A novel random forest-based approach for the non-destructive and explainable estimation of ammonia and chlorophyll in fresh-cut rocket leaves
The perceived visual quality of fruits and vegetables plays a central role in the choices made by retail customers. Machine learning (ML) approaches based on image analysis have been recently proposed to overcome the poor efficiency and subjectivity of human visual evaluation as well as the expensiv...
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| Main Authors: | Stefano Polimena, Gianvito Pio, Maria Cefola, Michela Palumbo, Michelangelo Ceci, Giovanni Attolico |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | Information Processing in Agriculture |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214317324000635 |
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