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Chemometrics

Improved calibration transfer between near-Infrared (NIR) spectrometers using canonical correlation analysis

, , , , , & show all
Pages 2188-2202 | Received 08 Dec 2018, Accepted 03 Apr 2019, Published online: 24 Apr 2019
 

Abstract

The application of mobile near-infrared (NIR) spectrometers in field measurements is growing. Calibration transfer techniques offer simple solutions for enabling models constructed on benchtop instruments for use on mobile spectrometers. Since different types of spectrometers with different components, scanning ranges and resolutions cause great differences in the spectral response, calibration transfer is difficult to apply. In this paper, we focus on calibration transfer among benchtop, portable and handheld spectrometers by a method of calibration transfer based on canonical correlation analysis (CTCCA). Its capability was illustrated by the example of a group of NIR spectra dataset for predicting reducing sugars, total sugar, and nicotine contents in tobacco leaves. The experimental results showed that the transferability of CTCCA was superior to other conventional calibration transfer methods, including piecewise direct standardization, spectral space transformation, calibration transfer based on independent component analysis, and calibration transfer based on the weight matrix. Moreover, the best transfer results were obtained in the three cases by canonical correlation analysis method executing transfer while the spectra were not interpolated, which shows that this approach has the advantage of easy implementation for calibration transfer. Therefore, CTCCA without interpolation calculation offers a new and simple solution for transferring the spectra acquired by mobile spectrometers to the optimized spectral models built on benchtop devices to improve the accuracy of the results. Additionally, the results show that the benchtop spectrometer is more suitable as the master instrument for calibration transfer with more accurate prediction than using a portable device as the master.

Disclosure statement

The authors report there are no conflicts of interest.

Additional information

Funding

This work is financially supported by the Base Unit Project of China Tobacco Zhejiang Industry (Grant No. 2017330000341485).

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