Assessment of the spatial distribution and risk associated with fruit rot disease in Areca catechu L.
Phytophthora meadii (McRae) is a hemibiotrophic oomycete fungus that infects tender nuts, growing buds, and crown regions, resulting in fruit, bud, and crown rot diseases in arecanut (Areca catechu L.), respectively. Among them, fruit rot disease (FRD) causes serious economic losses that are borne b...
| Main Authors: | , , , , , , |
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| Format: | Article |
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Multidisciplinary Digital Publishing Institute
2021
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| Online Access: | http://psasir.upm.edu.my/id/eprint/96091/ |
| _version_ | 1848862293642706944 |
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| author | Balanagouda, Patil Sridhara, Shankarappa Shil, Sandip Hegde, Vinayaka Naik, Manjunatha K. Narayanaswamy, Hanumappa Balasundram, Siva Kumar |
| author_facet | Balanagouda, Patil Sridhara, Shankarappa Shil, Sandip Hegde, Vinayaka Naik, Manjunatha K. Narayanaswamy, Hanumappa Balasundram, Siva Kumar |
| author_sort | Balanagouda, Patil |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Phytophthora meadii (McRae) is a hemibiotrophic oomycete fungus that infects tender nuts, growing buds, and crown regions, resulting in fruit, bud, and crown rot diseases in arecanut (Areca catechu L.), respectively. Among them, fruit rot disease (FRD) causes serious economic losses that are borne by the growers, making it the greatest yield-limiting factor in arecanut crops. FRD has been known to occur in traditional growing areas since 1910, particularly in Malnad and coastal tracts of Karnataka. Systemic surveys were conducted on the disease several decades ago. The design of appropriate management approaches to curtail the impacts of the disease requires information on the spatial distribution of the risks posed by the disease. In this study, we used exploratory survey data to determine areas that are most at risk. Point pattern (spatial autocorrelation and Ripley’s K function) analyses confirmed the existence of moderate clustering across sampling points and optimized hotspots of FRD were determined. Geospatial techniques such as inverse distance weighting (IDW), ordinary kriging (OK), and indicator kriging (IK) were performed to predict the percent severity rates at unsampled sites. IDW and OK generated identical maps, whereby the FRD severity rates were higher in areas adjacent to the Western Ghats and the seashore. Additionally, IK was used to identify both disease-prone and disease-free areas in Karnataka. After fitting the semivariograms with different models, the exponential model showed the best fit with the semivariogram. Using this model information, OK and IK maps were generated. The identified FRD risk areas in our study, which showed higher disease probability rates (>20%) exceeding the threshold level, need to be monitored with the utmost care to contain and reduce the further spread of the disease in Karnataka. |
| first_indexed | 2025-11-15T13:14:43Z |
| format | Article |
| id | upm-96091 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T13:14:43Z |
| publishDate | 2021 |
| publisher | Multidisciplinary Digital Publishing Institute |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-960912023-02-23T03:39:06Z http://psasir.upm.edu.my/id/eprint/96091/ Assessment of the spatial distribution and risk associated with fruit rot disease in Areca catechu L. Balanagouda, Patil Sridhara, Shankarappa Shil, Sandip Hegde, Vinayaka Naik, Manjunatha K. Narayanaswamy, Hanumappa Balasundram, Siva Kumar Phytophthora meadii (McRae) is a hemibiotrophic oomycete fungus that infects tender nuts, growing buds, and crown regions, resulting in fruit, bud, and crown rot diseases in arecanut (Areca catechu L.), respectively. Among them, fruit rot disease (FRD) causes serious economic losses that are borne by the growers, making it the greatest yield-limiting factor in arecanut crops. FRD has been known to occur in traditional growing areas since 1910, particularly in Malnad and coastal tracts of Karnataka. Systemic surveys were conducted on the disease several decades ago. The design of appropriate management approaches to curtail the impacts of the disease requires information on the spatial distribution of the risks posed by the disease. In this study, we used exploratory survey data to determine areas that are most at risk. Point pattern (spatial autocorrelation and Ripley’s K function) analyses confirmed the existence of moderate clustering across sampling points and optimized hotspots of FRD were determined. Geospatial techniques such as inverse distance weighting (IDW), ordinary kriging (OK), and indicator kriging (IK) were performed to predict the percent severity rates at unsampled sites. IDW and OK generated identical maps, whereby the FRD severity rates were higher in areas adjacent to the Western Ghats and the seashore. Additionally, IK was used to identify both disease-prone and disease-free areas in Karnataka. After fitting the semivariograms with different models, the exponential model showed the best fit with the semivariogram. Using this model information, OK and IK maps were generated. The identified FRD risk areas in our study, which showed higher disease probability rates (>20%) exceeding the threshold level, need to be monitored with the utmost care to contain and reduce the further spread of the disease in Karnataka. Multidisciplinary Digital Publishing Institute 2021 Article PeerReviewed Balanagouda, Patil and Sridhara, Shankarappa and Shil, Sandip and Hegde, Vinayaka and Naik, Manjunatha K. and Narayanaswamy, Hanumappa and Balasundram, Siva Kumar (2021) Assessment of the spatial distribution and risk associated with fruit rot disease in Areca catechu L. Journal of Fungi, 7 (10). art. no. 797. pp. 1-19. ISSN 2309-608X https://www.mdpi.com/2309-608X/7/10/797 10.3390/jof7100797 |
| spellingShingle | Balanagouda, Patil Sridhara, Shankarappa Shil, Sandip Hegde, Vinayaka Naik, Manjunatha K. Narayanaswamy, Hanumappa Balasundram, Siva Kumar Assessment of the spatial distribution and risk associated with fruit rot disease in Areca catechu L. |
| title | Assessment of the spatial distribution and risk associated with fruit rot disease in Areca catechu L. |
| title_full | Assessment of the spatial distribution and risk associated with fruit rot disease in Areca catechu L. |
| title_fullStr | Assessment of the spatial distribution and risk associated with fruit rot disease in Areca catechu L. |
| title_full_unstemmed | Assessment of the spatial distribution and risk associated with fruit rot disease in Areca catechu L. |
| title_short | Assessment of the spatial distribution and risk associated with fruit rot disease in Areca catechu L. |
| title_sort | assessment of the spatial distribution and risk associated with fruit rot disease in areca catechu l. |
| url | http://psasir.upm.edu.my/id/eprint/96091/ http://psasir.upm.edu.my/id/eprint/96091/ http://psasir.upm.edu.my/id/eprint/96091/ |