Hyperspectral remote sensing of foliar nitrogen content

http://www.pnas.orgPeer reviewe

Interdroplet bilayer arrays in millifluidic droplet traps from 3D-printed moulds

In droplet microfluidics, aqueous droplets are typically separated by an oil phase to ensure containment of molecules in individual droplets of nano-to-picoliter volume. An interesting variation of this method involves bringing two phospholipid-coated droplets into contact to form a lipid bilayer in-between the droplets. These interdroplet bilayers, created by manual pipetting of microliter droplets, have proved advantageous for the study of membrane transport phenomena, including ion channel electrophysiology. In this study, we adapted the droplet microfluidics methodology to achieve automated formation of interdroplet lipid bilayer arrays. We developed a ‘millifluidic’ chip for microliter droplet generation and droplet packing, which is cast from a 3D-printed mould. Droplets of 0.7–6.0 μL volume were packed as homogeneous or heterogeneous linear arrays of 2–9 droplets that were stable for at least six hours. The interdroplet bilayers had an area of up to 0.56 mm2, or an equivalent diameter of up to 850 μm, as determined from capacitance measurements. We observed osmotic water transfer over the bilayers as well as sequential bilayer lysis by the pore-forming toxin melittin. These millifluidic interdroplet bilayer arrays combine the ease of electrical and optical access of manually pipetted microdroplets with the automation and reproducibility of microfluidic technologies. Moreover, the 3D-printing based fabrication strategy enables the rapid implementation of alternative channel geometries, e.g. branched arrays, with a design-to-device time of just 24–48 hours

Reply toTownsend et al.: Decoupling contributions from canopy structure and leaf optics is critical for remote sensing leaf biochemistry

Non peer reviewe

Decoupling Contributions from Canopy Structure and Leaf Optics is Critical for Remote Sensing Leaf Biochemistry (Reply to Townsend, et al.)

Townsend et al. (1) agree that we explained that the apparent relationship (2) between foliar nitrogen (%N) and near-infrared (NIR) canopy reflectance was largely attributable to structure (which is in turn caused by variation in fraction of broadleaf canopy). Our conclusion that the observed correlation with %N was spurious (i.e., lacking a causal basis) is, thus, clearly justified: we demonstrated that structure explained the great majority of observed correlation, where the structural influence was derived precisely via reconciling the observed correlation with radiative-transfer theory. What this also suggests is that such correlations, although observed, do not uniquely provide information on canopy biochemical constituents

Microsatellite diversity of the Nordic type of goats in relation to breed conservation: how relevant is pure ancestry?

In the last decades, several endangered breeds of livestock species have been re-established effectively. However, the successful revival of the Dutch and Danish Landrace goats involved crossing with exotic breeds and the ancestry of the current populations is therefore not clear. We have generated genotypes for 27 FAO-recommended microsatellites of these landraces and three phenotypically similar Nordic-type landraces and compared these breeds with central European, Mediterranean and south-west Asian goats. We found decreasing levels of genetic diversity with increasing distance from the south-west Asian domestication site with a south-east-to-north-west cline that is clearly steeper than the Mediterranean east-to-west cline. In terms of genetic diversity, the Dutch Landrace comes next to the isolated Icelandic breed, which has an extremely low diversity. The Norwegian coastal goat and the Finnish and Icelandic landraces are clearly related. It appears that by a combination of mixed origin and a population bottleneck, the Dutch and Danish Land-races are separated from the other breeds. However, the current Dutch and Danish populations with the multicoloured and long-horned appearance effectively substitute for the original breed, illustrating that for conservation of cultural heritage, the phenotype of a breed is more relevant than pure ancestry and the genetic diversity of the original breed. More in general, we propose that for conservation, the retention of genetic diversity of an original breed and of the visual phenotype by which the breed is recognized and defined needs to be considered separately

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given

Reply to Ollinger et al.:Remote sensing of leaf nitrogen and emergent ecosystem properties

Various physical, chemical, and physiological processes, including canopy structure, impact surface reflectance. Remote sensing aims to derive ecosystem properties and their functional relationships, given these impacts. Ollinger et al. (1) do not distinguish between the forward and inverse problems in radiative transfer and, hence, misrepresent our results (2). The authors also suggest our conclusions are based on a subset of data from ref. 3, which is not the case

PANDORA Project for the study of photonuclear reactions below A = 60

info:eu-repo/semantics/publishe