Standardisation and Calibration Transfer for near Infrared Instruments: A Review

By Tom Fearn. 2001

240 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Analytical Chemistry, Biophysics

View Paper: https://www.semanticscholar.org/paper/e36d6e77dc44e1c528554752a26cb51b47deb561

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. E. Woltering
2. Ramin Nikzad‐Langerodi
3. Puneet Mishra
4. Jean-Michel Roger
5. Douglas N. Rutledge

In Analytical Chemistry

1. Ramin Nikzad‐Langerodi
2. Puneet Mishra
3. E. Woltering
4. Jean-Michel Roger
5. Douglas N. Rutledge

In Biophysics

1. Puneet Mishra
2. E. Woltering
3. Ramin Nikzad‐Langerodi
4. Jean-Michel Roger
5. Douglas N. Rutledge

Citations in the corpus

• Partial least square regression versus domain invariant partial least square regression with application to near-infrared spectroscopy of fresh fruit (2020, background): “In the case of different instruments, the differences could be due to different detector sensitivities, light source and calibration of the detectors [30,31].”
• Two standard-free approaches to correct for external influences on near-infrared spectra to make models widely applicable (2020, methodology): “Calibration transfer is also a widely explored domain in NIR spectroscopy where a model developed on one instrument needs to be transferred to a different instrument (Fearn, 2001; Feudale et al., 2002; Nicolai et al., 2007; Saeys et al., 2019).”