Construction of a sustainable model to predict the moisture content of porang powder (Amorphophallus oncophyllus) based on pointed-scan visible near-infrared spectroscopy

Construction of a sustainable model to predict the moisture content of porang powder (Amorphophallus oncophyllus) based on pointed-scan visible near-infrared spectroscopy

The moisture content of porang powder (PP) is an inherent quality parameter. Therefore, several analytical methods, such as oven drying and Karl–Fischer titration, were applied to determine the content. However, these techniques are noted to have various disadvantages, such as being time-consuming,...

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Bibliographic Details
Main Authors: Amanah Hanim Zuhrotul, Rahayoe Sri, Harmayani Eni, Hernanda Reza Adhitama Putra, Khoirunnisaa, Rohmat Ajeng Siti, Lee Hoonsoo
Format: Article
Language:English
Published: De Gruyter 2024-03-01
Series:Open Agriculture
Subjects:
moisture content
machine learning
partial least squares regression
spectroscopy
porang powder
Online Access:https://doi.org/10.1515/opag-2022-0268

Internet

https://doi.org/10.1515/opag-2022-0268

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