Data and code from: Environmental influences on drying rate of spray applied disinfestants from horticultural production services

This dataset includes all the data and R code needed to reproduce the analyses in a forthcoming manuscript:Copes, W. E., Q. D. Read, and B. J. Smith. Environmental influences on drying rate of spray applied disinfestants from horticultural production services. PhytoFrontiers, DOI pending.Study description: Instructions for disinfestants typically specify a dose and a contact time to kill plant pathogens on production surfaces. A problem occurs when disinfestants are applied to large production areas where the evaporation rate is affected by weather conditions. The common contact time recommendation of 10 min may not be achieved under hot, sunny conditions that promote fast drying. This study is an investigation into how the evaporation rates of six commercial disinfestants vary when applied to six types of substrate materials under cool to hot and cloudy to sunny weather conditions. Initially, disinfestants with low surface tension spread out to provide 100% coverage and disinfestants with high surface tension beaded up to provide about 60% coverage when applied to hard smooth surfaces. Disinfestants applied to porous materials were quickly absorbed into the body of the material, such as wood and concrete. Even though disinfestants evaporated faster under hot sunny conditions than under cool cloudy conditions, coverage was reduced considerably in the first 2.5 min under most weather conditions and reduced to less than or equal to 50% coverage by 5 min. Dataset contents: This dataset includes R code to import the data and fit Bayesian statistical models using the model fitting software CmdStan, interfaced with R using the packages brms and cmdstanr. The models (one for 2022 and one for 2023) compare how quickly different spray-applied disinfestants dry, depending on what chemical was sprayed, what surface material it was sprayed onto, and what the weather conditions were at the time. Next, the statistical models are used to generate predictions and compare mean drying rates between the disinfestants, surface materials, and weather conditions. Finally, tables and figures are created. These files are included:Drying2022.csv: drying rate data for the 2022 experimental runWeather2022.csv: weather data for the 2022 experimental runDrying2023.csv: drying rate data for the 2023 experimental runWeather2023.csv: weather data for the 2023 experimental rundisinfestant_drying_analysis.Rmd: RMarkdown notebook with all data processing, analysis, and table creation codedisinfestant_drying_analysis.html: rendered output of notebookMS_figures.R: additional R code to create figures formatted for journal requirementsfit2022_discretetime_weather_solar.rds: fitted brms model object for 2022. This will allow users to reproduce the model prediction results without having to refit the model, which was originally fit on a high-performance computing clusterfit2023_discretetime_weather_solar.rds: fitted brms model object for 2023data_dictionary.xlsx: descriptions of each column in the CSV data files

本数据集包含了复现即将发表论文中分析的所需全部数据及 R 语言代码：Copes, W. E., Q. D. Read, 和 B. J. Smith. 植物保护服务中园艺生产表面喷洒消毒剂干燥速率的环境影响。PhytoFrontiers，DOI 待定。研究概述：消毒剂使用说明通常规定了剂量和接触时间以杀灭生产表面上的植物病原体。当消毒剂应用于受天气条件影响的广阔生产区域时，蒸发速率受到影响，这便产生了问题。在炎热、阳光明媚的条件下，促进快速干燥的常见接触时间建议（10 分钟）可能无法实现。本研究旨在探究在凉爽至炎热、多云至晴朗的天气条件下，将六种商业消毒剂应用于六种不同基材材料时，其蒸发速率的变化情况。最初，表面张力低的消毒剂在硬质光滑表面扩展以提供 100% 的覆盖率，而表面张力高的消毒剂则形成珠状以提供约 60% 的覆盖率。应用于多孔材料的消毒剂迅速被材料本体吸收，如木材和混凝土。尽管在炎热阳光明媚的条件下，消毒剂的蒸发速度比在凉爽多云条件下快，但在大多数天气条件下，前 2.5 分钟内覆盖率显著降低，5 分钟后降至 50% 以下。数据集内容：本数据集包括 R 语言代码，用于导入数据并使用模型拟合软件 CmdStan 拟合贝叶斯统计模型，通过 brms 和 cmdstanr 包与 R 相接口。模型（一个用于 2022 年，一个用于 2023 年）比较了不同喷洒消毒剂的干燥速度，这取决于所喷洒的化学物质、喷洒的表面材料以及当时的天气条件。接下来，使用统计模型生成预测，并比较不同消毒剂、表面材料和天气条件下的平均干燥速率。最后，生成表格和图形。包含的文件有：Drying2022.csv：2022 年实验运行的干燥速率数据Weather2022.csv：2022 年实验运行的天气数据Drying2023.csv：2023 年实验运行的干燥速率数据Weather2023.csv：2023 年实验运行的天气数据disinfestant_drying_analysis.Rmd：包含所有数据处理、分析和表格创建的 RMarkdown 笔记本disinfestant_drying_analysis.html：笔记本的渲染输出MS_figures.R：用于创建符合期刊要求的图形的附加 R 语言代码fit2022_discretetime_weather_solar.rds：2022 年拟合的 brms 模型对象，允许用户在不需重新拟合模型的情况下复现模型预测结果，该模型最初在高性能计算集群上拟合fit2023_discretetime_weather_solar.rds：2023 年拟合的 brms 模型对象data_dictionary.xlsx：CSV 数据文件中每列的描述