Quantitative Phenotyping of Water-Stressed Tomato Plants Using Frequency-Domain Fluorescence Lifetime Imaging Microscope (FD-FLIM)

荧光寿命成像显微镜 显微镜 荧光 荧光显微镜 显微镜 频域 材料科学 光学 遥感 物理 计算机科学 计算机视觉 地质学
作者
Cheng‐Hao Lin,Yi Jing,Hsiao‐Mei Wu
标识
DOI:10.13031/aim.202500595
摘要

Abstract. Early detection of water stress in plants is essential for maintaining agricultural productivity and facilitating timely management decisions in the face of increasingly variable climate conditions. Water stress can adversely affect photosynthesis, reduce transpiration, and ultimately lead to irreversible yield loss. Conventional monitoring methods often rely on visible symptoms or destructive sampling, which can result in delays in preventive measures. Consequently, there is a growing demand for non-destructive and real-time tools capable of detecting physiological changes before visual signs appear. This study presents a frequency-domain fluorescence lifetime imaging microscopy (FD-FLIM) system that utilized n LED-based excitation design to monitor chlorophyll a fluorescence lifetime in tomato leaves. The system employs a 470 nm LED modulated at 30 MHz using a power amplifier, providing a compact and cost-effective alternative to traditional laser-based FLIM platforms. Tomato plants were subjected to two distinct water stress treatments: oven drying to simulate acute dehydration and non-watering to represent progressive drought. Fluorescence lifetime responses were analyzed using both modulation and phase-based methods from acquired microscopic images and were subsequently represented in a phasor diagram. The results indicated that the phase lifetime was more sensitive to early-stage stress, with phasor plot distributions shifting inward as stress increased, suggesting enhanced decay heterogeneity. Microscopic observations further corroborated the structural disruption in dehydrated tissues. While additional validation across various species and conditions is necessary, this research highlights the feasibility of LED-based FD-FLIM for non-destructive detection of water stress and lays the groundwork for future applications in plant phenotyping.
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