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DC Field | Value | Language |
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dc.contributor.author | Phonkrit Maniwara | en_US |
dc.contributor.author | Kazuhiro Nakano | en_US |
dc.contributor.author | Danai Boonyakiat | en_US |
dc.contributor.author | Shintaroh Ohashi | en_US |
dc.contributor.author | Masaru Hiroi | en_US |
dc.contributor.author | Tadahiro Tohyama | en_US |
dc.date.accessioned | 2018-09-04T09:44:07Z | - |
dc.date.available | 2018-09-04T09:44:07Z | - |
dc.date.issued | 2014-01-01 | en_US |
dc.identifier.issn | 02608774 | en_US |
dc.identifier.other | 2-s2.0-84904277283 | en_US |
dc.identifier.other | 10.1016/j.jfoodeng.2014.06.028 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84904277283&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/53133 | - |
dc.description.abstract | Visible 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.subject | Agricultural and Biological Sciences | en_US |
dc.title | The use of visible and near infrared spectroscopy for evaluating passion fruit postharvest quality | en_US |
dc.type | Journal | en_US |
article.title.sourcetitle | Journal of Food Engineering | en_US |
article.volume | 143 | en_US |
article.stream.affiliations | Niigata University | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
article.stream.affiliations | Kaisei Co., Ltd. | en_US |
Appears in Collections: | CMUL: Journal Articles |
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