Preparation, structural analysis and prebiotic potential of arabinoxylo-oligosaccharides

Arabinoxylo-oligosaccharides (AXOS) can be prepared enzymatically from arabinoxylans (AX) and AXOS are known to possess prebiotic potential. Here the structural features of 10 cereal AX were examined. AX were hydrolysed by Shearzyme® to prepare AXOS, and their structures were fully analysed. The prebiotic potential of the purified AXOS was studied in the fermentation experiments with bifidobacteria and faecal microbiota. In AX extracted from flours and bran, high amounts of a-L-Araf units are attached to the b-D-Xylp main chain, whereas moderate or low degree of substitution was found from husks, cob and straw. Nuclear magnetic resonance (NMR) spectroscopy showed that flour and bran AX contain high amounts of a-L-Araf units bound to the O-3 of b-D-Xylp residues and doubly substituted b-D-Xylp units with a-L-Araf substituents at O-2 and O-3. Barley husk and corn cob AX contain high amounts of b-D-Xylp(1→2)-a-L-Araf(1→3) side chains, which can also be found in AX from oat spelts and rice husks, and in lesser amounts in wheat straw AX. Rye and wheat flour AX and oat spelt AX were hydrolysed by Shearzyme® (with Aspergillus aculeatus GH10 endo-1,4-b-D-xylanase as the main enzyme) for the production of AXOS on a milligram scale. The AXOS were purified and their structures fully analysed, using mass spectrometry (MS) and 1D and 2D NMR spectroscopy. Monosubstituted xylobiose and xylotriose with a-L-Araf attached to the O-3 or O-2 of the nonreducing end b-D-Xylp unit and disubstituted AXOS with two a-L-Araf units at the nonreducing end b-D-Xylp unit of xylobiose or xylotriose were produced. Xylobiose with b-D-Xylp(1→2)-a-L-Araf(1→3) side chain was also purified. These AXOS were used as standards in further identification and quantification of corresponding AXOS from the hydrolysates in high-performance anion-exchange chromatography with pulsed amperometric detection (HPAEC-PAD) analysis. The prebiotic potential of AXOS was tested in in vitro fermentation experiments. Bifidobacterium adolescentis ATCC 15703 and B. longum ATCC 15707 utilized AXOS from the AX hydrolysates. Both species released L-arabinose from AXOS, but B. adolescentis consumed the XOS formed, whereas B. longum fermented the L-arabinose released. The third species tested, B. breve ATCC 15700, grew poorly on these substrates. When cultivated on pure AXOS, the bifidobacterial mixture utilized pure singly substituted AXOS almost completely, but no growth was detected with pure doubly substituted AXOS as substrates. However, doubly substituted AXOS were utilized from the mixture of xylose, XOS and AXOS. Faecal microbiota utilized both pure singly and doubly substituted AXOS. Thus, a mixture of singly and doubly substituted AXOS could function as a suitable, slowly fermenting prebiotic substance. This thesis contributes to the structural information on cereal AX and preparation of mono and doubly substituted AXOS from AX. Understanding the utilization strategies is fundamental in evaluating the prebiotic potential of AXOS. Further research is still required before AXOS can be used in applications for human consumption.

The rph2 Gene Is Responsible for High Level Resistance to Phosphine in Independent Field Strains of Rhyzopertha dominica

The lesser grain borer Rhyzopertha dominica (F.) is one of the most destructive insect pests of stored grain. This pest has been controlled successfully by fumigation with phosphine for the last several decades, though strong resistance to phosphine in many countries has raised concern about the long term usefulness of this control method. Previous genetic analysis of strongly resistant (SR) R. dominica from three widely geographically dispersed regions of Australia, Queensland (SRQLD), New South Wales (SRNSW) and South Australia (SRSA), revealed a resistance allele in the rph1 gene in all three strains. The present study confirms that the rph1 gene contributes to resistance in a fourth strongly resistant strain, SR2(QLD), also from Queensland. The previously described rph2 gene, which interacts synergistically with rph1 gene, confers strong resistance on SRQLD and SRNSW. We now provide strong circumstantial evidence that weak alleles of rph2, together with rph1, contribute to the strong resistance phenotypes of SRSA and SR2(QLD). To test the notion that rph1 and rph2 are solely responsible for the strong resistance phenotype of all resistant R. dominica, we created a strain derived by hybridising the four strongly resistant lines. Following repeated selection for survival at extreme rates of phosphine exposure, we found only slightly enhanced resistance. This suggests that a single sequence of genetic changes was responsible for the development of resistance in these insects.

