Sorghum dwarfing genes can affect radiation capture and radiation use efficiency

Presence of the dw3 sorghum dwarfing gene had negative effects on grain yield in some genetic backgrounds and environments. In a previous study we showed that this was due to a significant reduction in shoot biomass (mainly via reduced stem mass), which in turn negatively affected grain size. The current study examines whether shoot biomass was reduced via effects of dw3 on traits associated with resource capture, such as leaf area index (LAI), light interception (LI), and canopy extinction coefficient (k) or with resource use efficiency, such as radiation use efficiency (RUE). Three pairs of near-isogenic sorghum lines differing only in the presence or absence of the dwarfing allele dw3 (3-dwarfs vs 2-dwarfs) were grown in large field plots. Biomass accumulation and LI were measured for individual canopy layers to examine canopy characteristics of tall and short types. Similar to the previously reported effects on grain yield, the effects of dw3 on RUE, LI and k varied among genetic backgrounds and environments. Interactions between dw3 and genetic background, but also interactions with environment are likely to have modulated the extent to which RUE, LI, or k contributed to biomass differences between tall and short sorghum. © 2013 .

Pratylenchus thornei populations reduce water uptake in intolerant wheat cultivars

Pratylenchus thornei is a major pathogen of wheat crops in the northern grain region of Eastern Australia with an estimated annual yield loss of $38 million. Damaged crops show symptoms of water and nutrient stress that suggest uptake is significantly affected. In order to understand the mechanisms involved in reducing water uptake and consequently plant yield, detailed measurements of water extraction and leaf area were conducted on a range of wheat cultivars with differing levels of tolerance and resistance to P. thornei.

Weed–pathogen interactions and elevated CO2: growth changes in favour of the biological control agent

In this study, we used Parthenium hysterophorus and one of its biological control agents, the winter rust (Puccinia abrupta var. partheniicola) as a model system to investigate how the weed may respond to infection under a climate change scenario involving an elevated atmospheric CO2 (550 μmol mol−1) concentration. Under such a scenario, P. hysterophorus plants grew significantly taller (52%) and produced more biomass (55%) than under the ambient atmospheric CO2 concentration (380 μmol mol−1). Following winter rust infection, biomass production was reduced by 17% under the ambient and by 30% under the elevated atmospheric CO2 concentration. The production of branches and leaf area was significantly increased by 62% and 120%, under the elevated as compared with ambient CO2 concentration, but unaffected by rust infection under either condition. The photosynthesis and water use efficiency (WUE) of P. hysterophorus plants were increased by 94% and 400%, under the elevated as compared with the ambient atmospheric CO2 concentration. However, in the rust-infected plants, the photosynthesis and WUE decreased by 18% and 28%, respectively, under the elevated CO2 and were unaffected by the ambient atmospheric CO2 concentration. The results suggest that although P. hysterophorus will benefit from a future climate involving an elevation of the atmospheric CO2 concentration, it is also likely that the winter rust will perform more effectively as a biological control agent under these same conditions.

Stay-green alleles individually enhance grain yield in sorghum under drought by modifying canopy development and water uptake patterns

* Stay-green is an integrated drought adaptation trait characterized by a distinct green leaf phenotype during grain filling under terminal drought. We used sorghum (Sorghum bicolor), a repository of drought adaptation mechanisms, to elucidate the physiological and genetic mechanisms underpinning stay-green. * Near-isogenic sorghum lines (cv RTx7000) were characterized in a series of field and managed-environment trials (seven experiments and 14 environments) to determine the influence of four individual stay-green (Stg1–4) quantitative trait loci (QTLs) on canopy development, water use and grain yield under post-anthesis drought. * The Stg QTL decreased tillering and the size of upper leaves, which reduced canopy size at anthesis. This reduction in transpirational leaf area conserved soil water before anthesis for use during grain filling. Increased water uptake during grain filling of Stg near-isogenic lines (NILs) relative to RTx7000 resulted in higher post-anthesis biomass production, grain number and yield. Importantly, there was no consistent yield penalty associated with the Stg QTL in the irrigated control. * These results establish a link between the role of the Stg QTL in modifying canopy development and the subsequent impact on crop water use patterns and grain yield under terminal drought.

Growth analysis and biomass partitioning of Cyperus iria in response to rice planting density and nitrogen rate

Cyperus iria is a weed of rice with widespread occurrence throughout the world. Because of concerns about excessive and injudicious use of herbicides, cultural weed management approaches that are safe and economical are needed. Developing such approaches will require a better understanding of weed biology and ecology, as well as of weed response to increases in crop density and nutrition. Knowledge of the effects of nitrogen (N) fertilizer on crop-weed competitive interactions could also help in the development of integrated weed management strategies. The present study was conducted in a screenhouse to determine the effects of rice planting density (0, 5, 10, and 20 plants pot−1) and N rate (0, 50, 100, and 150 kg ha−1) on the growth of C. iria. Tiller number per plant decreased by 73–88%, leaf number by 85–94%, leaf area by 85–98%, leaf biomass by 92–99%, and inflorescence biomass by 96–99% when weed plants were grown at 20 rice plants pot−1 (i.e., 400 plants m−2) compared with weed plants grown alone. All of these parameters increased when N rates were increased. On average, weed biomass increased by 118–389% and rice biomass by 121–275% with application of 50–150 kg N ha−1, compared to control. Addition of N favored weed biomass production relative to rice biomass. Increased N rates reduced the root-to-shoot weight ratio of C. iria. Rice interference reduced weed growth and biomass and completely suppressed C. iria when no N was applied at high planting densities (i.e., 20 plants pot−1). The weed showed phenotypic plasticity in response to N application, and the addition of N increased the competitive ability of the weed over rice at densities of 5 and 10 rice plants pot−1 compared with 20 plants pot−1. The results of the present study suggest that high rice density (i.e., 400 plants m−2) can help suppress C. iria growth even at high N rates (150 kg ha−1).

Integrating pest population models with biophysical crop models to better represent the farming system

Farming systems frameworks such as the Agricultural Production Systems simulator (APSIM) represent fluxes through the soil, plant and atmosphere of the system well, but do not generally consider the biotic constraints that function within the system. We designed a method that allowed population models built in DYMEX to interact with APSIM. The simulator engine component of the DYMEX population-modelling platform was wrapped within an APSIM module allowing it to get and set variable values in other APSIM models running in the simulation. A rust model developed in DYMEX is used to demonstrate how the developing rust population reduces the crop's green leaf area. The success of the linking process is seen in the interaction of the two models and how changes in rust population on the crop's leaves feedback to the APSIM crop modifying the growth and development of the crop's leaf area. This linking of population models to simulate pest populations and biophysical models to simulate crop growth and development increases the complexity of the simulation, but provides a tool to investigate biotic constraints within farming systems and further moves APSIM towards being an agro-ecological framework.