Data and code from: Severity of charcoal rot disease in soybean genotypes inoculated with macrophomina phaseolina isolates differs among growth environments

Authors: Read, Quentin; Mengistu, Alemu; LITTLE, CHRISTOPHER - Kansas State University; KELLY, HEATHER - University Of Tennessee; Henry, Peter; Bellaloui, Nacer

Submitted to: Ag Data Commons
Publication Type: Database / Dataset
Publication Acceptance Date: 4/28/2025
Publication Date: 4/28/2025
Citation: Read, Q.D., Mengistu, A., Little, C.R., Kelly, H.M., Henry, P.M., Bellaloui, N. 2025. Data and code from: Severity of charcoal rot disease in soybean genotypes inoculated with macrophomina phaseolina isolates differs among growth environments. Ag Data Commons. 10:58. https://doi.org/10.15482/USDA.ADC/28347167.v1.
DOI: https://doi.org/10.15482/USDA.ADC/28347167.v1

Interpretive Summary: Charcoal rot (CR) of soybean is a widespread disease with a big economic impact. A major goal of CR research is to find a way to quickly and reliably identify soybean genotypes that are resistant to CR. We did four independent experiments in different environments: field, greenhouse, and growth chamber. The objective was to see how well we could predict whether different soybean genotypes are resistant to CR. Our results showed that testing in the field is the most reliable way to identify resistance. This dataset includes all the raw data and all the R statistical software code that we used to fit models to the data, make predictions, and produce all the figures and tables in the associated manuscript.

Technical Abstract: This dataset includes all the raw data and all the R statistical software code that we used to analyze the data and produce all the outputs that are in the figures, tables, and text of the associated manuscript. The data included here come from a series of tests designed to evaluate methods for identifying soybean genotypes that are resistant or susceptible to charcoal rot, a widespread and economically significant disease. Four independent experiments were performed to determine the variability in disease severity by soybean genotype and by isolated variant of the charcoal rot fungus: two field tests, a greenhouse test, and a growth chamber test. The tests differed in the number of genotypes and isolates used, as well as the method of inoculation. The accuracy of identifying resistant and susceptible genotypes varied by study, and the same isolate tested across different studies often had highly variable disease severity. Our results indicate that the non-field methods are not reliable ways to identify sources of charcoal rot resistance in soybean. The models fit in the R script archived here are Bayesian general linear mixed models with AUDPC (area under the disease progress curve) as the response variable. One-dimensional clustering is used to divide the genotypes into resistant and susceptible based on their model-predicted AUDPC values, and this result is compared with the preexisting resistance classification. Posterior distributions of the marginal means for different combinations of genotype, isolate, and other covariates are estimated and compared. Code to reproduce the tables and figures of the manuscript is also included.