitor software to combine NIRS + Lab data and send your Calibration Request. LabManager Analysis MachineLearning LINK

Spectroscopy and Chemometrics News Weekly 24, 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 24, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 24, 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)

"Near-Infrared (NIR) Spectroscopy to Differentiate Longissimus thoracis et lumborum (LTL) Muscles of Game Species" LINK

"Estimation of Harumanis (Mangifera indica L.) Sweetness using Near-Infrared (NIR) Spectroscopy" LINK

"Handheld Near-Infrared Spectrometers: Reality and Empty Promises" miniaturization NIRS FTNIR MEMS MOEMS LVFs LINK

BESTCentreLTU research hot off the press: | In collaboration with Assoc. Prof. Kellie Tuck from , we’ve developed new near-infrared emissive electrochemiluminophores for sensing in NIR transparent biological media. LINK

"Near-Infrared Emitter for Bioanalytical Applications" NIR ECL electrochemiluminescence LINK

"Fault detection with moving window PCA using NIRS spectra for the monitoring of anaerobic digestion process" LINK

"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

"Control of ascorbic acid in fortified powdered soft drinks using near-infrared spectroscopy (NIRS) and multivariate analysis." LINK

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

"Non-Invasive Blood Glucose Monitoring using Near-Infrared Spectroscopy based on Internet of Things using Machine Learning" LINK

"Investigating the Quality of Antimalarial Generic Medicines Using Portable Near-Infrared Spectroscopy" LINK

"Rapid quantitative detection of mineral oil contamination in vegetable oil by near-infrared spectroscopy" LINK

"THE DETERMINATION OF FATTY ACIDS IN CHEESES OF VARIABLE COMPOSITION (COW, EWE'S, AND GOAT) BY MEANS OF NEAR INFRARED SPECTROSCOPY" LINK

"Detection of melamine and sucrose as adulterants in milk powder using near-infrared spectroscopy with DD-SIMCA as one-class classifier and MCR-ALS as a means to provide pure profiles of milk and of both adulterants with forensic evidence" LINK

"Protein, weight, and oil prediction by singleseed nearinfrared spectroscopy for selection of seed quality and yield traits in pea (Pisum sativum)" LINK

"Modeling bending strength of oil-heat-treated wood by near-infrared spectroscopy" LINK

"ripening stages monitoring of Lamuyo pepper using a new‐generation near‐infrared spectroscopy sensor" LINK

"Should the Past Define the Future of Interpretation of Infrared and Raman Spectra?" 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

"Rapid identification of Lilium species and polysaccharide contents based on near infrared spectroscopy and weighted partial least square method." LINK

"A Rapid and Nondestructive Approach for the Classification of Different-Age Citri Reticulatae Pericarpium Using Portable Near Infrared Spectroscopy." LINK

Hyperspectral Imaging (HSI)

"Rapid detection of quality index of postharvest fresh tea leaves using hyperspectral imaging" LINK

"Non-Destructive Detection of Tea Leaf Chlorophyll Content Using Hyperspectral Reflectance and Machine Learning Algorithms" LINK

"A deep learning based regression method on hyperspectral data for rapid prediction of cadmium residue in lettuce leaves" LINK

"Deep learning applied to hyperspectral endoscopy for online spectral classification" DOI:10.1038/s41598-020-60574-6 LINK

"Detection of fish fillet substitution and mislabeling using multimode hyperspectral imaging techniques" LINK

Chemometrics and Machine Learning

"Molecules, Vol. 25, Pages 1453: Characterization, Quantification and Quality Assessment of Avocado (Persea americana Mill.) Oils" LINK

"Comprehensive Chemometrics - Chemical and Biochemical Data Analysis Reference Work • 2nd Edition • 2020" | books Chemometrics DataAnalysis Chemical Biochemical LINK

"Identification of invisible biological traces in forensic evidences by hyperspectral NIR imaging combined with chemometrics" LINK

Research on Spectroscopy

"Automatisierte und digitale Dokumentation der Applikation organischer Düngemittel" LINK

"Plenary Lecture Methods and Tools for Sensors Information Processing" LINK

Equipment for Spectroscopy

Using NIR scanner to assess grass in sward for composition prior to baling and wrapping for EU LIFE Farm4More project. Thanks to Dinamica Generale for providing the equipment LINK

"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

Agriculture NIR-Spectroscopy Usage

"Hyperspectral imaging using multivariate analysis for simulation and prediction of agricultural crops in Ningxia, China" LINK

"Placing Soil Information in the Hands of Farmers" LINK

"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

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

Other

LINK

NIR Calibration-Model Services

Near-Infrared Spectroscopy (NIRS)

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

Hyperspectral Imaging (HSI)

Chemometrics and Machine Learning

Research on Spectroscopy

"Automatisierte und digitale Dokumentation der Applikation organischer Düngemittel" LINK

"Plenary Lecture Methods and Tools for Sensors Information Processing" LINK

Equipment for Spectroscopy

Agriculture NIR-Spectroscopy Usage

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

Other

LINK

NIR Calibration-Model Services

Near-Infrared Spectroscopy (NIRS)

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

Hyperspectral Imaging (HSI)

Chemometrics and Machine Learning

Research on Spectroscopy

"Automatisierte und digitale Dokumentation der Applikation organischer Düngemittel" LINK

"Plenary Lecture Methods and Tools for Sensors Information Processing" LINK

Equipment for Spectroscopy

Agriculture NIR-Spectroscopy Usage

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

Other

LINK

March 16, 2020

Spectroscopy and Chemometrics News Weekly #11, 2020Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #11, 2020Spettroscopia e Chemiometria Weekly News #11, 2020

CalibrationModel.com

How to Develop Near-Infrared Spectroscopy Calibrations in the 21st Century? | Chemometrics Analytische Chemie LINK

Simplify the process of training machine learning models for NIR spectra data with applied near-infrared spectroscopy (NIRS) knowledge. quantitative multivariate prediction equations LINK

Spectroscopy and Chemometrics News Weekly 10, 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 10, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 10, 2020 | NIRS NIR Spettroscopia analisi chimica Spettrale Spettrometro IoT Sensore Attrezzatura analitica nearinfrared foodscience foodprocessing foodsafety foodproduction farming agriculture LINK

