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Modelling of Infection Mildew of Taro (Phytophthora colocasiae)

Published in Plant (Volume 4, Issue 6)
Received: 21 September 2016    Accepted: 7 October 2016    Published: 31 October 2016
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Abstract

Mildew taro caused by Phytophthora colocasiae affection is the most devastating of taro cultivation in Cameroon since 2010. It has been studied in leading the influence that can have a parameter considered favourable in the kinetics of the disease, and secondly, the interaction between plots through zoospores that can move from one field to another while estimating their dispersal throughout the plant. These models have allowed us to demonstrate that the duration of pathogen latency period, the number of sporangia produced on the surface of a lesion as well as the severity of the infection taken individually, are parameters to be taken into account in the development of a variety resistant to late blight taro. The dynamics of the fungus over time is represented by a matrix. The latter was used to establish a detailed estimate of the number of new infections caused by a sporangium placed in a landscape of healthy leaves. This number is known as the net rate of breeding base name (R0). The incidence and severity of disease are significantly reduced when the rate is less than or equal to one. So our approach can be used to guide research programs or evaluate the effectiveness of control strategies to design throughout the plant.

Published in Plant (Volume 4, Issue 6)
DOI 10.11648/j.plant.20160406.13
Page(s) 56-70
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Phytophthora colocasiae , Taro, Modelling, Simulation

References
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Cite This Article
  • APA Style

    Djouokep Léonel Gautier, Asseng Charles Carnot, Bowong Tsakou Samuel, Ambang Zachée, Monkam Tchamaha Fabrice. (2016). Modelling of Infection Mildew of Taro (Phytophthora colocasiae). Plant, 4(6), 56-70. https://doi.org/10.11648/j.plant.20160406.13

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    ACS Style

    Djouokep Léonel Gautier; Asseng Charles Carnot; Bowong Tsakou Samuel; Ambang Zachée; Monkam Tchamaha Fabrice. Modelling of Infection Mildew of Taro (Phytophthora colocasiae). Plant. 2016, 4(6), 56-70. doi: 10.11648/j.plant.20160406.13

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    AMA Style

    Djouokep Léonel Gautier, Asseng Charles Carnot, Bowong Tsakou Samuel, Ambang Zachée, Monkam Tchamaha Fabrice. Modelling of Infection Mildew of Taro (Phytophthora colocasiae). Plant. 2016;4(6):56-70. doi: 10.11648/j.plant.20160406.13

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  • @article{10.11648/j.plant.20160406.13,
      author = {Djouokep Léonel Gautier and Asseng Charles Carnot and Bowong Tsakou Samuel and Ambang Zachée and Monkam Tchamaha Fabrice},
      title = {Modelling of Infection Mildew of Taro (Phytophthora colocasiae)},
      journal = {Plant},
      volume = {4},
      number = {6},
      pages = {56-70},
      doi = {10.11648/j.plant.20160406.13},
      url = {https://doi.org/10.11648/j.plant.20160406.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.plant.20160406.13},
      abstract = {Mildew taro caused by Phytophthora colocasiae affection is the most devastating of taro cultivation in Cameroon since 2010. It has been studied in leading the influence that can have a parameter considered favourable in the kinetics of the disease, and secondly, the interaction between plots through zoospores that can move from one field to another while estimating their dispersal throughout the plant. These models have allowed us to demonstrate that the duration of pathogen latency period, the number of sporangia produced on the surface of a lesion as well as the severity of the infection taken individually, are parameters to be taken into account in the development of a variety resistant to late blight taro. The dynamics of the fungus over time is represented by a matrix. The latter was used to establish a detailed estimate of the number of new infections caused by a sporangium placed in a landscape of healthy leaves. This number is known as the net rate of breeding base name (R0). The incidence and severity of disease are significantly reduced when the rate is less than or equal to one. So our approach can be used to guide research programs or evaluate the effectiveness of control strategies to design throughout the plant.},
     year = {2016}
    }
    

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    AU  - Djouokep Léonel Gautier
    AU  - Asseng Charles Carnot
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    AU  - Ambang Zachée
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    PY  - 2016
    N1  - https://doi.org/10.11648/j.plant.20160406.13
    DO  - 10.11648/j.plant.20160406.13
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    UR  - https://doi.org/10.11648/j.plant.20160406.13
    AB  - Mildew taro caused by Phytophthora colocasiae affection is the most devastating of taro cultivation in Cameroon since 2010. It has been studied in leading the influence that can have a parameter considered favourable in the kinetics of the disease, and secondly, the interaction between plots through zoospores that can move from one field to another while estimating their dispersal throughout the plant. These models have allowed us to demonstrate that the duration of pathogen latency period, the number of sporangia produced on the surface of a lesion as well as the severity of the infection taken individually, are parameters to be taken into account in the development of a variety resistant to late blight taro. The dynamics of the fungus over time is represented by a matrix. The latter was used to establish a detailed estimate of the number of new infections caused by a sporangium placed in a landscape of healthy leaves. This number is known as the net rate of breeding base name (R0). The incidence and severity of disease are significantly reduced when the rate is less than or equal to one. So our approach can be used to guide research programs or evaluate the effectiveness of control strategies to design throughout the plant.
    VL  - 4
    IS  - 6
    ER  - 

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Author Information
  • Faculty of Science, Laboratory of Plant Biology and Physiology, University of Douala (Cameroon), Douala, Cameroon

  • Faculty of Science, Laboratory of Plant Biology and Physiology, University of Douala (Cameroon), Douala, Cameroon

  • Faculty of Science, Laboratory of Plant Biology and Physiology, University of Douala (Cameroon), Douala, Cameroon

  • Faculty of Science, Department of Plant Biology, Laboratory of Phytopathology and Microbiology, University of Yaounde, Yaoundé, Cameroon

  • Faculty of Science, Laboratory of Plant Biology and Physiology, University of Douala (Cameroon), Douala, Cameroon

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