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Non-invasive prediction of maca powder adulteration using a pocket-sized spectrophotometer and machine learning techniques

Published Online: 2024-05-07

Authors

Zaukuu, John-Lewis Zinia

Adams, Zeenatu Suglo

Donkor-Boateng, Nana Ama

Mensah, Eric Tetteh

Bimpong, Donald

Amponsah, Lois Adofowaa
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Text and Data Mining valid from 2024-05-07

Version of Record valid from 2024-05-07
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Article History

Received: 8 February 2024

Accepted: 2 May 2024

First Online: 7 May 2024

Competing interests

: The authors state that they have no known conflicting financial interests or personal ties that may have seemed to affect the work presented in this study.

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