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Rapid and Non-Destructive Detection of Decay in Peach Fruit at the Cold Environment Using a Self-Developed Handheld Electronic-Nose System

机译:使用自我开发的手持电子鼻系统在冷环境中快速和无损检测桃子果实中的腐烂

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摘要

Non-destructive detection of decay in fruit in real time during cold chain is important to recycle the decayed fruit in time for reverse supply chain. Fruit is commonly stored inside external packages during cold chain, making neither manual observation nor optical inspection techniques available to detect the decay in fruit. In this work, the potential of a self-developed handheld electronic nose (e-nose) instrument to non-destructively acquire volatile substances and then detect decay in peach fruit during cold chain (0 degrees C) was explored. A desktop e-nose instrument was considered as a comparison. The storage days of peach fruit during storage were also predicted by two instruments. Partial least squares discriminant analysis and least squares support vector machines (LS-SVM) were used for the classification of decay in peach fruit. Partial least squares regression and LS-SVM were used for the prediction of the storage days. Successive projection algorithm (SPA), uninformation variable elimination (UVE), UVE-SPA, and competitive adaptive reweighted sampling were applied to select the characteristic variables from e-nose data. The best model for the classification of decayed fruit during cold chain by the handheld e-nose instrument had the correct answer rate of prediction of 95.83% (94.64% for healthy samples and 100.00% for decayed samples). The best model for predicting the storage days of peach fruit during cold chain by the handheld e-nose instrument had the residual predictive deviation value of 9.283. The results indicate that the self-developed handheld e-nose system is a simple and non-destructive tool to detect decay in peach fruit during cold storage.
机译:在冷链期间实时地实时检测果实腐烂的衰减是重要的,对于回收衰减的果实,以逆转供应链。果实通常储存在冷链期间的外部包装内,既不是手动观察,也没有可用于检测水果中的腐烂的光学检测技术。在这项工作中,探索了自我开发的手持电子鼻子(E-鼻子)仪器以非破坏性地获取挥发物质的潜力,然后在冷链(0℃)期间检测桃果汁中的腐烂。桌面电子鼻仪被认为是比较。储存期间的桃子果实的储存日也预测了两种仪器。局部最小二乘判别分析和最小二乘支持向量机(LS-SVM)用于桃子果实中的衰减分类。部分最小二乘回归和LS-SVM用于预测储存天。应用连续投影算法(SPA),未顺势变量消除(UVE),UVE-SPA和竞争性自适应重复采样应用于从电子鼻数据中选择特征变量。手持式电子鼻器仪器在冷链期间腐烂水果分类的最佳模型具有95.83%的正确答案速率(健康样品的94.64%,腐烂样品的100.00%)。手持电子鼻仪器在冷链期间预测桃果实储存天的最佳模型具有9.283的残余预测偏差值。结果表明,自我开发的手持电子鼻系统是一种简单而非破坏性的工具,可以在冷藏过程中检测桃子果实中的腐烂。

著录项

  • 来源
    《Food analytical methods》 |2018年第11期|共15页
  • 作者单位

    Zhejiang Univ Zhejiang Prov Key Lab Hort Plant Integrat Biol State Agr Minist Lab Hort Plant Growth Dev &

    Qual Coll Agr &

    Biotechnol Zijingang Campus Hangzhou 310058 Zhejiang Peoples R China;

    Zhejiang Univ Zhejiang Prov Key Lab Hort Plant Integrat Biol State Agr Minist Lab Hort Plant Growth Dev &

    Qual Coll Agr &

    Biotechnol Zijingang Campus Hangzhou 310058 Zhejiang Peoples R China;

    Zhejiang Univ Zhejiang Prov Key Lab Hort Plant Integrat Biol State Agr Minist Lab Hort Plant Growth Dev &

    Qual Coll Agr &

    Biotechnol Zijingang Campus Hangzhou 310058 Zhejiang Peoples R China;

    Zhejiang Univ Dept Biosyst Engn Hangzhou 310058 Zhejiang Peoples R China;

    Zhejiang Univ Zhejiang Prov Key Lab Hort Plant Integrat Biol State Agr Minist Lab Hort Plant Growth Dev &

    Qual Coll Agr &

    Biotechnol Zijingang Campus Hangzhou 310058 Zhejiang Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 食品工业;
  • 关键词

    Peach fruit; Electronic nose; Decay; Reverse logistics; Supply chain; Cold chain;

    机译:桃子果;电子鼻子;衰变;逆向物流;供应链;冷链;

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