Near Infrared

"Klasifikasi Kopi Green Beans Arabika Sumatera Utara Menggunakan FT-Nirs dan Analisis Diskriminan" LINK

"APLIKASI NEAR INFRARED SPECTROSCOPY (NIRS) UNTUK MENGETAHUI KANDUNGAN HARA NITROGEN FOSFOR DAN KALIUM PADA INSTALASI …" LINK

" Identification of common wood species in northeast China using Vis/NIR spectroscopy" LINK

"Efficient Super Broadband NIR Ca2LuZr2Al3O12:Cr3+,Yb3+ Garnet Phosphor for pc‐LED Light Source toward NIR Spectroscopy Applications" LINK

"Performance comparison of sampling designs for quality and safety control of raw materials in bulk: a simulation study based on NIR spectral data and geostatistical …" LINK

"Prediction of drug dissolution from Toremifene 80 mg tablets using NIR spectroscopy" LINK

"Nearinfrared spectroscopy (NIRS) for taxonomic entomology: A brief review" LINK

"Determination of tomato quality attributes using portable NIR-sensors" LINK

"Exploring the potential of NIR hyperspectral imaging for automated quantification of rind amount in grated Parmigiano Reggiano cheese" LINK

"Rapid detection of adulteration of minced beef using Vis/NIR reflectance spectroscopy with multivariate methods." LINK

"Evaluation of quinclorac toxicity and alleviation by salicylic acid in rice seedlings using ground-based visible/near-infrared hyperspectral imaging." LINK

"An optimized non-invasive glucose sensing based on scattering and absorption separating using near-infrared spectroscopy" LINK

"Identification of waxy cassava genotypes using fourier‐transform near‐infrared spectroscopy" LINK

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

"Near-infrared-based Identification of Walnut Oil Authenticity" LINK

"Detection of flaxseed oil multiple adulteration by near-infrared spectroscopy and nonlinear one class partial least squares discriminant analysis" LINK

"Application research of sensor output digitization for compact near infrared IOT node" LINK

"Refining Transfer Set in Calibration Transfer of Near Infrared Spectra by Backward Refinement of Samples" LINK

"Highly identification of keemun black tea rank based on cognitive spectroscopy: Near infrared spectroscopy combined with feature variable selection" LINK

"Optimizing Rice Near-Infrared Models Using Fractional Order SavitzkyGolay Derivation (FOSGD) Combined with Competitive Adaptive Reweighted Sampling (CARS)" LINK

"Fourier transform near infrared spectroscopy as a tool to discriminate olive wastes: The case of monocultivar pomaces." LINK

"Evaluation of quinclorac toxicity and alleviation by salicylic acid in rice seedlings using ground-based visible/near-infrared hyperspectral imaging" LINK

"Near Infrared Spectrometric Investigations on the behaviour of Lactate." LINK

"Nondestructive rapid and quantitative analysis for the curing process of silicone resin by nearinfrared spectra" LINK

"An introduction to handheld infrared and Raman instrumentation" LINK

Hyperspectral

"Hyperspectral anomaly detection by local joint subspace process and support vector machine" LINK

"Assessment of matcha sensory quality using hyperspectral microscope imaging technology" LINK

Chemometrics

"Application of Infrared Spectroscopy and Chemometrics to the Cocoa Industry for Fast Composition Analysis and Fraud Detection" LINK

"Calibration models for the nutritional quality of fresh pastures by nearinfrared reflectance spectroscopy" LINK

"Achieving robustness to temperature change of a NIRS-PLSR model for intact mango fruit dry matter content" LINK

"Application of hyperspectral imaging combined with chemometrics for the non-destructive evaluation of the quality of fruit in postharvest" LINK

Equipment

"Characterization of Deep Green Infection in Tobacco Leaves Using a Hand-Held Digital Light Projection Based Near-Infrared Spectrometer and an Extreme Learning Machine Algorithm" LINK

"MEMS technology for fabricating plasmonic near-infrared spectrometers" LINK

"Sensors, Vol. 20, Pages 545: Development of Low-Cost Portable Spectrometers for Detection of Wood Defects" LINK

Environment

"Classification of Granite Soils and Prediction of Soil Water Content Using Hyperspectral Visible and Near-Infrared Imaging" LINK

"Determining mandatory nutritional parameters for Iberian meat products using a new method based on near infra-red reflectance spectroscopy and data mining" LINK

Agriculture

"Instrumental Procedures for the Evaluation of Juiciness in Peach and Nectarine Cultivars for Fresh Consumption" LINK

"The creation of the FT-NIR calibration for the determination of the amount of corn grain in concentrated feed" LINK

In this 9th clip from his presentation at the 2019 IFS Agronomic Conference, Wouter Saeys explains which type of NIR is best for measuring the nutrient content of manure, and why. Info on this paper is here; it's free for Society Members to download: LINK

"Remote Sensing, Vol. 12, Pages 928: Machine Learning Algorithms to Predict Forage Nutritive Value of In Situ Perennial Ryegrass Plants Using Hyperspectral Canopy Reflectance Data" LINK

"Development of a Method To Prioritize Protein-Ligand Pairs on Beads Using Protein Conjugated to a Near-IR Dye." LINK

"Agronomy, Vol. 10, Pages 148: Performance Evaluation of Two Commercially Available Portable Spectrometers to Non-Invasively Determine Table Grape and Peach Quality Attributes" LINK

"Investigation of a Medical Plant for Hepatic Diseases with Secoiridoids Using HPLC and FT-IR Spectroscopy for a Case of Gentiana rigescens" LINK

Food & Feed

"Comparison of sensory evaluation techniques for Hungarian wines" LINK

Laboratory

"Roadmap of cocoa quality and authenticity control in the industry: A review of conventional and alternative methods" LINK

CalibrationModel.com

Near Infrared

Hyperspectral

Chemometrics

Equipment

Environment

Agriculture

Food & Feed

"Comparison of sensory evaluation techniques for Hungarian wines" LINK

Laboratory

"Roadmap of cocoa quality and authenticity control in the industry: A review of conventional and alternative methods" LINK

CalibrationModel.com

Near Infrared

Hyperspectral

Chemometrics

Equipment

Environment

Agriculture

Food & Feed

"Comparison of sensory evaluation techniques for Hungarian wines" LINK

Laboratory

"Roadmap of cocoa quality and authenticity control in the industry: A review of conventional and alternative methods" LINK

