Phenotyping novel stay-green traits to capture genetic variation in senescence dynamics

Stay-green plants retain green leaves longer after anthesis and can have improved yield, particularly under water limitation. As senescence is a dynamic process, genotypes with different senescence patterns may exhibit similar final normalised difference vegetative index (NDVI). By monitoring NDVI from as early as awn emergence to maturity, we demonstrate that analysing senescence dynamics improves insight into genotypic stay-green variation. A senescence evaluation tool was developed to fit a logistic function to NDVI data and used to analyse data from three environments for a wheat (Triticum aestivum L.) population whose lines contrast for stay-green. Key stay-green traits were estimated including, maximum NDVI, senescence rate and a trait integrating NDVI variation after anthesis, as well as the timing from anthesis to onset, midpoint and conclusion of senescence. The integrative trait and the timing to onset and mid-senescence exhibited high positive correlations with yield and a high heritability in the three studied environments. Senescence rate was correlated with yield in some environments, whereas maximum NDVI was associated with yield in a drought-stressed environment. Where resources preclude frequent measurements, we found that NDVI measurements may be restricted to the period of rapid senescence, but caution is required when dealing with lines of different phenology. In contrast, regular monitoring during the whole period after flowering allows the estimation of senescence dynamics traits that may be reliably compared across genotypes and environments. We anticipate that selection for stay-green traits will enhance genetic progress towards high-yielding, stay-green germplasm.

Stay-green Drought Adaptation Trait Enhances Sorghum Production in Sub-tropical Australia, Central-Western India and Sub-Saharan Africa

Drought during grain filling is a common challenge for sorghum production in north-eastern Australia, central-western India, and sub-Saharan Africa. We show that the stay-green drought adaptation trait enhances sorghum grain yield under post-anthesis drought in these three regions. A positive relationship between stay-green and yield was generally found in breeding trials in north-eastern Australia that sampled 1668 unique hybrid combinations and 23 environments. Physiological studies in Australia also found that introgressing four individual stay-green (Stg1–4) quantitative trait loci (QTLs) into a senescent background reduced water demand before flowering and hence increased water supply during grain filling, resulting in higher grain yield relative to the senescent control. Studies in India found that various Stg QTLs affected both transpiration and transpiration efficiency, although these effects depended on the interaction between genetic background (S35 and R16) and individual QTLs. The yield variation unexplained by harvest index was related to transpiration efficiency in S35 (R2 = 0.29) and R16 (R2 = 0.72), and was related to total water extracted in S35 (R2 = 0.41) but not in R16. Finally, sixty-eight stay-green enriched lines were evaluated in six countries in sub-Saharan Africa during the 2013/14 season. Analysis of the data from Kenya indicates that stay-green and grain size were positively correlated at two sites: Kiboko (high yielding, r2=0.25) and Masongaleni (low yielding, r2=0.37). Together, these studies suggest that stay-green is a beneficial trait for sorghum production in the semi-arid tropics and is a consequence of traits altering the plant water budget.

Pleopod Cuticular Morphology as an Index of Moult Stage in the Ornate Rock Lobster, Panulirus ornatus (Fabricius 1789)

Seven discrete stages and substages of moulting in the ornate rock lobster, Panulirus ornatus, have been distinguished by microscopic examination of the cuticle and setae of the pleopods . The diagnostic features and the duration of each of the stages are described. Freezing did not visually alter the tissue features used to identify each moult stage. Pleopod morphology can reliably indicate whether a lobster has moulted within the previous 24 h or is within 72 h of the next ecdysis.

Phylogeography of the green turtle, Chelonia mydas, in the Southwest Indian Ocean

Patterns of mitochondrial DNA (mtDNA) variation were used to analyse the population genetic structure of southwestern Indian Ocean green turtle (Chelonia mydas) populations. Analysis of sequence variation over 396 bp of the mtDNA control region revealed seven haplotypes among 288 individuals from 10 nesting sites in the Southwest Indian Ocean. This is the first time that Atlantic Ocean haplotypes have been recorded among any Indo-Pacific nesting populations. Previous studies indicated that the Cape of Good Hope was a major biogeographical barrier between the Atlantic and Indian Oceans because evidence for gene flow in the last 1.5 million years has yet to emerge. This study, by sampling localities adjacent to this barrier, demonstrates that recent gene flow has occurred from the Atlantic Ocean into the Indian Ocean via the Cape of Good Hope. We also found compelling genetic evidence that green turtles nesting at the rookeries of the South Mozambique Channel (SMC) and those nesting in the North Mozambique Channel (NMC) belong to separate genetic stocks. Furthermore, the SMC could be subdivided in two different genetic stocks, one in Europa and the other one in Juan de Nova. We suggest that this particular genetic pattern along the Mozambique Channel is attributable to a recent colonization from the Atlantic Ocean and is maintained by oceanic conditions in the northern and southern Mozambique Channel that influence early stages in the green turtle life cycle.

