Comparison of Models for Quantification of Tomato Brown Rugose Fruit Virus Based on a Bioassay Using a Local Lesion Host

Author:

Nourinejhad Zarghani ShaheenORCID,Monavari Mehran,Ehlers JensORCID,Hamacher Joachim,Büttner CarmenORCID,Bandte MartinaORCID

Abstract

Considering the availability of serological and molecular biological methods, the bioassay has been paled into insignificance, although it is the only experimental method that can be used to demonstrate the infectivity of a virus. We compared goodness-of-fit and predictability power of five models for the quantification of tomato brown rugose fruit virus (ToBRFV) based on local lesion assays: the Kleczkowski model, Furumoto and Mickey models I and II, the Gokhale and Bald model (growth curve model), and the modified Poisson model. For this purpose, mechanical inoculations onto Nicotiana tabacum L. cv. Xanthi nc and N. glutionosa L. with defined virus concentrations were first performed with half-leaf randomization in a Latin square design. Subsequently, models were implemented using Python software and fitted to the number of local lesions. All models could fit to the data for quantifying ToBRFV based on local lesions, among which the modified Poisson model had the best prediction of virus concentration in spike samples based on local lesions, although data of individual indicator plants showed variations. More accurate modeling was obtained from the test plant N. glutinosa than from N. tabacum cv. Xanthi nc. The position of the half-leaves on the test plants had no significant effect on the number of local lesions.

Funder

Menno Chemie-Vertriebs mbH

Agro-Horti Testlabor

Publisher

MDPI AG

Subject

Plant Science,Ecology,Ecology, Evolution, Behavior and Systematics

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3