Standardisation and Calibration Transfer for near Infrared Instruments: A Review

Abstract

Transferring calibrations between near infrared instruments is not always straightforward, even when the instruments are nominally the same. Problems can include both wavelength shifts and differences in absorbance response between instruments. This review describes a number of chemometric methods that have been developed to aid calibration transfer. The approaches are classified under three headings: making robust calibrations, adjusting calibrations and adjusting spectra. Calibrations can be made more robust, and more transferable, by the appropriate use of spectral pre-treatments that reduce between-instrument variability. Robust calibrations can also be made by pooling data from several instruments when calibrating. Calibrations can be adjusted using skew and bias corrections estimated from a modest number of samples with known reference values. Under the third heading, adjusting spectra, come methods such as piecewise direct standardisation and the patented method of Shenk and Westerhaus that use spectral information from samples measured on two instruments to match the spectral response of the instruments.

Soil Organic Carbon Estimation in Croplands by Hyperspectral Remote APEX Data Using the LUCAS Topsoil Database

“…Therefore, the main challenge is to find a method to align laboratory and remote spectral data [45,60]. Many issues need to be addressed for this goal: first of all, it is necessary to consider the different technical characteristics of the two sensors [40], in particular the full width at half maximum (FWHM) response at each band, the spectral sampling interval and the spectral range, which entail a systematic differences between sensors [7,45]. However, when moving from laboratory to field conditions the radiometric resolution and the SNR hamper the alignments of dissimilar spectral outputs, and the atmospheric correction introduces non-systematic or random differences between laboratory and remote spectra.…”

“…Although a consistent number of spectral-transfer procedures were tested between two datasets both composed of laboratory spectra [38][39][40][41][42][43], the transfer between spectra acquired in laboratory conditions to those acquired by remote sensors is a still rare [44,45]. Moreover, in order to find a reliable transfer function, it is mandatory to collect and scan soil samples.…”

Transferência de calibração em métodos multivariados

“…F é estimada com o objetivo de produzir, a partir de um espectro x S registrado para uma nova amostra no equipamento secundário, um espectro ajustado, x a , que se assemelhe ao que seria obtido se a mesma amostra tivesse sido analisada no equipamento primário: ] j . Cada elemento do novo espectro terá, portanto, uma dependência linear simples em relação ao elemento correspondente do espectro original, ou seja, a matriz F ajustará separadamente as medidas em cada comprimento de onda 6 . Se os valores não-nulos de F estiverem localizados em uma diagonal secundária abaixo da diagonal principal, cada elemento ajustado será afetado pelo elemento correspondente ao comprimento de onda seguinte.…”

Simultaneous determination of furosemide and spironolactone in pharmaceutical formulations by spectrophotometric method using principal component regression

“…Recently, multivariate calibration methods appear to be the proper techniques that show the best performance for complex mixture resolution (Vigneau et al, 1997;Massart et al, 1998;Lavine 2000;Haaland et al, 2000;Fearn, 2001;Brereton, 2003;Geladi, 2003;Ragno et al, 2004 One major use of PCR lies in overcoming the multicollinearity problem which arises when two or more of the explanatory variables are close to being collinear. PCR can aptly deal with such situations by excluding some of the lowvariance principal components in the regression step.…”