Modelling the relationship between peel colour and the quality of fresh mango fruit using Random Forests

Mango (Mangifera indica L.) is one of the major tropical fruits exported through long supply chains to export markets. Production of high quality fruits and monitoring postharvest changes during storage and transport are thus primary concerns for exporters to ensure the premium value of fresh mango...

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Main Authors: Fukuda S., Yasunaga E., Nagle M., Yuge K., Sardsud V., Spreer W., Muller J.
Format: Article
Language:English
Published: 2014
Online Access:http://www.scopus.com/inward/record.url?eid=2-s2.0-84893726481&partnerID=40&md5=d2960ae54c1b464fac99803fb6948d4b
http://cmuir.cmu.ac.th/handle/6653943832/7394
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Institution: Chiang Mai University
Language: English
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spelling th-cmuir.6653943832-73942014-08-30T04:00:56Z Modelling the relationship between peel colour and the quality of fresh mango fruit using Random Forests Fukuda S. Yasunaga E. Nagle M. Yuge K. Sardsud V. Spreer W. Muller J. Mango (Mangifera indica L.) is one of the major tropical fruits exported through long supply chains to export markets. Production of high quality fruits and monitoring postharvest changes during storage and transport are thus primary concerns for exporters to ensure the premium value of fresh mango fruit after distribution. This study aims to demonstrate the applicability of Random Forests (RF) for estimating the internal qualities of mango based on peel colour. Two cultivars, namely Nam Dokmai and Irwin, having different fruit properties and grown in intensively managed orchards in Thailand and Japan, respectively, were used in this study. Postharvest changes in peel colour and fruit quality were observed under three storage conditions with respect to temperature. RF models were applied to establish a relationship between peel colour and fruit quality, and then tested the applicability based on model accuracy and variable importance computed by the RF. Specifically, this work demonstrates how the variable importance can be used to interpret the model results. The high accuracy and the information retrieved by the RF models suggest the applicability and practicality as a non-destructive assessment method for the quality of fresh mango fruit. © 2014 Published by Elsevier Ltd. 2014-08-30T04:00:56Z 2014-08-30T04:00:56Z 2014 Article 02608774 10.1016/j.jfoodeng.2014.01.007 JFOED http://www.scopus.com/inward/record.url?eid=2-s2.0-84893726481&partnerID=40&md5=d2960ae54c1b464fac99803fb6948d4b http://cmuir.cmu.ac.th/handle/6653943832/7394 English
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
language English
description Mango (Mangifera indica L.) is one of the major tropical fruits exported through long supply chains to export markets. Production of high quality fruits and monitoring postharvest changes during storage and transport are thus primary concerns for exporters to ensure the premium value of fresh mango fruit after distribution. This study aims to demonstrate the applicability of Random Forests (RF) for estimating the internal qualities of mango based on peel colour. Two cultivars, namely Nam Dokmai and Irwin, having different fruit properties and grown in intensively managed orchards in Thailand and Japan, respectively, were used in this study. Postharvest changes in peel colour and fruit quality were observed under three storage conditions with respect to temperature. RF models were applied to establish a relationship between peel colour and fruit quality, and then tested the applicability based on model accuracy and variable importance computed by the RF. Specifically, this work demonstrates how the variable importance can be used to interpret the model results. The high accuracy and the information retrieved by the RF models suggest the applicability and practicality as a non-destructive assessment method for the quality of fresh mango fruit. © 2014 Published by Elsevier Ltd.
format Article
author Fukuda S.
Yasunaga E.
Nagle M.
Yuge K.
Sardsud V.
Spreer W.
Muller J.
spellingShingle Fukuda S.
Yasunaga E.
Nagle M.
Yuge K.
Sardsud V.
Spreer W.
Muller J.
Modelling the relationship between peel colour and the quality of fresh mango fruit using Random Forests
author_facet Fukuda S.
Yasunaga E.
Nagle M.
Yuge K.
Sardsud V.
Spreer W.
Muller J.
author_sort Fukuda S.
title Modelling the relationship between peel colour and the quality of fresh mango fruit using Random Forests
title_short Modelling the relationship between peel colour and the quality of fresh mango fruit using Random Forests
title_full Modelling the relationship between peel colour and the quality of fresh mango fruit using Random Forests
title_fullStr Modelling the relationship between peel colour and the quality of fresh mango fruit using Random Forests
title_full_unstemmed Modelling the relationship between peel colour and the quality of fresh mango fruit using Random Forests
title_sort modelling the relationship between peel colour and the quality of fresh mango fruit using random forests
publishDate 2014
url http://www.scopus.com/inward/record.url?eid=2-s2.0-84893726481&partnerID=40&md5=d2960ae54c1b464fac99803fb6948d4b
http://cmuir.cmu.ac.th/handle/6653943832/7394
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