BioLeaf - Foliar Analysis


UpVision
3.1.2
Old Versions

Trusted App

About BioLeaf - Foliar Analysis

BioLeaf - Foliar Analysis™ performs the defoliation analysis of plants.

BioLeaf - Foliar Analysis™ identifies automatically the injured leaf regions caused by insect herbivory and then estimates the defoliation percentage related to the total area by using images either captured from the phone or loaded from the photo gallery.

If you are using our application, please cite us:

BioLeaf: A professional mobile application to measure foliar damage caused by insect herbivory. Computers and Electronics in Agriculture 129 (2016) 44–55.

Full paper: http://bioleaf.icmc.usp.br/paper/2016BIOLEAF.pdf

Key-features:

• Automatic and accurate quantification of the foliage loss in two steps.

• Interactive reconstruction of the leaf edges by using curves and zooming-in.

• A 4-language interface (English, Portuguese, Spanish and Russian)

• Suitable for several agricultural crops.

• Useful on the plant resistance evaluation.

• Non-destructive method.

BioLeaf - Foliar Analysis™ was developed by a Brazilian team of researchers from the Federal University of Mato Grosso do Sul - UFMS, in collaboration with researchers of Dom Bosco Catholic University - UCDB, lead by the group INOVISAO.

Contact:

If you have any question or suggestions, please send us an email to upvisiongroup@gmail.com. Your feedback is very important to improve our app. We are also open for collaboration!

What's New in the Latest Version 3.1.2

Last updated on Sep 30, 2024
- Permission fixes for accessing gallery files and camera on Android 14.
- Performance improvements and bug fixes.

Additional APP Information

Latest Version

3.1.2

Uploaded by

Amel Lamouchi

Requires Android

Android 6.0+

Available on

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Use APKPure App

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Security Report

BioLeaf - Foliar Analysis

3.1.2

The Security Report will be available soon. In the meantime, please note that this app has passed APKPure's initial safety checks.

SHA256:

be0c6ca5c9b9fc108582e98d09a4fd9c26b95b7230576e73b77f7f2e00d3c03a

SHA1:

7a949e42c57e15b5a977442341ea636a60ca0262