March 9, 2020

Spectroscopy and Chemometrics News Weekly #10, 2020Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #10, 2020Spettroscopia e Chemiometria Weekly News #10, 2020

CalibrationModel.com

Develop customized NIR applications and freeing up hours of spectroscopy analysts time LINK

Spectroscopy and Chemometrics News Weekly 9, 2020 | NIRS NIR Spectroscopy MachineLearning Spectrometer Analytical Analysis Lab Labs Laboratories Laboratory Software IoT Sensors materialsensing QA QC Quality foodtechnologies LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 9, 2020 | NIRS NIR Spektroskopie MachineLearning AI FoodScience Spektrometer IoT Sensor Nahinfrarot Analytik foodtech Analysentechnik Analysemethode Nahinfrarotspektroskopie FutureLab LINK

Spettroscopia e Chemiometria Weekly News 9, 2020 | NIRS NIR Spettroscopia MachineLearning analisi Spettrale Spettrometro Chem IoT Sensore analitica Lab Laboratorio Labtechnician analisi prova qualità QualityControl meatindustry LINK

Near Infrared

"Differentiation of Muscle Abnormalities in Turkey Breast Meat in Palestinian Market by Using VIS-NIR Spectroscopy" LINK

"On-line prediction of hazardous fungal contamination in stored maize by integrating Vis/NIR spectroscopy and computer vision." LINK

"Prediction of starch reserves in intact and ground grapevine cane wood tissues using near infrared reflectance spectroscopy (NIRS)" LINK

"Nitrate (NO3-) prediction in soil analysis using near-infrared (NIR) spectroscopy" LINK

"Can Near Infrared Spectroscopy (NIRS) Quantify The Quality of Fishmeal Circulating in Jember, Indonesia?" LINK

"Nondestructive VIS/NIR spectroscopy estimation of intravitelline vitamin E and cholesterol concentration in hen shell eggs" LINK

"NIR spectroscopy-multivariate analysis for rapid authentication, detection and quantification of common plant adulterants in saffron (Crocus sativus L.) stigmas" LINK

"Rapid discrimination of coal geographical origin via near-infrared spectroscopy combined with machine learning algorithms" LINK

"Applied Sciences, Vol. 10, Pages 616: The Brewing Industry and the Opportunities for Real-Time Quality Analysis Using Infrared Spectroscopy" LINK

"A Global Model for the Determination of Prohibited Addition in Pesticide Formulations by Near Infrared Spectroscopy" LINK

" Visible and near-infrared spectroscopy in Poland: from the beginning to the Polish Soil Spectral Library" LINK

"Visible and Near-Infrared Spectroscopic Discriminant Analysis Applied to Brand Identification of Wine" LINK

"Interaction between tau and water during the induced aggregation revealed by near-infrared spectroscopy" LINK

Raman

Using Raman Spectroscopy to Evaluate Packaging for Frozen Hamburgers - - LINK

Hyperspectral

"Hyperspectral imaging for Ink Identification in Handwritten Documents" LINK

"Effective hyperspectral band selection and multispectral sensing based data reduction and applications in food analysis" LINK

"Foods, Vol. 9, Pages 94: Rapid Screen of the Color and Water Content of Fresh-Cut Potato Tuber Slices Using Hyperspectral Imaging Coupled with Multivariate Analysis" LINK

"Detection of Microplastics Using Machine Learning" hyperspectral LINK

"Non-destructive determination of volatile oil and moisture content and discrimination of geographical origins of Zanthoxylum bungeanum Maxim. by hyperspectral …" LINK

"The hype in spectral imaging" Hyperspectral HSI LINK

"Multi-sensor integration approach based on hyperspectral imaging and electronic nose for quantitation of fat and peroxide value of pork meat" LINK

Chemometrics

"Investigating aquaphotomics for temperature-independent prediction of soluble solids content of pure apple juice" LINK

"Accuracy of Estimating Soil Properties with Mid‐Infrared Spectroscopy: Implications of Different Chemometric Approaches and Software Packages Related to Calibration Sample Size" LINK

"A correlation-analysis-based wavelength selection method for calibration transfer" LINK

"Vibrational spectroscopy and chemometrics tools for authenticity and improvement the safety control in goat milk" LINK

"Prediction and Analysis of Bamboo heating value Near Infrared Spectroscopy Based on Competitive Adaptive Weighted Sampling Algorithm" LINK

Environment

"Influence of two‐phase behavior of ethylene ionomers on diffusion of water" LINK

Agriculture

"Detection of Diseases on Wheat Crops by Hyperspectral Data" LINK

"Comparative data on effects of alkaline pretreatments and enzymatic hydrolysis on bioemulsifier production from sugarcane straw by Cutaneotrichosporon mucoides." LINK

"Prediction of soil macronutrient (nitrate and phosphorus) using near-infrared (NIR) spectroscopy and machine learning" LINK

"最小二乘支持向量机的核桃露饮品中脂肪成分的定量分析" "Determination of Fat in Walnut Beverage Based on Least Squares Support Vector Machine" LINK

"Scaling up of NIRS facility in Mali for analysis of biomass quality for GLDC crops" LINK

"Low cost hyper-spectral imaging system using linear variable bandpass filter for agriculture applications" LINK

Other

"Avaliação estatística das variáveis relacionadas a qualidade de farelo de soja para frangos de corte" LINK

"Diets selected and growth of steers grazing buffel grass (Cenchus ciliarus cv Gayndah)-Centro (Centrosema brasilianum cv Oolloo) pastures in a seasonally dry …" LINK

"Identification of Flax Oil by Linear Multivariate Spectral Analys" LINK

"Spectroscopic Investigations of Solutions of Lithium bis(fluorosulfonyl)imide (LiFSI) in Valeronitrile" LINK

"Quantitative analysis of the interaction of ammonia with 1-(2-hydroxyethyl)-3-methylimidazolium tetrafluoroborate ionic liquid. Understanding the volumetric and …" LINK

CalibrationModel.com

Near Infrared

Raman

Using Raman Spectroscopy to Evaluate Packaging for Frozen Hamburgers - - LINK

Hyperspectral

Chemometrics

Environment

"Influence of two‐phase behavior of ethylene ionomers on diffusion of water" LINK

