Optimisation of sampling and testing for asymptomatic olive trees infected by Xylella fastidiosa in Apulia region, Italy

Author:

D'ONGHIA Anna MariaORCID,SANTORO FrancoORCID,MINUTILLO Serena AnnaORCID,FRASHERI DajanaORCID,GALLO MarilitaORCID,GUALANO StefaniaORCID,CAVALLO GiuseppeORCID,VALENTINI FrancoORCID

Abstract

Early detection of Xylella fastidiosa outbreaks in Apulian olive groves is crucial, especially in buffer zones and pathogen-free areas where olive trees are asymptomatic. Three studies were conducted. Two were on the spatial and temporal progression of X. fastidiosa infections in tree canopies of asymptomatic or mildly symptomatic olive trees of tolerant (‘Leccino’) and susceptible (‘Cellina di Nardò’ and ‘Ogliarola salentina’) cultivars. Despite different trends in pathogen infection rates and concentrations between ‘Leccino’ and susceptible olive cultivars over the study period, results showed that sampling was most effective in the mid-upper part of tree canopies throughout the year, excluding the warmest and coldest periods. Stem xylem tissues were the most appropriate for detecting the pathogen compared to lower parts of mature leaves with petioles, using serological and molecular assays. Based on these results, a third study was conducted to compare molecular and serological tests (qPCR, real-time LAMP, DAS-ELISA, DTBIA) for detection of X. fastidiosa in the mid-upper part of asymptomatic branches of infected ‘Leccino’ trees that were sampled in an appropriate collection time, using stem xylem tissue as the most appropriate matrix for testing. The molecular methods showed the greatest sensitivity, with no undetermined results, while among the serological assays, DTBIA was more sensitive than DAS-ELISA. An improved protocol for monitoring asymptomatic olive trees is recommended.

Publisher

Firenze University Press

Subject

Horticulture,Plant Science,Agronomy and Crop Science

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