Spectroscopy and Chemometrics/Machine-Learning News Weekly #10, 2022

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 9, 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 9, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 9, 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)

“Near-infrared solar reflectance and chromaticity properties of novel green ceramic pigment Cr-doped Y3Al5O12” LINK

“Near-Infrared Spectroscopy (NIRS) as a Method for Biological Sex Discrimination in the Endangered Houston Toad (Anaxyrus houstonensis)” LINK

“Kernel Flow: a high channel count scalable time-domain functional near-infrared spectroscopy system” LINK

“Model Development of Non-Destructive Coffee Beans Moisture Content Determination Using Modified Near Infrared Spectroscopy Instrument” LINK

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

“Adaptively Optimized Gas Analysis Model with Deep Learning for Near-Infrared Methane Sensors” LINK

“Development of non-invasive blood glucose regression based on near-infrared spectroscopy combined with a deep learning method” LINK

“Assessing the Spectral Characteristics of Dye-and Pigment-Based Inkjet Prints by VNIR Hyperspectral Imaging” LINK

“Fusion of a Low-cost Electronic Nose and Near Infrared Spectroscopy for Qualitative and Quantitative Detection of Beef Adulterated with Duck” LINK

“NEAR INFRARED SPECTROSCOPY (NIRS) COUPLED WITH CHEMOMETRIC TOOLS USED FOR FOOD PRODUCTS ADULTERATION DETECTION” LINK

” A Nondestructive Identification Method of Producing Regions of Citrus Based on Near Infrared Spectroscopy” LINK

“Detecting the content of the bright blue pigment in cream based on deep learning and near-infrared spectroscopy” LINK

“A NIR Study on Hydrogen Bonds of Bamboo-Based Cellulose Ⅱ” LINK

“Vis-NIR Spectra Discriminant of Pesticide Residues on the Hami Melon Surface by GADF and Multi-Scale CNN” LINK

“Pedometric tools for classification of southwestern Amazonian soils: A quali-quantitative interpretation incorporating visible-near infrared spectroscopy” LINK

“… Frozen-Thawed Tuna with Non-Destructive Methods and Classification Models: Bioelectrical Impedance Analysis (BIA), Near-Infrared Spectroscopy (NIR) and Time …” LINK

“NIRS and Aquaphotomics Trace Robusta-to-Arabica Ratio in Liquid Coffee Blends” LINK

“Effect of Soil Particle Size on Prediction of Soil Total Nitrogen Using Discrete Wavelength NIR Spectral Data” LINK

“Research on Construction of Visible-Near Infrared Spectroscopy Analysis Model for Soluble Solid Content in Different Colors of Jujube” LINK

“A Nondestructive Identification Method of Producing Regions of Citrus Based on Near Infrared Spectroscopy” LINK




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

“Accessing High-Power Near-Infrared Spectroscopy Using Cr3+-Substituted Metal Phosphate Phosphors” LINK

“Can Grassland Chemical Quality Be Quantified Using Transform Near-Infrared Spectroscopy?” LINK

“System Design and Preliminary Analysis of the UQ Near Infrared Spectroscopy Data of the Hayabusa2 Re-entry” LINK

“A fast method to measure the degree of oxidation of dialdehyde celluloses using multivariate calibration and infrared spectroscopy” LINK

” In-Line Identification of Different Grades of GPPS Based on Near-Infrared Spectroscopy” LINK

“Eu2+Doped Layered Double Borate Phosphor with Ultrawide NearInfrared Spectral Distribution in Response to UltravioletBlue Light Excitation” LINK

“Near-Infrared Spectroscopy Applied to the Detection of Multiple Adulterants in Roasted and Ground Arabica Coffee” LINK




Raman Spectroscopy

“RAMANMETRIX: a delightful way to analyze Raman spectra. (arXiv:2201.07586v1 [physics.data-an])” LINK




Hyperspectral Imaging (HSI)

“Rapid and nondestructive determination of sorghum purity combined with deep forest and near-infrared hyperspectral imaging” LINK

“Intraoperative hyperspectral imaging (HSI) as a new diagnostic tool for the detection of cartilage degeneration” | LINK

“Application of Visible/Near-Infrared Hyperspectral Imaging with Convolutional Neural Networks to Phenotype Aboveground Parts to Detect Cabbage Plasmodiophora …” LINK

“Detection of nutshells in cumin powder using NIR Hyperspectral Imaging and chemometrics tools” LINK

“Gastric Cancer Detection by Two-step Learning in Near-Infrared Hyperspectral Imaging” LINK

“A Spectral and Spatial Attention Network for Change Detection in Hyperspectral Images” LINK




Chemometrics and Machine Learning

“Analysis and classification of peanuts with fungal diseases based on real-time spectral processing” LINK

“Chemometrics: An Excavator in Temperature-Dependent Near-Infrared Spectroscopy” LINK

“PLS-R Calibration Models for Wine Spirit Volatile Phenols Prediction by Near-Infrared Spectroscopy” LINK

“Development and assessment of spectroscopy methodologies and chemometrics strategies to detect pharmaceuticals blend endpoint in a pharmaceutical …” LINK

“Quick Measurement Method of Condensation Point of Diesel Based on Temperature-Compensation Model” LINK

“Prediction Model of TVB-N Concentration in Mutton Based on Near Infrared Characteristic Spectra” LINK

“Evaluation of a robust regression method (RoBoost-PLSR) to predict biochemical variables for agronomic applications: Case study of grape berry maturity monitoring” LINK




Facts

“Nondestructive internal quality evaluation of pears using X-ray imaging and Machine Learning” LINK




Research on Spectroscopy

“Mechanical-based and Optical-based Methods for Nondestructive Evaluation of Fruit Firmness” | LINK




