Spectroscopy and Chemometrics News Weekly #5+6, 2017


Chemometrics

Non-Destructive Sensor-Based Prediction of Maturity and Optimum Harvest Date of Sweet Cherry Fruit | sensors LINK


IDC unveils its Top 10 Predictions for global Robotics Industry Industry40 Robotics LINK


Spectroscopy

Global Molecular Spectroscopy Market is expected to reach USD 6.712 billion till 2024. htt… LINK!


Near Infrared

Assessing pre-harvest sprouting in cereals using near-infrared spectroscopy-based metabolomics LINK


Rapid screening of commercial extra virgin olive oil products for authenticity: Performance of a handheld NIR device LINK


Hyperspectral

Imec () launches TDI, multispectral and hyperspectral sensors | imaging HSI LINK


Near-infrared hyperspectral imaging of lamination and finishing processes in textile technology LINK


Spectral Imaging

Viavi Solutions and ESPROS Photonics Corporation Debut New Miniaturized Spectral Sensor and Multispectral Sensor LINK


Equipment

Meta-lenses bring benchtop performance to small, hand-held spectrometer – Science Daily LINK



Scan anywhere with Neospectra Spectrometer Case powered by XPNDBLS PhotonicsWest … LINK!


Agriculture

World feed production exceeds 1 billion MT LINK


Chemometric soil analysis on the determination of specific bands for the detection of magnesium & potassium by … LINK


Other

This app uses spectral analysis to analyze objects and their makeup HawkSpex LINK


Research details developments in the multivariate analysis software industry | MVA LINK

“The worlds first ever spectroscopy enabled iPhone!” Check out our video to see it in action: LINK


Investments in AI will triple in 2017. ($47 billion by 2020 per ) CIO CMO | LINK


Some aspects of fetal development have long puzzled scientists, but new molecular technologies are shining a light: https:/… LINK!


CalibrationModel.com

Spectroscopy and Chemometrics News Weekly 3+4, 2017 | Spectroscopy NIRS MVDA… LINK


Spektroskopie und Chemometrie Neuigkeiten Wöchentlich 3+4, 2017 | NIRS Spektroskopie Chemometrie Multivariate LINK


Spettroscopia e Chemiometria Weekly News 3+4, 2017 | NIRS Spettroscopia Chemiometria news LINK


WHITE PAPER: A novel knowledge-based Chemometric Software Framework for quantitative NIRS Calibration Modeling LINK



Improve Accuracy of fast non-destructive NIR Measurements by Optimal Calibration | spectroscopy sensor modeling LINK


NIRS as a secondary method requires extensive calibration on an ongoing basis | foodindustry Digitalization IoT LINK


Services for Optimization of Chemometric Application Methods of Near-Infrared Spectroscopy | Quality Control NIRS LINK


► Timesaving NIRS Calibration ► near-infrared spectroscopy | protein fat moisture sensor measurement scanning LINK





Uniqueness


It is easy
1. send your NIR data (we do not collect, share or sell your data)
2. receive your optimal model blueprint
3. build it, validate it, use it

We have a Chemometric software not to do chemometrics,
we have the solution to build an optimal model for your data
so you can get better NIR measurement results.

So we don’t name it a “Chemometric Software”.
It’s a service named, as that what it delivers, a Calibration Model.
It gives you an optimal chemometric model for your NIR data.
That is what you want to achieve.

So don’t bother about Chemometrics and endless helpless possibilities
and spend your time with clicking and waiting for a chemometric software,
when you can get an optimal model for your data as a service!

There is no lock-in.
Because there is no software to install.

There is no black-box.
Because the model is delivered as a detailed and complete blueprint in human readable form.

You stay independent.
Because you can always choose:
- You can still do it as you have done it before.
- You will experience that with the service you will get the better models faster and is inexpensive.

Let’s have a try
please contact us, so we can help you!

How to develop near-infrared spectroscopy calibrations in the 21st Century?


The Problem

Calibration modeling is a complex and very important part of NIR spectroscopy, especially for quantitative analysis. If the model is badly designed the best instrument precision and highest data quality does not help getting good and robust measurement results. And NIR Spectroscopy requires periodically recalibration and validation.


How are NIR models built today?

In a typical usage in industry, a single person is responsible to develop the models (see survey). He or she uses a Chemometric software that has a click-and-wait working process to adjust all the possible settings for the used algorithms in dialogs and wait for calculations and graphics and then to think about the next modeling steps and the time is limited to do so. Do we expect to find the best use-able or optimal model that way? How to develop near-infrared spectroscopy calibrations in the 21st Century?


Our Solution

Why not put all the knowledge a good model builder is using into software and let the machines do the possibilities of calculations and presenting the result? Designing the software that way, that the domain knowledge is built-in, not just only the algorithms for machine learning and make it possible to scale the calculations to multi-core computers and up to cloud servers. Extend the Chemometric Software with the Domain Knowledge and make as much computer power available as needed.

