Assessment of the Spatial Distribution and Risk Associated with Fruit Rot Disease in <i>Areca catechu</i> L.
<i>Phytophthora meadii</i> (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 (<i>Areca catechu</i> L.), respectively. Among them, fruit rot disease (FRD) causes se...
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| Format: | Article |
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MDPI AG
2021-09-01
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| Series: | Journal of Fungi |
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| Online Access: | https://www.mdpi.com/2309-608X/7/10/797 |
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| author | Patil Balanagouda Shankarappa Sridhara Sandip Shil Vinayaka Hegde Manjunatha K. Naik Hanumappa Narayanaswamy Siva K. Balasundram |
| author_facet | Patil Balanagouda Shankarappa Sridhara Sandip Shil Vinayaka Hegde Manjunatha K. Naik Hanumappa Narayanaswamy Siva K. Balasundram |
| author_sort | Patil Balanagouda |
| collection | DOAJ |
| description | <i>Phytophthora meadii</i> (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 (<i>Areca catechu</i> 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 | 2024-03-10T06:28:14Z |
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| institution | Directory Open Access Journal |
| issn | 2309-608X |
| language | English |
| last_indexed | 2024-03-10T06:28:14Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
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| series | Journal of Fungi |
| spelling | doaj.art-bc1acfbf66364e56a905ea865b1d7c542023-11-22T18:46:37ZengMDPI AGJournal of Fungi2309-608X2021-09-0171079710.3390/jof7100797Assessment of the Spatial Distribution and Risk Associated with Fruit Rot Disease in <i>Areca catechu</i> L.Patil Balanagouda0Shankarappa Sridhara1Sandip Shil2Vinayaka Hegde3Manjunatha K. Naik4Hanumappa Narayanaswamy5Siva K. Balasundram6Department of Plant Pathology, University of Agricultural and Horticultural Sciences, Shivamogga, Karnataka 577255, IndiaCenter for Climate Resilient Agriculture, University of Agricultural and Horticultural Sciences, Shivamogga, Karnataka 577255, IndiaResearch Centre, Division of Social Sciences, ICAR-Central Plantation Crops Research Institute, Mohitnagar, Jalpaiguri, West Bengal 735102, IndiaDivision of Crop Protection, ICAR-Central Plantation Crops Research Institute, Kasaragod, Kerala 671124, IndiaDepartment of Plant Pathology, University of Agricultural and Horticultural Sciences, Shivamogga, Karnataka 577255, IndiaDepartment of Plant Pathology, University of Agricultural and Horticultural Sciences, Shivamogga, Karnataka 577255, IndiaDepartment of Agriculture Technology, Faculty of Agriculture, Universiti Putra Malaysia, Serdang 43400, Malaysia<i>Phytophthora meadii</i> (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 (<i>Areca catechu</i> 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.https://www.mdpi.com/2309-608X/7/10/797fruit rot diseasepoint pattern analysissurface interpolationIDWarecanutdisease risk estimation |
| spellingShingle | Patil Balanagouda Shankarappa Sridhara Sandip Shil Vinayaka Hegde Manjunatha K. Naik Hanumappa Narayanaswamy Siva K. Balasundram Assessment of the Spatial Distribution and Risk Associated with Fruit Rot Disease in <i>Areca catechu</i> L. Journal of Fungi fruit rot disease point pattern analysis surface interpolation IDW arecanut disease risk estimation |
| title | Assessment of the Spatial Distribution and Risk Associated with Fruit Rot Disease in <i>Areca catechu</i> L. |
| title_full | Assessment of the Spatial Distribution and Risk Associated with Fruit Rot Disease in <i>Areca catechu</i> L. |
| title_fullStr | Assessment of the Spatial Distribution and Risk Associated with Fruit Rot Disease in <i>Areca catechu</i> L. |
| title_full_unstemmed | Assessment of the Spatial Distribution and Risk Associated with Fruit Rot Disease in <i>Areca catechu</i> L. |
| title_short | Assessment of the Spatial Distribution and Risk Associated with Fruit Rot Disease in <i>Areca catechu</i> L. |
| title_sort | assessment of the spatial distribution and risk associated with fruit rot disease in i areca catechu i l |
| topic | fruit rot disease point pattern analysis surface interpolation IDW arecanut disease risk estimation |
| url | https://www.mdpi.com/2309-608X/7/10/797 |
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