Development of a stable isotope index to assess decadal-scale vegetation change and application to woodlands of the Burdekin catchment, Australia

Forty-four study sites were established in remnant woodland in the Burdekin River catchment in tropical north-east Queensland, Australia, to assess recent (decadal) vegetation change. The aim of this study was further to evaluate whether wide-scale vegetation 'thickening' (proliferation of woody plants in formerly more open woodlands) had occurred during the last century, coinciding with significant changes in land management. Soil samples from several depth intervals were size separated into different soil organic carbon (SOC) fractions, which differed from one another by chemical composition and turnover times. Tropical (C4) grasses dominate in the Burdekin catchment, and thus δ13C analyses of SOC fractions with different turnover times can be used to assess whether the relative proportion of trees (C3) and grasses (C4) had changed over time. However, a method was required to permit standardized assessment of the δ13C data for the individual sites within the 13 Mha catchment, which varied in soil and vegetation characteristics. Thus, an index was developed using data from three detailed study sites and global literature to standardize individual isotopic data from different soil depths and SOC fractions to reflect only the changed proportion of trees (C3) to grasses (C3) over decadal timescales. When applied to the 44 individual sites distributed throughout the Burdekin catchment, 64% of the sites were shown to have experienced decadal vegetation thickening, while 29% had remained stable and the remaining 7% had thinned. Thus, the development of this index enabled regional scale assessment and comparison of decadal vegetation patterns without having to rely on prior knowledge of vegetation changes or aerial photography.

The genetic structure of Australasian green turtles (Chelonia mydas): Exploring the geographical scale of genetic exchange

Ecological and genetic studies of marine turtles generally support the hypothesis of natal homing, but leave open the question of the geographical scale of genetic exchange and the capacity of turtles to shift breeding sites. Here we combine analyses of mitochondrial DNA (mtDNA) variation and recapture data to assess the geographical scale of individual breeding populations and the distribution of such populations through Australasia. We conducted multiscale assessments of mtDNA variation among 714 samples from 27 green turtle rookeries and of adult female dispersal among nesting sites in eastern Australia. Many of these rookeries are on shelves that were flooded by rising sea levels less than 10 000 years (c. 450 generations) ago. Analyses of sequence variation among the mtDNA control region revealed 25 haplotypes, and their frequency distributions indicated 17 genetically distinct breeding stocks (Management Units) consisting either of individual rookeries or groups of rookeries in general that are separated by more than 500 km. The population structure inferred from mtDNA was consistent with the scale of movements observed in long-term mark-recapture studies of east Australian rookeries. Phylogenetic analysis of the haplotypes revealed five clades with significant partitioning of sequence diversity (Φ = 68.4) between Pacific Ocean and Southeast Asian/Indian Ocean rookeries. Isolation by distance was indicated for rookeries separated by up to 2000 km but explained only 12% of the genetic structure. The emerging general picture is one of dynamic population structure influenced by the capacity of females to relocate among proximal breeding sites, although this may be conditional on large population sizes as existed historically across this region.

Developments in controlled green-water larval culture technologies for estuarine fishes in Queensland, Australia and elsewhere

Since 1989, researchers with the Department of Primary Industries and Fisheries (DPI&F) in Queensland, Australia, have successfully used controlled low-water exchange green-water cultures to rear the larvae of estuarine fishes and crustaceans through to metamorphosis. High survivals and excellent fry condition have been achieved for several commercially important endemic species produced for various projects. They include barramundi or sea bass, Lates calcarifer, Australian bass, Macquaria novemaculeata, dusky flathead, Platycephalus fuscus, sand whiting, Sillago ciliata, red sea bream or snapper, Pagrus auratus, banana prawn, Fenneropenaeus merguiensis, and others. The consistent success of our standardised and relatively simple approach at different localities has led to it being incorporated into general fingerling production practices at several establishments in Australia. Although post-metamorphosis rearing methods have differed for each species investigated, due to various biological and behavioural traits and project requirements, these larval rearing methods have been successful with few species-specific modifications. Initially modelled on the Taiwanese approach to rearing Penaeids in aerated low-water exchange cultures, the approach similarly appears to rely on a beneficial assemblage of micro-organisms. Conceptually, these micro-organisms may include a mixture of the air-borne primary invaders of pure phytoplankton cultures when exposed to outdoor conditions. Whilst this would vary with different sites, our experiences with these methods have consistently been favourable. Mass microalgal cultures with eco-physiological youth are used to regularly augment larval fish cultures so that rearing conditions simulate an exponential growth-phase microalgal bloom. Moderate to heavy aeration prevents settlement of particulate matter and encourages aerobic bacterial decomposition of wastes. The green-water larval rearing approach described herein has demonstrated high practical utility in research and commercial applications, and has greatly simplified marine finfish hatchery operations whilst generally lifting production capacities for metamorphosed fry in Australia. Its potential uses in areas of aquaculture other than larviculture are also discussed.

