Paper record
A compact multimodal and imaging system for presymptomatic plant stress detection in NASA-controlled space agriculture
Sensing for Agriculture and Food Quality and Safety XVIII · 11 Jun 2026 · 10.1117/12.3101800
Abstract
A hybrid AI framework combining a spatial–spectral–temporal Transformer and unsupervised clustering was applied to five microgreen species—Pak Choi Cabbage, Tatsoi Mustard, Red Mizuna, Chinese Cabbage, and Arugula—grown for 3–4 weeks under water, nutrient, and combined stresses. Across five datasets collected within six months, the system achieved a Macro-F1 of 0.91 and a pre-symptomatic F1 of 0.88, enabling early detection before visible symptoms. Applications include NASA’s APH, Mars and Moon habitats, and terrestrial precision agriculture.
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