Equipment for Spectroscopy

“Application of a portable near-infrared spectrometer for rapid, non-destructive evaluation of moisture content in Para rubber timber” | LINK

“The Feasibility of Two Handheld Spectrometers for Meat Speciation Combined with Chemometric Methods and Its Application for Halal Certification” LINK

“Rapid identification of the storage age of dried tangerine peel using a hand-held near infrared spectrometer and machine learning” LINK

“pType NearInfrared Transparent Delafossite Thin Films with Ultrahigh Conductivity” LINK




Agriculture NIR-Spectroscopy Usage

“Agricultural practices of perennial energy crops affect nitrogen cycling microbial communities” LINK

“The Simultaneous Prediction of Soil Properties and Vegetation Coverage from Vis-NIR Hyperspectral Data with a One-Dimensional Convolutional Neural Network: A …” LINK

“Alginate-enabled green synthesis of S/Ag1. 93S nanoparticles, their photothermal property and in-vitro assessment of their anti-skin-cancer effects augmented by a …” LINK

“The Relative Performance of a Benchtop Scanning Monochromator and Handheld Fourier Transform Near-Infrared Reflectance Spectrometer in Predicting Forage …” LINK

“Compact meta-spectral image sensor for mobile applications” | LINK

“Detection of insect damaged rice grains using visible and near infrared hyperspectral imaging technique” LINK

“Terrain analysis, erosion simulations, and sediment fingerprinting: a case study assessing the erosion sensitivity of agricultural catchments in the border of the …” | LINK

” THE QUALITY OF FRESH AND ENSILED BIOMASS OF Brassica napus oleifera AND PROSPECTS OF ITS USE” LINK




Horticulture NIR-Spectroscopy Applications

“Interactions of Linearly Polarized and Unpolarized Light on Kiwifruit Using Aquaphotomics” LINK




Beverage and Drink Industry NIR Usage

“Beyond Beers Law: Quasi-Ideal Binary Liquid Mixtures” LINK




Other

” From Polymorph Screening to Dissolution Testing” LINK

“Charge and Spin Delocalization in Mixed-Valent Vinylruthenium-Triarylamine-Conjugates with Planarized Triarylamines” LINK

“РАЗРАБОТКА МЕТОДИКИ ВЫЯВЛЕНИЯ ФАЛЬСИФИКАЦИИ ЛЬНЯНОГО МАСЛА МЕТОДОМ БИК-СПЕКТРОСКОПИИ С ПРИМЕНЕНИЕМ …” LINK

“Bioelectrochemical Partial-Denitrification Coupled with Anammox for Autotrophic Nitrogen Removal” LINK

“Broadband Optical Phase Modulation by Colloidal CdSe Quantum Wells” LINK





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Spectroscopy and Chemometrics/Machine-Learning News Weekly #9, 2022

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 8, 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 8, 2022 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 8, 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)

“Research of Parameter Optimization of Preprocessing and Feature Extraction for NIRS Qualitative Analysis Based on PSO Method” LINK

“Fusion of a low-cost electronic nose and Fourier transform near-infrared spectroscopy for qualitative and quantitative detection of beef adulterated with duck.” LINK

“Assessment oil composition and species discrimination of Brassicas seeds based on hyperspectral imaging and portable near infrared (NIR) spectroscopy tools and …” LINK

“Prediksi Kualitas Buah Jambu Biji “Kristal” Secara NonDestruktif Menggunakan Portable Near Infrared Spectrometer (Nirs)” LINK

“Quantitative Analysis of Blend Uniformity within a Three-Chamber Feed Frame using Simultaneously Raman and Near-Infrared Spectroscopy” LINK

“Rapid Identification of Peucedanum Praeruptorum Dunn and its Adulterants by Hand-Held near-Infrared Spectroscopy” | LINK

“Methods of Detecting Multiple Chemical Substances Based on Near-Infrared Colloidal Quantum Dot Array and Spectral Reconstruction Algorithm” LINK

“Near-Infrared Spectroscopy Detection of Cotton/Polyester Content Based on Dropout Deep Belief Network” LINK

“Determining Pasture Biodiversity with NIRS” LINK

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

“NIR Calibration Transfer Method Based on Minimizing Mean Distribution Discrepancy” LINK

“Near infrared spectroscopy reveals instability in retinal mitochondrial metabolism and haemodynamics with blue light exposure at environmental levels” LINK

“Study on Characteristic Wavelength Extraction Method for Near Infrared Spectroscopy Identification Based on Genetic Algorithm” LINK

“Discrimination of Transgenic Canola (Brassica napus L.) and their Hybrids with B. rapa using Vis-NIR Spectroscopy and Machine Learning Methods” LINK

“Recent Advances in Application of Near-Infrared Spectroscopy for Quality Detections of Grapes and Grape Products” LINK

“Detection of calcium chloride salts in rubber cublum using Near-Infrared Spectroscopy Technique” LINK

“PLS-DA and Vis-NIR spectroscopy based discrimination of abdominal tissues of female rabbits” LINK

“Sparse Reconstruction using Block Sparse Bayesian Learning with Fast Marginalized Likelihood Maximization for Near-Infrared Spectroscopy” LINK

“Study on Online Detection Method of “Yali” Pear Black Heart Disease Based on Vis-Near Infrared Spectroscopy and AdaBoost Integrated Model” LINK

“Detection of Umami Substances and Umami Intensity Based on Near-Infrared Spectroscopy” LINK

“Farklı ana materyal üzerinde oluşmuş toprakların adli bilim için VNIRS tekniği ile spektral karakterizasyonu ve özelliklerinin tahmin edilmesi” LINK

“Prediction of soil hydraulic properties using VIS-NIR spectral data in semi-arid region of Northern Karnataka Plateau” LINK

“Rapid Assessment of Fresh Beef Spoilage Using Portable Near-Infrared Spectroscopy” LINK

