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At any scale, from a single microbe to the planet that nurtures us, water defines our place in the universe. It provides the hydraulic forces needed to give plants structure, and the medium enabling photosynthesis, the basis for most life on Earth, to occur. Knowledge of plant water status is vital to understanding the state or condition of vegetation, information which is essential to disciplines as diverse as agriculture, geography, and climatology. Non-destructive and remote sensing of plant water status allows the gathering of such information across wide geographic extents and over long periods of time. Monitoring vegetation remotely requires an understanding of how reflected light may be used to infer the water status of plants. Several greenhouse experiments were performed using maize (Zea mays L.) and soybean (Glycine max. (L.) Merr. – hereafter called “soy”) to examine changes in reflectance as these plants were subjected to water deficiency and, thereby, to water stress. These tests employed a new experimental design which allowed daily hyperspectral radiometric measurements from intact plants to be compared to representative determinations of relative water content and water potential obtained by destructive measurement techniques. It was discovered that a systematic increase in leaf-level visible light (photosynthetically active radiation – PAR) reflectance accompanied increasing levels of stress in maize, and, when relative water content was below 70%, in soy. This finding, resulting from some yet to be identified change in plant cells or internal leaf structure, is unexpected since there is no absorption of light by water molecules in the PAR spectral region. Despite extensive literature searches, no previous publication of the effect has been uncovered. The increase in PAR reflectance was shown to be useful in estimating the water status of maize, and, when RWC was less than 70%, of soy. More work is needed to determine if this effect can be used to estimate water status from the canopy level or above.