Agriculture

Other

CalibrationModel.com

Near Infrared

Raman

Using Raman Spectroscopy to Evaluate Packaging for Frozen Hamburgers - - LINK

Hyperspectral

Chemometrics

Environment

"Influence of two‐phase behavior of ethylene ionomers on diffusion of water" LINK

Agriculture

Other

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 NIR + Lab 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

Your 4 steps to the applicable NIR calibration:

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

Use NIR Calibrations

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

Unser Service ist anders

Wir erstellen die optimalen quantitativen Vorhersagemodelle für Ihre NIR-Analysebedürfnisse (kein Bedarf an mathematisch/statistischer Modellbildungssoftware an Ihrem Standort).
Die NIR-Predictor-Software und die Kalibrierungsmodelle sind bei Ihnen vor Ort. Für unseren Service ist keine Internetverbindung erforderlich. Sie können unbegrenzt Vorhersagen machen, die schnelle Messzyklen ohne zusätzliche Kosten ermöglichen (Nicht pro Vorhersage bezahlt).
Sie besitzen Ihre NIR + Lab Daten und die Kalibrierungen. Sie können auf den detaillierten Kalibrierbericht mit allen Einstellungen und Statistiken zugreifen (keine Black-Box-Modelle).

NIR-Kalibrierungen erhalten

Ihre 4 Schritte zur anwendbaren NIR Kalibrierung:

Download kostenloser NIR-Prädiktor hier
Kombiniere deine NIR-Spektren mit Labor-Referenzwerten, siehe Video für 2. und 3.
(Handbuch)
Erstellen Sie eine Kalibrierungsanfrage und senden Sie sie an info@CalibrationModel.com (CM)
Nach der Bearbeitung erhalten Sie einen Link zum Web Shop zum Herunterladen der Kalibrierungen.

NIR-Kalibrierungen verwenden

weitere Videos ansehen

Mit anderen Worten

Calibration Model vereinfacht den Prozess des Trainings von maschinellen Lernmodellen für NIRS-Daten
und bietet gleichzeitig die Möglichkeit, verschiedene Algorithmen und angewandtes Wissen aus der Nahinfrarotspektroskopie (NIRS) auszuprobieren.
Es ist mehr als nur eine AutoML-Plattform, es ist ein umfassender Service, bei dem Sie das optimale Modell und seinen beschreibenden Kalibrierungsbericht herunterladen können,
die Einblicke in die Datenaufbereitung, Feature-Engineering, Modelltraining und Hyperparameter-Tuning geben.

NIR Kalibrierung Starten

September 16, 2019

Spectroscopy and Chemometrics News Weekly #37, 2019Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #37, 2019Spettroscopia e Chemiometria Weekly News #37, 2019

CalibrationModel.com

The new Version V2.4 of the free NIR-Predictor supports multiple native file formats of miniature, mobile and desktop spectrometers get your spectra analyzed as easy as Drag’n’Drop. LINK

Spectroscopy and Chemometrics News Weekly 36, 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 36, 2019 | NIRS NIR Spektroskopie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse Qualitätslabor LINK

Spettroscopia e Chemiometria Weekly News 36, 2019 | NIRS NIR Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem predictionmodel LINK

Chemometrics

"Identification of Passion Fruit Oil Adulteration by Chemometric Analysis of FTIR Spectra" LINK

"Investigating the use of visible and near infrared spectroscopy to predict sensory and texture attributes of beef M.longissimus thoracis et lumborum." LINK

"Optimized prediction of sugar content in 'Snow' pear using near-infrared diffuse reflectance spectroscopy combined with chemometrics" LINK

"FT-NIR spectroscopy and multivariate classification strategies for the postharvest quality of green-fleshed kiwifruit varieties" FTNIR LINK

"An Approach to Rapid Determination of Tween-80 for the Quality Control of Traditional Chinese Medicine Injection by Partial Least Squares Regression in Near-Infrared Spectral Modeling" LINK

"Assessing macro-element content in vine leaves and grape berries of vitis vinifera by using near-infrared spectroscopy and chemometrics" LINK

"Investigating the use of visible and near infrared spectroscopy to predict sensory and texture attributes of beef M. longissimus thoracis et lumborum" LINK

"Rapid classification of commercial Cheddar cheeses from different brands using PLSDA, LDA and SPA-LDA models built by hyperspectral data" LINK

Near Infrared

"A Comparison of Sparse Partial Least Squares and Elastic Net in Wavelength Selection on NIR Spectroscopy Data." LINK

"Reliability of NIRS portable device for measuring intercostal muscles oxygenation during exercise" LINK

"Ability of near-infrared spectroscopy for non-destructive detection of internal insect infestation in fruits: Meta-analysis of spectral ranges and optical measurement modes." LINK

"Analysis of the Acid Detergent Fibre Content in Turnip Greens and Turnip Tops (Brassica rapa L. Subsp. rapa) by Means of Near-Infrared Reflectance." LINK

"Lipid-Core Plaque Assessed by Near-Infrared Spectroscopy and Procedure Related Microvascular Injury." LINK

"Analysis of the Acid Detergent Fibre Content in Turnip Greens and Turnip Tops (Brassica rapa L. Subsp. rapa) by Means of Near-Infrared Reflectance" Foods LINK

"Online monitoring of multiple component parameters during ethanol fermentation by near-infrared spectroscopy." LINK

Hyperspectral

"Identifying Freshness of Spinach Leaves Stored at Different Temperatures Using Hyperspectral Imaging." LINK

"Identifying Freshness of Spinach Leaves Stored at Different Temperatures Using Hyperspectral Imaging" Foods LINK

Equipment

"Investigations into the use of handheld near-infrared spectrometer and novel semi-automated data analysis for the determination of protein content in different cultivars of Panicum miliaceumL." LINK

Agriculture

"Use of near-infrared spectroscopy for the rapid evaluation of soybean [Glycine max (L.) Merri.] water soluble protein content." LINK

Food & Feed

"Rapid visible-near infrared (Vis-NIR) spectroscopic detection and quantification of unripe banana flour adulteration with wheat flour" LINK

.