“The Relationship Between Genetic Variations and NIRs Differences of Eucalyptus Pellita Provenances” LINK

“Geographical Origin Discrimination of Taiping Houkui Tea Using Convolutional Neural Network and Near-Infrared Spectroscopy” LINK

“Assessment of soil quality using VIS-NIR spectra in invaded coastal wetlands” | LINK

“Relationship Between Visible/Near Infrared Spectral Data and Fertilization Information at Different Positions of Hatching Eggs” LINK




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

“Near Infrared Spectral Wavelength Selection Based on Improved Team Progress Algorithm” LINK

“Coupling ATR-FTIR Spectroscopy and Chemometric Analysis for Rapid and Non-Destructive Ink Discrimination of Forensic Documents” LINK

“Model-based mid-infrared spectroscopy for on-line monitoring of volatile fatty acids in the anaerobic digester” LINK

“Depthdependent hydration dynamics in human skin: Vehiclecontrolled efficacy assessment of a functional 10% urea plus NMF moisturizer by nearinfrared confocal spectroscopic imaging (KOSIM IR) and capacitance method complemented by volunteer perception” LINK

“Detection of Umami Substances and Umami Intensity Based on Near-Infrared Spectroscopy” LINK

“Early Detection of Cauliflower Gray Mold Based on Near-Infrared Spectrum Feature Extraction” LINK




Hyperspectral Imaging (HSI)

“Hyperspectral imaging for non-destructive detection of honey adulteration” LINK

“Study on the Spectral Characteristics of Ground Objects in Land-Based Hyperspectral Imaging” LINK

“Combine Hyperspectral Imaging and Machine Learning to Identify the Age of Cotton Seeds” LINK

“Nondestructive detection of total soluble solids in grapes using VMD‐RC and hyperspectral imaging” LINK

“Nondestructive Detection of Codling Moth Infestation in Apples Using Pixel-Based NIR Hyperspectral Imaging with Machine Learning and Feature Selection” LINK

“Research on Rich Borer Detection Methods Based on Hyperspectral Imaging Technology” LINK




Chemometrics and Machine Learning

“A Data Fusion Model to Merge the Spectra Data of Intact and Powdered Cayenne Pepper for the Fast Inspection of Antioxidant Properties” LINK

“Rapid Determination of β-Glucan Content of Hulled and Naked Oats Using near Infrared Spectroscopy Combined with Chemometrics” LINK

“Prediction Model of TVB-N Concentration in Mutton Based on Near Infrared Characteristic Spectra” LINK

“Optimization of Fruit Pose and Modeling Method for Online Spectral Detection of Apple Moldy Core” LINK




Research on Spectroscopy

“Local Preserving Projection Similarity Measure Method Based on Kernel Mapping and Rank-Order Distance” LINK

“A Method for Detecting Sucrose in Living Sugarcane With Visible-NIR Transmittance Spectroscopy” LINK




Process Control and NIR Sensors

“Cognitive and linguistic dysfunction after thalamic stroke and recovery process: possible mechanism” LINK




Environment NIR-Spectroscopy Application

“Empower Innovations in Routine Soil Testing” LINK




Agriculture NIR-Spectroscopy Usage

“Preharvest phenotypic prediction of grain quality and yield of durum wheat using multispectral imaging” LINK

“Cove-Edged Graphene Nanoribbons with Incorporation of Periodic Zigzag-Edge Segments” LINK

“Utilizing near infra-red spectroscopy to identify physiologic variations during digital retinal imaging in preterm infants” | LINK




Forestry and Wood Industry NIR Usage

“Spectrometric prediction of nitrogen content in different tissue types of trees 2” LINK

“Spectrometric Prediction of Nitrogen Content in Different Tissues of Slash Pine Trees” LINK




Food & Feed Industry NIR Usage

“Optical techniques in non-destructive detection of wheat quality: A review” LINK




Chemical Industry NIR Usage

“Quantifying Polaron Mole Fractions and Interpreting Spectral Changes in Molecularly Doped Conjugated Polymers” LINK




Pharma Industry NIR Usage

“Quantitative Changes in Muscular and Capillary Oxygen Desaturation Measured by Optical Sensors during Continuous Positive Airway Pressure Titration for …” LINK




Medicinal Spectroscopy

“406: PERIOPERATIVE NONINVASIVE NEUROMONITORING IN INFANTS WITH CONGENITAL HEART DISEASE” LINK




Laboratory and NIR-Spectroscopy

“Available on line at Directory of Open Access Journals” LINK




Other

“A Spectroscopic Study of Dysprosium-Doped TlPb2Br5 for Development of Novel Mid-IR Gain Media” LINK

“No differences in splenic emptying during on-transient supine cycling between aerobically trained and untrained participants” | LINK

“Influence of Substrate Temperature on Structural and Optical Properties of Co-Evaporated Cu2SnS3/ITO Thin Films” LINK

“Synthesis and characterization of new multinary selenides Sn4In5Sb9Se25 and Sn6. 13Pb1. 87In5. 00Sb10. 12Bi2. 88Se35” LINK





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Spectroscopy and Chemometrics/Machine-Learning News Weekly #8, 2022

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 7, 2022 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality 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)

“Nirs Technology (Near Infrared Reflectance Spectroscopy) for Detecting Soil Fertility Case Study in Aceh Province” LINK

“Fourier transform and near infrared dataset of dialdehyde celluloses used to determine the degree of oxidation with chemometric analysis” LINK

“NIRS and Aquaphotomics Trace Robusta-to-Arabica Ratio in Liquid Coffee Blends” LINK

“Development of a generic NIRS calibration pipeline using deep learning and model ensembling: application to some reference datasets” LINK

