Spatial Distribution Patterns for Identifying Risk Areas Associated with False Smut Disease of Rice in Southern India

dc.bibliographicCitation.firstPage2947
dc.bibliographicCitation.issue12
dc.bibliographicCitation.journalTitleAgronomyeng
dc.bibliographicCitation.volume12
dc.contributor.authorHuded, Sharanabasav
dc.contributor.authorPramesh, Devanna
dc.contributor.authorChittaragi, Amoghavarsha
dc.contributor.authorSridhara, Shankarappa
dc.contributor.authorChidanandappa, Eranna
dc.contributor.authorPrasannakumar, Muthukapalli K.
dc.contributor.authorManjunatha, Channappa
dc.contributor.authorPatil, Balanagouda
dc.contributor.authorShil, Sandip
dc.contributor.authorPushpa, Hanumanthappa Deeshappa
dc.contributor.authorRaghunandana, Adke
dc.contributor.authorUsha, Indrajeet
dc.contributor.authorBalasundram, Siva K.
dc.contributor.authorShamshiri, Redmond R.
dc.date.accessioned2023-02-10T05:10:38Z
dc.date.available2023-02-10T05:10:38Z
dc.date.issued2022
dc.description.abstractFalse smut disease (FSD) of rice incited by Ustilaginoidea virens is an emerging threat to paddy cultivation worldwide. We investigated the spatial distribution of FSD in different paddy ecosystems of South Indian states, viz., Andhra Pradesh, Karnataka, Tamil Nadu, and Telangana, by considering the exploratory data from 111 sampling sites. Point pattern and surface interpolation analyses were carried out to identify the spatial patterns of FSD across the studied areas. The spatial clusters of FSD were confirmed by employing spatial autocorrelation and Ripley’s K function. Further, ordinary kriging (OK), indicator kriging (IK), and inverse distance weighting (IDW) were used to create spatial maps by predicting the values at unvisited locations. The agglomerative hierarchical cluster analysis using the average linkage method identified four main clusters of FSD. From the Local Moran’s I statistic, most of the areas of Andhra Pradesh and Tamil Nadu were clustered together (at I > 0), except the coastal and interior districts of Karnataka (at I < 0). Spatial patterns of FSD severity were determined by semi-variogram experimental models, and the spherical model was the best fit. Results from the interpolation technique, the potential FSD hot spots/risk areas were majorly identified in Tamil Nadu and a few traditional rice-growing ecosystems of Northern Karnataka. This is the first intensive study that attempted to understand the spatial patterns of FSD using geostatistical approaches in India. The findings from this study would help in setting up ecosystem-specific management strategies to reduce the spread of FSD in India.eng
dc.description.versionpublishedVersioneng
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/11367
dc.identifier.urihttp://dx.doi.org/10.34657/10401
dc.language.isoeng
dc.publisherBasel : MDPI
dc.relation.doihttps://doi.org/10.3390/agronomy12122947
dc.relation.essn2073-4395
dc.rights.licenseCC BY 4.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.subject.ddc630
dc.subject.ddc640
dc.subject.otherfalse smuteng
dc.subject.otherIndiaeng
dc.subject.otherinterpolation techniqueseng
dc.subject.otherriceeng
dc.subject.othersemi-variogrameng
dc.subject.otherspatial patternseng
dc.subject.otherUstilaginoidea virenseng
dc.titleSpatial Distribution Patterns for Identifying Risk Areas Associated with False Smut Disease of Rice in Southern Indiaeng
dc.typeArticleeng
dc.typeTexteng
tib.accessRightsopenAccess
wgl.contributorATB
wgl.subjectUmweltwissenschaftenger
wgl.typeZeitschriftenartikelger
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