Interpreting the variation in particle size of ground spice by high-resolution visual and spectral imaging: A ginger case study

Qing Han; Joseph Peller; Sara W. Erasmus; Christopher T. Elliott; Saskia M. van Ruth

doi:10.1016/j.foodres.2023.113023

Interpreting the variation in particle size of ground spice by high-resolution visual and spectral imaging: A ginger case study

Qing Han, Joseph Peller, Sara W. Erasmus, Christopher T. Elliott, Saskia M. van Ruth^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

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Abstract

High-resolution (HR) visual imaging and spectral imaging are common computer vision-based techniques used for food quality analysis and/or authentication based on the interaction of light and material surface and/or composition. The particle size of ground spices is an important morphological feature that affects the physico-chemical properties of food products containing such particles. This study aimed to interpret the impact of particle size of ground spice on its HR visual profile and spectral imaging profile using ginger powder as a representative spice powder model. The results revealed an increase in the light reflection with the decrease of particle size of ginger powder, which was manifested by the lighter colour (higher percentage of the colour code with lighter yellow colour) of the HR visual image and stronger reflection with spectral imaging. The study also revealed that, in spectral imaging, the influence of the particle size of ginger powder increased with rising wavelengths. Finally, the results indicated a relationship between spectral wavelengths, ginger particle size, and other natural variables of the products which might be generated from cultivation to processing. Ultimately, the impact of natural variables arising during the food production process on the physico-chemical properties of the product should be fully considered or even additionally evaluated prior to the application of specific food quality and/or authentication analytical techniques.

Original language	English
Article number	113023
Journal	Food Research International
Volume	170
Early online date	25 May 2023
DOIs	https://doi.org/10.1016/j.foodres.2023.113023
Publication status	Published - Aug 2023

Bibliographical note

Funding Information:
This work was supported by China Scholarship Council (grant agreement No. 201903250123) and the EU-China-Safe project (https://www.euchinasafe.eu/) which is funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 727864. Any opinions, findings and conclusions or recommendations expressed in this material are that of the authors and the European Commission does not accept any liability in this regard. The authors gratefully acknowledge all the companies for their participation in the study. We would like to thank our colleagues Zhijun Wang and Hongwei Yu from Food Quality and Design group, Wageningen University & Research for their great help in data analysis. We would also like to thank Thirza Sinke under the Master programme, Food Technology, Wageningen University & Research for her creative understanding and ideas for this study.

Funding Information:
This work was supported by China Scholarship Council (grant agreement No. 201903250123) and the EU-China-Safe project (https://www.euchinasafe.eu/) which is funded by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 727864. Any opinions, findings and conclusions or recommendations expressed in this material are that of the authors and the European Commission does not accept any liability in this regard. The authors gratefully acknowledge all the companies for their participation in the study. We would like to thank our colleagues Zhijun Wang and Hongwei Yu from Food Quality and Design group, Wageningen University & Research for their great help in data analysis. We would also like to thank Thirza Sinke under the Master programme, Food Technology, Wageningen University & Research for her creative understanding and ideas for this study.

Publisher Copyright:
© 2023 The Author(s)

Keywords

Food authenticity
Food powder
Food quality
High-resolution picture
Morphology
Near-infrared reflectance

ASJC Scopus subject areas

Food Science

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Interpreting the variation in particle size of ground spice by high-resolution visual and spectral imaging: A ginger case study
Copyright 2023 the authors. This is an open access article published under a Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits distribution and reproduction for non-commercial purposes, provided the author and source are cited.
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Cite this

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title = "Interpreting the variation in particle size of ground spice by high-resolution visual and spectral imaging: A ginger case study",

abstract = "High-resolution (HR) visual imaging and spectral imaging are common computer vision-based techniques used for food quality analysis and/or authentication based on the interaction of light and material surface and/or composition. The particle size of ground spices is an important morphological feature that affects the physico-chemical properties of food products containing such particles. This study aimed to interpret the impact of particle size of ground spice on its HR visual profile and spectral imaging profile using ginger powder as a representative spice powder model. The results revealed an increase in the light reflection with the decrease of particle size of ginger powder, which was manifested by the lighter colour (higher percentage of the colour code with lighter yellow colour) of the HR visual image and stronger reflection with spectral imaging. The study also revealed that, in spectral imaging, the influence of the particle size of ginger powder increased with rising wavelengths. Finally, the results indicated a relationship between spectral wavelengths, ginger particle size, and other natural variables of the products which might be generated from cultivation to processing. Ultimately, the impact of natural variables arising during the food production process on the physico-chemical properties of the product should be fully considered or even additionally evaluated prior to the application of specific food quality and/or authentication analytical techniques.",

keywords = "Food authenticity, Food powder, Food quality, High-resolution picture, Morphology, Near-infrared reflectance",

author = "Qing Han and Joseph Peller and Erasmus, {Sara W.} and Elliott, {Christopher T.} and {van Ruth}, {Saskia M.}",

