Using a whole-genome-sequencing approach to explore germplasm resources can serve as an important strategy for crop improvement, especially in investigating wild accessions that may contain useful genetic resources that have been lost during the domestication process. Here we sequence and assemble a draft genome of wild soybean and construct a recombinant inbred population for genotyping-by-sequencing and phenotypic analyses to identify multiple QTLs relevant to traits of interest in agriculture. We use a combination of de novo sequencing data from this work and our previous germplasm re-sequencing data to identify a novel ion transporter gene, GmCHX1, and relate its sequence alterations to salt tolerance. Rapid gain-of-function tests show the protective effects of GmCHX1 towards salt stress. This combination of whole-genome de novo sequencing, high-density-marker QTL mapping by re-sequencing and functional analyses can serve as an effective strategy to unveil novel genomic information in wild soybean to facilitate crop improvement.
The stress states in unintentionally doped GaN epilayers grown on Si͑111͒, 6H-SiC͑0001͒, and c-plane sapphire, and their effects on optical properties of GaN films were investigated by means of room-temperature confocal micro-Raman scattering and photoluminescence techniques. Relatively large tensile stress exists in GaN epilayers grown on Si and 6H-SiC while a small compressive stress appears in the film grown on sapphire. The latter indicates effective strain relaxation in the GaN buffer layer inserted in the GaN/sapphire sample, while the 50-nm-thick AlN buffer adopted in the GaN/Si sample remains highly strained. The analysis shows that the thermal mismatch between the epilayers and the substrates plays a major role in determining the residual strain in the films. Finally, a linear coefficient of 21.1Ϯ3.2 meV/GPa characterizing the relationship between the luminescent bandgap and the biaxial stress of the GaN films is obtained.
We compared 10 established and 2 new satellite reflectance algorithms 36 for estimating chlorophyll-a (Chl-a) in a temperate reservoir in southwest Ohio 37 using coincident hyperspectral aircraft imagery and dense coincident surface 38 observations collected within one hour of image acquisition to develop simple 39 proxies for algal blooms in water bodies sensitive to algal blooms (especially toxic 40 or harmful algal blooms (HABs)) and to facilitate portability between multispectral 41 satellite imagers for regional algal bloom monitoring. All algorithms were 42 compared with narrow band hyperspectral aircraft images. These images were 43 subsequently upscaled spectrally and spatially to simulate 5 current and near future 44 satellite imaging systems. Established and new Chl-a algorithms were then applied 45 to the synthetic satellite images and compared to coincident surface observations of 46Chl-a collected from 44 sites within one hour of aircraft acquisition of the imagery. 47We found several promising algorithm/satellite imager combinations for routine 48Chl-a estimation in smaller inland water bodies with operational and near-future 49 satellite systems. The CI, MCI, FLH, NDCI, 2BDA and 3 BDA Chl-a algorithms 50 worked well with CASI imagery. The NDCI, 2BDA, and 3BDA Chl-a algorithms 51 worked well with simulated WorldView-2 and 3, Sentinel-2, and MERIS-like 52 imagery. NDCI was the most widely applicable Chl-a algorithm with good 53 performance for CASI, WorldView 2 and 3, Sentinel-2 and MERIS-like imagery 54 and limited performance with MODIS imagery. A new fluorescence line height 55 "greenness" algorithm yielded the best Chl-a estimates with simulated Landsat-8 56 imagery. 57 ARTICLE INFO 58 Article history: 59 Received ….. 60 Submission to Remote Sensing of Environment 3 Keywords: chorophyll-a, algal bloom, harmful algal bloom, algorithm, satellite, 61 hyperspectral, multispectral 62 63 64 65
A distribution function for localized carriers, f (E, T ) = It reduces to the well-known band-tail and luminescence quenching models under certain approximations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.