dc.creator | Teixeira Badaró, Amanda | es |
dc.creator | García-Martín, Juan Francisco | es |
dc.creator | López Barrera, María del Carmen | es |
dc.creator | Barbin, Douglas Fernandes | es |
dc.creator | Álvarez-Mateos, María Paloma | es |
dc.date.accessioned | 2022-12-09T13:10:31Z | |
dc.date.available | 2022-12-09T13:10:31Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Teixeira Badaró, A., García-Martín, J.F., López Barrera, M.d.C., Barbin, D. F. y Álvarez-Mateos, M.P. (2020). Determination of pectin content in orange peels by near infrared hyperspectral imaging. Food Chemistry, 323, 126861. https://doi.org/10.1016/j.foodchem.2020.126861. | |
dc.identifier.issn | 0308-8146 | es |
dc.identifier.uri | https://hdl.handle.net/11441/140271 | |
dc.description.abstract | Pectin has several purposes in the food and pharmaceutical industry making its quantification important for
further extraction. Current techniques for pectin quantification require its extraction using chemicals and pro-
ducing residues. Determination of pectin content in orange peels was investigated using near infrared hyper-
spectral imaging (NIR-HSI). Hyperspectral images from orange peel (140 samples) with different amounts of
pectin were acquired in the range of 900–2500 nm, and the spectra was used for calibration models using
multivariate statistical analyses. Principal component analysis (PCA) and linear discriminant analysis (LDA)
showed better results considering three groups: low (0–5%), intermediate (10–40%) and high (50–100%) pectin
content. Partial least squares regression (PLSR) models based on full spectra showed higher precision
(R2 > 0.93) than those based on few selected wavelengths (R2 between 0.92 and 0.94). The results demonstrate
the potential of NIR-HSI to quantify pectin content in orange peels, providing a valuable technique for orange
producers and processing industries. | es |
dc.description.sponsorship | Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) – Finance Code 001 | es |
dc.format | application/pdf | es |
dc.format.extent | 9 p. | es |
dc.language.iso | eng | es |
dc.publisher | Elsevier | es |
dc.relation.ispartof | Food Chemistry, 323, 126861. | |
dc.rights | Atribución-CompartirIgual 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-sa/4.0/ | * |
dc.subject | Principal component analysis | es |
dc.subject | Linear discriminant analysis | es |
dc.subject | Partial least squares regression, near infrared spectra | es |
dc.subject | Agriculture | es |
dc.title | Determination of pectin content in orange peels by near infrared hyperspectral imaging | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ingeniería Química | es |
dc.relation.projectID | CAPES-Finance Code 001 | es |
dc.relation.publisherversion | https://doi.org/10.1016/j.foodchem.2020.126861 | es |
dc.identifier.doi | 10.1016/j.foodchem.2020.126861 | es |
dc.journaltitle | Food Chemistry | es |
dc.publication.volumen | 323 | es |
dc.publication.initialPage | 126861 | es |
dc.contributor.funder | Coordenação de Aperfeiçoamento de Pessoal de Nivel Superior. Brasil | es |