Spectroscopy and Chemometrics News Weekly #8, 2020

CalibrationModel.com

Knowledge-Based Variable Selection and Model Selection for near infrared spectroscopy NIRS LINK

Stop wasting too much time for NIRS Chemometrics Method development | foodanalyticaltechnologies analytic qualitycontrol foodindustry beverageindustry materialsensing LINK

Spectroscopy and Chemometrics News Weekly 7, 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 7, 2020 | NIRS NIR Spektroskopie MachineLearning Spektrometer IoT Sensor Nahinfrarot Chemie Analytik Analysengeräte Analysentechnik Analysemethode Nahinfrarotspektroskopie Laboranalyse LINK

Spettroscopia e Chemiometria Weekly News 7, 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)

“Determination of Glucose by NIR Spectroscopy Under Magnetic Field” LINK

“Sensors, Vol. 20, Pages 230: The Effect of Light Intensity, Sensor Height, and Spectral Pre-Processing Methods when using NIR Spectroscopy to Identify Different Allergen-Containing Powdered Foods” LINK

“Quantum mechanical modeling of NIR spectra of thymol” LINK

“Using a handheld near-infrared spectroscopy (NIRS) scanner to predict meat quality” LINK

“NIR spectroscopy in simulation–a new way for augmenting near-infrared phytoanalysis” LINK

“Using visible-near-infrared spectroscopy to classify lichens at a Neotropical Dry Forest” LINK

“Near infrared spectroscopy as a rapid method for detecting paprika powder adulteration with corn flour” LINK

“Application of deep learning and near infrared spectroscopy in cereal analysis” LINK

“Using near infrared spectroscopy to determine the scots pine place of growth” LINK

“Chagas disease vectors identification using visible and near-infrared spectroscopy” LINK

“Ensemble of extreme learning machines for multivariate calibration of near-infrared spectroscopy” LINK

“Quantification of Silymarin in Silybum marianum with near-infrared spectroscopy: a comparison of benchtop vs. handheld devices” LINK

“N-way partial least squares combined with new self-construction strategy—A promising approach of using near infrared spectral data for quantitative determination of …” LINK

“Identification of rice flour types with near-infrared spectroscopy associated with PLS-DA and SVM methods” LINK

” Multivariate Classification of Prunus Dulcis Varieties using Leaves of Nursery Plants and Near Infrared Spectroscopy” LINK




Hyperspectral

“Frost damage to maize in northeast India: assessment and estimated loss of yield by hyperspectral proximal remote sensing” LINK

“Identification of authenticity, quality and origin of saffron using hyperspectral imaging and multivariate spectral analysis” LINK




Chemometrics

“Early detection of chilling injury in green bell peppers by hyperspectral imaging and chemometrics” LINK

“Evaluating photosynthetic pigment contents of maize using UVE-PLS based on continuous wavelet transform” LINK

“Near-infrared spectroscopy coupled with chemometrics algorithms for the quantitative determination of the germinability of Clostridium perfringens in four different …” LINK

“Analysis of residual moisture in a freeze-dried sample drug using a multivariate fitting regression model” LINK

“Spectroscopy based novel spectral indices, PCA-and PLSR-coupled machine learning models for salinity stress phenotyping of rice” LINK

“Standardisation of near infrared hyperspectral imaging for quantification and classification of DON contaminated wheat samples” LINK

“Vibrational spectroscopy and chemometric data analysis: the principle components of rapid quality control of herbal medicines” LINK

“A Model for Yellow Tea Polyphenols Content Estimation Based on Multi-Feature Fusion” LINK




Process Control

“Review of near-infrared spectroscopy as a process analytical technology for real-time product monitoring in dairy processing” LINK




Environment

“POTENTIAL OF SENSOR-BASED SORTING IN ENHANCED LANDFILL MINING” LINK

“Characterization of the salt marsh soils and visible-near-infrared spectroscopy along a chronosequence of Spartina alterniflora invasion in a coastal wetland of …” LINK




Agriculture

“Remote Sensing, Vol. 12, Pages 126: Predicting Forage Quality of Grasslands Using UAV-Borne Imaging Spectroscopy” LINK

“Novel implementation of laser ablation tomography as an alternative technique to assess grain quality and internal insect development in stored products” LINK

“Comparative Study of Two Different Strategies for Determination of Soluble Solids Content of Apples From Multiple Geographical Regions by Using FT-NIR Spectroscopy” LINK




Food & Feed

“Adulteration of Olive Oil” LINK




Laboratory

“Laboratory Raman and VNIR spectroscopic studies of jarosite and other secondary mineral mixtures relevant to Mars” LINK




