Please install ImageJ from http://imagej.nih.gov/ij/. ImageJ2 at http://imagej.net is not supported.

The package LeafArea allows one to conveniently run ImageJ software within R. The package provides a user-friendly, automated tool for measuring leaf area from digital images. For more information on ImageJ, see the ImageJ User Guide, which is available http://imagej.nih.gov/ij/.

The ImageJ function run.ij computes the total area of all leaves (or leaf sections) in each image file in the target directory. Original leaf images are converted to black and white from threshold intensity levels, then leaf area is calculated by using leaf pixel counts and the calibration scale. The user can determine if the analyzed images will be saved for error checking: run.ij (save.image = TRUE) or run.ij (save.image = FALSE).

<img src="https://github.com/mattocci27/LeafArea/blob/master/figs/Fig1_final.png", width="320px">

From within R (>= 3.0.0), you can install:

• the latest version of LeafArea from CRAN with

  install.packages(“LeafArea”)

• the latest development version from github with

  # install.packages("devtools")
  devtools::install_github("mattocci27/LeafArea")

The package LeafArea requires ImageJ software, which is available from http://imagej.nih.gov/ij/. Details on how to install ImageJ on Linux, Mac OS X and Windows are available at http://imagej.nih.gov/ij/docs/install/. For Mac, the default path to ImageJ is “/Applications/ImageJ.app”. For Windows, "C:/Program Files/ImageJ. Otherwise, you need to specify the path to ImageJ to use LeafArea in R (see 3.1 Setting path to ImageJ). Note that in Linux system, ImageJ should be installed from the above URL instead of via the command lines. Java is also required, which is available at https://java.com/en/.

Capture leaf images by using a scanner and save them as jpeg or tiff files. Image size and resolution should be consistent across all the image files because the LeafArea functions estimate leaf area based on leaf pixel counts and the image size. Therefore, the LeafArea package does not support images from digital cameras, where the resolution depends on the distance of the camera to the object.

The LeafArea combines the leaf area of all images that share the same filename “prefix”, defined as the part of the filename preceding the first hyphen (-) or period (.) that may occur. For example, the areas of leaf images named A123-1.jpeg, A123-2.jpeg, and A123-3.jpeg would be combined into a single total leaf area (A123). This feature allows the user to treat multiple images as belonging to a single sample, if desired. Note that the functions in the package do not count the number of leaves in each image. If the user requires the number of leaves per image, the user must record these values by themselves.

When ImageJ is not installed in the common install directory in Linux or Windows, you need to specify the path to ImageJ in run.ij. This depends on the operating system being used (Windows, Linux or Mac). For example, when ImageJ is installed in a directory named “ImageJ” on the desktop of a Linux system, you can specify the path by typing run.ij (path.imagej = "~/Desktop/ImageJ"). Typing run.ij (path.imagej = ”C:/Users/<username>/Desktop/ImageJ”) works in Windows. For Mac, you do not have to specify the path as long as "ImageJ.app" exists in your computer.

To analyze your leaf images, you need to specify the path to directory that contains leaf images. This depends on the operating system being used (Windows, Linux or Mac). For example, when the target directory named "leaf data" is on desktop of Mac or Linux, you can specify the path by typing run.ij (set.directory = "~/Desktop/leaf data/"). Typing run.ij (set.directory = "C:/Users/<username>/Desktop/leaf data") works in Windows.

This is an example in the R help. First, I use eximg function to specify the path to example leaf images in the R temporary directory. Then, I run the run.ij function which will analyze leaf area automatically:

ex.dir <- eximg()
res <- run.ij(set.directory = ex.dir)

The object ex.dir is the path to the R temporary directory that contains example leaf images. This temporary directory will be eventually deleted after the analysis. The object res, returned from LeafArea is a data frame object, which contains name of samples in the first column and total leaf area of sample (cm²) in the second column.

res
#>   sample  total.leaf.area
#> 1     A1         350.340
#> 2   A123         418.473
#> 3     A2         177.188
#> 4   A300         384.919

You can change the following setting according to your images.

You need to tell LeafArea what a pixel represents in real-world terms of distance. When leaf images are captured in A4 image size with 100 ppi, the pixel density is roughly equal to 826 pixels per 21 cm. In this case, the calibration scale can be specified as `run.ij (distance.pixel = 826, known.distance =21)``.

