Negligible evidence for regional genetic population structure for two shark species Rhizoprionodon acutus (Rüppell, 1837) and Sphyrna lewini (Griffith & Smith, 1834) with contrasting biology

Biodiversity of sharks in the tropical Indo-Pacific is high, but species-specific information to assist sustainable resource exploitation is scarce. The null hypothesis of population genetic homogeneity was tested for scalloped hammerhead shark (Sphyrna lewini, n = 237) and the milk shark (Rhizoprionodon acutus, n = 207) from northern and eastern Australia, using nuclear (S. lewini, eight microsatellite loci; R. acutus, six loci) and mitochondrial gene markers (873 base pairs of NADH dehydrogenase subunit 4). We were unable to reject genetic homogeneity for S. lewini, which was as expected based on previous studies of this species. Less expected were similar results for R. acutus, which is more benthic and less vagile than S. lewini. These features are probably driving the genetic break found between Australian and central Indonesian R. acutus (F-statistics; mtDNA, 0.751–0.903, respectively; microsatellite loci, 0.038–0.047 respectively). Our results support the spatially homogeneous monitoring and management plan for shark species in Queensland, Australia.

Determination of management units for grey mackerel fisheries in northern Australia.

The requirement for Queensland, Northern Territory and Western Australian jurisdictions to ensure sustainable harvest of fish resources and their optimal use relies on robust information on the resource status. For grey mackerel (Scomberomorus semifasciatus) fisheries, each of these jurisdictions has their own management regime in their corresponding waters. The lack of information on stock structure of grey mackerel, however, means that the appropriate spatial scale of management is not known. As well, fishers require assurance of future sustainability to encourage investment and long-term involvement in a fishery that supplies lucrative overseas markets. These management and fisher-unfriendly circumstances must be viewed in the context of recent 3-fold increases in catches of grey mackerel along the Queensland east coast, combined with significant and increasing catches in other parts of the species' northern Australian range. Establishing the stock structure of grey mackerel would also immensely improve the relevance of resource assessments for fishery management of grey mackerel across northern Australia. This highlighted the urgent need for stock structure information for this species. The impetus for this project came from the strategic recommendations of the FRDC review by Ward and Rogers (2003), "Northern mackerel (Scombridae: Scomberomorus): current and future research needs" (Project No. 2002/096), which promoted the urgency for information on the stock structure of grey mackerel. In following these recommendations this project adopted a multi-technique and phased sampling approach as carried out by Buckworth et al (2007), who examined the stock structure of Spanish mackerel, Scomberomorus commerson, across northern Australia. The project objectives were to determine the stock structure of grey mackerel across their northern Australian range, and use this information to define management units and their appropriate spatial scales. We used multiple techniques concurrently to determine the stock structure of grey mackerel. These techniques were: genetic analyses (mitochondrial DNA and microsatellite DNA), otolith (ear bones) isotope ratios, parasite abundances, and growth parameters. The advantage of using this type of multi-technique approach was that each of the different methods is informative about the fish’s life history at different spatial and temporal scales. Genetics can inform about the evolutionary patterns as well as rates of mixing of fish from adjacent areas, while parasites and otolith microchemistry are directly influenced by the environment and so will inform about the patterns of movement during the fishes lifetime. Growth patterns are influenced by both genetic and environmental factors. Due to these differences the use of these techniques concurrently increases the likelihood of detecting different stocks where they exist. We adopted a phased sampling approach whereby sampling was carried out at broad spatial scales in the first year: east coast, eastern Gulf of Carpentaria (GoC), western GoC, and the NW Northern Territory (NW NT). By comparing the fish samples from each of these locations, and using each of the techniques, we tested the null hypothesis that grey mackerel were comprised of a single homogeneous population across northern Australia. Having rejected the null hypothesis we re-sampled the 1st year locations to test for temporal stability in stock structure, and to assess stock structure at finer spatial scales. This included increased spatial coverage on the east coast, the GoC, and WA. From genetic approaches we determined that there at least four genetic stocks of grey mackerel across northern Australia: WA, NW NT (Timor/Arafura), the GoC and the east Grey mackerel management units in northern Australia ix coast. All markers revealed concordant patterns showing WA and NW NT to be clearly divergent stocks. The mtDNA D-loop fragment appeared to have more power to resolve stock boundaries because it was able to show that the GoC and east coast QLD stocks were genetically differentiated. Patterns of stock structure on a finer scale, or where stock boundaries are located, were less clear. From otolith stable isotope analyses four major groups of S. semifasciatus were identified: WA, NT/GoC, northern east coast and central east coast. Differences in the isotopic composition of whole otoliths indicate that these groups must have spent their life history in different locations. The magnitude of the difference between the groups suggests a prolonged separation period at least equal to the fish’s life span. The parasite abundance analyses, although did not include samples from WA, suggest the existence of at least four stocks of grey mackerel in northern Australia: NW NT, the GoC, northern east coast and central east coast. Grey mackerel parasite fauna on the east coast suggests a separation somewhere between Townsville and Mackay. The NW NT region also appears to comprise a separate stock while within the GoC there exists a high degree of variability in parasite faunas among the regions sampled. This may be due to 1. natural variation within the GoC and there is one grey mackerel stock, or 2. the existence of multiple localised adult sub-stocks (metapopulations) within the GoC. Growth parameter comparisons were only possible from four major locations and identified the NW NT, the GoC, and the east coast as having different population growth characteristics. Through the use of multiple techniques, and by integrating the results from each, we were able to determine that there exist at least five stocks of grey mackerel across northern Australia, with some likelihood of additional stock structuring within the GoC. The major management units determined from this study therefore were Western Australia, NW Northern Territory (Timor/Arafura), the Gulf of Carpentaria, northern east Queensland coast and central east Queensland coast. The management implications of these results indicate the possible need for management of grey mackerel fisheries in Australia to be carried out on regional scales finer than are currently in place. In some regions the spatial scales of management might continue as is currently (e.g. WA), while in other regions, such as the GoC and the east coast, managers should at least monitor fisheries on a more local scale dictated by fishing effort and assess accordingly. Stock assessments should also consider the stock divisions identified, particularly on the east coast and for the GoC, and use life history parameters particular to each stock. We also emphasise that where we have not identified different stocks does not preclude the possibility of the occurrence of further stock division. Further, this study did not, nor did it set out to, assess the status of each of the stocks identified. This we identify as a high priority action for research and development of grey mackerel fisheries, as well as a management strategy evaluation that incorporates the conclusions of this work. Until such time that these priorities are addressed, management of grey mackerel fisheries should be cognisant of these uncertainties, particularly for the GoC and the Queensland east coast.