Spatial model of site index based on Y-ray spectrometry and a digital elevation model for two Pinus species in Tuan Toolara State Forest, Queensland, Australia

Site index prediction models are an important aid for forest management and planning activities. This paper introduces a multiple regression model for spatially mapping and comparing site indices for two Pinus species (Pinus elliottii Engelm. and Queensland hybrid, a P. elliottii x Pinus caribaea Morelet hybrid) based on independent variables derived from two major sources: g-ray spectrometry (potassium (K), thorium (Th), and uranium (U)) and a digital elevation model (elevation, slope, curvature, hillshade, flow accumulation, and distance to streams). In addition, interpolated rainfall was tested. Species were coded as a dichotomous dummy variable; interaction effects between species and the g-ray spectrometric and geomorphologic variables were considered. The model explained up to 60% of the variance of site index and the standard error of estimate was 1.9 m. Uranium, elevation, distance to streams, thorium, and flow accumulation significantly correlate to the spatial variation of the site index of both species, and hillshade, curvature, elevation and slope accounted for the extra variability of one species over the other. The predicted site indices varied between 20.0 and 27.3 m for P. elliottii, and between 23.1 and 33.1 m for Queensland hybrid; the advantage of Queensland hybrid over P. elliottii ranged from 1.8 to 6.8 m, with the mean at 4.0 m. This compartment-based prediction and comparison study provides not only an overview of forest productivity of the whole plantation area studied but also a management tool at compartment scale.

Developmental and physiological traits associated with high yield and stay-green phenotype in wheat

Water availability is a key limiting factor in wheat production in the northern grain belt of Australia. Varieties with improved adaptation to such conditions are actively sought. The CIMMYT wheat line SeriM82 has shown a significant yield advantage in multi-environment screening trials in this region. The objective of this study was to identify the physiological basis of the adaptive traits underpinning this advantage. Six detailed experiments were conducted to compare the growth, development, and yield of SeriM82 with that of the adapted cultivar, Hartog. The experiments were undertaken in field environments that represented the range of moisture availability conditions commonly encountered by winter crops grown on the deep Vertosol soils of this region. The yield of SeriM82 was 6-28% greater than that of Hartog, and SeriM82 exhibited a stay-green phenotype by maintaining green leaf area longer during the grain-filling period in all environments where yield was significantly greater than Hartog. However, where the availability of deep soil moisture was limited, SeriM82 failed to exhibit significantly greater yield or to express the stay-green phenotype. Thus, the stay-green phenotype was closely associated with the yield advantage of SeriM82. SeriM82 also exhibited higher mean grain mass than Hartog in all environments. It is suggested that small differences in water use before anthesis, or greater water extraction from depth after anthesis, could underlie the stay-green phenotype. The inability of SeriM82 to exhibit stay-green and higher yield where deep soil moisture was depleted indicates that extraction of deep soil moisture is important.

Sorghum stay-green QTL individually reduce post-flowering drought-induced leaf senescence

