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基于共聚焦拉曼光谱的油菜核盘菌早期鉴别

[Discriminate the Rape Sclerotinia at Early Stage Based on Confocal Raman Spectroscopy].

作者信息

Zhao Yan-ru, Li Xiao-li, Yu Ke-qiang, Cheng Fan, Liu Ji-qiang, He Yong

出版信息

Guang Pu Xue Yu Guang Pu Fen Xi. 2017 Feb;37(2):467-71.

Abstract

Oilseed rape(Brassica napus L. ) is a principal source of edible oil for human consumption and it feeds livestock as a by product with high energy and protein. However, oilseed plants often suffer from the invasion of various diseases, which could affect the yield and quality of the rapeseeds. Rape sclerotinia rot caused by the fungus sclerotinia sclerotiorum (Lib. ) de Bary may severely affect the growth of oilseed rape. Therefore, searching non-invasive detection methods of detection plant disease at early stage is crucial for monitoring growing conditions of crops. Confocal Raman spectroscopy in the region of 500~2 000 cm(-1) coupled with chemometrics methods were employed to discriminate the rape sclerotinia disease at early stage on the oilseed rape leaves. A total of 60 samples(30 healthy plant leaves and 30 infected leaves) were used to acquire the Raman spectra and wavelet transform was applied to remove the fluorescence background. Regression coefficients of the partial least squares-discriminant analysis(PLS-DA) were used to select the 8 characteristic peaks based on the whole Raman spectra. 983,1 001, 1 205, 1 521, 1 527, 1 658, 1 670 and 1 758 cm(-1) were employed to establish PLS-DA discriminate models and recognition accuracy was 100%. The results showed Raman spectra combined with chemometrics method is promising for detecting rape sclerotinia infection in the oilseed rape leaves at early stage. This study provided a theoretical reference for researching the interaction between the fungus and plants and early detecting of disease infection.

摘要

油菜(Brassica napus L.)是人类食用植物油的主要来源,其副产品可作为高能量和高蛋白的家畜饲料。然而,油料作物常常遭受各种病害的侵袭,这会影响油菜籽的产量和质量。由核盘菌(Sclerotinia sclerotiorum (Lib.) de Bary)引起的油菜菌核病可能会严重影响油菜的生长。因此,寻找早期检测植物病害的非侵入性方法对于监测作物生长状况至关重要。利用500~2000 cm(-1)区域的共焦拉曼光谱结合化学计量学方法,对油菜叶片早期的菌核病进行鉴别。共采集了60个样本(30片健康植株叶片和30片感染叶片)的拉曼光谱,并应用小波变换去除荧光背景。基于全拉曼光谱,利用偏最小二乘判别分析(PLS-DA)的回归系数选择了8个特征峰。采用983、1001、1205、1521、1527、1658、1670和1758 cm(-1)建立PLS-DA判别模型,识别准确率为100%。结果表明,拉曼光谱结合化学计量学方法有望早期检测油菜叶片中的菌核病感染。本研究为研究真菌与植物之间的相互作用以及病害感染的早期检测提供了理论参考。

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