The Plant journal : for cell and molecular biology · 2026
Dim green light enables day-and-night monitoring of leaf movements.
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Herrero Eva, Gill Alison R, Wijeweera Samalka, Ginzburg Daniel N, Stamford John D, Antoniades Andreas, Bromley Jennifer R, Mortimer Jenny C, Gilliham Matthew, Millar A Harvey, Webb Alex A R
Аннотация
Understanding plant growth, movement and development in the aerial plant body requires imaging across day-and-night cycles to quantify temporal dynamics and rhythmicity. This requires imaging in light during the day and in darkness at night without perturbing plant physiology. Nighttime imaging has typically depended on infrared (IR) illumination, producing monochrome datasets that require specialised hardware and separate analysis pipelines when combined with daytime RGB imaging. Here, we evaluated very low-intensity green (dimG) illumination from standard LEDs as a practical alternative for colour-consistent nighttime imaging and assessed its physiological impact in Arabidopsis thaliana and Lactuca sativa (lettuce). We show that high-resolution colour images can be obtained under dimG using low-cost cameras, with sufficient consistency between full-spectrum and dimG images to allow direct comparison and unified image analysis. We show that very low-fluence green light (<0.5 mmol m-2 s-1) does not sustain circadian oscillations of gene activity under continuous exposure and does not perturb rhythms when applied during the dark phase of diel cycles. DimG imaging enabled accurate detection of diel leaf-movement profiles in Arabidopsis circadian mutants, revealing genotype-specific phase differences under varying photoperiods. In lettuce, dimG pulses and continuous dimG enabled accurate quantification of diel leaf movement without affecting growth, stomatal opening, electron transport rate or chlorophyll content. Motion profiles under continuous dimG mirrored those under darkness. Our findings establish dim green illumination as a cost-effective solution for nighttime imaging, simplifying phenotyping workflows with minimal impact on physiology.