Mycelial growth assessment by digital image analysis in R software environment

Abstract

This study was aimed at developing a script in R to assess fungal growth in Petri dishes using computer vision. The script was developed to aid studies in agricultural phytopathology. The fungi used were Elsinoe ampelina, Fusarium oxysporum and Fusarium verticillioides. The images were analyzed with R and the EBImage package. The command computeFeatures.shape was used to calculate the area and the mean diameter of the colony and the label in square pixels. The script was run in a loop to automate the analysis of all images in sequence. The script developed in R with the package EBImage was able to recognize and measure the fungus colonies examined. Simultaneously with photographing, the mean diameter of colonies was obtained by calculating the arithmetic mean of the diameter measured with two straight perpendicular lines using a ruler. Using the mean diameter, the area of the colony was calculated as a circle. The coefficient of determination and the root mean square error were calculated using the measurements and the values obtained with the program. Based on the coefficient of determination, the measurements obtained with the software are similar to those made using a ruler. The script reduces the image analysis time and increases accuracy, especially for non-uniform colonies.Key words: software, computer vision, EBImage, mycelial growth. RESUMEN Este estudio tuvo como objetivo el desarrollo de un script en R para evaluar el crecimiento de hongos en placas de Petri utilizando la visión por ordenador. El script fue desarrollado para ayudar a los estudios de fitopatología agrícola. Los hongos utilizados fueron

Decision‐making for thrips control in soybean fields using precision agriculture principles

“…The calculation of the size of the areas for pest control in the spatial distribution maps was performed using the image manipulation procedure of the packages BiocManager (Morgan & Ramos, 2022) and EBImage (Pau et al., 2010), of the software RStudio: Integrated Development for R (Boston, MA, USA) (Rstudio Team, 2020). The maps were segmented into two regions, where white represented equal or larger densities than EIL and black when thrips densities were smaller than the EIL and each part was calculated in pixels (Silva et al., 2017). The area to be treated was calculated using Equation (1) from the figure depicted in pixels.…”

Is the study of fungal shape still useful?

“…19 Any morphometric approach relies on image capture which developed to recent array of diverse digital image analyses based on computer vision, a technology that can extract useful information by processing and manipulating images in a computer. 20 Images refer to hyphae, mycelia, spores when microscopic level structures are investigated or colonies, mycelial chords or strands, sporophores when macroscopic structures are envisaged. Software was developed to analyze images either microscopic or macroscopic photographs.…”

“…Software was developed to analyze images either microscopic or macroscopic photographs. ImageJ, Image Tool 21 or specialized packages in R. 20 Size is an important and a long history type of morphological character conveying information on species differences and adaptations. For instance, in Polyporales and Agaricales spore size is positively correlated with basidiocarp size 22,23 it was stated that small spores are adapted for effective wind dispersal and larger spores can provide more nutrients and ability to overcome hostile environment.…”