The study states that non-destructive detection technologies (NDDTs) address these issues by identifying diseases at early ...

A research team now proposes a novel Multi-Granularity Alignment (MGA) domain adaptation framework that dramatically improves cross-domain detection accuracy, enabling deep learning models to maintain ...

The introduction of deep learning-based disease detection models offers a more efficient, cost-effective solution that can identify diseases at an early stage, thus enabling timely intervention.

More information: Rui Kang et al, Toward Real Scenery: A Lightweight Tomato Growth Inspection Algorithm for Leaf Disease Detection and Fruit Counting, Plant Phenomics (2024).

The technology builds on a previous prototype patch, which detected plant disease by monitoring VOCs emitted by plants. Plants emit different combinations of VOCs under different circumstances.

Machine learning at the edge for AI-enabled multiplexed pathogen detection. Scientific Reports, 2023; 13 (1) DOI: 10.1038/s41598-023-31694-6 ...