Estimation in a multiplicative mixed model involving a genetic relationship matrix.

Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs) in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA) form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.

The climate change risk management matrix for the grazing industry of northern Australia

The complexity, variability and vastness of the northern Australian rangelands make it difficult to assess the risks associated with climate change. In this paper we present a methodology to help industry and primary producers assess risks associated with climate change and to assess the effectiveness of adaptation options in managing those risks. Our assessment involved three steps. Initially, the impacts and adaptation responses were documented in matrices by ‘experts’ (rangeland and climate scientists). Then, a modified risk management framework was used to develop risk management matrices that identified important impacts, areas of greatest vulnerability (combination of potential impact and adaptive capacity) and priority areas for action at the industry level. The process was easy to implement and useful for arranging and analysing large amounts of information (both complex and interacting). Lastly, regional extension officers (after minimal ‘climate literacy’ training) could build on existing knowledge provided here and implement the risk management process in workshops with rangeland land managers. Their participation is likely to identify relevant and robust adaptive responses that are most likely to be included in regional and property management decisions. The process developed here for the grazing industry could be modified and used in other industries and sectors. By 2030, some areas of northern Australia will experience more droughts and lower summer rainfall. This poses a serious threat to the rangelands. Although the impacts and adaptive responses will vary between ecological and geographic systems, climate change is expected to have noticeable detrimental effects: reduced pasture growth and surface water availability; increased competition from woody vegetation; decreased production per head (beef and wool) and gross margin; and adverse impacts on biodiversity. Further research and development is needed to identify the most vulnerable regions, and to inform policy in time to facilitate transitional change and enable land managers to implement those changes.

Lack of release of bound anthocyanins and phenolic acids from carrot plant cell walls and model composites during simulated gastric and small intestinal digestion

Separately, polyphenols and plant cell walls (PCW) are important contributors to the health benefits associated with fruits and vegetables. However, interactions with PCW which occur either during food preparation or mastication may affect bioaccessibility and hence bioavailability of polyphenols. Binding interactions between anthocyanins, phenolic acids (PAs) and PCW components, were evaluated using both a bacterial cellulose-pectin model system and a black carrot puree system. The majority of available polyphenols bound to PCW material with 60-70% of available anthocyanins and PAs respectively binding to black carrot puree PCW matter. Once bound, release of polyphenols using acidified methanol is low with only similar to 20% of total anthocyanins to similar to 30% of PAs being released. Less than 2% of bound polyphenol was released after in vitro gastric and small intestinal (S.I.) digestion for both the model system and the black carrot puree PCW matter. Confocal laser scanning microscopy shows localised binding of anthocyanins to PCW. Very similar patterns of binding for anthocyanins and PAs suggest that PAs form complexes with anthocyanins and polysaccharides. Time dependent changes in extractability with acidified methanol but not the total bound fraction suggests that initial nonspecific deposition on cellulose surfaces is followed by rearrangement of the bound molecules. Minimal release of anthocyanins and PAs after simulated gastric and S.I. digestion indicates that polyphenols in fruits and vegetables which bind to the PCW will be transported to the colon where they would be expected to be released by the action of cell wall degrading bacteria.