Mapping olive varieties and within-field spatial variability using high resolution QuickBird imagery

[Abstract]: The growth of the Australian olive (Olea europaea L.) industry requires support from research to ensure its profitability and sustainability. To contribute to this goal, our project tested the ability of remote sensing imagery to map olive groves and their attributes. Specifically, this study aimed to: (a) discriminate olives varieties; and to (b) detect and interpret within-field spatial variability. Using high spatial resolution (2.8m) QuickBird multispectral imagery acquired over Yallamundi (southeast Queensland) on 24 December 2003, both visual interpretation and statistical (divergence) measures were employed to discriminate olive varieties. Similarly, the detection and interpretation of within-field spatial variability was conducted on enhanced false colour composite imagery, and confirmed by the use of statistical methods. Results showed that the two olive varieties (i.e. Kalamata and Frantoio) can be visually differentiated and mapped on the enhanced image based on texture. The spectral signature plots showed little difference in the mean spectral reflectance values, indicating that the two varieties have a very low spectral separability. In terms of within-field spatial variability, the presence or absence of Rhodes grass (Chloris gayana) was detected using visual interpretation, corroborated by the results of quantitative statistical measures. Spatial variability in soil properties, caused by the presence of a patch of sandy soil, was also detected visually. Finally, the “imprint” of former cover-type or land-use prior to olive plantation establishment in 1998 was identified. More work is being done to develop image classification techniques for mapping within-field spatial variability in olive varieties, biomass and condition using hyperspectral image data, as well as interpreting the cause of observed variability

The importance of attractive three-point interaction in enantioselective surface chemistry: stereospecific adsorption of serine on the intrinsically chiral Cu{531} surface

Both enantiomers of serine adsorb on the intrinsically chiral Cu{531} surface in two different adsorption geometries, depending on the coverage. At saturation, substrate bonds are formed through the two oxygen atoms of the carboxylate group and the amino group (μ3 coordination), whereas at lower coverage, an additional bond is formed through the deprotonated β−OH group (μ4 coordination). The latter adsorption geometry involves substrate bonds through three side groups of the chiral center, respectively, which leads to significantly larger enantiomeric differences in adsorption geometries and energies compared to the μ3 coordination, which involves only two side groups. This relatively simple model system demonstrates, in direct comparison, that attractive interactions of three side groups with the substrate are much more effective in inducing strong enantiomeric differences in heterogeneous chiral catalyst systems than hydrogen bonds or repulsive interactions

Mapping the multi-decadal mangrove dynamics of the Australian coastline

Mangroves globally provide a diverse array of ecosystem services but these are impacted upon by both natural and anthropogenic drivers of change. In Australia, mangroves are protected by law and hence the natural drivers predominate. To determine annual national level changes in mangroves between 1987 and 2016, their extent (by canopy cover type)and dynamics were quantified using dense time-series (nominally every 16 days cloud permitting)of 25 m spatial resolution Landsat sensor data available within Digital Earth Australia (DEA). The potential area that mangroves occupied over this period was established as the union of mangrove maps generated for 1996, 2007–2010 and 2015/16 through the Global Mangrove Watch (GMW). Within this area, the green vegetation fractional cover (GVpc)was retrieved from each available cloud-masked Landsat scene through linear spectral unmixing. The 10th percentile (GVpc10)was then determined for each calendar year by comparing these data in a time-series. The percentage Planimetric Canopy Cover (PCC%)for each Landsat pixel was then estimated using a relationship between GVpc10 and LiDAR-derived PCC% (20%; resolvable at the Landsat resolution)varied from a minima of 10,715 ± 36 km (95% confidence interval)in 1992 to a maxima of 11,388 km ± 38 km (95% CI)in 2010, declining to 11,142 ± 57 km (95% CI)in 2017. In 2010 (maximum extent), the forests were classified as closed canopy (38.8%), open canopy (49.0%)and woodland mangrove (12.2%). The majority of change occurred along the northern Australian coastline and was concentrated in the major gulfs and sounds. The 30 national maps of annual mangrove extent represent a reference dataset, which is publicly available through the Terrestrial Environment Research Network (TERN)landscapes portal. Future efforts are focusing on the routine production of annual mangrove maps beyond 2019 as part of Australia's efforts to monitor the coastal environment

