Success!
We received your request and we'll contact you shortly 😊

Tomato Diseases Identification

🇺🇸 United States
Jose Martin  | 
19
ASO score
Text
31/100
Reviews
0/100
Graphic
18/100
Other
0/100
rating
App Rating
3.5
rating
Votes
18
rating
App Age
3y 9m
rating
Last Update
Aug 13, 2021

Compare with Category Top Apps

Metrics
Current App
Category Top Average
Difference
Rating
3.47
4.38
-21%
Number of Ratings (Voted)
18
353K
-100%
App Age
3y 9m
6y 0m
-38%
In-app Purchases Price
$0
$35
Update Frequency
1308d
40d
+3 147%
Title Length
30
25
+20%
Subtitle Length
30
26
+15%
Description Length
1 453
2 576
-44%
Number of Screenshots
4
6
-38 %
Size
61MB
147MB
-59 %

Category Ranking in United States

All
New
Trending Up
Trending Down
Top Mar 05, 2025 Mar 12, 2025
No results were found!
Top Mar 05, 2025 Mar 12, 2025
No results were found!
Top Mar 05, 2025 Mar 12, 2025
No results were found!
Top Mar 05, 2025 Mar 12, 2025
No results were found!

Ranking Keywords in United States

Keywords App Rank
tomato diseases identification
out out
tomato disease identifier
out out
identify tomatoes disease leaf
out out
disease identification
out out
identify tomato plant diseases
out out
plant spot
out out
Illustration
Analyze this and other apps using Asolytics tools

Text ASO

Title (
Characters: 30 of 30
)
Tomato Diseases Identification
Subtitle (
Characters: 30 of 30
)
Identify Tomatoes Disease Leaf
Description (
Characters: 1453 of 4000
)
Because symptoms in diseased plants can appear slowly, it is very difficult for farmers to notice and correctly diagnose the disease. Leaves are the most commonly observed part for detecting an infection. All the farmers have to do is to wave the phone in front of the leaf of a tomato diseased plant and the app would diagnose it and suggest ways to maintain the crop. The plant diseases are a major thread to losses of modern agricultural production. Plant disease severity is an important parameter to measure disease level and thus can be used to predict yield and recommend treatment. The rapid, accurate diagnosis of disease severity will help to reduce yield losses. Another Advantages: + You can protect them. + You can grow more crops. + You can have more reliable source of food 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 of tomato leafs) has been used to get the maximum accuracy. 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 will be improving 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. For any doubt, please contact me at bellostudios@gmail.com}
Read more

Visual ASO

Screenshots

Rating & Reviews

Reviews Overview
🧐 Coming Soon…
Rating
3.5
18 voters

Some Latest Reviews

Rebeca361
05 Jun, 2021
5
I found this tool really useful as it founds the disease just with a photo of a leaf, which is great! Also it is explained some treatments depending on the diseases
Jessica Hoz
05 Jun, 2021
5
I wanted to be certain that the disease of my tomato plants was late blight. With this app I could confirm it. There are so many types of tomatoes plant diseases.
Jessica Lange80
05 Jun, 2021
5
I have a lot of tomatoes growing in my little field. This help me to discover soon the tomato plant disease. Just taking a picture of tge leaf, just great!
Katemoss10
04 Jun, 2021
5
This is very cool. It detects the diseases trrough a photo of leaves.

Other

Additional Information
Rating:
3.45
Voted: 18
App Store Link:
Price: 1.99 $
Website:
Email: -
Privacy Policy:
Categories: Utilities
Size: 60MB
App Age: 3 years 9 months
Release Date: Jun 03, 2021
Last Update: Aug 13, 2021
Version: 1.3
Version history
1.3
Aug 13, 2021
The artificial intelligence has been improved and now is even more accurate.
1.1
Aug 12, 2021
The artificial intelligence has been improved and now is even more accurate.
Version history