Transcriptional regulation of a pineapple polyphenol oxidase gene and its relationship to blackheart.

Two genes encoding polyphenol oxidase (PPO) were isolated from pineapple (Ananas comosus[L.] Merr. cv. Smooth Cayenne). Sequence analyses showed that both contained a single intron and encoded typical chloroplast-localized PPO proteins, the sequences of which corresponded to two pineapple PPO cDNAs, PINPPO1 and PINPPO2, recently described by Stewart et al. (2001). Southern blot analyses suggested that pineapple contained only two PPO genes. Analysis of expression of PINPPO1 promoter GUS fusion constructs showed this promoter had a low basal activity and was cold- and wound-inducible, consistent with known mRNA expression profiles. Striking homologies to gibberellin response complexes (GARC) were observed in sequences of both the PINPPO1 and PINPPO2 promoters. Transient assays in mature pineapple fruit and stable expression in transgenic tobacco showed that PINPPO1 promoter-GUS fusions were indeed gibberellin (GA) responsive. A role for the element within the putative GARCs in mediating GA-responsiveness of the PINPPO1 promoter was confirmed by mutational analysis. PINPPO2 was also shown to be GA-responsive by RT-PCR analysis. Mutant PINPPO1 promoter-GUS fusion constructs, which were no longer GA-inducible, showed a delayed response to cold induction in pineapple fruit in transient assays, suggesting a role for GA in blackheart development. This was supported by observations that exogenous GA3 treatment induced blackheart in the absence of chilling. Sequences showing homology to GARCs are also present in some PPO promoters in tomato, suggesting that GA regulates PPO expression in diverse species.

Regulation of Gonadotropin-Releasing Hormone (GnRH)-Receptor Gene Expression in Tilapia: Effect of GnRH and Dopamine

The present work was designed to study certain aspects of the endocrine regulation of gonadotropin-releasing hormone receptor (GnRH-R) in the pituitary of the teleost fish tilapia. A GnRH-R was cloned from the pituitary of hybrid tilapia (taGnRH-R) and was identified as a typical seven-transmembrane receptor. Northern blot analysis revealed a single GnRH-R transcript in the pituitary of approximately 2.3 kilobases. The taGnRH-R mRNA levels were significantly higher in females than in males. Injection of the salmon GnRH analog (sGnRHa; 5–50 μg/kg) increased the steady-state levels of taGnRH-R mRNA, with the highest response recorded at 25 μg/kg and at 36 h. At the higher dose of sGnRHa (50 μg/kg), taGnRH-R transcript appeared to be down-regulated. Exposure of tilapia pituitary cells in culture to graded doses (0.1–100 nM) of seabream (sbGnRH = GnRH I), chicken II (cGnRH II), or salmon GnRH (sGnRH = GnRH III) resulted in a significant increase in taGnRH-R mRNA levels. The highest levels of both LH release and taGnRH-R mRNA levels were recorded after exposure to cGnRH II and the lowest after exposure to sbGnRH. The dopamine-agonist quinpirole suppressed LH release and mRNA levels of taGnRH-R, indicating an inhibitory effect on GnRH-R synthesis. Collectively, these data provide evidence that GnRH in tilapia can up- regulate, whereas dopamine down-regulates, taGnRH-R mRNA levels.

Optimal management of agricultural systems

To remain competitive, many agricultural systems are now being run along business lines. Systems methodologies are being incorporated, and here evolutionary computation is a valuable tool for identifying more profitable or sustainable solutions. However, agricultural models typically pose some of the more challenging problems for optimisation. This chapter outlines these problems, and then presents a series of three case studies demonstrating how they can be overcome in practice. Firstly, increasingly complex models of Australian livestock enterprises show that evolutionary computation is the only viable optimisation method for these large and difficult problems. On-going research is taking a notably efficient and robust variant, differential evolution, out into real-world systems. Next, models of cropping systems in Australia demonstrate the challenge of dealing with competing objectives, namely maximising farm profit whilst minimising resource degradation. Pareto methods are used to illustrate this trade-off, and these results have proved to be most useful for farm managers in this industry. Finally, land-use planning in the Netherlands demonstrates the size and spatial complexity of real-world problems. Here, GIS-based optimisation techniques are integrated with Pareto methods, producing better solutions which were acceptable to the competing organizations. These three studies all show that evolutionary computation remains the only feasible method for the optimisation of large, complex agricultural problems. An extra benefit is that the resultant population of candidate solutions illustrates trade-offs, and this leads to more informed discussions and better education of the industry decision-makers.

Environmental regulation in the pork producing industry - bring on the research!

Over the last 20 years, environmental management in Queensland has moved from the policy backwaters of government to the front line of operations by way of regulatory enforcement, industry programs and incentives. When the new Queensland Environmental Protection Act 1994 (EPA) came into effect, the business of environmental management has become a central feature of urban and rural development activity. The concept of environmentally sustainable development (ESD), has given life to the precautionary principle as a way for planners and regulators to place relevant controls on development. The planning, development and operation of pig farming systems has been effected by the new regulatory framework. Ever more definitive standards and approval permits have emerged which endeavour to achieve ESD. With these modern planning instruments in place, rural industry sectors have become, quite legitimately, concerned about future opportunities for research and innovation. This paper asserts that the capacity to engage in research and to achieve innovation in the pork producing industry is not hindered by Queensland environmental regulation frameworks. However, in order for research and innovation to prosper within these frameworks, some protocols need to be followed by the industry. What is at stake is community confidence.

