2015
DOI: 10.7287/peerj.preprints.1404v1
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Agricolae - Ten years of an open source statistical tool for experiments in breeding, agriculture and biology

Abstract: Plant breeders and educators working with the International Potato Center (CIP) needed freely available statistical tools. In response, we created first a set of scripts for specific tasks using the open source statistical software R. Based on this we eventually compiled the R package agricolae as it covered a niche. Here we describe for the first time its main functions in the form of an article. We also review its reception using download statistics, citation data, and feedback from a user survey. We highlig… Show more

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Cited by 644 publications
(642 citation statements)
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“…Images were collected using the Slidebook software package (Intelligent Imaging Innovations, Denver, CO) at exposure times ranging from 0.1 to 1 s. Spindle measurements were collected using the Line tool in the Slidebook software. Statistical significance was determined through an ANOVA using the R package “agricolae” (de Mendiburu, 2015). …”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Images were collected using the Slidebook software package (Intelligent Imaging Innovations, Denver, CO) at exposure times ranging from 0.1 to 1 s. Spindle measurements were collected using the Line tool in the Slidebook software. Statistical significance was determined through an ANOVA using the R package “agricolae” (de Mendiburu, 2015). …”
Section: Methodsmentioning
confidence: 99%
“…A total of 500 pollen grains from each plant were scored for viability based on color. Statistical significance was determined through an ANOVA using the R package “agricolae” (de Mendiburu, 2015). …”
Section: Methodsmentioning
confidence: 99%
“…To compare each trait between host plants, data were analyzed using one-way analysis of variance (ANOVA) followed by mean separation with Tukey HSD test ( P ≤ 0.05) contingent on a significant effect using R Studio (Racome, 2011) and R Statistical software (R Development Core Team, 2009). The following R packages were used for the data analysis: Plotrix (Lemon, 2006), Agricolae (de Mendiburu, 2015), Reshape (Wickham, 2007), Lattice (Sarkar, 2008), and Vegan (Oksanen et al, 2015). Ordination of the data using principal components analysis was used to determine which traits contributed the most variability.…”
Section: Methodsmentioning
confidence: 99%
“…Multiple comparison tests between groups after Kruskal–Wallis tests were done with the Kruskalmc function while the Student–Newman–Keuls test was used to compare means after the general linear model procedure. The Kruskal–Wallis and Student–Newman–Keuls tests used were those available in the R “agricolae” (version 1.1-8) package (De Mendiburu, 2014), all other tests were done using the R “Stats” (version 2.15.3) package. All the data were used in a first analysis based on a model with one factor (gene).…”
Section: Methodsmentioning
confidence: 99%