Blasting is an integral part of large-scale open cut mining that often occurs in close proximity to population centers and often results in the emission of particulate material and gases potentially hazardous to health. Current air quality monitoring methods rely on limited numbers of fixed sampling locations to validate a complex fluid environment and collect sufficient data to confirm model effectiveness. This paper describes the development of a methodology to address the need of a more precise approach that is capable of characterizing blasting plumes in near-real time. The integration of the system required the modification and integration of an opto-electrical dust sensor, SHARP GP2Y10, into a small fixed-wing and multi-rotor copter, resulting in the collection of data streamed during flight. The paper also describes the calibration of the optical sensor with an industry grade dust-monitoring device, Dusttrak 8520, demonstrating a high correlation between them, with correlation coefficients (R²) greater than 0.9. The laboratory and field tests demonstrate the feasibility of coupling the sensor with the UAVs. However, further work must be done in the areas of sensor selection and calibration as well as flight planning.

Background: The ability of sugarcane to accumulate high concentrations of sucrose in its culm requires adaptation to maintain cellular function under the high solute load. We have investigated the expression of 51 genes implicated in abiotic stress to determine their expression in the context of sucrose accumulation by studying mature and immature culm internodes of a high sucrose accumulating sugarcane cultivar. Using a sub-set of eight genes, expression was examined in mature internode tissues of sugarcane cultivars as well as ancestral and more widely related species with a range of sucrose contents. Expression of these genes was also analysed in internode tissue from a high sucrose cultivar undergoing water deficit stress to compare effects of sucrose accumulation and water deficit. Results: A sub-set of stress-related genes that are potentially associated with sucrose accumulation in sugarcane culms was identified through correlation analysis, and these included genes encoding enzymes involved in amino acid metabolism, a sugar transporter and a transcription factor. Subsequent analysis of the expression of these stress-response genes in sugarcane plants that were under water deficit stress revealed a different transcriptional profile to that which correlated with sucrose accumulation. For example, genes with homology to late embryogenesis abundant-related proteins and dehydrin were strongly induced under water deficit but this did not correlate with sucrose content. The expression of genes encoding proline biosynthesis was associated with both sucrose accumulation and water deficit, but amino acid analysis indicated that proline was negatively correlated with sucrose concentration, and whilst total amino acid concentrations increased about seven-fold under water deficit, the relatively low concentration of proline suggested that it had no osmoprotectant role in sugarcane culms. Conclusions: The results show that while there was a change in stress-related gene expression associated with sucrose accumulation, different mechanisms are responding to the stress induced by water deficit, because different genes had altered expression under water deficit.

The large amounts of nitrogen (N) fertiliser applied to most cropping systems support high yields but cause N pollution. More efficient use of N in cropping systems can be achieved through improved N management practices combined with genetic improvement of the crop. The magnitude of genetic variation in sugarcane (Saccharum officinarum L.) for internal nitrogen use efficiency (iNUE, biomass produced per unit tissue N) was investigated as this could provide a basis for breeding varieties with reduced N demand. Genotypes of a mapping population were examined for biomass production and physiological variables under low or high N supply in controlled conditions. Key findings were: (i) genotypic variation for biomass production and iNUE was up to 3-fold greater under low than high N supply, (ii) elite parent Q165FP07183_E1A.gif was among the best performing genotypes for biomass and iNUE at high N but not at low N supply, and (iii) several genotypes had high iNUE at both N supplies. While glutamine synthetase (GS; EC 6.3.1.2) activity has been linked with grain yield in other crops, no direct relationship was observed between whole tissue GS activity and vegetative biomass or iNUE in sugarcane genotypes. Soluble protein content was negatively correlated with iNUE and biomass production. This study demonstrates that there is considerable genetic variation for iNUE in sugarcane, which can be exploited for breeding. It is proposed that breeding programs should assess genotypes not only at high N, but also at low N supply rates to select genotypes that produce high biomass with low and high N supply.

Subsidence, resulting from underground coal mining can alter the structure of overlying rock formations changing hydrological conditions and potentially effecting ecological communities found on the surface. Of particular concern are impacts to endangered and/or protected swamp communities and swamp species sensitive to changes in hydrologic conditions. This paper describes a monitoring approach that uses UAVs with modified digital cameras and object-based image analysis methods to characterise swamp landcover on the Newnes plateau in the Blue Mountains near Sydney, Australia. The characterisation of swamp spatial distribution is key to identifying long term changes in swamp condition. In this paper we describe i) the characteristics of the UAV and the sensor, ii) the pre-processing of the remote sensing data with sub-decimeter pixel size to derive visible and near infrared multispectral imagery and a digital surface model (DSM), and iii) the application of object-based image analysis in eCognition using the multi-spectral data and DSM to map swamp extent. Finally, we conclude with a discussion of the potential application of remote sensing data derived from UAVs to conduct environmental monitoring.

Open-cut coal mining began in central Queensland’s Bowen Basin approximately 50 years ago. Over this period of time, mine rehabilitators have used a variety of tree, shrub, and groundcover species to create ‘novel ecosystems’ to stabilise soils and provide vegetative cover for pre-supposed final end-land uses. We examine post-mining rehabilitation from multiple soil and vegetation monitoring activities in the Bowen Basin to assess the similarity of landforms, plant composition, and trends in plant diversity compared to unmined reference communities.