Temporal expression of G-protein-coupled receptor 54 (GPR54), gonadotropin-releasing hormones (GnRH), and dopamine receptor D2 (drd2) in pubertal female grey mullet, Mugil cephalus.

The G-protein-coupled receptor 54 (muGPR54) cDNA was cloned from the brain of the grey mullet, and its expression level, as well as those of the gonadotropin-releasing hormones (GnRH1, GnRH2, GnRH3) and dopamine receptor D2 (drd2), in the brain, pituitary and ovary of pubertal fish (early, intermediate, advanced) were determined by real-time quantitative RT-PCR (QPCR). The muGPR54 cDNA has an open reading frame of 1140 bp with a predicted 380 amino acid peptide, containing seven putative transmembrane domains and putative N-glycosylation and protein kinase C phosphorylation sites. QPCR results showed that the early stage of puberty in grey mullet is characterized by significantly high levels of expression of GPR54, GnRH and drd2 in the brain relative to the intermediate and advanced stages, except for GnRH1 that increased at the advanced stage of puberty. In the pituitary, drd2 expression declined significantly at the advanced stage relative to levels at the intermediate stage. Ovarian expression of GPR54 significantly increased from the intermediate stage of puberty relative to the early stage while that of GnRH1 acutely increased at the advanced stage of puberty. The ovarian expression of drd2 decreased as puberty progressed, but the changes were not significant. The results suggest the possible role of GPR54 and GnRH in positively regulating pubertal development in grey mullet and the dopaminergic inhibition of reproductive function mediated by drd2.

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.

Wet season resting - economic insights from scenario modelling

Pasture degradation, particularly that attributable to overgrazing, is a significant problem across the northern Australian rangelands. Although grazing studies have identified the scope for wet season resting strategies to be used to rehabilitate degraded pastures, the economic outcome of these strategies has not been extensively demonstrated. An exploratory study of the prospective economic value of wet season resting is presented using an economic simulation model of a 28000 ha beef enterprise located in the Charters Towers region of north-eastern Australia to explore seven hypothetical scenarios centred on the projected performance of a wet season resting strategy. A series of 20-year simulations for a range of pasture recovery profiles, stocking capacity, animal productivity responses, beef prices and agistment options are compared with a baseline scenario of taking no action. Estimates of the net present value of the 20-year difference in total enterprise gross margins between the various resting options and the 'do nothing' option identify that wet season resting can offer a positive economic return for the range of scenarios examined, although this is contingent on the assumptions that are made concerning the trajectories of change in carrying capacity and animal productivity. Some implications for management and policy making to support the practical implementation of wet season resting strategies are discussed.

Drought stress characterization of post-rainy season (rabi) sorghum in India

During the post-rainy (rabi) season in India around 3 million tonnes of sorghum grain is produced from 5.7 million ha of cropping. This underpins the livelihood of about 5 million households. Severe drought is common as the crop grown in these areas relies largely on soil moisture stored during the preceding rainy season. Improvement of rabi sorghum cultivars through breeding has been slow but could be accelerated if drought scenarios in the production regions were better understood. The sorghum crop model within the APSIM (Agricultural Production Systems sIMulator) platform was used to simulate crop growth and yield and the pattern of crop water status through each season using available historical weather data. The current model reproduced credibly the observed yield variation across the production region (R2=0.73). The simulated trajectories of drought stress through each crop season were clustered into five different drought stress patterns. A majority of trajectories indicated terminal drought (43%) with various timings of onset during the crop cycle. The most severe droughts (25% of seasons) were when stress began before flowering and resulted in failure of grain production in most cases, although biomass production was not affected so severely. The frequencies of drought stress types were analyzed for selected locations throughout the rabi tract and showed different zones had different predominating stress patterns. This knowledge can help better focus the search for adaptive traits and management practices to specific stress situations and thus accelerate improvement of rabi sorghum via targeted specific adaptation. The case study presented here is applicable to other sorghum growing environments. © 2012 Elsevier B.V.

Flight directionality of Tribolium castaneum soon after take-off under glasshouse and field conditions

Flight directionality of the rust-red flour beetle, Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae), was investigated under glasshouse and field conditions using sticky traps placed around dense experimental infestations of T. castaneum derived from field-collected samples. Although beetles of this species are known to fly quite readily, information on flight of beetles away from grain resources is limited. Under still glasshouse conditions, T. castaneum does not demonstrate strong horizontal or vertical trajectories in their initial flight behaviour. Flight was significantly directional in half of the replicates, but trapped beetles were only weakly concentrated around the mean direction of flight. In the field, by contrast, emigration of T. castaneum was strongly directional soon after flight initiation. The mean vector lengths were generally >0.5 which indicates that trapped beetles were strongly concentrated around the calculated mean flight direction. A circular-circular regression of mean flight vs. mean downwind direction suggested that flight direction was generally correlated with downwind direction. The mean height at which T. castaneum individuals initially flew was 115.4 ± 7.0 cm, with 58.3% of beetles caught no more than 1 m above the ground. The height at which beetles were trapped did not correlate with wind speed at the time of sampling, but the data do indicate that wind speed significantly affected T. castaneum flight initiation, because no beetles (or very few; no more than three) were trapped in the field when the mean wind speed was above 3 m s−1. This study thus demonstrates that wind speed and direction are both important aspects of flight behaviour of T. castaneum, and therefore of the spatio-temporal dynamics of this species.