CalibrationModel.com

The new Version V2.4 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. LINK

Spectroscopy and Chemometrics News Weekly 36, 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 36, 2019 | NIRS NIR Spektroskopie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse Qualitätslabor LINK

Spettroscopia e Chemiometria Weekly News 36, 2019 | NIRS NIR Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem predictionmodel LINK

Chemometrics

Near Infrared

Hyperspectral

Equipment

"Investigations into the use of handheld near-infrared spectrometer and novel semi-automated data analysis for the determination of protein content in different cultivars of Panicum miliaceumL." LINK

Agriculture

"Use of near-infrared spectroscopy for the rapid evaluation of soybean [Glycine max (L.) Merri.] water soluble protein content." LINK

Food & Feed

"Rapid visible-near infrared (Vis-NIR) spectroscopic detection and quantification of unripe banana flour adulteration with wheat flour" LINK

.

CalibrationModel.com

Chemometrics

Near Infrared

Hyperspectral

Equipment

"Investigations into the use of handheld near-infrared spectrometer and novel semi-automated data analysis for the determination of protein content in different cultivars of Panicum miliaceumL." LINK

Agriculture

"Use of near-infrared spectroscopy for the rapid evaluation of soybean [Glycine max (L.) Merri.] water soluble protein content." LINK

Food & Feed

"Rapid visible-near infrared (Vis-NIR) spectroscopic detection and quantification of unripe banana flour adulteration with wheat flour" LINK

.

September 8, 2019

Spectroscopy and Chemometrics News Weekly #36, 2019Spektroskopie und Chemometrie Neuigkeiten Wöchentlich #36, 2019Spettroscopia e Chemiometria Weekly News #36, 2019

CalibrationModel.com

9 Reasons why near-Infrared Spectroscopy Applications need periodic Calibration Maintenance | NIR NIRS Infrared LINK

Improve Accuracy of fast Nondestructive NIRS Measurements by Optimal Chemometric Modelling | pauto QAQC LINK

Spectroscopy and Chemometrics News Weekly 35, 2019 | NIRS NIR Spectroscopy Chemometrics Spectrometer processcontrol Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality Check LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 35, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie LINK

Spettroscopia e Chemiometria Weekly News 35, 2019 | NIRS NIR Spettroscopia Chemiometria analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem predictionmodels LINK

Chemometrics

"Comparison of whole-tree wood property maps based on near-infrared spectroscopic calibrations utilizing data at different spatial resolutions" LINK

"Prediction of beef meat fatty acid composition by visible-near-infrared spectroscopy was improved by preliminary freeze-drying." LINK

"Scalable calibration transfer without standards via dynamic time warping for near-infrared spectroscopy" LINK

"Cross components calibration transfer of NIR spectroscopy model through PCA and weighted ELM-based TrAdaBoost algorithm" LINK

"Strategies for the efficient estimation of soil organic carbon at the field scale with vis-NIR spectroscopy: Spectral libraries and spiking vs. local calibrations" LINK

"Application of Near-Infrared for Online Monitoring of Heavy Fuel Oil at Thermoelectric Power Plants. Part I: Development of Chemometric Models" LINK

"Accuracy and biases in predicting the chemical and physical traits of many types of cheeses using different visible and near-infrared spectroscopic techniques and spectrum intervals" LINK

"A Regional Legacy Soil Dataset for Prediction of Sand and Clay Content with Vis-Nir-Swir, in Southern Brazil" LINK

"Rapid prediction of atrazine sorption in soil using visible near-infrared spectroscopy" LINK

"Developing Calibration Model for Prediction of Malt Barley and Teff Genotypes Quality Traits Using Near Infrared Spectroscopy (NIRS)" LINK

" Prediction of Glycogen and Moisture Contents in Japanese Wagyu Beef by Fourier Transform Near-infrared Spectroscopy for Quality Evaluation" LINK

Near Infrared

"基于核局部保持投影的近红外光谱玉米单倍体识别研究" "Research on Identifying Maize Haploid Seeds Using Near Infrared Spectroscopy Based on Kernel Locality Preserving Projection" LINK

"种基于近红外光谱与化学计量学的绿茶快速无损鉴别方法" "Nondestructive Identification of Green Tea Based on Near Infrared Spectroscopy" LINK

"纺织品近红外光谱定性分析的一种新方法" "A New Method for Qualitative Analysis of Near Infrared Spectra of Textiles" LINK

"NIR-based Sudan I to IV and Para-Red food adulterants screening" LINK

"Evaluation of sensory and texture profile analysis properties of stored Khalal Barhi dates nondestructively using Vis/NIR spectroscopy" LINK

"Safety and quality issues in summer squashes using handheld portable NIRS sensors for real-time decision making and on-vine monitoring" LINK

"Age grading An. gambiae and An. arabiensis using near infrared spectra and artificial neural networks." mosquitoes LINK

"Identification of turkey meat and processed products using near infrared spectroscopy" LINK

"Development and Testing of a Portable Soil Nitrogen Detector Based on Near-infrared Spectroscopy" LINK

Raman

" “Resonance” Raman spectroscopy with 1-nm resolution" LINK

Equipment

"Single-nanowire spectrometers" nanowire nanotechnology LINK

"Scientists Develop Smallest Spectrometer Ever, And The Applications Are Incredible" LINK

Agriculture

"Rapid Estimation of Wheat Straw Decomposition Constituents Using Near-Infrared Spectroscopy" Agronomy LINK

"Evaluating different approaches to non-destructive nitrogen status diagnosis of rice using portable RapidSCAN active canopy sensor." LINK

Medicinal

"Effect of Reduced Point NIR Spectroscopy on Glucose Prediction Error in Human Blood Tissue" LINK

CalibrationModel.com

Chemometrics

Near Infrared

Raman

" “Resonance” Raman spectroscopy with 1-nm resolution" LINK

Equipment

"Single-nanowire spectrometers" nanowire nanotechnology LINK

"Scientists Develop Smallest Spectrometer Ever, And The Applications Are Incredible" LINK

Agriculture

Medicinal

"Effect of Reduced Point NIR Spectroscopy on Glucose Prediction Error in Human Blood Tissue" LINK

CalibrationModel.com

Chemometrics

Near Infrared

Raman

" “Resonance” Raman spectroscopy with 1-nm resolution" LINK

Equipment

"Single-nanowire spectrometers" nanowire nanotechnology LINK

"Scientists Develop Smallest Spectrometer Ever, And The Applications Are Incredible" LINK

Agriculture

Medicinal

"Effect of Reduced Point NIR Spectroscopy on Glucose Prediction Error in Human Blood Tissue" LINK

NIR-Predictor – Manual

NIR-Predictor – Manual
Predicting Spectra
Creating your own Calibrations
Configure the Calibrations for prediction usage
Applications
- The use-all case
Prediction Result Report
Enter lab values to NIR spectra
- Entering the laboratory reference values for NIR calibrations
- Create Properties File
Create Calibration Request
- When all is fine
Program Settings
Further References

NIR-Predictor – Manual

Predicting Spectra

It’s easy to use with NIR-Predictor,
just drag & drop your data for getting the prediction results.

