Non-destructive methods for mango ripening prediction: Visible and near[1]infrared spectroscopy (visNIRS) and laser Doppler vibrometry (LDV): Data

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dc.contributor.authordel carmen Alamar Gavidia, Maria
dc.contributor.authorO'Brien, Ciara
dc.contributor.authorFalagan Sama, Natalia
dc.contributor.authorLandahl, Sandra
dc.contributor.authorTerry, Leon
dc.contributor.authorKourmpetli, Sofia
dc.date.accessioned2024-06-10T05:56:01Z
dc.date.available2024-06-10T05:56:01Z
dc.date.issued2024-03-12 09:10
dc.description.abstractThis data set includes reference measurements (firmness, colour [lightness, chroma and hue angle], total soluble solids [TSS], individual sugar concentrations [glucose, fructose, sucrose]), as well as visible and near-infrared spectroscopic (vis-NIRS) data (nm) and resonant frequency measured by laser Doppler vibroemetry (LDV) on 'Keitt' and 'Kent' mango fruit.
dc.description.sponsorshipThis work was funded by Orchard House Foods Ltd. and Cranfield University through the Cranfield Industrial Partnership PhD Scheme.
dc.identifier.citationAlamar Gavidia, Maria del carmen; O'Brien, Ciara; Falagan Sama, Natalia; Landahl, Sandra; Terry, Leon; Kourmpetli, Sofia (2024). Non-destructive methods for mango ripening prediction: Visible and near[1]infrared spectroscopy (visNIRS) and laser Doppler vibrometry (LDV): Data. Cranfield Online Research Data (CORD). Dataset. https://doi.org/10.17862/cranfield.rd.25381456
dc.identifier.doi10.17862/cranfield.rd.25381456
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/22352
dc.publisherCranfield University
dc.rightsCC BY 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectMangifera indica'
dc.subject'Firmness'
dc.subject'Food loss'
dc.subject'chemometrics methods'
dc.subject'resonant frequency'
dc.subject'postharvest'
dc.titleNon-destructive methods for mango ripening prediction: Visible and near[1]infrared spectroscopy (visNIRS) and laser Doppler vibrometry (LDV): Data
dc.typeDataset

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