Plants Diseases Identifier
Plant Disease Leaf Detector
$2.99
2.0for iPhone, iPad and more
Age Rating
Plants Diseases Identifier Screenshots
About Plants Diseases Identifier
It is very important to know the disease of your crops since the very beginning. Discover your plant disease using a photo of your plant leaf. Leaves are the most commonly observed part for detecting an infection.
Take note that symptoms in some plants can appear slowly, so usually it is difficult for farmers to notice and correctly diagnose the plant disease.
+ This app could diagnose the disease of the following diseases:
Apple scab, Cedar apple rust, Black rot, Powdery mildew, Cercospora leaf spot, Gray leaf spot, Common rust, Northern leaf blight, Eriophyes vitis, Grape esca (Black Measles), Leaf blight (Isariopsis leaf spot), Orange haunglongbing (Citrus greening), Leaf scorch, Early blight, Leaf Mold,
Septoria leaf spot, Two-spotted spider mite, Tomato target spot, Mosaic virus, Tomato yellow leaf curl virus, Bacterial spot and Late blight.
+ So you can take a picture of the following plant leaves to detect them:
Tomatoes, Pepper, Apple, Pear, Quince, Grape vines, Cabbage, Broccoli, Potato, Lemon, Orange, Sweet potato, Cauliflower, Raspberry, Squash, Corn, Peach, Strawberry, Roses, Apricot, Nectarine and Plum.
The rapid, accurate diagnosis of disease severity will help to reduce yield losses.
Another Advantages:
+ You can have more reliable source of food
+ You can grow more crops.
+ You can protect them.
This app allows the opportunity to use computer vision techniques to monitor the disease type and severity and increase yields.
A huge image database (thousand of images) has been used to get the maximum accuracy using artificial neural networks .
This app has also an option to report an image that couldn’t be recognised. If that is the case, it is automated that you can report it immediately by email to the author. So it guarantees that the database image will be improved constantly.
The intended purpose of this app is help the farmers to build a better and bigger crops, which results in a more sustainable world.
Diseases are a major thread to losses of modern agricultural production. Keep your crops healthy.
For any doubt, please contact me at bellostudios@gmail.com.
Take note that symptoms in some plants can appear slowly, so usually it is difficult for farmers to notice and correctly diagnose the plant disease.
+ This app could diagnose the disease of the following diseases:
Apple scab, Cedar apple rust, Black rot, Powdery mildew, Cercospora leaf spot, Gray leaf spot, Common rust, Northern leaf blight, Eriophyes vitis, Grape esca (Black Measles), Leaf blight (Isariopsis leaf spot), Orange haunglongbing (Citrus greening), Leaf scorch, Early blight, Leaf Mold,
Septoria leaf spot, Two-spotted spider mite, Tomato target spot, Mosaic virus, Tomato yellow leaf curl virus, Bacterial spot and Late blight.
+ So you can take a picture of the following plant leaves to detect them:
Tomatoes, Pepper, Apple, Pear, Quince, Grape vines, Cabbage, Broccoli, Potato, Lemon, Orange, Sweet potato, Cauliflower, Raspberry, Squash, Corn, Peach, Strawberry, Roses, Apricot, Nectarine and Plum.
The rapid, accurate diagnosis of disease severity will help to reduce yield losses.
Another Advantages:
+ You can have more reliable source of food
+ You can grow more crops.
+ You can protect them.
This app allows the opportunity to use computer vision techniques to monitor the disease type and severity and increase yields.
A huge image database (thousand of images) has been used to get the maximum accuracy using artificial neural networks .
This app has also an option to report an image that couldn’t be recognised. If that is the case, it is automated that you can report it immediately by email to the author. So it guarantees that the database image will be improved constantly.
The intended purpose of this app is help the farmers to build a better and bigger crops, which results in a more sustainable world.
Diseases are a major thread to losses of modern agricultural production. Keep your crops healthy.
For any doubt, please contact me at bellostudios@gmail.com.
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What's New in the Latest Version 2.0
Last updated on Jul 12, 2022
Old Versions
The identifier accuracy has been improved. The supervised machine learning engine has become more adaptive.
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Version History
2.0
Jul 12, 2022
The identifier accuracy has been improved. The supervised machine learning engine has become more adaptive.
1.8
Apr 28, 2022
Accuracy of the identifier has been improved. The supervised machine learning engine is more adaptive.
1.7
Aug 20, 2021
Improved the accuracy of the disease identifier. The machine learning engine has become more adaptive.
1.6
Jun 28, 2021
Improved the accuracy of the disease identifier, as more photos has been added to the dataset. So the machine learning engine has become more adaptive.
1.5
Jun 14, 2021
Improved the accuracy of the disease identifier, as more photos has been added to the dataset. So the machine learning engine has become more adaptive.
1.4
Apr 21, 2021
Improved the accuracy of the disease identifier, as more photos has been added to the dataset. So the machine learning engine has become more adaptive.
1.3
Feb 25, 2021
Improved the accuracy of the disease identifier, as more photos has been added to the dataset. So the machine learning engine has become more adaptive.
1.2
Dec 16, 2020
Improved the accuracy of the disease identifier, as more photos has been added to the dataset. So the machine learning engine has become more adaptive.
1.1
Nov 2, 2020
Improved the accuracy of the disease identifier, as more photos has been added to the dataset. So the machine learning engine has become more adaptive.
1.0
Oct 31, 2020
Plants Diseases Identifier FAQ
Click here to learn how to download Plants Diseases Identifier in restricted country or region.
Check the following list to see the minimum requirements of Plants Diseases Identifier.
iPhone
Requires iOS 13.0 or later.
iPad
Requires iPadOS 13.0 or later.
iPod touch
Requires iOS 13.0 or later.
Plants Diseases Identifier supports English
