Risk quantification as an epidemiological analysis strategy: Analysis and application to bud rot in oil palm

Bud rot (BR), caused by Phytophthora palmivora, limits growth and development of oil palms in the American continent, particularly in Colombia. Due to the absence of systematic epidemiological analyses and determination of risk factors associated with BR, this study aimed to employ deterministic mat...

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Bibliographic Details
Published in:Plant pathology 2024-09, Vol.73 (7), p.1922-1936
Main Authors: Ramírez‐Gil, Joaquín Guillermo, Rivera‐Lozano, Carlos Mauricio, Tapiero, Aníbal L.
Format: Article
Language:English
Subjects:
Bayesian analysis
Bayesian statistics
Cox proportional hazard risk
driving edaphoclimatic variables
Epidemiology
frequentist statistics
Genetic analysis
Genotype & phenotype
Genotypes
Hybrids
Manganese
Markov chains models
Mathematical models
Plant diseases
Relative humidity
Risk analysis
Risk assessment
Risk factors
Rot
Statistical methods
Statistical models
Transition probabilities
Vegetable oils
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Summary:Bud rot (BR), caused by Phytophthora palmivora, limits growth and development of oil palms in the American continent, particularly in Colombia. Due to the absence of systematic epidemiological analyses and determination of risk factors associated with BR, this study aimed to employ deterministic mathematical models and frequentist and Bayesian statistical methods to quantify the genetic response and edaphoclimatic variables as risk indicators of BR. From 2011 to 2014, the severity of BR in oil palm crops was recorded monthly in two locations: Tumaco (hot spot) and Villavicencio (cold spot), determining the edaphoclimatic variables at each site. Using the area under the disease progress stairs curve, temporal models were applied to determine the rate of disease development (R0) to quantify risk at locality and genotype levels. Subsequently, the observed intensity and severity levels of BR were adjusted to models such as survival curves, Cox proportional hazard risk and transition probabilities, or Markov states, with the aim of quantifying and characterizing risk factors associated with genotype and edaphoclimatic variables at each location. The risk in Tumaco was three times higher than in Villavicencio, and the R0 values were differential by genotype, with Tenera more susceptible than Hybrids. Moreover, the risk of BR increased when periods of 2–3 months occurred with successive instances of precipitation and relative humidity greater than 150 mm/month and 90%, respectively, and when manganese and zinc levels were below optimal. This approach allowed us to characterize epidemiological factors that cause plant diseases, allowing quantification of the risk of BR. Quantification of risk in plant epidemiological analysis serves as an alternative to enhance methods and tools for comprehending the temporal dynamics of disease. Here, we address bud rot in oil palm under tropical conditions.
ISSN:0032-0862
1365-3059
DOI:10.1111/ppa.13949