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This study presents the development of a Shiny application in R for phytosanitary monitoring of chrysanthemum crops. The tool enables visualization, analysis, and management of field-collected pest data (thrips, leafminers, aphids), integrating geographic, temporal, and taxonomic information. Through interactive dashboards, heat maps, and dynamic tables, users can identify infestation patterns, calculate incidence rates by block and week, and optimize control strategies. The application was built with tidyverse (dplyr, ggplot2), leaflet for mapping, and shinydashboard for the interface. This development demonstrates how R transforms raw data into actionable knowledge, reducing agrochemical use through evidence-based decision making.

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R in the Greenhouse: Shiny as a Bridge Between Statistical Analysis and Agricultural Decision-Making

  • 会议论文

  • 发表日期：

    2026年

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  • Giovanny Reales Rodríguez

摘要

This study presents the development of a Shiny application in R for phytosanitary monitoring of chrysanthemum crops. The tool enables visualization, analysis, and management of field-collected pest data (thrips, leafminers, aphids), integrating geographic, temporal, and taxonomic information. Through interactive dashboards, heat maps, and dynamic tables, users can identify infestation patterns, calculate incidence rates by block and week, and optimize control strategies. The application was built with tidyverse (dplyr, ggplot2), leaflet for mapping, and shinydashboard for the interface. This development demonstrates how R transforms raw data into actionable knowledge, reducing agrochemical use through evidence-based decision making.