The amount of memory available can be increased. By default, LeafArea uses 4 GB of memory. Typing run.ij (set.memory = 8) will allocate 8 GB of memory to LeafArea.

The edges of images may have shadowing, which can affect image analysis (i.e., ImageJ may recognize the shaded area as leaf area). The edges of images can be removed by specifying the number of pixels (default = 20). For example, run.ij (trim.pixel = 20) will remove 20 pixels from the edges of each image.

Leaf images often contain dirt and dust. To prevent dust from affecting the image analysis, the lower limit of analyzed size can be specified. For example, typing run.ij (low.size = 0.7) will remove objects smaller than 0.7 cm² in the analysis.

When you want to remove angular objects (e.g., cut petioles, square papers for scale) from the images, the analyzed lower limit of circularity can be increased (default = 0). For example, run.ij (low.circ = 0.3) will skip cut petioles from the analysis.

<img src="https://github.com/mattocci27/LeafArea/blob/master/figs/circ.png", width=480">

By default, the LeafArea combines the leaf area of all images that share the same filename “prefix”, defined as the part of the filename preceding the first hyphen (-) or period (.) that may occur. You can change this setting by using regular expressions. For example, typing run.ij (prefix = ‘\\.|-|_’) will combine the area of leaf images named A123-1.jpeg, A123-2_1.jpeg, A123-2_1.jpeg into a single total leaf area (A123).

A list object of data frames of area (cm²) of each object in each image can be returned by typing run.ij (log = T):

ex.dir <- eximg()
run.ij(set.directory = ex.dir, log = T)

#> $summary
#>   sample total.leaf.area
#> 1     A1         350.340
#> 2   A123         418.473
#> 3     A2         177.188
#> 4   A300         384.919
#>
#> $each.image
#> $each.image$`A1-01.jpeg.txt`
#>      Area
#> 1 116.799
#> 2 124.069
#>
#> $each.image$`A1-02.jpeg.txt`
#>      Area
#> 1 109.472
#>
#> $each.image$`A123-01.jpeg.txt`
#>      Area
#> 1 184.773
#>
#> $each.image$`A123-02.jpeg.txt`
#>      Area
#> 1 123.151
#> 2 110.549
#>
#> $each.image$A2.jpeg.txt
#>     Area
#> 1 43.328
#> 2 47.558
#> 3 41.427
#> 4 44.875
#>
#> $each.image$`A300-1.jpeg.txt`
#>      Area
#> 1 158.065
#>
#> $each.image$`A300-2.jpeg.txt`
#>      Area
#> 1 124.784
#> 2 102.070

By default, run.ij returns a single data frame object, which contains name of samples in the first column and total leaf area of sample (cm²) in the second column (see 3.0).

Analyzed images can be exported in the same directory as set.directory for error checking. Typing run.ij (save.image = TRUE) will export analyzed images. If you use the eximg function to set the target directory, analyzed images will be exported to a temporary directory, which will be eventually deleted. If you choose your home directory as the target directory, analyzed images will be exported to it.

Analyzed image can be displayed by using ImageJ software (defalt = FALSE). When you choose run.ij (check.image = TRUE), press any keys to close ImageJ. Note that when check.image = TRUE, the analysis would take considerable time. This option may only work on R console.

You can skip this step if ImageJ succeeds in analyzing the leaf images. If ImageJ fails to recognize leaf images, you can manually guide the image analysis for particular images through ImageJ GUI (See the ImageJ user guide 30.1 Measure...[m], http://imagej.nih.gov/ij/docs/guide/user-guide.pdf). The results for these manually-analyzed images will still be handled by the file management function resmerge.ij in run.ij. Multiple tab-delimited text files with a leaf area value (one text file for each original JPEG image file) generated by ImageJ can be merged into a single data frame. The names of text files should be the same as the image files (e.g., A123-1.txt, A123-2.txt, A123-3.txt). For example, when the text files are on the desktop of a Mac, files can be merged using resmerge.ij(“~/Desktop”):

resmerge.ij(“~/Desktop”)
#>   sample  total.leaf.area
#> 1   A123         418.473

The output and the option “prefix” are same as run.ij. See ?resmerge.ij in R for a more detailed description.