Sorghum is an important source of food, feed, and biofuel, especially in the semi-arid tropics because this cereal is well adapted to harsh, drought-prone environments. Post-flowering drought adaptation in sorghum is associated with the stay-green phenotype. Alleles that contribute to this complex trait have been mapped to four major QTL, Stg1-Stg4, using a population derived from BTx642 and RTx7000. Near-isogenic RTx7000 lines containing BTx642 DNA spanning one or more of the four stay-green QTL were constructed. The size and location of BTx642 DNA regions in each RTx7000 NIL were analysed using 62 DNA markers spanning the four stay-green QTL. RTx7000 NILs were identified that contained BTx642 DNA completely or partially spanning Stg1, Stg2, Stg3, or Stg4. NILs were also identified that contained sub-portions of each QTL and various combinations of the four major stay-green QTL. Physiological analysis of four RTx7000 NILs containing only Stg1, Stg2, Stg3, or Stg4 showed that BTx642 alleles in each of these loci could contribute to the stay-green phenotype. RTx7000 NILs containing BTx642 DNA corresponding to Stg2 retained more green leaf area at maturity under terminal drought conditions than RTx7000 or the other RTx7000 NILs. Under post-anthesis water deficit, a trend for delayed onset of leaf senescence compared with RTx7000 was also exhibited by the Stg2, Stg3, and Stg4 NILs, while significantly lower rates of leaf senescence in relation to RTx7000 were displayed by all of the Stg NILs to varying degrees, but particularly by the Stg2 NIL. Greener leaves at anthesis relative to RTx7000, indicated by higher SPAD values, were exhibited by the Stg1 and Stg4 NILs. The RTx7000 NILs created in this study provide the starting point for in-depth analysis of stay-green physiology, interaction among stay-green QTL and map-based cloning of the genes that underlie this trait.

Plant hosts of the phytoplasmas and rickettsia-like-organisms associated with strawberry lethal yellows and green petal diseases

Candidatus Phytoplasma australiense (Ca. P. australiense) is associated with the plant diseases strawberry lethal yellows (SLY), strawberry green petal (SGP), papaya dieback (PDB), Australian grapevine yellows (AGY) and Phormium yellow leaf (PYL; New Zealand). Strawberry lethal yellows disease is also associated with a rickettsia-like-organism (RLO) or infrequently with the tomato big bud (TBB) phytoplasma, the latter being associated with a wide range of plant diseases throughout Australia. In contrast, the RLO has been identified only in association with SLY disease, and Ca. P. australiense has been detected only in a limited number of plant host species. The aim of this study was to identify plant hosts that are possible reservoirs of Ca. P. australiense and the SLY RLO. Thirty-one plant species from south-east Queensland were observed with disease between 2001 and 2003 and, of these, 18 species tested positive using phytoplasma-specific primers. The RLO was detected in diseased Jacksonia scoparia and Modiola caroliniana samples collected at Stanthorpe. The TBB phytoplasma was detected in 16 different plant species and Ca. P. australiense Australian grapevine yellows strain was detected in six species. The TBB phytoplasma was detected in plants collected at Nambour, Stanthorpe, Warwick and Brisbane. Ca. P. australiense was detected in plants collected at Nambour, Stanthorpe, Gatton and Allora. All four phytoplasmas were detected in diseased Gomphocarpus physocarpus plants collected at Toowoomba, Allora, Nambour and Gatton. These results indicated that the vector(s) of Ca. P. australiense are distributed throughout south-east Queensland and the diversity of phytoplasmas detected in G. physocarpus suggests it is a feeding source for phytoplasma insect vectors or it has a broad susceptibility to a range of phytoplasmas.

Estimating crop area using seasonal time series of enhanced vegetation index from MODIS satellite imagery

Cereal grain is one of the main export commodities of Australian agriculture. Over the past decade, crop yield forecasts for wheat and sorghum have shown appreciable utility for industry planning at shire, state, and national scales. There is now an increasing drive from industry for more accurate and cost-effective crop production forecasts. In order to generate production estimates, accurate crop area estimates are needed by the end of the cropping season. Multivariate methods for analysing remotely sensed Enhanced Vegetation Index (EVI) from 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery within the cropping period (i.e. April-November) were investigated to estimate crop area for wheat, barley, chickpea, and total winter cropped area for a case study region in NE Australia. Each pixel classification method was trained on ground truth data collected from the study region. Three approaches to pixel classification were examined: (i) cluster analysis of trajectories of EVI values from consecutive multi-date imagery during the crop growth period; (ii) harmonic analysis of the time series (HANTS) of the EVI values; and (iii) principal component analysis (PCA) of the time series of EVI values. Images classified using these three approaches were compared with each other, and with a classification based on the single MODIS image taken at peak EVI. Imagery for the 2003 and 2004 seasons was used to assess the ability of the methods to determine wheat, barley, chickpea, and total cropped area estimates. The accuracy at pixel scale was determined by the percent correct classification metric by contrasting all pixel scale samples with independent pixel observations. At a shire level, aggregated total crop area estimates were compared with surveyed estimates. All multi-temporal methods showed significant overall capability to estimate total winter crop area. There was high accuracy at pixel scale (>98% correct classification) for identifying overall winter cropping. However, discrimination among crops was less accurate. Although the use of single-date EVI data produced high accuracy for estimates of wheat area at shire scale, the result contradicted the poor pixel-scale accuracy associated with this approach, due to fortuitous compensating errors. Further studies are needed to extrapolate the multi-temporal approaches to other geographical areas and to improve the lead time for deriving cropped-area estimates before harvest.

