Factors influencing near infrared spectroscopy analysis of agro-products: a review

Abstract

The near infrared (NIR) spectroscopy technique has wide applications in agriculture with the advantages of being nondestructive, sensitive, safe and rapid. However, there are still more than 40 error sources influencing the robustness and accuracy of its calibration and operation. Environmental, sample and instrument factors that influence the analysis are discussed in this review, including temperature, humidity and other factors that introduce uncertainty. Error sources from livestock products, fruit and vegetables, which are the most common objects in the field of NIR analysis, are also emphasized in the second part. In addition, studies utilizing different instruments, spectral pretreatments, variable selection methods, wavelength ranges, detection modes and calibration methods are tabulated to illustrate the complications they introduce and how they influence NIR analysis. It is suggested that large scale of data with abundant varieties can be used to build a more robust calibration model, in order to improve the robustness and accuracy of the NIR analytical model, and overcome problems caused by confining analysis to too many uniform samples.

Keywords

agro-product / error source / influence factor / near infrared spectroscopy

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Acknowledgements

The authors gratefully acknowledge the financial support provided by the Science and Technology Cooperation Project between Hong Kong, Macao and Taiwan (2015DFT30150).

Compliance with ethics guidelines

Xiao Xu, Lijuan Xie, and Yibin Ying declare that they have no conflicts of interest or financial conflicts to disclose. This article is a review and does not contain any studies with human or animal subjects performed by any of the authors.

RIGHTS & PERMISSIONS

The Author(s) 2019. Published by Higher Education Press. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0)