A Bayesian hurdle model for analysis of an insect resistance monitoring database

Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models. © 2014 Springer Science+Business Media New York.

Mikveh Israel Centenary Coin

Obverse: Silver 10 Lirot coin, a stylized spikelet of corn. Reverse: Schematic plough.

Optimizing genotype by environment by management to maximize opportunities for maize productivity in North Eastern Australia.

The major objective of this experiment was to identify optimum plant population densities for different maize maturity groups depending on the environments’ potential and identify situations that reduce risk of crop failures while maximizing opportunities for better yield when weather conditions are good.

Status, challenges and tools for identification and diagnosis of Peronosclerospora and Sclerophthora of regulatory concern for graminicolous crops

Graminicolous Downy Mildew (GDM) diseases caused by the genera Peronosclerospora (13 spp.) and Sclerophthora (6 spp. and 1 variety) are poorly studied but destructive diseases of major crops such as corn, sorghum, sugarcane and other graminoids. Eight of the 13 described Peronosclerospora spp. are able to infect corn. In particular, P. philippinensis (= P. sacchari), P. maydis, P. heteropogonis, and S. rayssiae var. zeae cause major losses in corn yields in tropical Asia. In 2012 a new species, P. australiensis, was described based on isolates previously identified as P. maydis in Australia; this species is now a pathogen of major concern. Despite the strong impact of GDM diseases, there are presently no reliable molecular methods available for their detection. GDM pathogens are among the most difficult Oomycetes to identify using molecular tools, as their taxonomy is very challenging, and little genetic sequence data are available for development of molecular tools to detect GDM pathogens to species level. For example, from over 15 genes used in identification, diagnostics or phylogeny of Phytophthora, only ITS1 and cox2 show promise for use with GDM pathogens. Multiplex/multigene conventional and qPCR assays are currently under evaluation for the detection of economically important GDM spp. Scientists from the USA, Germany, Canada, Australia, and the Philippines are collaborating on the development and testing of diagnostic tools for these pathogens of concern.

Aiming for the management of the small hive beetle, Aethina tumida, using relative humidity and diatomaceous earth

Small hive beetles (SHBs) are a global pest of European honeybee colonies. In the laboratory, the survival of adult SHBs was evaluated in relation to relative humidity (RH = 56, 64, 73, 82 and 96 %) and treatment with diatomaceous earth (DE) across 4 days. Low RH reduced survival. The application of DE reduced survival in addition to RH. Adults treated with corn flour (control) showed no difference in survival from untreated beetles. Scanning electron microscopy images showed no scarification of adult beetle cuticle after exposure to DE; therefore, water loss is likely facilitated through non-abrasive means such as the adsorption of cuticular lipids. The data agree with the hypothesis that DE causes mortality through water loss from treated insects. Egress, ingress, mortality and the egg-laying behaviours of beetles were observed in relation to a popular in-hive trench trap with and without the addition of DE. Traps filled with DE resulted in 100 % mortality of beetles compared with 8.6 % mortality when no DE was present. A simple method for visually determining beetle sex was used and documented.

Networks of stored grain diseases and pests: Strategies for sampling and mitigation

Pathogens and pests of stored grains move through complex dynamic networks linking fields, farms, and bulk storage facilities. Human transport and other forms of dispersal link the components of this network. A network model for pathogen and pest movement through stored grain systems is a first step toward new sampling and mitigation strategies that utilize information about the network structure. An understanding of network structure can be applied to identifying the key network components for pathogen or pest movement through the system. For example, it may be useful to identify a network node, such as a local grain storage facility, through which grain from a large number of fields will be accumulated and move through the network. This node may be particularly important for sampling and mitigation. In some cases more detailed information about network structure can identify key nodes that link two large sections of the network, such that management at the key nodes will greatly reduce the risk of spread between the two sections. In addition to the spread of particular species of pathogens and pests, we also evaluate the spread of problematic subpopulations, such as subpopulations with pesticide resistance. We present an analysis of stored grain pathogen and pest networks for Australia and the United States.

