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Plant.id is a machine learning-based plant identification API launched in 2018, [6] with the plant disease identification API, plant.health, released in April 2022. [4] The plant.id API is suitable for integration into other software, such as mobile apps [ 7 ] or urban trees from remote-sensing imagery.
An app for smartphones (and a web version) was launched in 2013, [4] which allows to identify thousands of plant species from photographs taken by the user. It is available in several languages. As of 2019 it had been downloaded over 10 million times, in more than 180 countries worldwide. [1]
[7] [8] It is the primary application for crowd-sourced biodiversity data in places such as Mexico, southern Africa, and Australia, [9] [10] [11] and the project has been called "a standard-bearer for natural history mobile applications." [12] Most of iNaturalist's software is open source. [13]
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Pl@ntNet is a global citizen science project which provides an app and a website for plant identification through photographs, based on machine-learning; Leaf Snap is an iOS app developed by the Smithsonian Institution that uses visual recognition software to identify North American tree species from photographs of leaves. [citation needed]
Field guides instruct foragers to carefully identify species before assuming that any wild plant is edible. Accurate determination ensures edibility and safeguards against potentially fatal poisoning. Some plants that are generally edible can cause allergic reactions in some individuals.
Spectrolyzer is a Microsoft Windows-based software package developed by Binary Detect (previously named Medicwave) that provides bioinformatics data analysis tools for different mass spectrometers. It focuses on finding protein biomarkers and detecting protein deviations.
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