Evaluation of Machine Learning Models for Stress Symptom Classification of Cucumber Seedlings Grown in a Controlled Environment
Stress by unfavorable environmental conditions, including temperature, light intensity, and photoperiod, significantly impact early-stage growth in crops, such as cucumber seedlings, often resulting in yield reduction and quality degradation. Advanced machine learning (ML) models combined with image...
Saved in:
| Main Authors: | Kyu-Ho Lee, Samsuzzaman, Md Nasim Reza, Sumaiya Islam, Shahriar Ahmed, Yeon Jin Cho, Dong Hee Noh, Sun-Ok Chung |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Agronomy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4395/15/1/90 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Automated Seedling Contour Determination and Segmentation Using Support Vector Machine and Image Features
by: Samsuzzaman, et al.
Published: (2024-12-01) -
Determination of the Possibilities of Using Different Compost Materials as Seedling Growing Medias in Tomato, Cucumber and Pepper
by: İbrahim Karataş, et al.
Published: (2024-10-01) -
Effects of Chaetomium globosum and Trichoderma asperellum on root configuration and growth of cucumber seedlings
by: Wang Yu, et al.
Published: (2025-07-01) -
Improved YOLOv8 Algorithm was Used to Segment Cucumber Seedlings Under Complex Artificial Light Conditions
by: Duokuo Zhang, et al.
Published: (2025-01-01) -
Salinity tolerance in Cucumis sativus seedlings: the role of pistachio wood vinegar on the improvement of biochemical parameters and seedlings vigor
by: Sediqeh Afsharipour, et al.
Published: (2025-02-01)