It supports an automatic file format detection.
So you don’t need to specify the instrument type and settings! See the list of supported formats and NIR Vendors: NIR-Predictor supported Spectral Data File Formats

Use the included data to checkout how it feels:

Open the demo Spectra folder by using the Menu > Open Demo Spectra or press F8.
There are files with spectra from different Vendors.
Drag & drop a spectra file onto the NIR-Predictor window (or press Ctrl+O as for ’Open some files).
The spectra will be
- loaded
- pre-processed
- predicted and
- reported

Note:
All the steps are fully automatic.
All calibrations that are compatible with the spectra, will produce prediction results in one go.
To select specific calibrations choose the Application. Where the ” ” empty means use all the calibrations.
To define a Application read more in chapter “Applications”

Hint:
To get access to Statistics of Predictions and Reports use the Menu > Show more/less (Ctrl+M) or you can simply resize the window. Here you can also re-do the Analyze step manually with changed inputs (e.g. Result Ordering).

Creating your own Calibrations

How it works – step by step

You have measured your samples with you NIR-Instrument Software.
And got the Lab-values of these samples.

samples
-> measured NIR-spectra
-> Lab-references analytics
Now you need to combine these data.
NIR-spectra + Lab-references
-> PropertiesBySamples

Note: If you combined these data already in your NIR software used,
and you can export it as a JCAMP-DX file then use
Menu > Create Request File .req ... (F2)
and read the “Help.html” and NIR-Predictor JCAMP.
Else proceed as below.

The NIR-Predictor provides tooling for that:

Menu > Create Properties File... (F6)

Select the folder with your NIR spectra measured for an application.
NIR-Predictor creates a customized Properties file template for that data to enter the Lab values.

Note: You don’t need to specify your instrument or vendor or an application. It’s all done automatically. And also the sample spectra are detected and grouped automatically!
Use your favorite editor or spreadsheet program to enter and copy&paste
the Lab-references Values into the columns “Prop1”, “Prop2” etc. and save the file.
A final check of your entered data is done by NIR-Predictor,
to make sure your data ist complete and all is fine.

Menu > Create Calibration Request... (F7)

Select the folder with the filled file.
A CalibrationRequest.zip is created with the necessary data
if enougth diverse Lab values are entered.
Email the CalibrationRequest.zip file
to info@CalibrationModel.com to develop the calibrations.
When your calibrations are ready, you will receive an email with a link
to the CalibrationModel WebShop where
you can purchase and download the calibration files,
that work with our free NIR-Predictor software without internet access.

Note: Your sent NIR data is deleted after processing.
We do not collect your NIR data!

Note: Further details can be found under “Create Properties File” and “Create Calibration Request”.

Configure the Calibrations for prediction usage

Configuration:

in NIR-Predictor : Menu > Open Calibrations (F9)
an explorer window is opened where the calibrations are located
create a folder for your application, choose a name
copy the calibration file(s) (*.cm) into that folder
in NIR-Predictor : Menu > Search and load Applications (F4)

Usage:

in NIR-Predictor : open the Application drop down list, and select your application by name
if all is fine, the calibration file is valid and not expired, it shows : Calibration “1 valid calibation”
the NIR-Predictor is now ready to predict
to switch the application, goto 6.

Applications

The Application concept allows to group multiple Calibrations together for an Application. By selecting an Application before prediction, only the Calibrations belonging to the Application will be used for Prediction. In the Demo Data this is used to have multiple spectrometer as Application. This can be used easily as e.g. as Application “Meat Products” containing Fat and Moisture Calibration.

To create an Application, create a folder with the Application’s name inside the Calibrations folder, and move/copy all the Calibrations files to this Application folder. To remove a Calibration from the Application, remove the Calibration file from the Application folder.

After creating an new Application folder, press menu Search and load Applications (F4) to update the NIR-Predictor dialog where the Application can be selected via the dropdown list. You don’t need to close the NIR-Predictor.

After moving Calibration files around, press menu Search and load Calibrations (F5) to update the NIR-Predictor dialog.

The use-all case

In the NIR-Predictor dialog where the Application can be selected via the dropdown list, the empty "" name means that all (yes all) valid Calibrations will be used for prediction.

Note: The Prediction Report will contain only results from spectral compatible Calibrations with the given spectra. That allows to automatically handle the multi vendor NIR instrument usage.

Prediction Result Report

Histograms of Prediction Values per Property

Shows the distribution of the predicted results per calibration. The histogram range contains the range of the calibrated property and includes the predicted results.

The histogram bar (bin) color is defined as follow:

blue : all predictions inside calibration range.
red : all predictions outside calibration range.
orange : some overlaps with calibration range.
So not all spectra in a orange bin are outside calibration range.

Histograms of Prediction Values — Histograms

Note: Predicted values are always shown in Histogram table and Prediction Value List table, even if the spectrum does not fit into model (spectrum different to model, aka Residual Outlier) shown as Out = X.

Note: Old browsers like Microsoft Internet Explorer 11 don’t support the grafics for Histogram charts. Use an current browser like Firefox or Chrome or Edge.

Note: If your browser opens the report too slow, try to deactivate some browser plugins, because they can filter what you look at and some add-ons are really slow.

Spectra Plot Thumbnail on the Prediction Report

Visualizes the min,median,max spectrum of the spectra dropped as files on the NIR-Predictor. This gives a minimal and good spectral overview of the predicted property results.

