First recitation

TEXT

My first recitation: Using Markdown for the first time

Topic: Anaerobic Soil disinfestation and the effects on soilborne diseases

Soilborne diseases evaluated: Fusarium sp., Meloidogyne sp. and Sclerotinia sp.

[Link] https://apsjournals.apsnet.org/doi/10.1094/PHYTO-10-19-0386-R)

If you need more information about this technique ASD, please contact the authors of the paper, Anna Testen, Andres Sanabria and Karina Garcia from Ohio State University.

• Report content

  • Objectives
  • Methods and material
  • Results
  • Discussions

In this oportunity just results will be discussed, but if you need more information about the objectives, methods and materials, please contact the authors of the paper.

Soil pH results

Treatment description

T1: Aerobic control - nontreated soil + soil saturation

T2: Anaerobic control - nontreated soil + soil saturation

T3: Soil treated with wheat bran + soil saturation

T4: Soil treated with wheat bran and molasses + soil saturation

Code chunk 1 - Ctrl + Alt + I

#Uploading data
library(readxl)

## Warning: package 'readxl' was built under R version 4.5.3

pHdata <- read_excel("C:/Master Ohio Classes/Fall 2026/Data Visualization/Data for recitation.xlsx")  
summary(pHdata)

##     Block            Treatment               pH       
##  Length:16          Length:16          Min.   :4.900  
##  Class :character   Class :character   1st Qu.:5.075  
##  Mode  :character   Mode  :character   Median :5.550  
##                                        Mean   :5.625  
##                                        3rd Qu.:6.200  
##                                        Max.   :6.600

Code chunk 2 - using the Add Chunk command in the editor toolbar and select R

#Test when the distribution is not normal
friedman_result <- friedman.test(pH ~ Treatment | Block, data = pHdata)
print(friedman_result)

## 
##  Friedman rank sum test
## 
## data:  pH and Treatment and Block
## Friedman chi-squared = 11.1, df = 3, p-value = 0.0112

Code chunk 3 - using the Add Chunk command in the editor toolbar and select R

#Test to compare all pairs of treatments using Nemenyi test 
install.packages("PMCMRplus")
library(PMCMRplus)
frdAllPairsNemenyiTest(pH ~ Treatment | Block, data = pHdata)

Pairwise comparisons using Nemenyi-Wilcoxon-Wilcox all-pairs test for a two-way balanced complete block design

Data: pH and Treatment and Block

Results discussion:

T4 vs. T1 (p = 0.014): Significant. Because this value is less than 0.05, there is a statistically significant difference in pH between Treatment 1 and Treatment 4.

T4 vs. T2 (p = 0.066): Not significant (Marginal). This is slightly above 0.05. While there might be a slight trend, it is not strictly statistically significant.

All other pairs (p > 0.05): Not significant.

T2 vs. T1 (p = 0.947) — Highly similar.

T3 vs. T1 (p = 0.221) — No significant difference.

T3 vs. T2 (p = 0.519) — No significant difference.

T4 vs. T3 (p = 0.692) — No significant difference.