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Development of a Model to Predict the Primary Infection Date of Bacterial Spot (Xanthomonas campestris pv. vesicatoria) on Hot Pepper
A population model of bacterial spot caused by Xanthomonas campestris pv. vesicatoria on hot pepper was developed to predict the primary disease infection date. The model estimated the pathogen population on the surface and within the leaf of the host based on the wetness period and temperature. For...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society of Plant Pathology
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4174847/ https://www.ncbi.nlm.nih.gov/pubmed/25288995 http://dx.doi.org/10.5423/PPJ.OA.09.2013.0090 |
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author | Kim, Ji-Hoon Kang, Wee-Soo Yun, Sung-Chul |
author_facet | Kim, Ji-Hoon Kang, Wee-Soo Yun, Sung-Chul |
author_sort | Kim, Ji-Hoon |
collection | PubMed |
description | A population model of bacterial spot caused by Xanthomonas campestris pv. vesicatoria on hot pepper was developed to predict the primary disease infection date. The model estimated the pathogen population on the surface and within the leaf of the host based on the wetness period and temperature. For successful infection, at least 5,000 cells/ml of the bacterial population were required. Also, wind and rain were necessary according to regression analyses of the monitored data. Bacterial spot on the model is initiated when the pathogen population exceeds 10(15) cells/g within the leaf. The developed model was validated using 94 assessed samples from 2000 to 2007 obtained from monitored fields. Based on the validation study, the predicted initial infection dates varied based on the year rather than the location. Differences in initial infection dates between the model predictions and the monitored data in the field were minimal. For example, predicted infection dates for 7 locations were within the same month as the actual infection dates, 11 locations were within 1 month of the actual infection, and only 3 locations were more than 2 months apart from the actual infection. The predicted infection dates were mapped from 2009 to 2012; 2011 was the most severe year. Although the model was not sensitive enough to predict disease severity of less than 0.1% in the field, our model predicted bacterial spot severity of 1% or more. Therefore, this model can be applied in the field to determine when bacterial spot control is required. |
format | Online Article Text |
id | pubmed-4174847 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Korean Society of Plant Pathology |
record_format | MEDLINE/PubMed |
spelling | pubmed-41748472014-10-06 Development of a Model to Predict the Primary Infection Date of Bacterial Spot (Xanthomonas campestris pv. vesicatoria) on Hot Pepper Kim, Ji-Hoon Kang, Wee-Soo Yun, Sung-Chul Plant Pathol J Research Article A population model of bacterial spot caused by Xanthomonas campestris pv. vesicatoria on hot pepper was developed to predict the primary disease infection date. The model estimated the pathogen population on the surface and within the leaf of the host based on the wetness period and temperature. For successful infection, at least 5,000 cells/ml of the bacterial population were required. Also, wind and rain were necessary according to regression analyses of the monitored data. Bacterial spot on the model is initiated when the pathogen population exceeds 10(15) cells/g within the leaf. The developed model was validated using 94 assessed samples from 2000 to 2007 obtained from monitored fields. Based on the validation study, the predicted initial infection dates varied based on the year rather than the location. Differences in initial infection dates between the model predictions and the monitored data in the field were minimal. For example, predicted infection dates for 7 locations were within the same month as the actual infection dates, 11 locations were within 1 month of the actual infection, and only 3 locations were more than 2 months apart from the actual infection. The predicted infection dates were mapped from 2009 to 2012; 2011 was the most severe year. Although the model was not sensitive enough to predict disease severity of less than 0.1% in the field, our model predicted bacterial spot severity of 1% or more. Therefore, this model can be applied in the field to determine when bacterial spot control is required. Korean Society of Plant Pathology 2014-06 /pmc/articles/PMC4174847/ /pubmed/25288995 http://dx.doi.org/10.5423/PPJ.OA.09.2013.0090 Text en ©The Korean Society of Plant Pathology This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Kim, Ji-Hoon Kang, Wee-Soo Yun, Sung-Chul Development of a Model to Predict the Primary Infection Date of Bacterial Spot (Xanthomonas campestris pv. vesicatoria) on Hot Pepper |
title | Development of a Model to Predict the Primary Infection Date of Bacterial Spot (Xanthomonas campestris pv. vesicatoria) on Hot Pepper |
title_full | Development of a Model to Predict the Primary Infection Date of Bacterial Spot (Xanthomonas campestris pv. vesicatoria) on Hot Pepper |
title_fullStr | Development of a Model to Predict the Primary Infection Date of Bacterial Spot (Xanthomonas campestris pv. vesicatoria) on Hot Pepper |
title_full_unstemmed | Development of a Model to Predict the Primary Infection Date of Bacterial Spot (Xanthomonas campestris pv. vesicatoria) on Hot Pepper |
title_short | Development of a Model to Predict the Primary Infection Date of Bacterial Spot (Xanthomonas campestris pv. vesicatoria) on Hot Pepper |
title_sort | development of a model to predict the primary infection date of bacterial spot (xanthomonas campestris pv. vesicatoria) on hot pepper |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4174847/ https://www.ncbi.nlm.nih.gov/pubmed/25288995 http://dx.doi.org/10.5423/PPJ.OA.09.2013.0090 |
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