Spectroscopy and Chemometrics News Weekly #10, 2021

NIR Calibration-Model Services

Spectroscopy and Chemometrics News Weekly 9, 2021 | 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, 2021 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 9, 2021 | NIRS NIR Spettroscopia MachineLearning analisi chimica Spettrale Spettrometro Chem IoT Sensore Attrezzatura analitica Laboratorio analisi prova qualità Analysesystem QualityControl LINK

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Near-Infrared Spectroscopy (NIRS)

“Rapid and cost-effective nutrient content analysis of cotton leaves using near-infrared spectroscopy (NIRS)” LINK

“Near-Infrared ( NIR ) supported by image analysis and MachineLearning as a fast screening tool for cannabis flower composition analysis by remote sensing and spectral markers for marker assisted breeding.” | Cannabinoids Research LINK

“NIR spectroscopy is coming to your smartphone” NIRS LINK




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

“Simultaneous quantification of chemical constituents in matcha with visible-near infrared hyperspectral imaging technology” LINK

“Application of ANOVA-simultaneous component analysis to quantify and characterise effects of age, temperature, syrup adulteration and irradiation on near-infrared …” LINK

“Quality Evaluation of Keemun black tea by fusing data obtained from near-infrared reflectance spectroscopy and computer vision sensors” LINK

“Rice Freshness Identification Based on Visible Near-Infrared Spectroscopy and Colorimetric Sensor Array” LINK

“Identification of storage years of black tea using near-infrared hyperspectral imaging with deep learning methods” LINK

“Comparison of Raman and Near-Infrared Chemical Mapping for the Analysis of Pharmaceutical Tablets” LINK

“A Review of the Discriminant Analysis Methods for Food Quality Based on Near-Infrared Spectroscopy and Pattern Recognition.” LINK

“An integrated near-infrared spectral chip for on-field sensing” LINK

“Identification of Multi-Class Drugs Based on Near Infrared Spectroscopy and Bidirectional Generative Adversarial Networks” LINK

“Authentication of Edible Oils Using Fourier Transform Infrared Spectroscopy and Pattern Recognition Methods” LINK

“Prediction of Soil Properties by Visible and Near-Infrared Reflectance Spectroscopy” LINK

“Prediction of cooking times of freshly harvested common beans and their susceptibility to develop the Hard-To-Cook defect using near infrared spectroscopy” LINK

“Anomaly detection during milk processing by autoencoder neural network based on near-infrared spectroscopy” LINK

” Can a smartphone near-infrared spectroscopy sensor predict days on feed and marbling score?” LINK

“Classification of aflatoxin B1 naturally contaminated peanut using visible and near-infrared hyperspectral imaging by integrating spectral and texture features” LINK

“Is this Melon Sweet? A quantitative classification for near-infrared spectroscopy” LINK

“Mineral equilibrium in commercial curd and predictive ability of near-infrared spectroscopy” LINK

“Characterization of connective tissues using near-infrared spectroscopy and imaging” LINK




Hyperspectral Imaging (HSI)

” Machine learning techniques for analysis of hyperspectral images to determine quality of food products: a review” LINK




Chemometrics and Machine Learning

“Nondestructive qualitative and quantitative analysis of Yaobitong capsule using near-infrared spectroscopy in tandem with chemometrics” LINK

“Detection and quantification of cow milk adulteration using portable near-infrared spectroscopy combined with chemometrics” LINK

“Real-time release testing of dissolution based on surrogate models developed by machine learning algorithms using NIR spectra, compression force and particle size distribution as input data.” LINK

“Development of a Universal Calibration Model for Quantification of Adulteration in Thai Jasmine Rice Using Near-infrared Spectroscopy” LINK

“Broiler Diets Formulated Based on Digestible Amino Acid Values as Determined by in vivo and Prediction Methods” LINK




Equipment for Spectroscopy

“Quantification of Silymarin in Silybi mariani fructus: challenging the analytical performance of benchtop vs. handheld NIR spectrometers on whole seeds” LINK




Process Control and NIR Sensors

“Sample Mass Estimate for the Use of Near-Infrared and Raman Spectroscopy to Monitor Content Uniformity in a Tablet Press Feed Frame of a Drug Product Continuous Manufacturing Process” LINK




Agriculture NIR-Spectroscopy Usage

“Partial Least Squares Estimation of Crop Moisture and Density by Near-Infrared Spectroscopy” LINK

“Estimation of Starch Hydrolysis in Sweet Potato (Beni Haruka) Based on Storage Period Using Nondestructive Near-Infrared Spectrometry” Agriculture LINK

“Precision feeding comes in small packages” LINK

” Effects of irrigation and planting geometry on cotton (Gossypium hirsutum L.) fiber quality and seed composition” LINK




Food & Feed Industry NIR Usage

“Effect of penetration depth and particle size on detection of wheat flour adulterant using hyperspectral imaging” LINK

The new section on portable foodsafety devices, co-edited by has been published in J AOAC. We thank the many contributors who made this section possible! LINK

“Determination of phosphorus status in bread wheat leaves by visible and near-infrared spectral discriminant analysis” LINK

“Evaluation of the Production Performance and the Meat Quality of Chickens Reared in Organic System. As Affected by the Inclusion of Calliphora sp. in the Diet” LINK

“Determination of Moisture, Fat, Carbohydrates and Protein Contents in Flour by Near Infrared Spectroscopy” LINK




Laboratory and NIR-Spectroscopy

“A Paradigm Shift: From “Sample to Laboratory” to “Laboratory to Sample” ” LINK





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