“Foods : Rapid Differentiation of Unfrozen and Frozen-Thawed Tuna with Non-Destructive Methods and Classification Models: Bioelectrical Impedance Analysis (BIA), Near-Infrared Spectroscopy (NIR) and Time Domain Reflectometry (TDR)” LINK

“Rapid and accurate determination of prohibited components in pesticides based on near infrared spectroscopy” LINK

“NIR spectroscopic methods for monitoring blend potency in a feed frame – calibration transfer between offline and inline using a continuum regression filter” LINK

“A FT-NIR Process Analytical Technology Approach for Milk Renneting Control” LINK

“Construction and Verification of a Mathematical Model for Near-Infrared Spectroscopy Analysis of Gel Consistency in Southern Indica Rice” LINK

“Research on Construction of Visible-Near Infrared Spectroscopy Analysis Model for Soluble Solid Content in Different Colors of Jujube” LINK

“Quantitative Detection of Agaricus Bisporus Freshness Based on VIS-NIR Spectroscopy” LINK

“Foods : Rapid Determination of β-Glucan Content of Hulled and Naked Oats Using near Infrared Spectroscopy Combined with Chemometrics” LINK

“A ready-to-use portable VIS-NIR spectroscopy device to assess superior EVOO quality” | LINK

“Challenges, Opportunities and Recent Advances in Near Infrared Spectroscopy Applications for Monitoring Blend Uniformity in the Continuous Manufacturing of Solid …” LINK

“The use of near-infrared reflectance spectroscopy (NIRS) to predict dairy fibre feeds in vitro digestibility” LINK

“Near-Infrared Reflectance Spectroscopy (NIRS) detection to differentiate morning and afternoon milk based on nutrient contents and fatty acid profiles” LINK

“Application of Various Algorithms for Spectral Variable Selection in NIRS Modeling of Red Ginseng Extraction” LINK

“Near infrared spectroscopy to predict plaque progression in plaque-free artery regions” LINK

“The evolution of chemometrics coupled with near infrared spectroscopy for fruit quality evaluation” LINK

“Quantitative Detection of Agaricus Bisporus Freshness Based on VIS-NIR Spectroscopy” LINK

“Application of SG-MSC-MC-UVE-PLS Algorithm in Whole Blood Hemoglobin Concentration Detection Based on Near Infrared Spectroscopy” LINK

“Near infrared reflectance spectroscopy as a tool to predict non-starch polysaccharide composition and starch digestibility profiles in common monogastric …” LINK

“Development of SOP for NIRS spectral measurement on fresh grounded yam tubers and cassava roots” LINK

“Development of calibration models within a closed feed frame to determine drug concentration using near infrared spectroscopy” LINK

“Amazonian cacao-clone nibs discrimination using NIR spectroscopy coupled to naïve Bayes classifier and a new waveband selection approach” LINK

“Foods : A FT-NIR Process Analytical Technology Approach for Milk Renneting Control” LINK

“Study on Soil Salinity Estimation Method of “Moisture Resistance” Using Visible-Near Infrared Spectroscopy in Coastal Region” LINK

“Can Grassland Chemical Quality Be Quantified Using Transform Near-Infrared Spectroscopy?” LINK

“High Near-Infrared Reflective Zn 1-x A x WO 4 Pigments with Various Hues Facilely Fabricated by Tuning Doped Transition Metal Ions (A= Co, Mn, and Fe)” LINK

“Rapid Differentiation of Unfrozen and Frozen-Thawed Tuna with Non-Destructive Methods and Classification Models: Bioelectrical Impedance Analysis (BIA), Near-Infrared Spectroscopy (NIR) and Time Domain Reflectometry (TDR)” LINK

“The Relationship Between Genetic Variations and NIRs Differences of Eucalyptus Pellita Provenances” LINK

“Prediction of quality of total mixed ration for dairy cows by near infrared reflectance spectroscopy and empirical equations” LINK




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

“Agricultural products quality determination by means of near infrared spectroscopy” LINK

“A Near-Infrared TDLAS Online Detection Device for Dissolved Gas in Transformer Oil” LINK

“Near-Infrared Spectroscopy Detection of Cotton/Polyester Content Based on Dropout Deep Belief Network” LINK

“Study on Near-Infrared Spectrum Acquisition Method of Non-Uniform Solid Particles” LINK

“Scanning interferometric near-infrared spectroscopy” LINK

“A broadband near‐infrared Sc1‐x(PO3)3:xCr3+ phosphor with enhanced thermal stability and quantum yield by Yb3+ codoping” LINK

“Minerals : Geometallurgical Characterisation with Portable FTIR: Application to Sediment-Hosted Cu-Co Ores” LINK




Hyperspectral Imaging (HSI)

“Developing deep learning based regression approaches for prediction of firmness and pH in Kyoho grape using Vis/NIR hyperspectral imaging” LINK

“Robustness and accuracy evaluation of moisture prediction model for black tea withering process using hyperspectral imaging” LINK




Spectral Imaging

“Remote Sensing : Improved Method to Detect the Tailings Ponds from Multispectral Remote Sensing Images Based on Faster R-CNN and Transfer Learning” LINK




Chemometrics and Machine Learning

“Nir Spectral Techniques and Chemometrics Applied to Food Processing” | LINK

“Consistent Value Creation from Bioprocess Data with Customized Algorithms: Opportunities Beyond Multivariate Analysis” LINK

“Effect of variable selection algorithms on model performance for predicting moisture content in biological materials using spectral data” LINK

“Chemometrics: An Excavator in Temperature-Dependent Near-Infrared Spectroscopy” LINK

“Development of Calibration-Free/Minimal Calibration Wavelength Selection for Iterative Optimization Technology Algorithms toward Process Analytical Technology Application” LINK




Equipment for Spectroscopy

“The utility of a near-infrared spectrometer to predict the maturity of green peas (Pisum sativum)” LINK

