Department of Biological Sciences & Chemistry, College of Arts and Sciences, University of Nizwa, Oman.
UoN Chair of Oman Medicinal Plants and Marine Products, University of Nizwa, Oman.
Spectrochim Acta A Mol Biomol Spectrosc. 2018 Jun 5;198:27-32. doi: 10.1016/j.saa.2018.02.065. Epub 2018 Feb 27.
Nucleic acid & serology based methods have revolutionized plant disease detection, however, they are not very reliable at asymptomatic stage, especially in case of pathogen with systemic infection, in addition, they need at least 1-2days for sample harvesting, processing, and analysis. In this study, two reflectance spectroscopies i.e. Near Infrared reflectance spectroscopy (NIR) and Fourier-Transform-Infrared spectroscopy with Attenuated Total Reflection (FT-IR, ATR) coupled with multivariate exploratory methods like Principle Component Analysis (PCA) and Partial least square discriminant analysis (PLS-DA) have been deployed to detect begomovirus infection in papaya leaves. The application of those techniques demonstrates that they are very useful for robust in vivo detection of plant begomovirus infection. These methods are simple, sensitive, reproducible, precise, and do not require any lengthy samples preparation procedures.
基于核酸和血清学的方法已经彻底改变了植物病害的检测,然而,在无症状阶段,它们的可靠性并不高,特别是对于具有系统性感染的病原体,此外,它们需要至少 1-2 天的时间来进行样本采集、处理和分析。在这项研究中,我们使用了两种反射光谱技术,即近红外反射光谱(NIR)和傅里叶变换红外光谱结合衰减全反射(FT-IR,ATR),并结合主成分分析(PCA)和偏最小二乘判别分析(PLS-DA)等多元探索方法,来检测番木瓜叶片中的曲叶病毒感染。这些技术的应用表明,它们非常有助于番木瓜曲叶病毒感染的活体稳健检测。这些方法简单、敏感、可重现、精确,并且不需要进行任何冗长的样本制备程序。