Plantix is a diagnostic app for farmers, gardeners and everybody working in agriculture. Whether you are a farmer interested in sustainable practice or an urban gardener loving tomatoes, the app tests your crops on diseases, pests and nutrient deficiencies with the help of a simple smartphone picture
Download: Android 4.0.3 (14.71MB)
Language: English / German / Portuguese / Hindi (as the team of developers comments, they’re working on traslations into Spanish, French and Arabic)
Runs offline: partially (without connection, the image can not be uploaded to the server running the identification algorithm)
Last update: Android 28/04/2017 (v. 1.6.3. preview)
Website of the developer: PEAT GmbH
Plantix is an application focused to the identification of plant diseases and pests in order to reduce the loss of harvests as a result of these problems. In addition to recognizing different types of agricultural pests and diseases, it provides information on the conditions that trigger these problems, as well as recommendations about the most appropriate chemical or biological pest control in the affected crops. At the moment and according to the Plantix developer team, among there are included plant pathology experts, this tool can identify more than 120 diseases in the 30 crops more widespread in the world.
There are 3 versions of the application:
- Beta version, which is analyzed in this article and is available to any user regardless of their location. In a way, it can be considered as a base version from which the system is learning to recognize the different images. The collaboration of the users is very important in this version, since all the uploaded images are analyzed, being used like “food” of the system. All data are anonymized once the necessary analysis are performed.
- Version for Germany and India, which incorporates specific information about these geographical regions and is only available for download in those countries.
- Internal version only available to development team.
The operation is simple: it is only necessary to select the crop type among the 30 available and take a photo of the leaf or fruit affected by the disease or plague with the device you’re using (the app does not seem to admit images already stored in the smartphone or tablet). If the system is able to identify the plant disease or pest, it will show the approximate result, being able to consult a factsheet. Otherwise, you can do a manual search (there are available several filters and a textual search, although this last option does not recognize the scientific names of species) or ask the community (for this, it is necessary to open a user account).
In the present case and to test the effectiveness of the application, several tests have been carried out based on images obtained from the internet. Initially, it has been tried to identify different diseases and pests common in apple trees and strawberry crops, with a negative result. Subsequently, the test has focused in the search for images of some of the diseases included in the application itself, such as cabbage whitefly (Aleyrodes proletella) or powdery mildew, one of the most common tomato diseases, which also affects other vegetables and fruit trees. In the case of the insect, the system has not been able to recognize the pest, while it has identified without a problem an image of a leaf affected by powdery mildew uploaded on the web The Spruce (see attached image).
Mobile app for pest and disease management of crops (Icrisat 09/09/2016)
Images: screenshots 30/04/2017. ©PEAT GmbH
As Simone Strey, CEO of PEAT, says in one of Plantix’s introductory videos, «every year, between 15 and 30% of world harvest is lost due to plant pathogens and pests». These conditions manifest occasionally during the post-harvest period, also contributing to increase the volume of food that is discarded before reaching the consumer. These problems caused a country like India to present economic losses of $13 billion in 2016, according to government data.
Plantix aims to reduce these losses through the application of image recognition algorithms and artificial intelligence systems that allow rapid identification and remedy of pests and diseases of the most common crops. Although the conditions under which the tests have been carried out are not the most appropriate and taking into account that the application is still in beta, being this the main reason why the application has received a low rating pending new developments and progress, it should be noted the work that PEAT is developing. In fact, one of the lines of development that they want to launch in 2017 is the installation of Plantix on drones, agricultural machinery and greenhouses for pest and disease identification.