Application Name	Fungi REPAINT Assay
Version	2.0.0
Documentation Version	01.02.2022 - 1
Input Image(s)	2D (standard): RGB
Input Parameter(s)	None
Keywords	phenomic, fungus, fungi, spore, growth, conidium, hypha, phenotype, plate, well, multiwell, 96, photo, biolog, macro, assay, microplate
Short Description	Quantification of fungal phenomics (conidia and hyphae coverage and radial distribution) in a 96-well Biolog microplate.
References / Literature	For more information regarding the assay check e.g. https://www.nature.com/articles/s41396-020-0709-0 .

IKOSA Prisma Fungi REPAINT Assay

You can use this or any other of our image analysis applications through your IKOSA® account. If it is not listed in the available applications, please contact your organization’s IKOSA® administrator or our team at support@ikosa.ai.

Application description

This application automatically measures the relative conidia and hyphae coverage in the 96 wells of a Biolog FF microplate. This microplate includes 95 carbon sources and water. The application was trained and evaluated on images showing different stages of conidia and hyphae of the following types of fungi: trichoderma, metarhizium robertsii, aspergillus niger, and penicillium sp.

In the following sections, we provide the necessary input data requirements that are necessary to obtain accurate image analysis results and a description of the output files.

Input data requirements

Input image(s)

Input for this application is the following image data:

Image type	Color channels	Color depth (per channel)	Size (px)	Resolution (μm/px)

Image type

Color channels

Color depth (per channel)

Size (px)

Resolution (μm/px)

2D (standard)

Check image formats

File formats

3 (RGB)

8 Bit

Max: 7,245 x 7,245

Image content

Photo of standard Biolog multiwell plate with 96 wells.

Additional requirements

The dimensions of the multiwell plate must be the same as for a Biolog multiwell plate with 96 wells (12.75 x 8.5 cm; well diameter: 5 mm; well distance: ~5 mm).
The multiwell plate is placed on a homogeneous white background.
Image and well plate borders have to be approximately parallel.
The multiwell plate is rotated in a way that labels of wells are shown in correct order (starting with A1 at the top left; see examples below).
The photo was taken under an angle of approximately 90 degrees (avoid perspective distortion).
The individual wells have to be clearly distinguishable.
The application was optimized for well diameters of 200 pixels, significantly smaller and larger diameters could affect the results.

Important:

For all images, the following requirements apply:

The illumination must be constant throughout the image(s).
The sample must be in focus, i.e. no blurry regions in image(s).

Input parameter(s)

No additional input parameters are required for this application.

Description of output files and their content

Files

	File format	Description

File format

Description

1

csv

result.csv

Coverage of conidia/hyphae for each well.

Content

result.csv

Single csv-file

Column NO.	Column name	Examples	Value range	Description

Column NO.	Column name	Examples	Value range	Description
1	well	A01	A01-H12	Name of the well.
2	coverage conidia [%]	25	0 - 100	Percentage of the well area covered with conidia.
3	coverage hyphae [%]	75	0 - 100	Percentage of the well area, covered with hyphae.
4	mean intensity conidia [0,1]	0.60	0 - 1	Mean intensity of the area classified as conidia in the range [0,1], where 0 corresponds to a bright conidia color, and 1 corresponds to a dark conidia color. Due to different illuminations in the images, the value cannot be compared between different images.
5-14	radial distribution [conidia/hyphae] bin [x] [%]	50	0 - 100	The circular area of the well is divided into 5 annuli. For each annulus with index [x], the percentage of the area covered by conidia/hyphae is given. A visualization of the annuli and their indices is given shown in the image below:
15-24	intensity histogram conidia bin x ([a, b]) [%]	0.3	0 - 100	A histogram of the intensities of the area classified as conidia. Each bin contains the percentage of the well area classified as conidia in the intensity range [a, b].

Error information

More information about errors can be found in the Application Error Documentation.

Contact

If you have any questions about this app, as well as suggestions or ideas for new ones, email us at support@ikosa.ai.

Feel free to book a 30-minute meeting to speak with us about IKOSA and the apps!

https://calendly.com/kolaido/book-the-ikosa-platform-demo

IKOSA Knowledge Base

2.0.0 Fungi REPAINT Assay

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