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Estimating near-infrared leaf reflectance from leaf structural characteristics¹

² Department of Botany, University of Wyoming, Laramie, Wyoming 82071-3165 USA; ³ USDA Agricultural Research Service, Remote Sensing and Modeling Laboratory, Beltsville Agricultural Research Center,10300 Baltimore Avenue, Beltsville, Maryland 20707 USA; and ⁴ Department of Biology, Wake Forest University, P.O. Box 7325, Winston-Salem, North Carolina 27109 USA

The relationship between near-infrared reflectance at 800 nm (NIRR) from leaves and characteristics of leaf structure known to affect photosynthesis was investigated in 48 species of alpine angiosperms. This wavelength was selected to discriminate the effects of leaf structure vs. chemical or water content on leaf reflectance. A quantitative model was first constructed correlating NIRR with leaf structural characteristics for six species, and then validated using all 48 species. Among the structural characteristics tested in the reflectance model were leaf trichome density, the presence or absence of both leaf bicoloration and a thick leaf cuticle (>1 µm), leaf thickness, the ratio of palisade mesophyll to spongy mesophyll thickness (PM/SM), the proportion of the mesophyll occupied by intercellular air spaces (%IAS), and the ratio of mesophyll cell surface area exposed to IAS (A_mes) per unit leaf surface area (A), or A_mes/A. Multiple regression analysis showed that measured NIRR was highly correlated with A_mes/A, leaf bicoloration, and the presence of a thick leaf cuticle (r = 0.93). In contrast, correlations between NIRR and leaf trichome density, leaf thickness, the PM/SM ratio, or %IAS were relatively weak (r < 0.25). A model incorporating A_mes/A, leaf bicoloration, and cuticle thickness predicted NIRR accurately for 48 species (r = 0.43; P < 0.01) and may be useful for linking remotely sensed data to plant structure and function.

Key Words: A_mes/A • bicoloration • leaf structure • mesophyll • near-infrared • reflectance

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