Tropical Plant PathologyPub Date : 2018-01-01Epub Date: 2018-05-10DOI: 10.1007/s40858-018-0221-5
Sètondji Alban Paterne Etchiha Afoha, Antoine Affokpon, Lieven Waeyenberge, Nancy de Sutter, Clément Agbangla, Alexandre Dansi, Daniel L Coyne, Nicole Viaene
{"title":"Molecular diversity of <i>Scutellonema bradys</i> populations from Benin, based on ITS1 rDNA and COI mtDNA.","authors":"Sètondji Alban Paterne Etchiha Afoha, Antoine Affokpon, Lieven Waeyenberge, Nancy de Sutter, Clément Agbangla, Alexandre Dansi, Daniel L Coyne, Nicole Viaene","doi":"10.1007/s40858-018-0221-5","DOIUrl":"10.1007/s40858-018-0221-5","url":null,"abstract":"<p><p>In Benin, yam production continues to face numerous production constraints, including yield and quality reduction by <i>Scutellonema bradys</i>. Implementation of efficient management techniques against this pest requires an improved understanding, including at the molecular level, of the pest. The current study aimed at identifying the <i>Scutellonema</i> spp. associated with yam in Benin and investigating the phylogenetic relationships between populations. Nematodes of the genus <i>Scutellonema</i> were obtained from tubers exhibiting external dry rot symptoms. DNA was extracted from nematodes belonging to 138 populations collected from 49 fields from 29 villages. For 51 of these populations, both the ITS1 and COI regions could be amplified <i>via</i> PCR, sequenced, compared with available sequences in the NCBI database and were identified as <i>S. bradys</i>. Maximum likelihood was used to construct 60% consensus phylogenetic trees based on 51 sequences. This phylogenetic analysis did not reveal any genetic separation between populations by cultivar, village, cropping system nor by agroecological zone. Neither could any subgroups within <i>S. bradys</i> be separated, indicating that no subspecies were present. An earlier published species-specific primer set was verified with the DNA of the 51 sequences and was considered a reliable and rapid method for <i>S. bradys</i> identification.</p>","PeriodicalId":48767,"journal":{"name":"Tropical Plant Pathology","volume":"43 4","pages":"323-332"},"PeriodicalIF":2.5,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7370939/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38203062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tropical Plant PathologyPub Date : 2017-01-01Epub Date: 2017-02-14DOI: 10.1007/s40858-017-0138-4
Jonathan S West, Gail G M Canning, Sarah A Perryman, Kevin King
{"title":"Novel Technologies for the detection of Fusarium head blight disease and airborne inoculum.","authors":"Jonathan S West, Gail G M Canning, Sarah A Perryman, Kevin King","doi":"10.1007/s40858-017-0138-4","DOIUrl":"https://doi.org/10.1007/s40858-017-0138-4","url":null,"abstract":"<p><p>Many pathogens are dispersed by airborne spores, which can vary in space and time. We can use air sampling integrated with suitable diagnostic methods to give a rapid warning of inoculum presence to improve the timing of control options, such as fungicides. Air sampling can also be used to monitor changes in genetic traits of pathogen populations such as the race structure or frequency of fungicide resistance. Although some image-analysis methods are possible to identify spores, in many cases, species-specific identification can only be achieved by DNA-based methods such as qPCR and LAMP and in some cases by antibody-based methods (lateral flow devices) and biomarker-based methods ('electronic noses' and electro-chemical biosensors). Many of these methods also offer the prospect of rapid on-site detection to direct disease control decisions. Thresholds of spore concentrations that correspond to a disease risk depend on the sampler (spore-trap) location (whether just above the crop canopy, on a UAV or drone, or on a tall building) and also need to be considered with weather-based infection models. Where disease control by spore detection is not possible, some diseases can be detected at early stages using optical sensing methods, especially chlorophyll fluorescence. In the case of <i>Fusarium</i> infections on wheat, it is possible to map locations of severe infections, using optical sensing methods, to segregate harvesting of severely affected areas of fields to avoid toxins entering the food chain. This is most useful where variable crop growth or microclimates within fields generate spatially variable infection, i.e. parts of fields that develop disease, while other areas have escaped infection and do not develop any disease.</p>","PeriodicalId":48767,"journal":{"name":"Tropical Plant Pathology","volume":"42 3","pages":"203-209"},"PeriodicalIF":2.5,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40858-017-0138-4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38203086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}