A supervised machine learning approach for the prediction of antioxidant activities of Amaranthus viridis seed

Author:

Olawoye BabatundeORCID,Fagbohun Oladapo Fisoye,Popoola-Akinola Oyekemi,Akinsola Jide Ebenezer Taiwo,Akanbi Charles Taiwo

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference24 articles.

1. Multivariate analyses of selected trace elements from Kigelia africana (Lam.) Benth. plant by ICP-OES: a chemometrics approach;Fagbohun;Journal of Trace Elements and Minerals,2023

2. Antimicrobial, antioxidant and phyto-chemicals from fruit and vegetable wastes: a review;Joshi;Int. J. Food Ferment. Technol.,2012

3. Antioxidant activity of Amaranthus species from the Amaranthaceae family–A review;Adegbola;South Afr. J. Bot.,2020

4. Nutritional constituents of pseudo cereals and their potential use in food systems: a review;Mir;Trends Food Sci. Technol.,2018

5. Development of Gluten-free Pasta Using Amaranth Flour and Pea Protein Flour;Gupta,2019

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