“Effect of lanthanum content on the thermophysical properties and near-infrared reflection properties of lanthanum-cerium oxides” LINK




Process Control and NIR Sensors

“Emerging non-destructive imaging techniques for fruit damage detection: Image processing and analysis” LINK




Environment NIR-Spectroscopy Application

“Fusion of visible nearinfrared and midinfrared data for modelling key soilforming processes in loess soils” LINK




Agriculture NIR-Spectroscopy Usage

“Preharvest phenotypic prediction of grain quality and yield of durum wheat using multispectral imaging” LINK

“Remote Sensing : A Random Forest Algorithm for Retrieving Canopy Chlorophyll Content of Wheat and Soybean Trained with PROSAIL Simulations Using Adjusted Average Leaf Angle” LINK

“Agriculture : Application of Fourier Transform Infrared Spectroscopy and Multivariate Analysis Methods for the Non-Destructive Evaluation of Phenolics Compounds in Moringa Powder” LINK




Horticulture NIR-Spectroscopy Applications

“Nondestructive detection of total soluble solids in grapes using VMDRC and hyperspectral imaging” LINK




Forestry and Wood Industry NIR Usage

“Influence of growth parameters on wood density of Acacia auriculiformis” | LINK




Food & Feed Industry NIR Usage

“Data fusion of near-infrared diffuse reflectance spectra and transmittance spectra for the accurate determination of rice flour constituents” LINK




Medicinal Spectroscopy

“Carbon Dots with Intrinsic Bioactivities for Photothermal Optical Coherence Tomography, tumorspecific Therapy and Postoperative Wound Management” LINK




Other

“Potential denitrification activity response to long-term nitrogen fertilization-A global meta-analysis” LINK

“Annealing induced phase transformation from amorphous to polycrystalline SnSe2 thin film photo detector with enhanced light-matter interaction” LINK

“MoS2/PVA Hybrid Hydrogel with Excellent LightResponsive Antibacterial Activity and Enhanced Mechanical Properties for Wound Dressing” LINK

“Influence of Substrate Temperature on Structural and Optical Properties of Co-Evaporated Cu2SnS3/ITO Thin Films” | LINK





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Digitization in the field of NIR spectroscopy (smart sensors)

Digitalization is advancing, also in NIR spectroscopy, which enables trainable miniature smart sensors e.g. for analyses in the food&feed, chemical and pharmaceutical sectors.

The calibration is the core of a NIR spectroscopy sensor, it enables the numerous applications and should therefore not be the weakest link in the measurement chain.

The development of calibrations that turn NIR spectrometers into smart sensors is done manually by experts (NIR specialist, chemometrician, data scientist) with so-called chemometrics software.

This is very time-consuming (time to market) and the result is person-dependent and thus suboptimal, because each expert has his own preferred way of proceeding. In addition, the calibrations have to be maintained, as new data has been collected in the meantime, which can be used to extend and improve the calibrations.

This is where our automated service comes in, combining the knowledge and good practices of NIR spectroscopy and chemometrics collected in one software and using machine learning to generate optimal calibrations.

Based on this, we have developed a complete technology platform (Time to Market) that covers the entire process from sending NIR + Lab data, to NIR Calibration as a Service, from online purchase of calibrations, to NIR Predictor software that directly evaluates newly measured NIR data locally and generates result reports.

Besides the free desktop version with user interface, the NIR Predictor can also be integrated (OEM). This can be integrated in parallel as a complement to your current Predictor, allowing the user to choose how they want to calibrate. And give them the advantage in NIR feasibility studies and NIR spectrometer evaluations to quickly provide the customer with a solid and accurate calibration that will make their NIR system deliver better results.

Advantages for your NIR users (internal or external)
  • no initial costs (no chemometrics software license required),
  • calculable operating costs (fixed amount instead of time and hourly rate) (calibration development, calibration maintenance)
  • easy to use (no chemometrics and software training),
  • quicker to use (no calibration development work) and
  • better calibrations (precision, accuracy, robustness, …)


Our chargeable service is based on the calibration development and the annual calibration use. Calibration development and calibration use can also be carried out separately (manufacturer / user).

For you as a spectrometer manufacturer, this means that you can deliver your system pre-calibrated for certain applications without incurring software license costs. And without your application specialists having to provide additional calibration services.

The unique advantages of our calibration service together with the free NIR Predictor are:
  • no software license costs (chemometrics software, predictor software, OEM integration)
  • no chemometrics know-how necessary
  • no time needed to develop optimal NIR calibrations.


If interested in using/evaluating the service :

About CalibrationModel.com : Time and knowledge intensive creation and optimization of chemometric evaluation methods for spectrometers as a service to enable more accurate analysis and measurement results.



see also

Paradigm Change in NIR

Five Mistakes to avoid on Digitalization in NIR

NIR – Total cost of ownership (TCO)

OEM / White Label Software

White Paper



NIR Analysis in Laboratory and Laboratories – aka NIR Labs and NIR testing


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 summariesNIR News Weekly” here.

