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Classification of Cucumber Green Mottle Mosaic Virus (CGMMV) infected watermelon seeds using Raman spectroscopy

机译:用拉曼光谱法对黄瓜绿斑驳花叶病毒(CGMMV)感染的西瓜种子进行分类

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The Cucumber Green Mottle Mosaic Virus (CGMMV) is a globally distributed plant virus. CGMMV-infected plants exhibit severe mosaic symptoms, discoloration, and deformation. Therefore, rapid and early detection of CGMMV infected seeds is very important for preventing disease damage and yield losses. Raman spectroscopy was investigated in this study as a potential tool for rapid, accurate, and nondestructive detection of infected seeds. Raman spectra of healthy and infected seeds were acquired in the 400 cm-1 to 1800 cm-1 wavenumber range and an algorithm based on partial least-squares discriminant analysis was developed to classify infected and healthy seeds. The classification model's accuracies for calibration and prediction data sets were 100% and 86%, respectively. Results showed that the Raman spectroscopic technique has good potential for nondestructive detection of virus-infected seeds.
机译:黄瓜绿斑驳花叶病毒(CGMMV)是全球分布的植物病毒。受CGMMV感染的植物表现出严重的花叶症状,变色和变形。因此,快速,早期发现受CGMMV感染的种子对于预防疾病和产量损失非常重要。在这项研究中,拉曼光谱法被研究为快速,准确和无损检测受感染种子的潜在工具。在400 cm-1至1800 cm-1波数范围内获取健康和感染种子的拉曼光谱,并开发了基于偏最小二乘判别分析的算法来对感染和健康种子进行分类。分类模型对校准和预测数据集的准确性分别为100%和86%。结果表明,拉曼光谱技术具有无损检测病毒感染种子的潜力。

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