note = "Funding Information: This work was supported by China Scholarship Council (grant agreement No. 201903250123) and the EU-China-Safe project (https://www.euchinasafe.eu/) which is funded by the European Union{\textquoteright}s Horizon 2020 research and innovation programme under grant agreement No. 727864. Any opinions, findings and conclusions or recommendations expressed in this material are that of the authors and the European Commission does not accept any liability in this regard. The authors gratefully acknowledge all the companies for their participation in the study. We would like to thank our colleagues Zhijun Wang and Hongwei Yu from Food Quality and Design group, Wageningen University & Research for their great help in data analysis. We would also like to thank Thirza Sinke under the Master programme, Food Technology, Wageningen University & Research for her creative understanding and ideas for this study. Funding Information: This work was supported by China Scholarship Council (grant agreement No. 201903250123) and the EU-China-Safe project (https://www.euchinasafe.eu/) which is funded by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 727864. Any opinions, findings and conclusions or recommendations expressed in this material are that of the authors and the European Commission does not accept any liability in this regard. The authors gratefully acknowledge all the companies for their participation in the study. We would like to thank our colleagues Zhijun Wang and Hongwei Yu from Food Quality and Design group, Wageningen University & Research for their great help in data analysis. We would also like to thank Thirza Sinke under the Master programme, Food Technology, Wageningen University & Research for her creative understanding and ideas for this study. Publisher Copyright: {\textcopyright} 2023 The Author(s)",

year = "2023",

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doi = "10.1016/j.foodres.2023.113023",

language = "English",

volume = "170",

journal = "Food Research International",

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AU - Han, Qing

AU - Peller, Joseph

AU - Erasmus, Sara W.

AU - Elliott, Christopher T.

AU - van Ruth, Saskia M.

N1 - Funding Information: This work was supported by China Scholarship Council (grant agreement No. 201903250123) and the EU-China-Safe project (https://www.euchinasafe.eu/) which is funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 727864. Any opinions, findings and conclusions or recommendations expressed in this material are that of the authors and the European Commission does not accept any liability in this regard. The authors gratefully acknowledge all the companies for their participation in the study. We would like to thank our colleagues Zhijun Wang and Hongwei Yu from Food Quality and Design group, Wageningen University & Research for their great help in data analysis. We would also like to thank Thirza Sinke under the Master programme, Food Technology, Wageningen University & Research for her creative understanding and ideas for this study. Funding Information: This work was supported by China Scholarship Council (grant agreement No. 201903250123) and the EU-China-Safe project (https://www.euchinasafe.eu/) which is funded by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 727864. Any opinions, findings and conclusions or recommendations expressed in this material are that of the authors and the European Commission does not accept any liability in this regard. The authors gratefully acknowledge all the companies for their participation in the study. We would like to thank our colleagues Zhijun Wang and Hongwei Yu from Food Quality and Design group, Wageningen University & Research for their great help in data analysis. We would also like to thank Thirza Sinke under the Master programme, Food Technology, Wageningen University & Research for her creative understanding and ideas for this study. Publisher Copyright: © 2023 The Author(s)

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N2 - High-resolution (HR) visual imaging and spectral imaging are common computer vision-based techniques used for food quality analysis and/or authentication based on the interaction of light and material surface and/or composition. The particle size of ground spices is an important morphological feature that affects the physico-chemical properties of food products containing such particles. This study aimed to interpret the impact of particle size of ground spice on its HR visual profile and spectral imaging profile using ginger powder as a representative spice powder model. The results revealed an increase in the light reflection with the decrease of particle size of ginger powder, which was manifested by the lighter colour (higher percentage of the colour code with lighter yellow colour) of the HR visual image and stronger reflection with spectral imaging. The study also revealed that, in spectral imaging, the influence of the particle size of ginger powder increased with rising wavelengths. Finally, the results indicated a relationship between spectral wavelengths, ginger particle size, and other natural variables of the products which might be generated from cultivation to processing. Ultimately, the impact of natural variables arising during the food production process on the physico-chemical properties of the product should be fully considered or even additionally evaluated prior to the application of specific food quality and/or authentication analytical techniques.

AB - High-resolution (HR) visual imaging and spectral imaging are common computer vision-based techniques used for food quality analysis and/or authentication based on the interaction of light and material surface and/or composition. The particle size of ground spices is an important morphological feature that affects the physico-chemical properties of food products containing such particles. This study aimed to interpret the impact of particle size of ground spice on its HR visual profile and spectral imaging profile using ginger powder as a representative spice powder model. The results revealed an increase in the light reflection with the decrease of particle size of ginger powder, which was manifested by the lighter colour (higher percentage of the colour code with lighter yellow colour) of the HR visual image and stronger reflection with spectral imaging. The study also revealed that, in spectral imaging, the influence of the particle size of ginger powder increased with rising wavelengths. Finally, the results indicated a relationship between spectral wavelengths, ginger particle size, and other natural variables of the products which might be generated from cultivation to processing. Ultimately, the impact of natural variables arising during the food production process on the physico-chemical properties of the product should be fully considered or even additionally evaluated prior to the application of specific food quality and/or authentication analytical techniques.

KW - Food authenticity

KW - Food powder

KW - Food quality

KW - High-resolution picture

KW - Morphology

KW - Near-infrared reflectance

U2 - 10.1016/j.foodres.2023.113023

DO - 10.1016/j.foodres.2023.113023

M3 - Article

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SN - 0963-9969

VL - 170

JO - Food Research International

JF - Food Research International

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Interpreting the variation in particle size of ground spice by high-resolution visual and spectral imaging: A ginger case study

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

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