A Simple Method of Instrument Standardisation for a near Infrared Sorting Machine: The Utilisation of Average Spectra as Input Vectors

Abstract

A new concept of spectral adjustment was examined to solve the problem of calibration transfer in a near infrared (NIR) sweetness sorting machine. Instead of pairing the absorbance values of each sample measured by master and slave instrument, the average spectrum of each instrument was used. Two identical NIR instruments, equipped with interactance fibre optics, were used as model instruments and a calibration equation for Brix determination of apples was developed as a model calibration. For each instrument, master and slave, each average spectrum was calculated from the spectra of an identical group of apples and then spectral matching of the slave instrument to the master was performed. The curve fitting method, either linear regression or polynomial, could not work well. However, by adding the difference spectrum, the differences of average absorbance values at wavelength i between the master and slave instruments, the spectrum of each sample measured by the slave instrument could successfully standardise the slave instrument. The matching was successfully done by adding the difference spectrum between the two average spectra to the slave instrument's spectra. It was found that the method could be used to compensate for both the wavelength shift and photometric change and it also proved that the method was applicable for both multiple linear regression and partial least squares equations.