Other

“Combining analytical tools to identify adulteration: some practical examples” LINK

“… questioned whether the growth and sustainability of AI technology will lead to the need for two copyright systems — one to address human creation and one to address machine creation.” LINK





NIR Calibration Service explained

Our Service is different

  • We build the optimal quantitative prediction models for your NIR analytical needs (No need for mathematical/statistical model building software usage at your site).
  • The NIR-Predictor software and the calibration models are at your site. No internet connection needed to our service. You can do unlimited predictions, that allows fast measurement cycles with no extra cost (Not payed per prediction).
  • You own your data and the calibrations. You can have access to the detailed Calibration Report with all the settings and statistics (No Black-Box Models).

Get NIR Calibrations

Get NIR Calibrations - Workflow
Your 4 steps to the applicable NIR calibration:
  1. Download free NIR-Predictor here
  2. Combine NIR-Spectra with Lab-Reference values, see Video for 2. and 3. (manual)
  3. Create a Calibration Request and sent it to info@CalibrationModel.com (CM)
  4. After processing you will get a link to the Web Shop to download the calibrations.



Use NIR Calibrations

Use NIR Calibrations Workflow
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In other words

Calibration Model simplifies the process of training machine learning models for NIRS data while providing an opportunity to trying different algorithms and applied near-infrared spectroscopy (NIRS) knowledge. It’s more than an AutoML platform, it’s a full service where you can download the optimal model and its describing Calibration Report that provide insights into the data preparation, feature engineering, model training, and hyperparameter tuning.

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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


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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.




Spectroscopy and Chemometrics News Weekly #1, 2020

CalibrationModel.com

Five Mistakes to avoid on Digitalization in NIR-Spectroscopy – that Lab Managers, Executives and CEOs must know! NIRSpectroscopy NIRS Sensors NearInfrared Analyzers DigitalTransformation QualityControl foodtech machinelearning AI datascience LINK

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

Do you develop NIR / NIRS calibrations by yourself? Can you sell it? No? Buy it! Digitalization LabManager LabAutomation CEO Digitalisation Spectroscopy AutoML LowCost lowerCost SaveMoney SaveTime Efficiency Effectivity LINK

5 Fehler, die es bei der Digitalisierung in der NIR-Spektroskopie zu vermeiden gilt – das müssen Labormanager, Führungskräfte und CEOs wissen! NIRSpectroscopy NIRS Sensor NearInfrared Analyzers DigitalTransformation foodtech machinelearning LINK

Spectroscopy & Chemometrics News Weekly 52, 2019 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Food Analysis Lab Labs Laboratories Laboratory Software IoT Sensors QA QC Testing Quality Check LINK

Spectroscopy & Chemometrics News Weekly 51, 2019 | NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry Chemical Analysis Lab Labs Laboratories Laboratory AI 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

“Estimation and classification of popping expansion capacity in popcorn breeding programs using NIR spectroscopy” LINK

“Simultaneous detection of quality and safety in spinach plants using a new generation of NIRS sensors” LINK

“Identification of Genuine and Adulterated Pinellia ternata by Mid-Infrared (MIR) and Near-Infrared (NIR) Spectroscopy with Partial Least Squares – Discriminant …” LINK

“Monitoring coffee roasting cracks and predicting with in situ near-infrared spectroscopy” LINK

“Assessment of a soil fertility index using visible and near-infrared spectroscopy in the rice paddy region of southern China” LINK

“Conversion of the Felixton Mill laboratory from conventional to NIRS analysis.” LINK

“Automatic cancer discrimination based on near-infrared spectrum and class-modeling technique” LINK

“Food powders classification using handheld Near-Infrared Spectroscopy and Support Vector Machine” LINK

“Development and validation of a method for separation of pregabalin and gabapentin capsules using Near Infrared hyperspectral imaging” LINK

“Field-resolved infrared spectroscopy of biological systems” Nature LINK

“Infrared spectroscopy finally sees the light” nature LINK

“Journal Highlight: Estimation of protein and fatty acid composition in shellintact cottonseed by near Infrared reflectance spectroscopy” LINK

” Visible/near-infrared Spectroscopy as a Novel Technology for Nondestructive Detection of Escherichia coli ATCC 8739 in Lettuce Samples” LINK

“The model updating based on near infrared spectroscopy for the sex identification of silkworm pupae from different varieties by a semi-supervised learning with pre …” LINK

