Spectroscopy and Chemometrics News Weekly #26, 2020

NIR Calibration-Model Services

Get the new Free NIR-Predictor V2.6 software – Reads and predicts *.spc spectra file format (Thermo-Scientific / Galactic GRAMS) – Spectra Plots on the Prediction Reports NIRS NIR Spectroscopy Spectrometer QualityControl Laboratory Food Analysis LINK

Pro Tip: The NIR calibration is the central key to accurate NIR measurement | NIRS LINK

Spectroscopy and Chemometrics News Weekly 25, 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 25, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 25, 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)

“Study on Detection Methods for Frying Times of Soybean Oil Based on NIRS” LINK

“Non-destructive Detection the Content of Acid Detergent Fiber in Corn Stalk Using NIRS” LINK

“Differentiation of South African Game Meat Using Near-Infrared (NIR) Spectroscopy and Hierarchical Modelling” LINK

“Changes in chemical components with NIR spectroscopy and durability of samama wood treated with boron, methyl methacrylate and heat treatment” LINK

“NIR spectroscopy application for determination caffeine content of Arabica green bean coffee” LINK

“Principle Component Analysis (PCA)-Classification of Arabica green bean coffee of North Sumatera Using FT–NIRS” LINK

“Prediction of water content in Lintong green bean coffee using FT-NIRS and PLS method” LINK




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

“Detection of aflatoxin B1 on corn kernel surfaces using visible-near infrared spectroscopy” LINK

“Soil NPK Levels Characterization Using Near Infrared and Artificial Neural Network” LINK

“Rapid and Non-destructive Detecting Frying Times of Peanut Oil Based on Near Infrared Reflectance Spectroscopy” LINK

“Biosensors, Vol. 10, Pages 41: Rapid Nondestructive Detection of Water Content and Granulation in Postharvest Shatian Pomelo Using Visible/Near-Infrared Spectroscopy” LINK

” Estimation of moisture in wood chips by Near Infrared Spectroscopy” LINK

“Nondestructive determination of lignin content in Korla fragrant pear based on near-infrared spectroscopy” LINK

“Near-infrared spectroscopy of the placenta for monitoring fetal oxygenation during labour.” LINK

“Confirmation of brand identification in infant formulas by near-infrared spectroscopy fingerprints” LINK

“Application of near-infrared hyperspectral imaging to identify a variety of silage maize seeds and common maize seeds” LINK

“Protein, weight, and oil prediction by single-seed near-infrared spectroscopy for selection of seed quality and yield traits in pea (Pisum sativum).” phenotyping LINK

“Estimating δ15N and δ13C in Barley and Pea Mixtures Using Near-Infrared Spectroscopy with Genetic Algorithm Based Partial Least Squares Regression” LINK




Raman Spectroscopy

“Diagnosis of Citrus Greening using Raman Spectroscopy-Based Pattern Recognition” LINK




Hyperspectral Imaging (HSI)

“Germination Prediction of Sugar Beet Seeds Based on HSI and SVM-RBF” LINK

“Diagnosis of Late Blight of Potato Leaves Based on Deep Learning Hyperspectral Images” LINK

“Rapid detection of quality index of postharvest fresh tea leaves using hyperspectral imaging.” LINK

“Applied Sciences, Vol. 10, Pages 2259: Hyperspectral Inversion Model of Chlorophyll Content in Peanut Leaves” LINK




Chemometrics and Machine Learning

“Spectroscopic techniques combined with chemometrics for fast on-site characterization of suspected illegal antimicrobials” LINK

“Comparison of CNN Algorithms on Hyperspectral Image Classification in Agricultural Lands” LINK




Research on Spectroscopy

“Lanthanide complexes with N-(2, 6-dimethylphenyl) oxamate: Synthesis, characterisation and cytotoxicity” LINK




Equipment for Spectroscopy

“Monitoring wine fermentation deviations using an ATR-MIR spectrometer and MSPC charts” LINK




Agriculture NIR-Spectroscopy Usage

“Rapid Measurement of Soybean Seed Viability Using Kernel-Based Multispectral Image Analysis” LINK

“Remote Sensing, Vol. 12, Pages 1256: Crop Separability from Individual and Combined Airborne Imaging Spectroscopy and UAV Multispectral Data” LINK

“Portable IoT NIR Spectrometer for Detecting Undesirable Substances in Forages of Dairy Farms” LINK




Food & Feed Industry NIR Usage

“Prediction of infertile chicken eggs before hatching by the Naïve-Bayes method combined with visible near infrared transmission spectroscopy” LINK

“Statistical Analysis of Protein Content in Wheat Germplasm Based on Near-infrared Reflectance Spectroscopy” LINK




