Why NIR Method Maintenance?Warum NIR Methoden Wartung?Perché NIR Metodo di manutenzione?


Why do we need periodic recalibration for NIR Spectroscopy?
Why do we need to recalibrate the NIRS method on an ongoing basis?

NIR Spectroscopy requires
extensive application calibration
and validation on an ongoing basis.



NIR Calibrations are based on mathematical models, based on spectral and reference data, and these data sources changes with time due to the following facts:

  • natural biological substances changes by season, weather, origin (continents, country), pollution, evolution of species, genetically changes, related especially to: Food & Feed
  • product production processes change by improvements, process parameters, timing, physical properties, environment, changed raw material variations, different suppliers, related especially to: Pharmacy, Chemistry, Process Analytical Technology (PAT), Quality by Design (QbD)
  • sample preparation changes chopping, grinding, milling, mixing (homogeneous), sieving, numerous effects of variable particle sizes, heating/freezing temperature program (ramp, hold), wet, dry, pressure and density, thickness, aging and contamination of samples between NIR and Lab measurement, air-tight transport cell, weight or volume, see NIR Sample Preparation
  • sample measurement changes measurement cell cleaning, container, glasses, petri glasses, cuvettes, plastic coverage, auto sampler adjustments and sampling plan, positioning, measurement area, fixed vs. moving spot, sample temperature, spectral resolution, apodization method (FT-NIR), number of scans, measurement repeats, averaging with/out outliers
  • reference method changes different method types, different Labs, refinements
  • SOP changes QA/QC procedures
  • instrument / spectrometer changes drifts by temperature and aging of electronic components, aging and defilement (dirt) of reference substances, wavelength accuracy, signal to noise ratio
  • new NIR data is collected continuously and should be used to extend the calibration, fill the matrix gaps, to increase robustness, and in some cases the older data can be faded out.
Because of all these changes, NIR Spectroscopy requires extensive application calibration and validation on an ongoing basis.

It's like the weather forecast models, everything is changing and so the models need to be adjusted. Thankfully for NIR the period is longer than for the weather. But there is an interval, that means the models can not be held frozen and constant if the measurement results should be reliable. NIR requires periodic calibration and maintenance to ensure that it is operating correctly.

Please tell us your NIR Calibration maintenance interval and see how other NIR users do right now. Their are some NIR Guideline recommendations below....

well you should check this again after you have given your vote here:

[yop_poll id="7"]

[yop_poll id="21"]

Recommended Readings:



Related answer to question:
  • What is the reason to deviate NIR results from wet analysis?



Why do we need periodic recalibration for NIR Spectroscopy?
Why do we need to recalibrate the NIRS method on an ongoing basis?

NIR Spectroscopy requires
extensive application calibration
and validation on an ongoing basis.



NIR Calibrations are based on mathematical models, based on spectral and reference data, and these data sources changes with time due to the following facts:

  • natural biological substances changes by season, weather, origin (continents, country), pollution, evolution of species, genetically changes, related especially to: Food & Feed
  • product production processes change by improvements, process parameters, timing, physical properties, environment, changed raw material variations, different suppliers, related especially to: Pharmacy, Chemistry, Process Analytical Technology (PAT), Quality by Design (QbD)
  • sample preparation changes chopping, grinding, milling, mixing (homogeneous), sieving, numerous effects of variable particle sizes, heating/freezing temperature program (ramp, hold), wet, dry, pressure and density, thickness, aging and contamination of samples between NIR and Lab measurement, air-tight transport cell, weight or volume, see NIR Sample Preparation
  • sample measurement changes measurement cell cleaning, container, glasses, petri glasses, cuvettes, plastic coverage, auto sampler adjustments and sampling plan, positioning, measurement area, fixed vs. moving spot, sample temperature, spectral resolution, apodization method (FT-NIR), number of scans, measurement repeats, averaging with/out outliers
  • reference method changes different method types, different Labs, refinements
  • SOP changes QA/QC procedures
  • instrument / spectrometer changes drifts by temperature and aging of electronic components, aging and defilement (dirt) of reference substances, wavelength accuracy, signal to noise ratio
  • new NIR data is collected continuously and should be used to extend the calibration, fill the matrix gaps, to increase robustness, and in some cases the older data can be faded out.
Because of all these changes, NIR Spectroscopy requires extensive application calibration and validation on an ongoing basis.

It's like the weather forecast models, everything is changing and so the models need to be adjusted. Thankfully for NIR the period is longer than for the weather. But there is an interval, that means the models can not be held frozen and constant if the measurement results should be reliable. NIR requires periodic calibration and maintenance to ensure that it is operating correctly.