“… Study on the Determination of ppm-Level Concentration of Histamine in Tuna Fish Using a Dry Extract System for Infrared Coupled with Near-Infrared Spectroscopy” LINK




Raman

“Transmission Raman Spectroscopic Quantification of Active Pharmaceutical Ingredient in Coated Tablets of Hot-Melt Extruded Amorphous Solid Dispersion” LINK




Hyperspectral

“Plastic waste monitoring and recycling by hyperspectral imaging technology” LINK

“Comparison of Ink Classification Capabilities of Classic Hyperspectral Similarity Features” LINK




Chemometrics

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

“Development of Partial Least Square (PLS) Prediction Model to Measure the Ripeness of Oil Palm Fresh Fruit Bunch (FFB) by Using NIR Spectroscopy” LINK




Facts

“Bombs and cocaine: detecting nefarious nitrogen sources using remote sensing and machine learning” LINK




Agriculture

“Laboratory-based hyperspectral image analysis for the classification of soil texture” LINK

“Research on simultaneous detection of SSC and FI of blueberry based on hyperspectral imaging combined MS-SPA” LINK

“Polymers, Vol. 12, Pages 78: Insight into the Intermolecular Interaction and Free Radical Polymerizability of Methacrylates in Supercritical Carbon Dioxide” LINK

“Optimizing the procedure of grain nutrient predictions in barley via hyperspectral imaging.” LINK




Other

“绿泥石矿物近红外光谱吸收谱带的位移机理与控制机制研究” LINK

“Spektroskopie – Unverwechselbarer molekularer Fingerabdruck” LINK





Five Mistakes to avoid on Digitalization in NIR-Spectroscopy – that Lab Managers, Executives and CEOs must know!

The fast and non-destructive NIR-Spectroscopy analysis method is based on predictive models that are built upon spectral and Lab reference data.

Developing such models with Chemometric techniques or Machine Learning Algorithms can now be fully automatized with many advantages.

If your company uses NIR-Spectroscopy, do you know if your company yet tried this calibration service? And if not, why not?

Here are some possible reasons why such services are blocked in your company.

With the knowledge where and why it may be blocked, you are able to overcome the barriers and go for innovation.

Misbeliefs of People that may block Advanced Services (AI and Automatic Machine Learning)


5 Mistakes to avoid on Digitalization in NIR-Spectroscopy
Misbeliefs People Remove barriers
1 You need to program or scripting with data modeling tools (R, Phyton, TensorFlow, Matlab, sas, SPSS, H2O, scikit, …..) The opinion that only PhD (statisticians, data scientists) are smart enough to create models. Give the service a try, and compare! There are free trials for calibration development.
2 We have done it always manually by hand. We must see the plots and interpret the stats in every step.
Job protectionism : “My job will dramatically change if that will work, so I will never prepare real-life data to give someone a possibility to try such a service.”
AI / ML haters (NIR-Specialists, NIR-Experts) don’t belive in automated calibration. Give the service a try, and compare! You will see plots and stats! There are free trials for calibration development.
3 Against any new hardware, software or service because of supposed new problems. Preserving ones – the permission gate keepers (IT) Give it a try, without an account, download the free NIR-Predictor software (full version, no limitations) with included demo data, it installs and runs without Administrator priviledge!
4 Ensures that new methodologies follow the rules. Any new thing will give extra work for them. Compliance and Regulation officers. Get access to the detailed model blueprint (ISO 12099) – there is no vendor lock-in or black-box model. You can even anonymize your data for Knowledge Protection – see JCAMP-Anonymizer.
5 Our employees are open for new things. Our employees do not block. Managers, executives, board level. Remove the Barriers to Innovation!


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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

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*) 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

Start Calibrate – NIR Quick Guide

Quick Start NIR Workflow: step by step

1. Check if your NIR-Device Data Format is directly supported (anyway you can convert to JCAMP) : NIR-Predictor supported Spectral Data File Formats

2. Download the free NIR-Predictor Software that contains demo data so you can play with it to see if it is the way you want analyse your NIR spectra (no registration needed) : NIR-Predictor Download

3. With your “NIR device” measurement software:

  • measure samples with NIR, that gets you spectra files,
  • label them with a proper sample name, so you know which is which,
  • and determine quantitative reference values by Laboratory reference method.
  • at least 60 samples with different contents is needed for a minimal calibration.
  • NIR-Predictor helps to create a template file (.csv) to enter the Lab values.

4. Creating your own Calibrations with NIR-Predictor to combine your NIR and Lab data for a calibration request : watch Video read Manual



Videos


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