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| Application of electronic nose and GC-MS for detection of strawberries with vibrational damage |
| Jingshan Rao a,*, Yuchen Zhang a,*, Zhichao Yang * , Shaojia Li * , Di Wu *,**, Chongde Sun * , Kunsong Chen * |
| *College of Agriculture & Biotechnology / Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology/The State Agriculture Ministry Laboratory of Horticultural Plant Growth, Development and Quality Improvement, Zhejiang University, Zijingang Campus, Hangzhou 310058, P. R. China; 22016039@zju.edu.cn@zju.edu.cn (J.R.), 21716142@zju.edu.cn (Y.Z.), 22016147@zju.edu.cn (Z.Y.), shaojiali@zju.edu.cn (S.L.), di_wu@zju.edu.cn (D.W.), adesun2006@zju.edu.cn (C.S.), akun@zju.edu.cn (K.C.)
**Zhejiang University Zhongyuan Institute, Zhengzhou 450000, People’s Republic of China
aJingshan Rao and Yuchen Zhang contributed equally to this work.
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Abstract
Objectives: This study evaluated the potential of using electronic nose (e-nose) technology to nondestructively detect strawberry fruits with vibrational damage based on their volatile substances (VOCs).
Materials and methods: Four groups of strawberries with different durations of vibrations (0, 0.5, 1, and 2 h) were prepared, and their e-nose signals were collected at 0, 1, 2, and 3 days after vibration treatment.
Results: The results showed that when the samples from all four sampling days during storage were used for modelling, both the levels of vibrational damage and the day after the damage happened were accurately predicted. The best models had residual prediction deviation values of 2.984 and 5.478. The discrimination models for damaged strawberries also obtained good classification results, with an average correct answer rate of calibration and prediction of 99.24%. When the samples from each sampling day or vibration time were used for modelling, better results were obtained, but these models were not suitable for an actual situation. The gas chromatography–mass spectrophotometry results showed that the VOCs of the strawberries varied after experiencing vibrations, which was the basis for e-nose detection.
Limitations: The changes in VOCs released by other forces should be studied in the future.
Conclusions: The above results showed the potential use of e-nose technology to detect strawberries that have suffered vibrational damage.
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Corresponding Authors:
Di Wu
E-mail: di_wu@zju.edu.cn
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电子鼻和GC-MS在草莓振动损伤检测中的应用
目的：本研究评估了利用电子鼻（e-nose）技术基于其挥发性物质（VOC）以无损检测具有振动损伤的草莓果实的潜力。
材料与方法：制备4组不同持续振动时间（0、0.5、1、2 h）的草莓，并在振动处理后0、1、2、3 d采集电子鼻信号。
结果：结果表明，采用4个采样日的样品进行建模，可以准确地预测振动损伤程度和损伤时间。最佳模型的残差预测偏差分别为2.984和5.478。对受损草莓的判别模型也取得了较好的分类效果，校正和预测的平均正确率为99.24%。当使用每个采样日或振动时间的样本进行建模时，可以获得较好的结果，但这些模型并不适合实际情况。气相色谱-质谱分析结果表明，草莓在振动后，其挥发性有机化合物发生了变化，这是电子鼻检测的基础。
局限性：其他因素引起挥发性有机物的变化有待于今后研究
结论：电子鼻技术在草莓振动损伤检测中的应用潜力。
关键词：
草莓,
电子鼻,
振动损伤,
无损,
气相色谱-质谱
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