Modelling the relationship between peel colour and the quality of fresh mango fruit using Random Forests
Modelling the relationship between peel colour and the quality of fresh mango fruit using Random Forests
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DOI：
10.1016/j.jfoodeng.2014.01.007
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发表时间：
2014-06-01
影响因子：
5.5
通讯作者：
Mueller, Joachim
中科院分区：
文献类型：
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作者：
Fukuda, Shinji;Yasunaga, Eriko;Mueller, Joachim
芒果（Mangifera indica L.）是通过长供应链出口到出口市场的主要热带水果之一。因此，生产高质量的水果和监测收获后在储存和运输过程中的变化是出口商的主要关切，以确保新鲜芒果在分销后的高价值。本研究的目的是证明随机森林（RF）的适用性，估计内部质量的芒果果皮颜色的基础上。两个品种，即南Dokmai和欧文，具有不同的水果特性，分别在泰国和日本的集中管理的果园，在这项研究中使用。采后果皮颜色和果实品质的变化，观察在三个贮藏条件下相对于温度。应用RF模型建立果皮颜色与果实品质之间的关系，然后基于RF计算的模型精度和变量重要性来测试RF模型的适用性。具体来说，这项工作演示了如何使用变量重要性来解释模型结果。高精度和信息检索的RF模型表明的适用性和实用性作为一种无损评价方法的新鲜芒果果实的品质。(C)2014爱思唯尔有限公司版权所有。
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. (C) 2014 Elsevier Ltd. All rights reserved.