Other

“On-Site Identification of the Material Composition of PV Modules with Mobile Spectroscopic Devices” LINK





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Spectroscopy and Chemometrics News Weekly #23, 2020

NIR Calibration-Model Services

New Free NIR-Predictor V2.6 software is released – New : reads and predicts also *.spc spectra file format (Thermo-Scientific / Galactic GRAMS) – Spectra Plots on the Prediction Reports NIRS NIR Spectroscopy Spectrometer QualityControl Lab Laboratory Analysis LINK
Spectra Plot


Spectroscopy and Chemometrics News Weekly 22, 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 22, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 22, 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)

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

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

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

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

“Determination of metmyoglobin in cooked tan mutton using Vis/NIR hyperspectral imaging system” LINK

“The past, present, and prospective on UV-VIS-NIR skin photonics and spectroscopy-a wavelength guide.” LINK

“Differentiation of South African Game Meat Using Near-Infrared (NIR) Spectroscopy and Hierarchical Modelling” LINK

“Study on Detection Methods for Frying Times of Soybean Oil Based on NIRS” LINK

“Non-destructive Detection the Content of Acid Detergent Fiber in Corn Stalk Using NIRS” LINK

“Changes in chemical components with NIR spectroscopy and durability of samama wood treated with boron, methyl methacrylate and heat treatment” LINK

“Principle Component Analysis (PCA)-Classification of Arabica green bean coffee of North Sumatera Using FT–NIRS” LINK




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

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

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

“Fast Detection Method of Antarctic Krill Meat Quality Based on Near Infrared Spectroscopy” LINK

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

“Determination of pectin content in orange peels by Near Infrared Hyperspectral Imaging” LINK

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

“Determination of nutritional parameters of bee pollen by Raman and infrared spectroscopy.” LINK

“Detection of aflatoxin B1 on corn kernel surfaces using visible-near infrared spectroscopy” LINK

“Soil NPK Levels Characterization Using Near Infrared and Artificial Neural Network” LINK

” Estimation of moisture in wood chips by Near Infrared Spectroscopy” LINK

“Biosensors, Vol. 10, Pages 41: Rapid Nondestructive Detection of Water Content and Granulation in Postharvest Shatian Pomelo Using Visible/Near-Infrared Spectroscopy” LINK

“Prognostic value of near-infrared spectroscopy in hypoxic-ischaemic encephalopathy” LINK




Raman Spectroscopy

“Quantitative models for detecting the presence of lead in turmeric using Raman spectroscopy” LINK




Hyperspectral Imaging (HSI)

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

“Discriminative Reconstruction for Hyperspectral Anomaly Detection With Spectral Learning” LINK

“Classification of common recyclable garbage based on hyperspectral imaging and deep learning” LINK

“Based on hyperspectral polarization to build the quantitative remote sensing model of jujube in Southern Xinjiang” LINK

“Study on quality distribution characteristics of jujube canopy based on multi-angle hyperspectral polarization” LINK

“Germination Prediction of Sugar Beet Seeds Based on HSI and SVM-RBF” LINK




Chemometrics and Machine Learning

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

“Simultaneous determination of goat milk adulteration with cow milk and their fat and protein contents using NIR spectroscopy and PLS algorithms” LINK

“Optimization and comparison of models for prediction of soluble solids content in apple by online Vis/NIR transmission coupled with diameter correction method” LINK

“Building kinetic models for apple crispness to determine the optimal freshness preservation time during shelf life based on spectroscopy” LINK

“Incorporation of two-dimensional correlation analysis into discriminant analysis as a potential tool for improving discrimination accuracy: Near-infrared spectroscopic discrimination of adulterated olive oils.” LINK

“Spectroscopic techniques combined with chemometrics for fast on-site characterization of suspected illegal antimicrobials” LINK




Environment NIR-Spectroscopy Application

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




Agriculture NIR-Spectroscopy Usage

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

“Remote Sensing, Vol. 12, Pages 1308: Machine Learning Based On-Line Prediction of Soil Organic Carbon after Removal of Soil Moisture Effect” LINK

“Detection of Nutrition and Toxic Elements in Pakistani Pepper Powders Using Laser Induced Breakdown Spectroscopy” LINK

“Agriculture, Vol. 10, Pages 177: Prediction of Soil Oxalate Phosphorus using Visible and Near-Infrared Spectroscopy in Natural and Cultivated System Soils of Madagascar” LINK




Forestry and Wood Industry NIR Usage

“Linear Discriminant Analysis of spectral measurements for discrimination between healthy and diseased trees of Olea europaea L. artificially infected by Fomitiporia …” LINK