Please tell us your NIR Calibration maintenance interval and see how other NIR users do right now. Their are some NIR Guideline recommendations below....

well you should check this again after you have given your vote here:

[yop_poll id="7"]

[yop_poll id="21"]

Recommended Readings:



Related answer to question:
  • What is the reason to deviate NIR results from wet analysis?



Why do we need periodic recalibration for NIR Spectroscopy?
Why do we need to recalibrate the NIRS method on an ongoing basis?

NIR Spectroscopy requires
extensive application calibration
and validation on an ongoing basis.



NIR Calibrations are based on mathematical models, based on spectral and reference data, and these data sources changes with time due to the following facts:

  • natural biological substances changes by season, weather, origin (continents, country), pollution, evolution of species, genetically changes, related especially to: Food & Feed
  • product production processes change by improvements, process parameters, timing, physical properties, environment, changed raw material variations, different suppliers, related especially to: Pharmacy, Chemistry, Process Analytical Technology (PAT), Quality by Design (QbD)
  • sample preparation changes chopping, grinding, milling, mixing (homogeneous), sieving, numerous effects of variable particle sizes, heating/freezing temperature program (ramp, hold), wet, dry, pressure and density, thickness, aging and contamination of samples between NIR and Lab measurement, air-tight transport cell, weight or volume, see NIR Sample Preparation
  • sample measurement changes measurement cell cleaning, container, glasses, petri glasses, cuvettes, plastic coverage, auto sampler adjustments and sampling plan, positioning, measurement area, fixed vs. moving spot, sample temperature, spectral resolution, apodization method (FT-NIR), number of scans, measurement repeats, averaging with/out outliers
  • reference method changes different method types, different Labs, refinements
  • SOP changes QA/QC procedures
  • instrument / spectrometer changes drifts by temperature and aging of electronic components, aging and defilement (dirt) of reference substances, wavelength accuracy, signal to noise ratio
  • new NIR data is collected continuously and should be used to extend the calibration, fill the matrix gaps, to increase robustness, and in some cases the older data can be faded out.
Because of all these changes, NIR Spectroscopy requires extensive application calibration and validation on an ongoing basis.

It's like the weather forecast models, everything is changing and so the models need to be adjusted. Thankfully for NIR the period is longer than for the weather. But there is an interval, that means the models can not be held frozen and constant if the measurement results should be reliable. NIR requires periodic calibration and maintenance to ensure that it is operating correctly.

Please tell us your NIR Calibration maintenance interval and see how other NIR users do right now. Their are some NIR Guideline recommendations below....

well you should check this again after you have given your vote here:

[yop_poll id="7"]

[yop_poll id="21"]

Recommended Readings:



Related answer to question:
  • What is the reason to deviate NIR results from wet analysis?


Extend NIR calibrations (re-calibration)NIR Kalibrationen erweitern (Re-Kalibration)

How to extend a NIR calibration with new measured sample spectra and optimize the calibration again? The important thing is not stubbornly cling to the existing chemometric model settings, but to evaluate the whole data set and newly re-modeling, so as to enable better performance. In practice, it is so that new NIR data fill the gaps in the base model, bring in concentration range extensions with them, the raw materials or the process has changed somewhat, and thus a new calibration optimization is certainly useful. Because the added new variations in the data pool generates a totally new picture, so that a different pre-processing and a modified wavelength selection can provide a much better and robust compensation for unwanted effects and increase the overall calibration performance and improve the models accuracy.

Wie soll man bestehende NIR Kalibrationen mit neu gemessenen Spektren zu einer neuen Kalibration vereinen?

Wichtig dabei ist, nicht stur an den Einstellungen des bestehenden chemometrischen Modelles festzuhalten, sondern die ganze Datenmenge neu zu bewerten und neu zu Modellieren, um so bessere Performance zu ermöglichen.

In der Praxis ist es so, dass neue NIR Daten die Lücken im Basismodell stopfen, Konzentrations Bereichs-Erweiterungen mit sich bringen, die Rohstoffe oder der Prozess sich etwas verändert hat und somit eine neu Optimierung sicher sinnvoll ist.

Da die zusätzlichen neuen Variationen im Datenpool ein völlig neues Bild ergeben, so kann eine andere Datenvorbehandlung und eine modifizierte Wellenlängen Auswahl eine viel bessere und robuste Kompensation unerwünschter Effekte bieten und erhöht dadurch auch die gesamte Kalibrierung Performance und verbessert die Modell Genauigkeit.