Polymerization induced self-assembly : tuning of morphology using ionic strength and pH

Investigations of RAFT dispersion polymerization-induced self-assembly (PISA) of 2-hydroxypropyl methacrylate (HPMA) in water/methanol at 60 °C using a cationically charged macroRAFT agent as the stabilizer block, namely P(N,N-diethylaminoethyl methacrylate)-stat-poly((ethylene glycol) methyl ether methacrylate) (PDEAEMA-stat-PEGMA), have been conducted with a view to tune particle morphologies by manipulation of the pH and the ionic strength. Above the LCST (45 °C) of (PDEAEMA-stat-PEGMA), the system can only be conducted as a dispersion polymerization at sufficiently low pH such that the stabilizer block is sufficiently protonated to ensure solubility in the continuous phase. It is demonstrated (reported in the form of an extensive morphology diagram) that a range of morphologies including spherical particles, rods and vesicles can be accessed by adjustment of the pH (via addition of HCl) and the ionic strength (via the concentration of NaCl). A decrease in the charge density of the coronal stabilizer layer via an increase in the pH (less protonation) shifts the system towards higher order morphologies. At a given pH, an increase in ionic strength leads to more extensive charge screening, thus allowing formation of higher order morphologies

Aquilegia, Vol. 24 No. 3, May-June 2000: Newsletter of the Colorado Native Plant Society

https://epublications.regis.edu/aquilegia/1180/thumbnail.jp

Genetic and genomic tools to improve drought tolerance in wheat

Tolerance to drought is a quantitative trait, with a complex phenotype, often confounded by plant phenology. Breeding for drought tolerance is further complicated since several types of abiotic stress, such as high temperatures, high irradiance, and nutrient toxicities or deficiencies can challenge crop plants simultaneously. Although marker-assisted selection is now widely deployed in wheat, it has not contributed significantly to cultivar improvement for adaptation to low-yielding environments and breeding has relied largely on direct phenotypic selection for improved performance in these difficult environments. The limited success of the physiological and molecular breeding approaches now suggests that a careful rethink is needed of our strategies in order to understand better and breed for drought tolerance. A research programme for increasing drought tolerance of wheat should tackle the problem in a multi-disciplinary approach, considering interaction between multiple stresses and plant phenology, and integrating the physiological dissection of drought-tolerance traits and the genetic and genomics tools, such as quantitative trait loci (QTL), microarrays, and transgenic crops. In this paper, recent advances in the genetics and genomics of drought tolerance in wheat and barley are reviewed and used as a base for revisiting approaches to analyse drought tolerance in wheat. A strategy is then described where a specific environment is targeted and appropriate germplasm adapted to the chosen environment is selected, based on extensive definition of the morpho-physiological and molecular mechanisms of tolerance of the parents. This information was used to create structured populations and develop models for QTL analysis and positional cloning.Delphine Fleury, Stephen Jefferies, Haydn Kuchel and Peter Langridg

Evaluation of Australian wheat genotypes for response to variable nitrogen application

Aims: The key aim was to assess the genetic variation for nitrogen (N) response and stability in spring wheat germplasm to determine the scope for improvement of nitrogen use efficiency (NUE) under water-limited, low yielding conditions. A further aim was to evaluate NUE stability and NUE-protein yield (PY) as suitable NUE-related traits for selection. Methods: The traits measured included grain yield (GY, kg ha−1) and NUE (kg GY kg−1 N) under varying N applications at all sites, and NUE for protein yield (NUE-PY), harvest index and plant height at some sites. In addition, two of the trials used two seeding rates to provide an assessment of the impact of plant density on NUE. Results: Genetic variation was significant for all traits studied. Grain yield was affected by both genotype (G) and N rate and the interaction between the two. Interestingly, harvest index and height showed no direct response to varying N applications. However, for these traits, there was a significant G effect and N response (G × N interaction). Conclusions: Increasing N inputs led to variable responses for GY at different sites. Importantly, genetic variation in N response was detected. The information and screening techniques will enable plant breeders to select wheat genotypes that show a consistent response to high N. There is clear scope to improve NUE in spring wheat grown in low yielding environments.Saba Mahjourimajd, Haydn Kuchel, Peter Langridge, Mamoru Okamot

Genetic basis for variation in wheat grain yield in response to varying nitrogen application

Nitrogen (N) is a major nutrient needed to attain optimal grain yield (GY) in all environments. Nitrogen fertilisers represent a significant production cost, in both monetary and environmental terms. Developing genotypes capable of taking up N early during development while limiting biomass production after establishment and showing high N-use efficiency (NUE) would be economically beneficial. Genetic variation in NUE has been shown previously. Here we describe the genetic characterisation of NUE and identify genetic loci underlying N response under different N fertiliser regimes in a bread wheat population of doubled-haploid lines derived from a cross between two Australian genotypes (RAC875 × Kukri) bred for a similar production environment. NUE field trials were carried out at four sites in South Australia and two in Western Australia across three seasons. There was genotype-by-environment- by-treatment interaction across the sites and also good transgressive segregation for yield under different N supply in the population. We detected some significant Quantitative Trait Loci (QTL) associated with NUE and N response at different rates of N application across the sites and years. It was also possible to identify lines showing positive N response based on the rankings of their Best Linear Unbiased Predictions (BLUPs) within a trial. Dissecting the complexity of the N effect on yield through QTL analysis is a key step towards elucidating the molecular and physiological basis of NUE in wheat.Saba Mahjourimajd, Julian Taylor, Beata Sznajder, Andy Timmins, Fahimeh Shahinnia, Zed Rengel, Hossein Khabaz-Saberi, Haydn Kuchel, Mamoru Okamoto, Peter Langridg