Prediction of ‘Nules Clementine’ mandarin susceptibility to rind breakdown disorder using Vis/NIR spectroscopy

Show simple item record

dc.contributor.author Magwaza, Lembe S.
dc.contributor.author Opara, Umezuruike Linus
dc.contributor.author Terry, Leon A.
dc.contributor.author Landahl, Sandra
dc.contributor.author Cronje, Paul J.
dc.contributor.author Nieuwoudt, Helene
dc.contributor.author Mouazen, Abdul Mounem
dc.contributor.author Saeys, Wouter
dc.contributor.author Nicolai, Bart M.
dc.date.accessioned 2016-05-20T11:14:18Z
dc.date.available 2016-05-20T11:14:18Z
dc.date.issued 2012-07-15
dc.identifier.citation Lembe S. Magwaza, Umezuruike Linus Opara, Leon A. Terry, Sandra Landahl, Paul J. Cronje, Hélène Nieuwoudt, Abdul Mounem Mouazen, Wouter Saeys, Bart M. Nicolaï, Prediction of ‘Nules Clementine’ mandarin susceptibility to rind breakdown disorder using Vis/NIR spectroscopy, Postharvest Biology and Technology, Volume 74, December 2012, Pages 1-10 en_UK
dc.identifier.issn 0925-5214
dc.identifier.uri http://dx.doi.org/10.1016/j.postharvbio.2012.06.007
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/9905
dc.description.abstract The use of diffuse reflectance visible and near infrared (Vis/NIR) spectroscopy was explored as a non-destructive technique to predict ‘Nules Clementine’ mandarin fruit susceptibility to rind breakdown (RBD) disorder by detecting rind physico-chemical properties of 80 intact fruit harvested from different canopy positions. Vis/NIR spectra were obtained using a LabSpec® spectrophotometer. Reference physico-chemical data of the fruit were obtained after 8 weeks of storage at 8 °C using conventional methods and included RBD, hue angle, colour index, mass loss, rind dry matter, as well as carbohydrates (sucrose, glucose, fructose, total carbohydrates), and total phenolic acid concentrations. Principal component analysis (PCA) was applied to analyse spectral data to identify clusters in the PCA score plots and outliers. Partial least squares (PLS) regression was applied to spectral data after PCA to develop prediction models for each quality attribute. The spectra were subjected to a test set validation by dividing the data into calibration (n = 48) and test validation (n = 32) sets. An extra set of 40 fruit harvested from a different part of the orchard was used for external validation. PLS-discriminant analysis (PLS-DA) models were developed to sort fruit based on canopy position and RBD susceptibility. Fruit position within the canopy had a significant influence on rind biochemical properties. Outside fruit had higher rind carbohydrates, phenolic acids and dry matter content and lower RBD index than inside fruit. The data distribution in the PCA and PLS-DA models displayed four clusters that could easily be identified. These clusters allowed distinction between fruit from different preharvest treatments. NIR calibration and validation results demonstrated that colour index, dry matter, total carbohydrates and mass loss were predicted with significant accuracy, with residual predictive deviation (RPD) for prediction of 3.83, 3.58, 3.15 and 2.61, respectively. The good correlation between spectral information and carbohydrate content demonstrated the potential of Vis/NIR as a non-destructive tool to predict fruit susceptibility to RBD. en_UK
dc.language.iso en en_UK
dc.publisher Elsevier en_UK
dc.rights Attribution-Non-Commercial-No Derivitives 3.0 Unported (CC BY-NC-ND 3.0). You are free to: Share — copy and redistribute the material in any medium or format. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. Information: Non-Commercial — You may not use the material for commercial purposes. No Derivatives — If you remix, transform, or build upon the material, you may not distribute the modified material. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits. en_UK
dc.rights “NOTICE: this is the author’s version of a work that was accepted for publication in Postharvest Biology and Technology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Postharvest Biology and Technology, VOL 74, 15/07/2012, DOI: 10.1016/j.postharvbio.2012.06.007” en_UK
dc.subject Non-destructive en_UK
dc.subject Vis/near infrared spectroscopy en_UK
dc.subject Rind breakdown disorder en_UK
dc.subject RBD en_UK
dc.subject Citrus en_UK
dc.subject Nules clementine en_UK
dc.subject Mandarin en_UK
dc.subject Canopy position en_UK
dc.title Prediction of ‘Nules Clementine’ mandarin susceptibility to rind breakdown disorder using Vis/NIR spectroscopy en_UK
dc.type Article en_UK


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search CERES


Browse

My Account

Statistics