Variation in water extraction with maize plant density and its impact on model application

The use of maize simulation models to determine the optimum plant population for rainfed environments allows the evaluation of plant populations over multiple years and locations at a lower cost than traditional field experimentation. However the APSIM maize model that has been used to conduct some of these 'virtual' experiments assumes that the maximum rate of soil water extraction by the crop root system is constant across plant populations. This untested assumption may cause grain yield to be overestimated in lower plant populations. A field experiment was conducted to determine whether maximum rates of water extraction vary with plant population, and the maximum rate of soil water extraction was estimated for three plant populations (2.4, 3.5 and 5.5 plants m(-2)) under water limited conditions. Maximum soil water extraction rates in the field experiment decreased linearly with plant population, and no difference was detected between plant populations for the crop lower limit of soil water extraction. Re-analysis of previous maize simulation experiments demonstrated that the use of inappropriately high extraction-rate parameters at low plant populations inflated predictions of grain yield, and could cause erroneous recommendations to be made for plant population. The results demonstrate the importance of validating crop simulation models across the range of intended treatments. (C) 2013 Elsevier E.V. All rights reserved.

QTL analysis in multiple sorghum populations facilitates the dissection of the genetic and physiological control of tillering

Tillering in sorghum can be associated with either the carbon supply–demand (S/D) balance of the plant or an intrinsic propensity to tiller (PTT). Knowledge of the genetic control of tillering could assist breeders in selecting germplasm with tillering characteristics appropriate for their target environments. The aims of this study were to identify QTL for tillering and component traits associated with the S/D balance or PTT, to develop a framework model for the genetic control of tillering in sorghum. Four mapping populations were grown in a number of experiments in south east Queensland, Australia. The QTL analysis suggested that the contribution of traits associated with either the S/D balance or PTT to the genotypic differences in tillering differed among populations. Thirty-four tillering QTL were identified across the populations, of which 15 were novel to this study. Additionally, half of the tillering QTL co-located with QTL for component traits. A comparison of tillering QTL and candidate gene locations identified numerous coincident QTL and gene locations across populations, including the identification of common non-synonymous SNPs in the parental genotypes of two mapping populations in a sorghum homologue of MAX1, a gene involved in the control of tiller bud outgrowth through the production of strigolactones. Combined with a framework for crop physiological processes that underpin genotypic differences in tillering, the co-location of QTL for tillering and component traits and candidate genes allowed the development of a framework QTL model for the genetic control of tillering in sorghum.

Weed dynamics as influenced by tillage system, sowing time and weed competition duration in dry-seeded rice

Cultural practices alter patterns of crop growth and can modify dynamics of weed-crop competition, and hence need to be investigated to evolve sustainable weed management in dry-seeded rice (DSR). Studies on weed dynamics in DSR sown at different times under two tillage systems were conducted at the Agronomic Research Farm, University of Agriculture, Faisalabad, Pakistan. A commonly grown fine rice cultivar 'Super Basmati' was sown on 15th June and 7th July of 2010 and 2011 under zero-till (ZT) and conventional tillage (CONT) and it was subjected to different durations of weed competition [10, 20, 30, 40, and 50 days after sowing (DAS) and season-long competition]. Weed-free plots were maintained under each tillage system and sowing time for comparison. Grassy weeds were higher under ZT while CONT had higher relative proportion of broad-leaved weeds in terms of density and biomass. Density of sedges was higher by 175% in the crop sown on the 7th July than on the 15th June. Delaying sowing time of DSR from mid June to the first week of July reduced weed density by 69 and 43% but their biomass remained unaffected. Tillage systems had no effect on total weed biomass. Plots subjected to season-long weed competition had mostly grasses while broad-leaved weeds were not observed at harvest. In the second year of study, dominance of grassy weeds was increased under both tillage systems and sowing times. Significantly less biomass (48%) of grassy weeds was observed under CONT than ZT in 2010; however, during 2011, this effect was non-significant. Trianthema portulacastrum and Dactyloctenium aegyptium were the dominant broad-leaved and grassy weeds, respectively. Cyperus rotundus was the dominant sedge weed, especially in the crop sown on the 7th July. Relative yield loss (RYL) ranged from 3 to 13% and 7 to16% when weeds were allowed to compete only for 20 DAS. Under season-long weed competition, RYL ranged from 68 to 77% in 2010 and 74 to80% in 2011. The sowing time of 15th June was effective in minimizing weed proliferation and rectifying yield penalty associated with the 7th July sowing. The results suggest that DSR in Pakistan should preferably be sown on 15th June under CONT systems and weeds must be controlled before 20 DAS to avoid yield losses. Successful adoption of DSR at growers' fields in Pakistan will depend on whether growers can control weeds and prevent shifts in weed population from intractable weeds to more difficult-to-control weeds as a consequence of DSR adoption.