Spectroscopy and Chemometrics News Weekly #36, 2020

NIR Calibration-Model Services

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


This week’s NIR news Weekly is sponsored by Your-Company-Name-Here – NIR-spectrometers. Check out their product page … link

Spectroscopy and Chemometrics News Weekly 35, 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 35, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 35, 2020 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK




Near-Infrared Spectroscopy (NIRS)

“Estimating Roughage Quality with Near Infrared Reflectance (NIR) Spectroscopy and Chemometric Techniques” LINK

“Detection of Insect Damage in Green Coffee Beans Using VIS-NIR Hyperspectral Imaging” LINK

“Revisiting Water Speciation in Hydrous Alumino-Silicate glasses: A Discrepancy between Solid-state 1H NMR and NIR spectroscopy in the Determination of X-OH …” LINK

“Prediction of Organic Carbon Content of Intertidal Sediments Based on Visible-Near Infrared Spectroscopy” “可见-近红外光谱的潮间带沉积物有机碳含量的几种模型预测方法” LINK




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

“Predicting soil phosphorus and studying the effect of texture on the prediction accuracy using machine learning combined with near-infrared spectroscopy” LINK

“CIC nanoGUNE reaches new depths in infrared nanospectroscopy” LINK

“Distinguishing Hemp from Marijuana by Mid-Infrared Spectroscopy” LINK

“Glucobrassicin Enhancement Using Low Red to Far-Red Light Ratio in ‘Ruby Ball’ Cabbage and High-Throughput Glucobrassicin Estimation Using Near-Infrared …” LINK

“Near-infrared spectroscopy outperforms genomic selection for predicting sugarcane feedstock quality traits” LINK

“Estimation of critical nitrogen contents in peach orchards using visible-near infrared spectral mixture analysis” LINK

“Non-destructive and rapid measurement of sugar content in growing cane stalks for breeding programmes using visible-near infrared spectroscopy” LINK

“Quantitative Analysis of Protein and Polysaccharide in Lilium Lanzhou Based on Near Infrared Spectroscopy” LINK

“Time-stretch infrared spectroscopy” LINK

“Using near infrared reflectance spectroscopy for estimating nutritional quality of Brachiaria humidicola in breeding selections” LINK

“Quantification of phenolic acids by partial least squares Fouriertransform infrared (PLSFTIR) in extracts of medicinal plants” LINK




Chemometrics and Machine Learning

“Predicting adulteration of Palm oil with Sudan IV dye using shortwave handheld spectroscopy and comparative analysis of models” LINK

“Self-adaptive models for predicting soluble solid content of blueberries with biological variability by using near-infrared spectroscopy and chemometrics” LINK

“Rapid identification and quantitative pit mud by near infrared Spectroscopy with chemometrics” LINK

“Methane emission detection and flux quantification from exploratory hydraulic fracturing in the United Kingdom, using unmanned aerial vehicle sampling” LINK




Research on Spectroscopy

“MD dating: molecular decay (MD) in pinewood as a dating method” LINK

“Improved Dimensional Stability and Mold Resistance of Bamboo via In Situ Growth of Poly(Hydroxyethyl Methacrylate-N-Isopropyl Acrylamide)” Polymers LINK




Equipment for Spectroscopy

“Applied Sciences, Vol. 10, Pages 4896: A Novel Single-Channel Arrangement in Chirp Transform Spectrometer for High-Resolution Spectrum Detection” LINK




Agriculture NIR-Spectroscopy Usage

“Angle Distribution Measurement of Scattered Light Intensity from Needle-shaped Crystals in a Magnetic Field for Gout Diagnosis” LINK

“Use of barley silage or corn silage with dry-rolled barley, corn, or a blend of barley and corn on predicted nutrient total tract digestibility and growth performance of …” LINK

“Identification of Leaf-Scale Wheat Powdery Mildew (Blumeria graminis f. sp. Tritici) Combining Hyperspectral Imaging and an SVM Classifier” Plants LINK

“Smartphone-supported portable micro-spectroscopy/imaging system to character morphology and spectra of samples at microscale” LINK

“Novel Antioxidant Packaging Films Based on Poly(-Caprolactone) and Almond Skin Extract: Development and Effect on the Oxidative Stability of Fried Almonds” LINK

“Applied Sciences, Vol. 10, Pages 4907: Experimental Comparison of Diesel and Crude Rapeseed Oil Combustion in a Swirl Burner” LINK

“Molecules, Vol. 25, Pages 3260: Comparison of Bioactive Phenolic Compounds and Antioxidant Activities of Different Parts of Taraxacum mongolicum” LINK




Horticulture NIR-Spectroscopy Applications

“Application of a Vis-NIR Spectroscopic Technique to Measure the Total Soluble Solids Content of Intact Mangoes in Motion on a Belt Conveyor” LINK




Forestry and Wood Industry NIR Usage

“Online analysis of wood extractives” LINK




Food & Feed Industry NIR Usage

Near-Infrared Spectroscopy as a Beef Quality Tool to Predict Consumer Acceptance” Foods LINK

“Rapid Vitality Estimation and Prediction of Corn Seeds Based on Spectra and Images Using Deep Learning and Hyperspectral Imaging Techniques” LINK

“Identification of Bacterial Blight Resistant Rice Seeds Using Terahertz Imaging and Hyperspectral Imaging Combined With Convolutional Neural Network.” LINK

“A simple design for the validation of a FT-NIR screening method: Application to the detection of durum wheat pasta adulteration.” LINK




Laboratory and NIR-Spectroscopy

In-line UV-Vis Spectroscopy Market Research Report 2019-2030 | Industry Report, Industry …: Success of this technology depends on the in-depth knowledge of the link between optical instrumentation design and its effect on data quality. LINK




Other

“The Detection of Substitution Adulteration of Paprika with Spent Paprika by the Application of Molecular Spectroscopy Tools” LINK

“Non-destructive Detection of Apple Maturity by Constructing Spectral Index based on Reflectance Spectrum” LINK





Spectroscopy and Chemometrics News Weekly #35, 2020

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 34, 2020 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality 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)

“Modelos NIRS para as características químicas da madeira de Eucalyptus benthamii Maiden & Cambage” LINK

“Application of in situ near infra-red spectroscopy (NIRS) for monitoring biopharmaceuticals production by cell cultures” LINK

“Using the NIRS for analyzes of soil clay content” LINK

“Determination of compost maturity using near infrared spectroscopy (NIRS)” LINK

“Screening Risk Assessment of Agricultural Areas under a High Level of Anthropopressure Based on Chemical Indexes and VIS-NIR Spectroscopy” LINK