Food & Feed Industry NIR Usage

“Quantification of Ash and Moisture in Wheat Flour by Raman Spectroscopy” LINK

“Visualization accuracy improvement of spectral quantitative analysis for meat adulteration using Gaussian distribution of regression coefficients in hyperspectral …” LINK




Laboratory and NIR-Spectroscopy

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




Other

“Machine vision detection of pests, diseases, and weeds: A review” LINK

“On-Site Identification of the Material Composition of PV Modules with Mobile Spectroscopic Devices” LINK

“Synthesis of N-Doped ZnO Nanocomposites for Sunlight Photocatalytic Degradation of Textile Dye Pollutants” LINK





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Spectroscopy and Chemometrics News Weekly #21, 2020

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

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


NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 20, 2020 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 20, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 20, 2020 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK




Near-Infrared Spectroscopy (NIRS)

“New applications of visnir spectroscopy for the prediction of soil properties” LINK

“Simultaneous determination of quality parameters in yerba mate (Ilex paraguariensis) samples by application of near-infrared (NIR) spectroscopy and partial least …” LINK

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

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

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




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

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

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

“Performance Improvement of Near-Infrared Spectroscopy-Based Brain-Computer Interface Using Regularized Linear Discriminant Analysis Ensemble Classifier Based on Bootstrap Aggregating.” LINK

“Continuously measurement of the dry matter content using near-infrared spectroscopy” LINK

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

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

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

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

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

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

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




Raman Spectroscopy

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




Hyperspectral Imaging (HSI)

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

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

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

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

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




Chemometrics and Machine Learning

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

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

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




Equipment for Spectroscopy

“Determination of soluble solids content in Prunus avium by Vis/NIR equipment using linear and non-linear regression methods” LINK

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




Environment NIR-Spectroscopy Application

“An Evaluation of Citizen Science Smartphone Apps for Inland Water Quality Assessment” LINK




Agriculture NIR-Spectroscopy Usage

“Robustness of visible/near and midinfrared spectroscopic models to changes in the quantity and quality of crop residues in soil” LINK

“Complex Food Recognition using Hyper-Spectral Imagery” LINK

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




Horticulture NIR-Spectroscopy Applications

” The Effect of Spent Mushroom Substrate and Cow Slurry on Sugar Content and Digestibility of Alfalfa Grass Mixtures” LINK




Laboratory and NIR-Spectroscopy

“The influence analysis of reflectance anisotropy of canopy on the prediction accuracy of Cu stress based on laboratory multi-directional measurement” LINK

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









Spectroscopy and Chemometrics News Weekly #15, 2020

CalibrationModel.com

Do you want better NIRS prediction results? Use your Near-Infrared Analysis data and do recalibration adjustment | modelling spectral applications LINK

Spectroscopy and Chemometrics News Weekly 14, 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 14, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 14, 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)

“Prediction of moisture content of wood using Modified Random Frog and Vis-NIR hyperspectral imaging” LINK

“NIRS prediction of dry matter content of single olive fruit with consideration of variable sorting for normalisation pre-treatment” LINK

“Near infrared reflectance spectroscopy (NIRS) evaluation of the nutritive value of leaf and green pruning residues of grapevine (Vitis vinifera L.) cultivars” LINK

“Proximate composition determination in goat cheese whey by near infrared spectroscopy (NIRS)” LINK

“An Overview on the Applications of Typical Non-linear Algorithms Coupled With NIR Spectroscopy in Food Analysis” LINK

“Untargeted identification of adulterated Sanqi powder by near-infrared spectroscopy and one-class model” LINK

“Near‐infrared reflectance spectroscopy based online moisture measurement in copra” LINK

“Handheld Near Infrared spectroscopy for cannabis analysis: from the analytical problem to the chemometric solution” LINK




Hyperspectral Imaging

“APPLICATION OF HYPERSPECTRAL REMOTE SENSING IN THE DETECTION OF MARINE OIL SPILL” LINK

“Deep learning applied to hyperspectral endoscopy for online spectral classification” LINK

“Rapid Distinguish of Edible Oil Adulteration Using a Hyperspectral Spectroradiometer” LINK




Chemometrics in Near-Infrared Spectroscopy (NIR)

“Quality Classification of Panax notoginseng Based on Near Infrared Spectroscopy Combined with Multi-class Correlation Vector Machine” LINK

“Detection of mites Tyrophagus putrescentiae and Cheyletus eruditus in flour using hyperspectral imaging system coupled with chemometrics” LINK

“PC 2D-COS: A Principal Component Base Approach to Two-Dimensional Correlation Spectroscopy” LINK