Optimal eradication: when to stop looking for an invasive plant

The notion of being sure that you have completely eradicated an invasive species is fanciful because of imperfect detection and persistent seed banks. Eradication is commonly declared either on an ad hoc basis, on notions of seed bank longevity, or on setting arbitrary thresholds of 1% or 5% confidence that the species is not present. Rather than declaring eradication at some arbitrary level of confidence, we take an economic approach in which we stop looking when the expected costs outweigh the expected benefits. We develop theory that determines the number of years of absent surveys required to minimize the net expected cost. Given detection of a species is imperfect, the optimal stopping time is a trade-off between the cost of continued surveying and the cost of escape and damage if eradication is declared too soon. A simple rule of thumb compares well to the exact optimal solution using stochastic dynamic programming. Application of the approach to the eradication programme of Helenium amarum reveals that the actual stopping time was a precautionary one given the ranges for each parameter.

Wild dogma: An examination of recent "evidence" for dingo regulation of invasive mesopredator release in Australia

There is growing interest in the role that apex predators play in shaping terrestrial ecosystems and maintaining trophic cascades. In line with the mesopredator release hypothesis, Australian dingoes (Canis lupus dingo and hybrids) are assumed by many to regulate the abundance of invasive mesopredators, such as red foxes Vulpes vulpes and feral cats Felis catus, thereby providing indirect benefits to various threatened vertebrates. Several recent papers have claimed to provide evidence for the biodiversity benefits of dingoes in this way. Nevertheless, in this paper we highlight several critical weaknesses in the methodological approaches used in many of these reports, including lack of consideration for seasonal and habitat differences in activity, the complication of simple track-based indices by incorporating difficult-to-meet assumptions, and a reduction in sensitivity for assessing populations by using binary measures rather than potentially continuous measures. Of the 20 studies reviewed, 15 of them (75%) contained serious methodological flaws, which may partly explain the inconclusive nature of the literature nvestigating interactions between invasive Australian predators. We therefore assert that most of the “growing body of evidence” for mesopredator release is merely an inconclusive growing body of literature only. We encourage those interested in studying the ecological roles of dingoes relative to invasive mesopredators and native prey species to account for the factors we identify, and caution the value of studies that have not done so.

A physiological framework to explain genetic and environmental regulation of tillering in sorghum

Tillering determines the plant size of sorghum (Sorghum bicolor) and an understanding of its regulation is important to match genotypes to prevalent growing conditions in target production environments. The aim of this study was to determine the physiological and environmental regulation of variability in tillering among sorghum genotypes, and to develop a framework for this regulation. * Diverse sorghum genotypes were grown in three experiments with contrasting temperature, radiation and plant density to create variation in tillering. Data on phenology, tillering, and leaf and plant size were collected. A carbohydrate supply/demand (S/D) index that incorporated environmental and genotypic parameters was developed to represent the effects of assimilate availability on tillering. Genotypic differences in tillering not explained by this index were defined as propensity to tiller (PTT) and probably represented hormonal effects. * Genotypic variation in tillering was associated with differences in leaf width, stem diameter and PTT. The S/D index captured most of the environmental effects on tillering and PTT most of the genotypic effects. * A framework that captures genetic and environmental regulation of tillering through assimilate availability and PTT was developed, and provides a basis for the development of a model that connects genetic control of tillering to its phenotypic consequences.

Deriving optimal fishing effort for managing Australia's Moreton Bay multispecies trawl fishery with aggregated effort data

Deriving an estimate of optimal fishing effort or even an approximate estimate is very valuable for managing fisheries with multiple target species. The most challenging task associated with this is allocating effort to individual species when only the total effort is recorded. Spatial information on the distribution of each species within a fishery can be used to justify the allocations, but often such information is not available. To determine the long-term overall effort required to achieve maximum sustainable yield (MSY) and maximum economic yield (MEY), we consider three methods for allocating effort: (i) optimal allocation, which optimally allocates effort among target species; (ii) fixed proportions, which chooses proportions based on past catch data; and (iii) economic allocation, which splits effort based on the expected catch value of each species. Determining the overall fishing effort required to achieve these management objectives is a maximizing problem subject to constraints due to economic and social considerations. We illustrated the approaches using a case study of the Moreton Bay Prawn Trawl Fishery in Queensland (Australia). The results were consistent across the three methods. Importantly, our analysis demonstrated the optimal total effort was very sensitive to daily fishing costs—the effort ranged from 9500–11 500 to 6000–7000, 4000 and 2500 boat-days, using daily cost estimates of $0, $500, $750, and $950, respectively. The zero daily cost corresponds to the MSY, while a daily cost of $750 most closely represents the actual present fishing cost. Given the recent debate on which costs should be factored into the analyses for deriving MEY, our findings highlight the importance of including an appropriate cost function for practical management advice. The approaches developed here could be applied to other multispecies fisheries where only aggregated fishing effort data are recorded, as the literature on this type of modelling is sparse.