Correction: Hyperspectral technology and machine learning models to estimate the fruit quality parameters of mango and strawberry crops

Authors

Abdallah Elshawadfy Elwakeel (ORCID: https://orcid.org/0000-0002-9360-051X)
Osama Elsherbiny (ORCID: https://orcid.org/0000-0003-3031-7108)
Hoda Galal (ORCID: https://orcid.org/0000-0003-2563-5865)
Ahmed Elbeltagi (ORCID: https://orcid.org/0000-0002-5506-9502)
Mohamed S. Abd El-baki
Nadia G. Abd El-Fattah
Ali Salem
Mohamed Hoodh Ibrahim
Salah Elsayed

Publication Details

Journal: PLoS ONE
Published: 2026-03-12
DOI: https://doi.org/10.1371/journal.pone.0345011
Primary Topic: Spectroscopy and Chemometric Analyses
Type: article
Field-Weighted Citation Impact: 0.00

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article

Correction: Hyperspectral technology and machine learning models to estimate the fruit quality parameters of mango and strawberry crops

Abdallah Elshawadfy Elwakeel, Osama Elsherbiny, Hoda Galal, Ahmed Elbeltagi et al.

Mar 12, 2026

PLoS ONE

Spectroscopy and Chemometric Analyses

article

Correction: Hyperspectral technology and machine learning models to estimate the fruit quality parameters of mango and strawberry crops

Abdallah Elshawadfy Elwakeel, Osama Elsherbiny, Hoda Galal, Ahmed Elbeltagi, Mohamed S. Abd El-baki, Nadia G. Abd El-Fattah, Ali Salem, Mohamed Hoodh Ibrahim, Salah Elsayed

March 12, 2026article en

Abstract

No abstract available for this paper.

PLoS ONEVol. 21(3)

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Spectroscopy and Chemometric Analyses

DOI Open Access PDF OpenAlex

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Correction: Hyperspectral technology and machine learning models to estimate the fruit quality parameters of mango and strawberry crops — Abdallah Elshawadfy Elwakeel, Osama Elsherbiny, et al. · PLoS ONE (2026) | TGRS Research Map | TGRS