Knyazikhin et al. (1) dealt with the necessity to disentangle efforts Celgosivir IC50 of canopy structural and leaf optical properties in canopy reflectance spectra (5), however they do not offer an sufficient rationale for the inference that %N and various other leaf properties can’t be characterized from imaging spectroscopy. Rather, inside our opinion, the paper by Knyazikhin et al. illustrated the fact that physics and biology of leaves and canopies can’t be examined in isolation and, correspondingly, that people have to better realize why specific spectroscopic methods work, given that they are not fully reconciled by existing radiative-transfer models. More extensive simulations over broader wavelength ranges are required, using improved parameterization of leaf structural, physiological, and optical properties. For instance, the authors used a single leaf spectrum derived from one PROSPECT simulation, but, as they acknowledged, leaf albedo varies substantially among species, including those in the study, and that variation is related to physiology, biochemistry, and internal leaf structure (2, 3). Use of species-specific simulations of leaf spectra could potentially lead to significant changes in the authors findings across the full 400- to 2,500-nm spectrum. Thus, a reasonable inference drawn from Knyazikhin et al. (1) and previous work (5) is usually that canopy structure is a potentially confounding factor in analyzing vegetation reflectance spectra, not Celgosivir IC50 that NIR and/or SW broadband satellite data cannot be directly linked to leaf-level processes. Finally, Knyazikhin et al. (1) argue that links between leaf biochemistry (e.g., %N) and hyperspectral reflectance data are obscured by variation in leaf-surface albedo, which seems inconsistent with a sizeable and growing body of empirical evidence (2, 3). Statistically strong associations between leaf or canopy biochemistry and imaging spectroscopy, within and across a diverse range of species, have repeatedly been demonstrated, albeit for reasons that we are currently unable to fully Celgosivir IC50 represent within radiative-transfer models. In any case, progress in remote sensing requires integration of both biologically and actually based approaches, and better linkages between the two will improve our ability to remotely detect biologically meaningful leaf optical properties. Footnotes The authors declare no conflict of interest.. The analyses focused primarily on 800- to 850-nm albedo, and, thus, it is unclear whether the email address details are appropriate to narrow-waveband (e.g., 10 nm) and full-spectrum (e.g., 400C2500 nm) research, as the personal of leaf-level variant in foliar nutrition specifically, such as for example nitrogen, is certainly most prominent in shortwave infrared locations (>1,100 nm) which were not really addressed with the writers (2, 3). Knyazikhin et al. (1) dealt with the necessity to disentangle efforts of canopy structural and leaf optical properties in canopy reflectance spectra (5), however they do not really provide an sufficient rationale for the inference that %N and various other leaf properties can’t be characterized from imaging spectroscopy. Rather, inside our opinion, the paper by Knyazikhin et al. illustrated the fact that biology and physics of leaves and canopies can’t be examined in isolation and, correspondingly, that people have to better realize why specific spectroscopic methods function, simply because they are not completely reconciled by existing radiative-transfer versions. More intensive Goat polyclonal to IgG (H+L)(FITC) simulations over broader wavelength runs are needed, using improved parameterization of leaf structural, physiological, and optical properties. For example, the writers used an individual leaf spectrum produced from one Potential customer simulation, but, because they recognized, leaf albedo varies significantly among types, including those in the analysis, and that variant relates to physiology, biochemistry, and inner leaf framework (2, 3). Usage of Celgosivir IC50 species-specific simulations of leaf spectra may potentially result in significant adjustments in the writers findings over the complete 400- to 2,500-nm range. Thus, an acceptable inference attracted from Knyazikhin et al. (1) and prior work (5) is certainly that canopy framework is a possibly confounding element in analyzing vegetation reflectance spectra, not really that NIR and/or SW broadband satellite television data can’t be directly associated with leaf-level procedures. Finally, Knyazikhin et al. (1) argue that links between leaf biochemistry (e.g., %N) and hyperspectral reflectance data are obscured by variant in leaf-surface albedo, which appears inconsistent using a sizeable and developing body of Celgosivir IC50 empirical proof (2, 3). Statistically solid interactions between leaf or canopy biochemistry and imaging spectroscopy, within and across a different range of types, have frequently been confirmed, albeit for factors that we are unable to completely represent within radiative-transfer versions. Regardless, progress in remote control sensing needs integration of both biologically and bodily based techniques, and better linkages between your two will improve our ability to remotely detect biologically meaningful leaf optical properties. Footnotes The authors declare no discord of interest..