“… an algorithm for processing Red Green Blue (RGB) images for the estimation of crude protein in grasses vs Near Infrared Reflectance Spectroscopy Technology (NIRS …” LINK

“Monitoring of cheese maturation using near infrared-hyperspectral imaging (NIR-HIS)” LINK

“Selection of sugarcane clones via multivariate models using near-infrared (NIR) spectroscopy data” LINK




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

“Rapid and simultaneous analysis of multiple wine quality indicators through near-infrared spectroscopy with twice optimization for wavelength model” LINK

“Manuka honey adulteration detection based on near-infrared spectroscopy combined with aquaphotomics” LINK

” Identification of Marine Fish Taxa by Linear Discriminant Analysis of Reflection Spectra in the Near-Infrared Region” LINK

“Assessment of Intact Macadamia Nut Internal Defects Using Near-Infrared Spectroscopy” LINK

“Rational design of near-infrared platinum(ii)-acetylide conjugated polymers for photoacoustic imaging-guided synergistic phototherapy under 808 nm irradiation.” LINK

“Classification of fish species from different ecosystems using the near infrared diffuse reflectance spectra of otoliths” LINK

“Three new Amazonian species of Myrcia sect. Myrcia (Myrtaceae) based on morphology and near-infrared spectroscopy” LINK

“Rapid Online Determination of Feed Concentration in Nitroguanidine Spray Drying Process by Near Infrared Spectroscopy” LINK




Raman Spectroscopy

“Monitoring the Caustic Dissolution of Aluminum Alloy in a Radiochemical Hot Cell Using Raman Spectroscopy” LINK




Hyperspectral Imaging (HSI)

“Hyperspectral Imaging and Deep Learning for Food Safety Assessment” LINK




Chemometrics and Machine Learning

“Rapid and Nondestructive Freshness Determination of Tilapia Fillets by a Portable Near-Infrared Spectrometer Combined with Chemometrics Methods” LINK

“Non-Targeted Detection of Adulterants in Almond Powder Using Spectroscopic Techniques Combined with Chemometrics.” LINK




Environment NIR-Spectroscopy Application

“Mobile Proximal Sensing with Visible and Near Infrared Spectroscopy for Digital Soil Mapping” LINK




Agriculture NIR-Spectroscopy Usage

“Imaging Techniques for Chicken Products Detection” LINK

“Usage of visual and near-infrared spectroscopy to predict soil properties in forest stands” LINK

“NUTRIENT CONTENT OF SOYBEAN MEAL FROM DIFFERENT ORIGINS BASED ON NEAR INFRARED REFLECTANCE SPECTROSCOPY” LINK

“Robustness of visible near-infrared and mid-infrared spectroscopic models to changes in the quantity and quality of crop residues in soil” LINK

“Use of leaf hyperspectral data and different regression models to estimate photosynthetic parameters (Vcmax and Jmax) in three different row crops” LINK

“Rapid and direct detection of small microplastics in aquatic samples by a new near infrared hyperspectral imaging (NIR-HSI) method” LINK




Horticulture NIR-Spectroscopy Applications

“Prediction of Soluble Solids Content During Storage of Apples with Different Maturity Based on VIS/NIR Spectroscopy” LINK

“A new spectral pretreatment method for detecting soluble solids content of pears using Vis/NIR spectroscopy” LINK

“Research on the Performance of Juicy Peach Sugar Content Detection Model Based on Near Infrared Spectroscopy” LINK




Forestry and Wood Industry NIR Usage

“The Effect of Construction and Demolition Waste Plastic Fractions on Wood-Polymer Composite Properties” LINK




Food & Feed Industry NIR Usage

“Non-destructive Assessment of Flesh Firmness and Dietary Antioxidants of Greenhouse-grown Tomato (Solanum lycopersicum L.) at Different Fruit Maturity Stages” LINK

“Comparative analysis of rice seed viability detection based on different spectral bands” LINK

“Detection of chocolate powder adulteration with peanut using near-infrared hyperspectral imaging and Multivariate Curve Resolution” LINK





Spectroscopy and Chemometrics News Weekly #24, 2020

NIR Calibration-Model Services

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

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

Spectroscopy and Chemometrics News Weekly 23, 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 23, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 23, 2020 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK




Near-Infrared Spectroscopy (NIRS)

“Fiber Content Determination of Linen/Viscose Blends Using NIR Spectroscopy” LINK

“Characterization of a high power time-domain NIRS device: towards faster and deeper investigation of biological tissues” LINK

“… chamosite from an hydrothermalized oolitic ironstone (Saint-Aubin-des-Châteaux, Armorican Massif, France): crystal chemistry, Vis-NIR spectroscopy (red variety) and …” LINK

“Study on evolution methods for the optimization of machine learning models based on FT-NIR spectroscopy” LINK

“Vibrational coupling to hydration shell – Mechanism to performance enhancement of qualitative analysis in NIR spectroscopy of carbohydrates in aqueous environment.” LINK

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

For food analysts, how to choose between a ‘classic’ method and a ‘modern’ technique such as FT-NIR or RMN? Our recently available paper tries to answer that question based on error evaluation: LINK

“FT-NIR combined with chemometrics versus classic chemical methods as accredited analytical support for decision-making: application to chemical compositional compliance of feedingstuffs” LINK




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

“Functional Classification of Feed Items in Pampa Grassland, Based on Their Near-Infrared Spectrum” LINK

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

“Near-infrared spectroscopy as a new method for post-harvest monitoring of white truffles” LINK

“Rapid Prediction of Apparent Amylose, Total Starch, and Crude Protein by Near‐Infrared Reflectance Spectroscopy for Foxtail Millet (Setaria italica)” LINK

