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dc.contributor.authorPhonkrit Maniwaraen_US
dc.contributor.authorKazuhiro Nakanoen_US
dc.contributor.authorDanai Boonyakiaten_US
dc.contributor.authorShintaroh Ohashien_US
dc.contributor.authorMasaru Hiroien_US
dc.contributor.authorTadahiro Tohyamaen_US
dc.date.accessioned2018-09-04T09:44:07Z-
dc.date.available2018-09-04T09:44:07Z-
dc.date.issued2014-01-01en_US
dc.identifier.issn02608774en_US
dc.identifier.other2-s2.0-84904277283en_US
dc.identifier.other10.1016/j.jfoodeng.2014.06.028en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84904277283&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/53133-
dc.description.abstractVisible and short-wave near infrared spectroscopy (Vis/SWNIRS) was investigated using a non-destructive method for evaluating passion fruit quality. In this study, interactance and transmission measurements were performed and their competences were compared. Prediction models of soluble solids content (SSC), titratable acidity (TA), ascorbic acid content (ASC), ethanol concentration (EtOH), peel firmness (PF) and pulp percentage (PP) were developed based on multivariate methods of partial least square regression (PLSR) analysis. The PLS models from interactance measurements provided better prediction results than the transmission technique. The best model was obtained from interactance SSC calibration with a correlation coefficient between measured and predicted values (R) of 0.923. Furthermore, the PLS models generated from interactance and transmission spectra also provided satisfactorily prediction results for EtOH, PF and PP. However, all calibrations failed to predict ASC by providing low correlations and high root mean square errors of prediction (RMSEP). © 2014 Elsevier Ltd. All rights reserved.en_US
dc.subjectAgricultural and Biological Sciencesen_US
dc.titleThe use of visible and near infrared spectroscopy for evaluating passion fruit postharvest qualityen_US
dc.typeJournalen_US
article.title.sourcetitleJournal of Food Engineeringen_US
article.volume143en_US
article.stream.affiliationsNiigata Universityen_US
article.stream.affiliationsChiang Mai Universityen_US
article.stream.affiliationsKaisei Co., Ltd.en_US
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