Spectra Plot color legend: min,median,max spectrum by predicted property or if no calibration is available by spectral intensity.
The min,median,max is determined from the predicted properties or if not available from the intensity of the spectra.
Beside the histogram of the predicted properties, where the distribution can be seen, the spectra shown are the ones from min,median,max predicted property.
This gives a minimal and good spectral overview of the predicted property results.
The “Spectral Range” and number of datapoints is shown in the Prediction Report Header below the listed spectra files.
To zoom the spectra plot a little, zoom the report in the browser (hold ctrl + mouse wheel, or pinch on touch screen).
The spectra plots and histograms are stored with the report and can be archived.

Note

Note that the spectra are shown in the raw values that are loaded, they are not shown pre-processed as the calibration model uses them to make the prediction.
Note that the median property spectrum is the median from the predicted property pobulation and not the “median” of the calibration property range.
Note that in the multi calibration prediction case, the spectra are selected for each property based on the related predicted property values and so the spectra plots shows typical different spectra.

Plot of predicted Spectra — Spectra Plot

Outlier Detection

To safeguard the prediction results, outliers are automatically checked for each individual prediction. This is based on limits that are determined when creating the calibration with the base data. Thus, a strange spectral measurement can be detected and signaled as an outlier even without base data only by means of the calibration and the NIR predictor. A prediction result with outlier warning is to be distrusted. How the various outlier tests are interpreted and how to avoid them in practice is described here.

The spectrum is an outlier to the model, if the spectrum is not similar with the spectra and lab-values the model is built with.

This legend is shown on each NIR-Predictor prediction report below the results:

Outlier (Out) Symbol Description

“X” : spectrum does not fit into model (spectrum different to model)
“O” : spectrum is wide outside model center (spectrum similar to model but far away)
“=” : prediction is outside upper or lower range of model (property outside model range)
“-” : spectrum is incompatible to calibration

Note: A prediction result with outlier warning is to be distrusted.

There are 3 outlier cases (X, O, =) and the incompatible data case “-”.

The bad case is “X”
the medium case is “O”
and the soft case is “=”.

The technical names in literature correspond to:

“X” : Spectral Residual Outlier
“O” : Leverage Outlier
“=” : Property Range Outlier

These 3 outlier cases can appear in combinations, like “XO=” or “XO” or “O=” or “X=”. The more outlier marker are shown the more likely the spectrum is an Outlier.

The default setting in NIR-Predictor Menu > “Report with Simplified Outlier Symbols”

is ON, that will show only the worst case instead of all combinations to have a simplified minimal information.
if OFF, that will show the combinations (e.g. “XO=” or “XO” or “O=” or “X=”), which is more informative for analyzing problem cases.

Some hints to avoid these Outliers:

“X” : spectrum does not fit into model (spectrum different to model)
Check if the spectrum is noise only, or has no proper signal. That can happen when measured past the sample or measured into the air or at a different substance. If you have multiple NIR instruments of the same type, use spectra measured with different instruments for the calibration.
“O” : spectrum is wide outside model center (spectrum similar to model but far away) Sample temperature has an effect on NIR spectra shape, use spectra measured at different (typical use) temperatures (sample temperature, instrument temperature).
“=” : prediction is outside upper or lower range of model (property outside model range)
Use more spectra for the calibration in the Lab value region where your special interest is. If the predicted value is only a little bit out of the calibration range, it can be Ok. Add these spectra to the calibration spectra (with the Lab values), to extend the prediction range of the calibration.
“-” : spectrum is incompatible to calibration
The spectra (from the NIR instrument) has a different wavelength range or a different resolution than the spectra used for calibration. Check Instrument settings (wavelength range, resolution)

Result Ordering

To change the ordering, a drop-down-box is located below the Analyze button. If there is an analysis from the current session, and the Result Ordering is changed, the data is re-Analyzed and reported with the new Result Ordering setting. That allows to compare the different orderings. The Result Ordering is listed in the Prediction Report above the Prediction Value List and stored in the settings.

The order/sorting of the prediction results of the spectra can be defined:

GivenOrder (default) the given order of the spectra from file select dialog or drag&drop

*) sorted : ascending sort

Date_Name sorted by Date (if any) and then by Name
Name_Date sorted by Name and then by Date
Date_NamesWithNumbers sorted by Date (if any) and then by Name with number logic
NamesWithNumbers_Date sorted by Name with number logic (e.g. “ABC1” is before “ABC002” ) and then by Date

*) as above but sorted Rev : reverse sort = descending sort

Rev_Date_Name
Rev_Name_Date
Rev_Date_NamesWithNumbers
Rev_NamesWithNumbers_Date

E.g. with reverse sort by Rev_Date_Name, the newest spectra appear on top.

Print to PDF

Depending on how many calibrations are used the result table is getting broader. To print the report (e.g. to Adobe PDF, FreePDF or Microsoft XPS), sometimes the landscape format is shorter in number of pages or in portrait a scale of 80% fits nicely. Or try another internet browser (Mozilla Firefox, Google Chrome, Microsoft Edge, …) to print the report and set the browser as your default browser so it will be opened by default.

Archiving Reports

Each report is contained in one file only, including the grafics. To save storage space the report file folder can be compressed to a zip file (.zip, .7z).

Enter lab values to NIR spectra

Entering the laboratory reference values for NIR calibrations

We have developed specialized tools into NIR-Predictor to combine the NIR and Lab data is a sample-based safe manner.

The main target is to improve Data Quality during the step of combining of the Lab data and the NIR data, because to model a good reliable calibration the data that build the base needs to be of high quality.

It also simplifies to enter the lab values manually to the corresponding NIR data, because of automatically grouping repeated NIR measurements of the same sample, so the lab values can be entered sample based and not by spectrum.

It helps to avoid false reference data, because of the broken relation of NIR spectra and reference values, data entry on the wrong position in the table.

And Helps to detect errors of duplicated or multiple copies of spectra files, and checks for inconsistencies in Date-Time and Sample-Naming. It also checks for missing values.

That all increases the Data Quality for the next step of Calibration Development, and makes data entry a less time consuming and less risky work.

How it works

Menu > Create Properties File... (F6) select the folder with your NIR spectra measured for an application. NIR-Predictor creates a Properties file template for that data : PropertiesBySamples.csv.txt
Use your favorite editor or spreadsheet program to enter and copy&paste the Lab Values into the columns and save the file.
Menu > Create Calibration Request... (F7) select the folder with the filled file for a last check and a Calibration Request file is created with the needed data as a single zip file.
Email the Calibration Request file to info@CalibrationModel.com to develop the calibrations.