Defining and predicting the 'break of the season' for north-east Queensland grazing areas

For pasture growth in the semi-arid tropics of north-east Australia, where up to 80% of annual rainfall occurs between December and March, the timing and distribution of rainfall events is often more important than the total amount. In particular, the timing of the 'green break of the season' (GBOS) at the end of the dry season, when new pasture growth becomes available as forage and a live-weight gain is measured in cattle, affects several important management decisions that prevent overgrazing and pasture degradation. Currently, beef producers in the region use a GBOS rule based on rainfall (e. g. 40mm of rain over three days by 1 December) to define the event and make their management decisions. A survey of 16 beef producers in north-east Queensland shows three quarters of respondents use a rainfall amount that occurs in only half or less than half of all years at their location. In addition, only half the producers expect the GBOS to occur within two weeks of the median date calculated by the CSIRO plant growth days model GRIM. This result suggests that in the producer rules, either the rainfall quantity or the period of time over which the rain is expected, is unrealistic. Despite only 37% of beef producers indicating that they use a southern oscillation index (SOI) forecast in their decisions, cross validated LEPS (linear error in probability space) analyses showed both the average 3 month July-September SOI and the 2 month August-September SOI have significant forecast skill in predicting the probability of both the amount of wet season rainfall and the timing of the GBOS. The communication and implementation of a rigorous and realistic definition of the GBOS, and the likely impacts of anthropogenic climate change on the region are discussed in the context of the sustainable management of northern Australian rangelands.

Queensland Coastal Wetland Resources: Cape Tribulation to Bowling Green Bay

This report provides key resource data for the ongoing assessment of the requirement for additional Marine Protected Areas (e.g. FHAs under the Queensland Fisheries Act 1994) in regions of high fish habitat value in northern Queensland from Cape Tribulation to Bowling Green Bay (hereafter referred to as the Study Area). The study also provides baseline information on the coastal wetlands within this Study Area for consideration in the Ramsar site nomination process. The Study Area extends from Cape Tribulation (16o 6’S, 145o 24’E) to Bowling Green Bay (19o 30’S, 147o 24’E) in tropical north Queensland. The project aimed to: 1. document and map the coastal wetland communities of the Study Area; 2. document levels of existing disturbance to and protection of the wetlands; 3. examine existing recreational, indigenous and commercial fisheries resources in the region; 4. evaluate the conservation values of the areas investigated from the viewpoint of fisheries productivity and as habitat for important and/or threatened species for future FHA/MPA declaration. Dataset URL Link: Queensland Coastal Wetlands Resources Mapping data. [Dataset]

Measuring and predicting canopy nitrogen nutrition in wheat using a spectral index—The canopy chlorophyll content index (CCCI).

Varying the spatial distribution of applied nitrogen (N) fertilizer to match demand in crops has been shown to increase profits in Australia. Better matching the timing of N inputs to plant requirements has been shown to improve nitrogen use efficiency and crop yields and could reduce nitrous oxide emissions from broad acre grains. Farmers in the wheat production area of south eastern Australia are increasingly splitting N application with the second timing applied at stem elongation (Zadoks 30). Spectral indices have shown the ability to detect crop canopy N status but a robust method using a consistent calibration that functions across seasons has been lacking. One spectral index, the canopy chlorophyll content index (CCCI) designed to detect canopy N using three wavebands along the "red edge" of the spectrum was combined with the canopy nitrogen index (CNI), which was developed to normalize for crop biomass and correct for the N dilution effect of crop canopies. The CCCI-CNI index approach was applied to a 3-year study to develop a single calibration derived from a wheat crop sown in research plots near Horsham, Victoria, Australia. The index was able to predict canopy N (g m-2) from Zadoks 14-37 with an r2 of 0.97 and RMSE of 0.65 g N m-2 when dry weight biomass by area was also considered. We suggest that measures of N estimated from remote methods use N per unit area as the metric and that reference directly to canopy %N is not an appropriate method for estimating plant concentration without first accounting for the N dilution effect. This approach provides a link to crop development rather than creating a purely numerical relationship. The sole biophysical input, biomass, is challenging to quantify robustly via spectral methods. Combining remote sensing with crop modelling could provide a robust method for estimating biomass and therefore a method to estimate canopy N remotely. Future research will explore this and the use of active and passive sensor technologies for use in precision farming for targeted N management.