As it was since the beginning

User  → Chemometric Software → one Computer → some results to choose from

==> User’s time needed to click-and-wait for creating results

Our Solution

User → (Domain Knowledge → automatized Chemometric Software) → many Computers → the best models

==> User’s time used to study the best models and reasoning about his product / process

Note that the “Domain Knowledge” here does perfectly support the User’s product and process knowledge to get the things done right and efficient.


Scaling at three layers

  • Knowledge : use the domain knowledge to drive the Chemometric Software
  • Chemometric Software : support many machine learning algorithms and data pre-processings and make it automatic
  • Computer : support multi-core calculations and scale it to the cloud

The hard part in doing this, is of course the aggregation of the needed domain knowledge and transform it into software. The Domain Knowledge for building Chemometric NIR Spectroscopic models is well known and it’s huge and spreads multiple disciplines. Knowledge-driven software for computing helps to find the gold needle in the haystacks. It’s all about scaling that makes it possible. See Proof of Concept.


New possibilities

  • NIR users can get help working more efficient and getting better models.
  • New types of applications for NIR can be discovered.
  • Evaluation of NIR Applications to replace conventional analytical methods.
  • Hopeless calibrations development efforts can be re-started.
  • Higher model accuracy and robustness can be delivered.
  • Automate the experimental data part of your application study.
  • Person independent optimization will show new solutions, because it’s not limited by a single mindset => combining all the aggregated knowledge and its combinations.
  • Software independent optimization will show new solutions, because none of vendor specific limitations and missing algorithms are present => combining all open available algorithms and there permutations.
  • Computing service is included.

Contact us for trial

Your NIR data is modeled by thousands of different useful calibration models and you get the best of them! That was not possible before in such a easy and fast way! See How it works

Benefit

The NIR Calibration service offers the following benefit: Saving money
  • Improving the accuracy and reliability of already used NIR calibration models have high potential in various manufacturing processes as well as in quality assurance.
  • increased accuracy of analysis => better control of the production process => optimum process flow => better quality => less waste => more throughput.
  • quick and inexpensive to create professional NIR calibration models.
  • relief of their own staff
Time savings
  • for data cleaning (increasing data quality) – missing data, outlier search, wrong data (conflicting information), outlier removal
  • for the search for the optimal NIR model parameter settings (calibration set, wavelength selection, data pretreatments, factor selection)
  • for the calculation of different variations of the model
  • for the validation, evaluation and selection of the optimal model (error, SEP, RMSEP, RMSEC, RPD, fit, R2, bias, slope, …)
  • time-consuming calculation of huge calibration models
  • no long trial and error and waiting in the used NIR software until the calibrations seems to work
NIR analytical accuracy
  • higher reliability due to accuracy and robustness of NIR calibration models
  • the possibility of comparison with your own created or already existing or purchased NIR calibrations
  • what performance increase of analytical accuracy is possible
  • improvement of robustness with respect to change of the product matrix and possible instruments drift
Professional NIR calibration models
  • decades of experience in chemometrics for NIR spectroscopy
  • based on theoretical and applied good practice and know-how
  • application of various guidelines and rules
  • application of vendor-independent NIR chemometric software
  • outsourcing of NIR calibration method development and calibration equation maintenance
  • improving the robustness of NIR prediction model
  • avoid traps and pitfalls of the complicated chemometrics
Detailed results
  • The service provides optimal calibration settings for your NIR data.
  • You get full insight into the NIR calibration, as it is produced and detailed statistical values as a performance index assisted with graphics.

NIR Calibration Service

Services and software for data analysis and analytical modeling for spectroscopy.

This NIR calibration service provides the custom development of optimal quantitative NIR calibration models based on your collected NIR and reference data for vendor independent full range NIR spectrometer analyzers (NIR = Near Infra Red spectroscopy) based on chemometric multivariate methods like Partial Least Square Regression (PLS, PLSR) and Principal Component Regression (PCR).

The key points

The NIR calibration model is decisive for the analysis accuracy.

NIR analysis results make the difference.

Near-Infrared Data Modeling Calibration Service

The problems

Imagine how many publications and literature of NIR spectroscopy (JNIRS) and chemometrics (Journal of Chemometrics) is present.

Did you find the time for the right to designate to read, to study, to incorporate them into practice? Do you have all this knowledge at your calibration developments always present, that you consider anything important, the statistical results, interpret them correctly, analyze the graphs accurately and apply all the tips & tricks of optimizing correctly?

We have the solution for you!

We’ll help you to create and optimize your calibrations. You retain complete control. You have your calibration, with our help, himself under control.

You can view the complete calibration of all the settings down to the smallest detail precisely documented and visualized.

You can also make any changes in the settings. This means you remain independent and have the control in your hand.

We will help you for the time-consuming and knowledge-intensive part. You get the best calibration solution and decide for yourself

Try it and see for yourself