Ok that is it, the NIR-Predictor guides you through the steps needed. And if you need to know more details, the Chapter “Create Properties File” is for you.

Create Properties File

Note:

If you have (exported) JCAMP-DX files containing the Lab-Values, you don’t need to do this step.
You can send the JCAMP file with your Request (.req) file directly to the calibration service at info@CalibrationModel.com.
If your JCAMP-DX files does NOT contain Lab-Values, this is a way to go.

For calibrating the spectra to the lab-values you need to assign the lab-values to the spectra. The easiest way is to have a table where each spectrum (row) is linked to multiple lab-values (columns). This function Create Properties File build such a table for the selected spectra folder automatically!

This table is stored in the file PropertiesBySamples.csv.txt. This can be created for any spectra folder you like. The file extension is .csv.txt to make it easy to edit in a text editor and also in a spreadsheet (excel). The columns are standard TAB separated.

The file header line contains :

Sample Replicates Names Prop1 Prop2 Prop3 DateFirst DateLast Hashes

Where Name and Date describes the spectrum.

Prop1, Prop2, Prop3 are the place to enter the Lab Reference Concentrations properties corresponding to each spectrum. It can be extended to Prop4, Prop5, … etc. Of course you can enter real word names like “Fat (%)” instead of “Prop1”. It’s recommended to put the measurement unit beside the name.

Replicates is the number of replicated or repeated spectra of a sample that is grouped together in the Sample based property file. Sample name and the DateFirst / DateLast between the sample spectra are measured.

Date format is ISO-8601. Missing Dates are 0002-02-02T00:00:00.0000000.

If the file PropertiesBySamples.csv.txt already exist in the selected folder, the user will be notified (it will not be overwritten, because the file may contain user entered Lab-values). The Lab Reference Concentrations values are initialized to 0 (zero) and needed to be changed.

Note: 0 is not interpreted as missing value! If you have a 0 concentration value, put in 0 or 0.0 .

The entry of properties is as easy as possible, because it’s organized by Sample (and not by Spectra), so it’s like your Lab-Value Table that is sample based. The sample rows are sorted in a special way by Sample name. Sorting by Date or alphabetically by Sample can done easily in a spreadsheet program.

Note: when coping lab values to the samples make sure they correspond, so that there are no gaps and the sorting is the same.

The Spectra (rows) are initially sorted by name (and date) to have the replicates/repeats together. You can sort for your convenience in a spreadsheet program.

Enter the Lab Reference Concentrations to the spectra/sample.

Enter the Lab-Values in spreadsheet (e.g. Excel) or a text editor (e.g. Notepad++). If done, use the next menu Create Calibration Request.

Hints: Data handling:

The NIR-Predictor creates the PropertiesBySamples.csv.txt once, after that the user is responsible for its content. That means NIR-Predictor does not change this file anymore.
You can remove entire rows (spectra) in the property file. You don’t need to remove the spectra files. The NIR-Predictor is aware of the relation, the PropertiesBySamples.csv.txt defines what will be calibrated.
How to add more spectra files?
The additional spectra can be handled in a separate folder, create the property file and copy the spectra to the other folder and copy/merge the property files together in your editor or spreadsheet.

Or

Copy the spectra into the folder, rename the PropertiesBySamples.csv.txt to e.g. “PropertiesBySamples-Part1.csv.txt” and use Create Properties File to create a new PropertiesBySamples.csv.txt with all the spectra. You can copy/merge the content of the Properties files together in your editor or spreadsheet.
What happens with possible duplicate rows? It does no harm to the Calibration because we do an exact checking and data cleaning in the calibration process.
What happens to duplicate spectra names? The spectra names are not relevant for the calibration process. The spectra names are helpful to assign the lab-values to the corresponding spectrum entry. That’s why the table is initially sorted by name. The spectra names can be edited by the user.

Create Calibration Request

The menu function Create Calibration Request packs a created Properties file (see “Create Properties File”) and it’s linked spectra files in a compressed ZIP file for sending to the CalibrationModel.com Service.

Please note that the number of measured quantitative samples need to be at least 60 . That means you need at least 60 different spectra (not counting the replicate/repeated measurements).

It shows additional property information about the data you have entered, like – the property type (Quantitative) – it’s range (min – max) and – the number of unique values and – if the Lab-values are enough diverse to get calibrated.

First select the folder with the PropertiesBySamples.csv.txt and measured spectra files of samples you have Lab-values. The data is checked and you get notified what is missing or might be wrong. If something needs to be changed, edit the PropertiesBySamples.csv.txt and do Create Calibration Request again. Your last selected folder is remembered, so you can press return in the folder selection dialog.

Hint: The keyboard shortcuts for redoing it after you edited some entries is : F7 Return – that allows you to get the property information quickly.

Hint: If you open the PropertiesBySamples.csv.txt in a spreadsheet program, you can create Histogram plots of the entered Lab-values, to see in which range are to less samples measurements.

When all is fine

When all is fine the “CalibrationRequest.zip” file is created for that data.

The ZIP file contains:

your PropertiesBySamples.csv.txt
your personal REQuest file for your computer system, that looks like
e.g. “337dcdc06b2d6dfb0b5c4bba578642312edf2ae84d909281624d7e26283e8b07 WIN-GB0PB48GSK4.req”
the spectra data files

Note: If the CalibrationRequest.zip file is already created and you change the PropertiesBySamples.csv.txt make sure to delete the old CalibrationRequest.zip file first! In the dialog it states if it was successfully created or NOT because it already exist. So you are always on the safe side.

Note: CalibrationRequest.zip file name contains the property names to know what would be calibrated and at the end an identification number for referencing the file. E.g. “CalibrationRequest ‘Prop1’ – ‘Prop2’ h31T3wOH.zip”

Program Settings

The users program settings are stored in UserSettings.json
The program counters are stored in GlobalCounters.json

Further References

Data File Formats : NIR-Predictor supported Spectral Data File Formats
Release Notes : NIR-Predictor – Release Notes History
Frequently Asked Questions: NIR-Predictor – FAQ