A Revised Design for Microarray Experiments to Account for Experimental Noise and Uncertainty of Probe Response

Background Although microarrays are analysis tools in biomedical research, they are known to yield noisy output that usually requires experimental confirmation. To tackle this problem, many studies have developed rules for optimizing probe design and devised complex statistical tools to analyze the output. However, less emphasis has been placed on systematically identifying the noise component as part of the experimental procedure. One source of noise is the variance in probe binding, which can be assessed by replicating array probes. The second source is poor probe performance, which can be assessed by calibrating the array based on a dilution series of target molecules. Using model experiments for copy number variation and gene expression measurements, we investigate here a revised design for microarray experiments that addresses both of these sources of variance. Results Two custom arrays were used to evaluate the revised design: one based on 25 mer probes from an Affymetrix design and the other based on 60 mer probes from an Agilent design. To assess experimental variance in probe binding, all probes were replicated ten times. To assess probe performance, the probes were calibrated using a dilution series of target molecules and the signal response was fitted to an adsorption model. We found that significant variance of the signal could be controlled by averaging across probes and removing probes that are nonresponsive or poorly responsive in the calibration experiment. Taking this into account, one can obtain a more reliable signal with the added option of obtaining absolute rather than relative measurements. Conclusion The assessment of technical variance within the experiments, combined with the calibration of probes allows to remove poorly responding probes and yields more reliable signals for the remaining ones. Once an array is properly calibrated, absolute quantification of signals becomes straight forward, alleviating the need for normalization and reference hybridizations

Direct in situ spectroscopic evidence of the crucial role played by surface oxygen vacancies in the O2-sensing mechanism of SnO2

NAP-XPS characterisation of SnO2 under operando conditions shows that resistance change, band bending and surface O-vacancy concentration are correlated with ambient O2 concentration, challenging current preconceptions of gas sensor function

Satellites: ambition for forest initiative

Full text (Correspondence is 300 words). Lynch et al. (Nature 496, 293-294; 2013) are surely right to say that satellites are essential for monitoring deforestation under the REDD+ provisions of a future climate agreement; indeed the need to use remotely sensed and ground based data in combination for this purpose was formally recognized by decision of the United Nations Framework on Climate Change Conference (UNFCCC) of Parties in 2009. What seems less likely is that a comprehensive rapid response monitoring system will, as Lynch et al. hope, be enshrined in international law under the UNFCCC at the 19th Conference of Parties, in Warsaw later this year. Nature is perhaps not the appropriate place to debate national sovereignty concerns, but these would represent a significant barrier to putting in place such a proposal. Cloud is also a constraint on optical remote sensing although screening and compositing methods can help reduce its effects. Radar can penetrate cloud but in our view is not yet established as an operational means for the capture of changes to forest ecosystems in the suitably systematic and repeatable manner required for monitoring deforestation although may become operationally relevant in the future. As participants in these processes we disagree strongly with the suggestion that the outputs of Global Observation of Forest and Land Cover Dynamics Programme (GOFC-GOLD) or the Global Forest Observations Initiative (GFOI) lack ambition and an understanding of the potential of satellites. On the contrary the aim of these activities is show objectively and without bias in favour of one approach or another how remote sensing helps systematic global monitoring to make REDD+ a reality, in the context of wider societal engagement and capacity building that are essential for its success.JRC.H.3-Forest Resources and Climat

Genome sequence of the soil bacterium Saccharomonospora azurea type strain (NA-128T)

Saccharomonospora azurea Runmao et al. 1987 is a member of the genus Saccharomonospora, which is in the family Pseudonocardiaceae and thus far poorly characterized genomically. Members of the genus Saccharomonospora are of interest because they originate from diverse habitats, such as leaf litter, manure, compost, the surface of peat, and moist and over-heated grain, and may play a role in the primary degradation of plant material by attacking hemicellulose. Next to S. viridis, S. azurea is only the second member in the genus Saccharomonospora for which a completely sequenced type strain genome will be published. Here we describe the features of this organism, together with the complete genome sequence with project status ‘Improved high quality draft’, and the annotation. The 4,763,832 bp long chromosome with its 4,472 protein-coding and 58 RNA genes was sequenced as part of the DOE funded Community Sequencing Program (CSP) 2010 at the Joint Genome Institute (JGI)