Abstract :
Due to the importance of plants in the Earth´s ecosystem, their photobiological responses have become the subject of extensive research in life sciences. Leaf optical models have been developed to assist in the analysis of remotely sensed data to derive information on leaf biochemistry and anatomy from foliar spectral curves (transmittance and reflectance). In this paper, we investigate the implications of using in vitro pigment absorption spectra to model foliar optical properties in the visible domain. Typically, pigment absorption spectra have been determined using light absorption spectroscopy (AS) or by applying a data fitting approach. Alternatively, we propose the use of photoacoustic pigment AS, which, despite being available in the literature, has not been used in the modeling of foliar optical properties before. We also perform computational experiments in which foliar modeled spectral curves generated using these different absorption data sets are compared with actual measured data. Our findings indicate that the proposed alternative not only allows key pigments to be individually incorporated into the models, which, in turn, increases the predictability of the simulations, but also enables the generation of modeled foliar spectral curves that are more accurate than those obtained using absorption data derived from standard AS procedures.
Keywords :
atmospheric boundary layer; atmospheric electromagnetic wave propagation; atmospheric radiation; vegetation; Earth´s ecosystem; actual measured data; computational experiments; data fitting approach; foliar modeled spectral curves; foliar optical properties; foliar optical properties modeling; foliar spectral curves; leaf anatomy; leaf biochemistry information; leaf optical models; leaf optical properties modeling; life sciences research; light absorption spectroscopy; photoacoustic absorption spectral data; photoacoustic pigment; photobiological responses; pigment absorption spectra; reflectance; remotely sensed data analysis; transmittance; visible domain; visible range; Biochemical analysis; Biochemistry; Biomedical optical imaging; Ecosystems; Electromagnetic wave absorption; Geoscience; Information analysis; Optical sensors; Pigmentation; Predictive models; Leaf; photoacoustic absorption spectroscopy (PAS); pigments; reflectance; transmittance;