Early monitoring of drought stress in safflower (Carthamus tinctorius L.) using hyperspectral imaging: A comparison of machine learning tools and feature selection approaches

Early monitoring of drought stress in safflower (Carthamus tinctorius L.) using hyperspectral imaging: A comparison of machine learning tools and feature selection approaches

Early detection of drought stress is essential for preventing permanent plant damage and minimizing yield loss. This study utilized hyperspectral imaging at the leaf level to visualize drought stress in safflower plants (Carthamus tinctorius L.). Three safflower genotypes, Palenus, A82, and IL-111,...

Full description

Saved in:
Bibliographic Details
Main Authors: Fatemeh Salek, Seyed Ahmad Mireei, Abbas Hemmat, Mehrnoosh Jafari, Mohammad R. Sabzalian, Majid Nazeri, Wouter Saeys
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Plant Stress
Subjects:
Crop yield
K-means clustering
Partial least squares discriminant analysis (PLS-DA)
Pixel-wise classification
Soft independent modeling of class analogy (SIMCA)
Online Access:http://www.sciencedirect.com/science/article/pii/S2667064X24003063
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items