“New Induced Mutation Genetic Algorithm for Spectral Variables Selection in Near Infrared Spectroscopy” LINK

“Quantification of Plant Root Species Composition in Peatlands Using FTIR Spectroscopy” LINK

“Functional classification of feed items in pampa grassland, based on their near-infrared spectrum” LINK

“A feasibility of nondestructive rapid detection of total volatile basic nitrogen content in frozen pork based on portable near-infrared spectroscopy” LINK

” Machine Learning Classification of Articular Cartilage Integrity Using Near Infrared Spectroscopy” LINK

“Has the time come to use near-infrared spectroscopy in your science classroom?” LINK

“Feasibility of using near-infrared measurements to detect changes in water quality” LINK

“A novel CC-tSNE-SVR model for rapid determination of diesel fuel quality by near infrared spectroscopy” LINK

“Optimizing analysis of coal property using laser-induced breakdown and near-infrared reflectance spectroscopies” LINK

“Probing Active Sites and Reaction Intermediates of Electrocatalysis Through Confocal Near-Infrared Photoluminescence Spectroscopy: A Perspective.” LINK

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

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

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

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

“Examining the Utility of Visible Near-Infrared and Optical Remote Sensing for the Early Detection of Rapid ‘Ōhi‘a Death” LINK

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

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




Raman Spectroscopy

“Differentiating cancer cells using Raman spectroscopy (Conference Presentation)” LINK

“Applied Sciences, Vol. 10, Pages 3545: Raman Spectral Analysis for Quality Determination of Grignard Reagent” LINK

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




Hyperspectral Imaging (HSI)

“Estimating leaf mercury content in Phragmites australis based on leaf hyperspectral reflectance” LINK

“A hyperspectral microscope based on a birefringent ultrastable common-path interferometer (Conference Presentation)” LINK

“Hyperspectral imaging of beet seed germination prediction” LINK

“Hyperspectral imaging for discrimination of Keemun black tea quality categories: Multivariate calibration analysis and data fusion” LINK

“Potential of deep learning and snapshot hyperspectral imaging for classification of species in meat” LINK

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




Spectral Imaging

“Identify the ripening stage of avocado by multispectral camera using semi-supervised learning on small dataset” LINK

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




Chemometrics and Machine Learning

“Sample selection, calibration and validation of models developed from a large dataset of near infrared spectra of tree leaves” Eucalyptus forage quality LINK

“Determination of Loline Alkaloids and Mycelial Biomass in Endophyte-Infected Schedonorus Pratensis by Near-Infrared Spectroscopy and Chemometrics” LINK

“Detection and Assessment of Nitrogen Effect on Cold Tolerance for Tea by Hyperspectral Reflectance with PLSR, PCR, and LM Models” LINK

“Application of vibrationnal spectroscopy and chemometrics to access the quality of Locally produced antimalarial medicines in the Democratic Republic of Congo.” LINK

“Predicting total petroleum hydrocarbons in field soils with VisNIR models developed on laboratoryconstructed samples” LINK

“National spectral data and learning algorithms for potentially toxic elements modelling in forest soil horizons” LINK

“Rapid determination of the textural properties of silver carp (Hypophthalmichthys molitrix) using near-infrared reflectance spectroscopy and chemometrics” LINK

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




Equipment for Spectroscopy

“NearInfrared Multipurpose LanthanideImaging Nanoprobes” LINK




Process Control and NIR Sensors

“Non-invasive measurement of quality attributes of processed pomegranate products” LINK




Environment NIR-Spectroscopy Application

“Spectral Feature Selection Optimization for Water Quality Estimation.” LINK

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

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




Agriculture NIR-Spectroscopy Usage

“Development of a compact multimodal imaging system for rapid characterisation of intrinsic optical properties of freshly excised tissue (Conference Presentation)” LINK

“Agriculture, Vol. 10, Pages 181: Grafting and ShadingThe Influence on Postharvest Tomato Quality” LINK

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

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

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

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




Horticulture NIR-Spectroscopy Applications

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




Forestry and Wood Industry NIR Usage

“Nutritional characterization of trees from the Amazonian piedmont, Putumayo department, Colombia” LINK




Food & Feed Industry NIR Usage

“Approaches, applications, and future directions for hyperspectral vegetation studies: An emphasis on yieldlimiting factors in wheat” LINK

“Beef Nutritional Quality Testing and Food Packaging” LINK




Laboratory and NIR-Spectroscopy

“UV Irradiation and Near Infrared Characterization of Laboratory Mars Soil Analog Samples: the case of Phthalic Acid, Adenosine 5′-Monophosphate, L-Glutamic Acid …” molecular biosignatures; spectroscopy; lifedetection LINK




Other

LINK

“Effect of substrate temperature on the microstructural and optical properties of RF sputtered grown ZnO thin films” LINK

Using near-infrared light to 3-D print an ear inside the body LINK

“Eco-friendly dye sensitized solar cell using natural dye with solid polymer electrolyte as hole transport material” solarcell 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

NIR-Predictor

New: NIR-Predictor V2.6 with new features

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

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

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

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

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

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



Download

Key Features of NIR-Predictor

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

Super flexible prediction

Loads multiple files at once in

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

It allows you to

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

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

Videos


Properties File Creator

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

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

Properties File Creator saves you from:

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

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

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

Top 8 Reasons why you should use
Automated NIR Calibration Service

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

Reduce Total Cost of Ownership (TCO) of your NIR

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

Download


About the included Demo-Spectra and Demo-Calibrations

The demo calibrations for the spectrometers from

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

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

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

The demo calibrations for the FOSS are built with the

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


References

Quickstart: NIR-Predictor – Manual

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

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

Frequently Asked Questions: NIR-Predictor – FAQ

WebShop : CalibrationModel WebShop