” Classification Modeling Method for Near-Infrared Spectroscopy of Tobacco Based on Multimodal Convolution Neural Networks” LINK




Process Control

“Recent Advances in Information and Communications Technology (ICT) and Sensor Technology for Monitoring Water Quality” LINK




Environment

“Narrow-band reflectance indices for mapping the combined effects of water and nitrogen stress in field grown tomato crops” LINK




Agriculture and NIR-Spectroscopy

“Hyperspectral vegetation indexes to monitor wheat plant height under different sowing conditions” LINK

“Determination of soluble solids content in oranges using visible and near infrared full transmittance hyperspectral imaging with comparative analysis of models” LINK

“Precision Agriculture Technologies for Management of Plant Diseases” LINK

“Oxygenating blubber: a challenge for fat animals” LINK

“Foods, Vol. 9, Pages 193: Detection of Beef Adulterated with Pork Using a Low-CostElectronic Nose Based on Colorimetric Sensors” LINK

“Bulk optical properties of citrus tissues and the relationship with quality properties” LINK

“Applied Sciences, Vol. 10, Pages 1319: Artificial Intelligence Assisted Mid-Infrared Laser Spectroscopy In Situ Detection of Petroleum in Soils” LINK

“Applied Sciences, Vol. 10, Pages 1309: Quantifying the Effect of Catalysts on the Lifetime of Transformer Oil” LINK

“Agronomy, Vol. 10, Pages 282: Agriculture Management Impacts on Soil Properties and Hydrological Response in Istria (Croatia)” LINK

“Crystals, Vol. 10, Pages 122: Flexible and Structural Coloured Composite Films from Cellulose Nanocrystals/Hydroxypropyl Cellulose Lyotropic Suspensions” LINK

“Sensors, Vol. 20, Pages 1065: Collaborative Analysis on the Marked Ages of Rice Wines by Electronic Tongue and Nose based on Different Feature Data Sets” LINK

“Agronomy, Vol. 10, Pages 267: Estimation of the Constituent Properties of Red Delicious Apples Using a Hybrid of Artificial Neural Networks and Artificial Bee Colony Algorithm” LINK

“Evaluation of analytical and statistical approaches for predicting in vitro nitrogen solubility and in vivo pre‐caecal crude protein digestibility of cereal grains in growing …” LINK




Food & Feed and NIR Sensors

“Foods, Vol. 9, Pages 221: Non-Targeted Authentication Approach for Extra Virgin Olive Oil” LINK




Medicinal

“Near-IR Photochemistry for Biology: Exploiting the Optical Window of Tissue.” LINK




Laboratory and NIR Spectroscopy

“Experiments for determination of species of field-collected lab-rared mosquitoes using near-infrared spectroscopy (A1T1)” LINK





Spectroscopy and Chemometrics News Weekly #3, 2020

Near Infrared (NIR) Spectroscopy

“Fourier-transform near infrared spectroscopy (FT-NIRS) rapidly and non-destructively predicts daily age and growth in otoliths of juvenile red snapper Lutjanus …” LINK

“Desarrollo de Modelos NIRS de Predicción para el Análisis de la Finura de Fibras Textiles de Vicuña y Llama” LINK

“fNIRS-GANs: Data augmentation using generative adversarial networks for classifying motor tasks from functional near-infrared spectroscopy.” LINK

” Simulated NIR spectra as sensitive markers of the structure and interactions in nucleobases” LINK

“Penentuan Parameter Mutu Buah Jeruk Siam Garut Secara Nondestruktif Menggunakan Spektroskopi NIR” LINK

“Rapid non-destructive moisture content monitoring using a handheld portable Vis–NIR spectrophotometer during solar drying of mangoes (Mangifera indica L.)” LINK

“VIS-NIR wave spectrometric features of acorns (Quercus robur L.) for machine grading” LINK

“Portable NIR Spectroscopy: Affordable Technology for Developing Countries” LINK

“NIR spectroscopy used for non-destructive evaluation of the chemical composition of the investigated papers in addition to typically used standard methods.” LINK

“Feasibility study on prediction of gasoline octane number using NIR spectroscopy combined with manifold learning and neural network” LINK

“Authentication of Tokaj Wine (Hungaricum) with the Electronic Tongue and Near Infrared Spectroscopy” LINK

“Environmental advantages of visible and near infrared spectroscopy for the prediction of intact olive ripeness” LINK

“Rapid screening and quantitative analysis of adulterant Lonicerae Flos in Lonicerae Japonicae Flos by Fourier-transform near infrared spectroscopy” LINK

