UV Hyperspectral Imaging and Chemometrics for Honeydew Detection: Enhancing Cotton Fiber Quality
Cotton, the most widely produced natural fiber, is integral to the textile industry and sustains the livelihoods of millions worldwide. However, its quality is frequently compromised by contamination, particularly from honeydew, a substance secreted by insects that leads to the formation of sticky f...
Saved in:
Main Authors: | Mohammad Al Ktash, Mona Knoblich, Frank Wackenhut, Marc Brecht |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Chemosensors |
Subjects: | |
Online Access: | https://www.mdpi.com/2227-9040/13/1/21 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Classical and machine learning tools for identifying yellow-seeded Brassica napus by fusion of hyperspectral features
by: Fan Liu, et al.
Published: (2025-01-01) -
A new band selection framework for hyperspectral remote sensing image classification
by: B. L. N. Phaneendra Kumar, et al.
Published: (2024-12-01) -
New Insights on Quality, Safety, Nutritional, and Nutraceutical Properties of Honeydew Honeys from Italy
by: Andrea Mara, et al.
Published: (2025-01-01) -
Chemometric Methods—A Valuable Tool for Investigating the Interactions Between Antifungal Drugs (Including Antifungal Antibiotics) and Food
by: Agnieszka Wiesner-Kiełczewska, et al.
Published: (2025-01-01) -
Quantitative analysis and resolution of pharmaceuticals in the environment using multivariate curve resolution-alternating least squares (MCR-ALS)
by: Mostafa Ahmed, et al.
Published: (2019-06-01)