Genetic and Malt Quality Diversity of East Asian Two-Rowed Barley Accessions in Relationship to North American Malting Barley.

Because of epidemics of Fusarium head blight (FHB; caused by Fusarium graminearum Schwabe [teleomorph Gibberella zeae (Schwein.) Petch]) in the northern Great Plains of the United States and Canada in the past two decades, malting barley breeders have been forced to use nonadapted barley (Hordeum vulgare L.) accessions as sources of FHB resistance. Many of the resistant accessions are from East Asia, and limited information is available on their genetic diversity and malt quality. The objectives of this study were to determine the genetic diversity among 30 East Asian accessions and two North American cultivars. Genetic diversity was based on 49 simple-sequence repeat markers. All accessions were tested for barley grain brightness; protein content; 1,000-kernel weight; malting loss; fine-grind malt extract; content of plump kernels, free amino nitrogen, soluble protein, and wort beta-glucan; the Kolbach index (i.e., the ratio of malt soluble protein to malt total protein); a-amylase activity; diastatic power; won color; and wort viscosity. A few accessions had equal quality compared with Harrington and Conlon barley for individual traits but not for all. Qing 2, Mokkei 93-78, and Nitakia 48 could be excellent sources for increased malt extract; Nitakia 48 is a possible source for low wort viscosity; and Mokkei 93-78 and Nitakia 48 are putative sources of low beta-glucan content. The cluster analyses also implied that the malt quality of an accession cannot be predicted based on the country where it was developed.

Consequences of Corymbia (Myrtaceae) hybridisation on leaf-oil profiles

The present study examines patterns of heritability of plant secondary metabolites following hybridisation among three genetically homogeneous taxa of spotted gum (Corymbia henryi (S.T.Blake) K.D.Hill & L.A.S.Johnson, C. citriodora subsp. variegata (F.Muell.) K.D.Hill & L.A.S.Johnson and C. citriodora (Hook.) K.D.Hill & L.A.S.Johnson subsp. citriodora (section Maculatae), and their congener C. torelliana (F.Muell.) K.D.Hill & L.A.S.Johnson (section Torellianae)). Hexane extracts of leaves of all four parent taxa were statistically distinguishable (ANOSIM: global R = 0.976, P = 0.008). Hybridisation patterns varied among the taxa studied, with the hybrid formed with C. citriodora subsp. variegata showing an intermediate extractive profile between its parents, whereas the profiles of the other two hybrids were dominated by that of C. torelliana. These different patterns in plant secondary-metabolite inheritance may have implications for a range of plant-insect interactions.

Sweetcorn colour change and consumer perception associated with increasing zeaxanthin for the amelioration of age-related macular degeneration

Age-related macular degeneration (AMD) is the leading cause of blindness in the developed world. Increasing dietary intake of lutein- and zeaxanthin-rich foods is a potential means of preventing, or at least slowing the progression of AMD. Zeaxanthin levels in tropical super-sweetcorn was increased from 1.1 to 11.9 µg/g FW through conventional breeding and selection, associated with both an increase in the proportion of zeaxanthin relative to other carotenoids, and a general increase in carotenoid synthesis. Increasing zeaxanthin was associated with a colour shift from traditional ‘canary-yellow’ kernels to a golden-orange colour. Kernel colour was most closely correlated (r2=69%) with an increase in beta-arm carotenoid concentration. Consumer analysis revealed that prior to any knowledge of zeaxanthin-related health benefit, consumers would readily purchase both yellow and gold cobs. Once the health benefit was explained, this extended to deep-gold cobs. Colour difference between regular yellow sweetcorn and high-zeaxanthin sweetcorn could potentially be used as a visual means of differentiating high-zeaxanthin sweetcorn in the marketplace.

