Leaf movements as a quantitative metric for early stress detection

Herrero, E.; Wijeweera, S.; Gill, A. R.; Bampton, C.; Sullivan, W.; Stamford, J. D.; Bromley, J.; Antoniades, A. Z.; Mortimer, J. C.; Webb, A. A. R.; Gilliham, M.; Millar, A. H.

doi:10.64898/2026.06.16.732190

bioRxiv · 10.64898/2026.06.16.732190

Leaf movements as a quantitative metric for early stress detection

Herrero, E.·Wijeweera, S.·Gill, A. R.·Bampton, C.·Sullivan, W.·Stamford, J. D.·Bromley, J.·Antoniades, A. Z.·Mortimer, J. C.·Webb, A. A. R.·Gilliham, M.·Millar, A. H.

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Abstract

Early, precise, and non-destructive stress detection is essential for maintaining crop productivity, particularly in high-density plant growth systems like controlled environment agriculture (CEA), where manual monitoring is often impractical. Using plant motion as a proxy for growth and plant health, we demonstrate a method for early, non-invasive stress detection through quantitative leaf-movement analysis in lettuce and five other CEA relevant crops. Leaf-movement dynamics under stress were imaged with a low-cost, scalable Raspberry Pi imaging setup and quantified using a repurposed open-source motion estimation algorithm; Tracking Rhythms in Plants (TRiP). Our system detected stress-induced changes in leaf-movement within 1 hour of stress, with the timing dependent on the nature of the stress. Sustained reductions in leaf-movement coincide with decreased biomass accumulation. This approach offers a non-invasive, rapid, scalable, and cost-effective solution for continuous crop monitoring, with potential for application in both terrestrial and space farming CEA systems. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/732190v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@19ee20eorg.highwire.dtl.DTLVardef@b0804org.highwire.dtl.DTLVardef@3b3fa8org.highwire.dtl.DTLVardef@1d04026_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstract:C_FLOATNO Quantification of leaf-movement dynamics as a high-throughput proxy for plant physiological status, enabling early stress detection and timely intervention to mitigate yield penalties in CEA settings (image made with biorender.org). C_FIG

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Herrero, E., Wijeweera, S., Gill, A. R., Bampton, C., Sullivan, W., Stamford, J. D., Bromley, J., Antoniades, A. Z., Mortimer, J. C., Webb, A. A. R., Gilliham, M., Millar, A. H.. 2026-06-18. Leaf movements as a quantitative metric for early stress detection. https://doi.org/10.64898/2026.06.16.732190

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