“Rapid analysis of soluble solid content in navel orange based on visible-near infrared spectroscopy combined with a swarm intelligence optimization method” LINK

“Establishment and relevant analysis of plant’s spectral reflectivity database in visible and near-infrared bands” LINK




Hyperspectral Imaging

“Mineral Mapping of Drill Core Hyperspectral Data with Extreme Learning Machines” LINK

“Deep learning classifiers for hyperspectral imaging: A review” LINK

“Texture and Shape Features for Grass Weed Classification Using Hyperspectral Remote Sensing Images” LINK

“Avoiding Overfitting When Applying Spectral-Spatial Deep Learning Methods on Hyperspectral Images with Limited Labels” LINK

“Estimation Model of Winter Wheat Yield Based on Uav Hyperspectral Data” LINK




Chemometrics and Machine Learning

“Validation of near infrared spectroscopy as an age-prediction method for plastics” LINK

Whoever leads in ArtificialIntelligence in 2030 will rule the world until 2100 | fintech AI MachineLearning DeepLearning robotics LINK

“Chemical Composition of Hexene-Based Linear Low-Density Polyethylene by Infrared Spectroscopy and Chemometrics” LINK

“Establishment of Plot-Yield Prediction Models in Soybean Breeding Programs Using UAV-Based Hyperspectral Remote Sensing” LINK

“DEVELOPING NEAR INFRARED SPECTROSCOPIC MODELS FOR PREDICTING DENSITY OF Eucalyptus WOOD BASED ON INDIRECT MEASUREMENT” LINK

“NIR reflectance spectroscopy and SIMCA for classification of crops flour” LINK




NIR Equipment

“Prediction of meat quality traits in the abattoir using portable and hand-held near-infrared spectrometers” LINK

“A Plug-and-play Hyperspectral Imaging Sensor Using Low-cost Equipment” LINK




NIR in Environment

“The use of hyperspectral remote sensing to detect PCB contaminated soils in the 0.35 to 12 micron spectral range” LINK




NIR in Agriculture

“Fast measurement of phosphates and ammonium in fermentation-like media: a feasibility study” LINK

“Detection of early decay on citrus using hyperspectral transmittance imaging technology coupled with principal component analysis and improved watershed …” LINK

“Determination of Nutritive Value of Some Feedstuffs Used in Poultry Nutrition by Near Infrared Reflectance Spectroscopy (NIRS) and Chemical Methods” LINK

“근적외선분광법을 이용한 사료용 벼의 사료가치 평가” “Evaluation of Feed Values for Whole Crop Rice Using Near Infrared Reflectance Spectroscopy” LINK

“Classification of crop flours based on protein contents using near infra-red spectroscopy and principle component analysis” LINK

“In-field detection of Alternaria solani in potato crops using hyperspectral imaging” LINK




NIR in Laboratory

“Use of Remote sensing technology to assess grapevine quality” LINK


CalibrationModel.com

Spectroscopy and Chemometrics News Weekly 2, 2020 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical AI Application Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 2, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 2, 2020 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem predictionmodel LINK


Start Calibrate

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.




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

CalibrationModel.com (CM) versus Others

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

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

See also: pricing

Start Calibrate

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

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

Spectroscopy and Chemometrics News Weekly #40, 2019

CalibrationModel.com

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

Spectroscopy and Chemometrics News Weekly 39, 2019 | NIRS NIR Spectroscopy Chemometrics Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory Software Sensors QA QC Testing Quality Checking LINK

Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 39, 2019 | NIRS NIR Spektroskopie Chemometrie Spektrometer Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

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




Chemometrics

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

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

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




Near Infrared

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

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

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

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

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




Infrared

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

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




Equipment

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




Environment

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




Agriculture

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

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

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




Food & Feed

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

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

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

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




Laboratory

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





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


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


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


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

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

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

    DATA = exported
Spectra and (Lab-)reference values as JCAMP-DX or other data formats
    CALIB = single quantitative property


Sending DATA
    DATA is sent by email, 2-3 days later, receive email with link to
      WebShop to purchase CALIB with PayPal/CreditCard
    DATA is
deleted after processing (Terms of Service TOS)
    optional: JCAMP
Anonymizer (removes sensitive information) before sending DATA


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


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


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


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

NIR-Predictor

New: NIR-Predictor V2.6 with new features

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

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

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

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

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

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



Download

Key Features of NIR-Predictor

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

Super flexible prediction

Loads multiple files at once in

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

It allows you to

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

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

Videos


Properties File Creator

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

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

Properties File Creator saves you from:

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

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

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

Top 8 Reasons why you should use
Automated NIR Calibration Service

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

Reduce Total Cost of Ownership (TCO) of your NIR

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

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