Analysis of Crude Protein and Allergen Abundance in Peanuts (Arachis hypogaea cv. Walter) from Three Growing Regions in Australia

The effects of plant growth conditions on concentrations of proteins, including allergens, in peanut (Arachis hypogaea L.) kernels are largely unknown. Peanuts (cv. Walter) were grown at five sites (Taabinga, Redvale, Childers, Bundaberg, and Kairi) covering three commercial growing regions in Queensland, Australia. Differences in temperature, rainfall, and solar radiation during the growing season were evaluated. Kernel yield varied from 2.3 t/ha (Kairi) to 3.9 t/ha (Childers), probably due to differences in solar radiation. Crude protein appeared to vary only between Kairi and Childers, whereas Ara h 1 and 2 concentrations were similar in all locations. 2D-DIGE revealed significant differences in spot volumes for only two minor protein spots from peanuts grown in the five locations. Western blotting using peanut-allergic serum revealed no qualitative differences in recognition of antigens. It was concluded that peanuts grown in different growing regions in Queensland, Australia, had similar protein compositions and therefore were unlikely to show differences in allergenicity.

Zeaxanthin biofortification of sweet-corn and factors affecting zeaxanthin accumulation and colour change

Zeaxanthin, along with its isomer lutein, are the major carotenoids contributing to the characteristic colour of yellow sweet-corn. From a human health perspective, these two carotenoids are also specifically accumulated in the human macula, and are thought to protect the photoreceptor cells of the eye from blue light oxidative damage and to improve visual acuity. As humans cannot synthesise these compounds, they must be accumulated from dietary components containing zeaxanthin and lutein. In comparison to most dietary sources, yellow sweet-corn (Zea mays var. rugosa) is a particularly good source of zeaxanthin, although the concentration of zeaxanthin is still fairly low in comparison to what is considered a supplementary dose to improve macular pigment concentration (2 mg/person/day). In our present project, we have increased zeaxanthin concentration in sweet-corn kernels from 0.2 to 0.3 mg/100 g FW to greater than 2.0 mg/100 g FW at sweet-corn eating-stage, substantially reducing the amount of corn required to provide the same dosage of zeaxanthin. This was achieved by altering the carotenoid synthesis pathway to more than double total carotenoid synthesis and to redirect carotenoid synthesis towards the beta-arm of the pathway where zeaxanthin is synthesised. This resulted in a proportional increase of zeaxanthin from 22% to 70% of the total carotenoid present. As kernels increase in physiological maturity, carotenoid concentration also significantly increases, mainly due to increased synthesis but also due to a decline in moisture content of the kernels. When fully mature, dried kernels can reach zeaxanthin and carotene concentrations of 8.7 mg/100 g and 2.6 mg/100 g, respectively. Although kernels continue to increase in zeaxanthin when harvested past their normal harvest maturity stage, the texture of these 'over-mature' kernels is tough, making them less appealing for fresh consumption. Increase in zeaxanthin concentration and other orange carotenoids such as p-carotene also results in a decline in kernel hue angle of fresh sweet-corn from approximately 90 (yellow) to as low as 75 (orange-yellow). This enables high-zeaxanthin sweet-corn to be visually-distinguishable from standard yellow sweet-corn, which is predominantly pigmented by lutein.

Inactivation of Aspergillus flavus spores by curcumin-mediated photosensitization

Minimizing fungal infection is essential to the control of mycotoxin contamination of foods and feeds but many potential control methods are not without their own safety concerns for the consumers. Photodynamic inactivation is a novel light-based approach which offers a promising alternative to conventional methods for the control of mycotoxigenic fungi. This study describes the use of curcumin to inactivate spores of Aspergillus flavus, one of the major aflatoxin producing fungi in foods and feeds. Curcumin is a natural polyphenolic compound from the spice turmeric (Curcuma longa). In this study the plant has shown to be an effective photosensitiser when combined with visible light (420 nm). The experiment was conducted in in vitro and in vivo where A. flavus spores were treated with different photosensitiser concentration and light dose both in buffer solution and on maize kernels. Comparison of fungal load from treated and untreated samples was determined, and reductions of fungal spore counts of up to 3 log CFU ml−1 in suspension and 2 log CFU g−1 in maize kernels were obtained using optimal dye concentrations and light dose combinations. The results in this study indicate that curcumin-mediated photosensitization is a potentially effective method to decontaminate A. flavus spores in foods and feeds.

Automating Crop Damage Assessments with Unmanned Aerial Systems and Machine Learning

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising methodology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.