Seed bank persistence and germination of chinee apple (Ziziphus mauritiana Lam.)

Chinee apple (Ziziphus mauritiana Lam.) is a thorny tree that is invading tropical woodlands of northern Australia. The present study reports three experiments related to the seed dynamics of chinee apple. Experiment 1 and 2 investigated persistence of seed lots under different soil types (clay and river loam), levels of pasture cover (present or absent) and burial depths (0, 2.5, 10 and 20 cm). Experiment 3 determined the germination response of chinee apple seeds to a range of alternating day/night temperatures (11/6°C up to 52/40°C). In the longevity experiments (Expts 1 and 2), burial depth, soil type and burial duration significantly affected viability. Burial depth had the greatest influence, with surface located seeds generally persisting for longer than those buried below ground. Even so, no viable seeds remained after 18 and 24 months in the first and second experiment, respectively. In Expt 3 seeds of chinee apple germinated under a wide range of alternating day/night temperatures ranging from 16/12°C to 47 /36°C. Optimal germination (77%) occurred at 33/27°C and no seeds germinated at either of the lowest (11/6°C) or highest (52/40°C) temperature regimes tested. These findings indicated that chinee apple has the potential to expand its current distribution to cooler areas of Australia. Control practices need to be undertaken for at least two years to exhaust the seed bank.

A novel and effective technology for mitigating nitrous oxide emissions from land-applied manures

Land-applied manures produce nitrous oxide (N2O), a greenhouse gas (GHG). Land application can also result in ammonia (NH3) volatilisation, leading to indirect N2O emissions. Here, we summarise a glasshouse investigation into the potential for vermiculite, a clay with a high cation exchange capacity, to decrease N2O emissions from livestock manures (beef, pig, broiler, layer), as well as urea, applied to soils. Our hypothesis is that clays adsorb ammonium, thereby suppressing NH3 volatilisation and slowing N2O emission processes. We previously demonstrated the ability of clays to decrease emissions at the laboratory scale. In this glasshouse work, manure and urea application rates varied between 50 and 150 kg nitrogen (N)/ha. Clay : manure ratios ranged from 1 : 10 to 1 : 1 (dry weight basis). In the 1-year trial, the above-mentioned N sources were incorporated with vermiculite in 1 L pots containing Sodosol and Ferrosol growing a model pasture (Pennisetum clandestinum or kikuyu grass). Gas emissions were measured periodically by placing the pots in gas-tight bags connected to real-time continuous gas analysers. The vermiculite achieved significant (P ≤ 0.05) and substantial decreases in N2O emissions across all N sources (70% on average). We are currently testing the technology at the field scale; which is showing promising emission decreases (~50%) as well as increases (~20%) in dry matter yields. This technology clearly has merit as an effective GHG mitigation strategy, with potential associated agronomic benefits, although it needs to be verified by a cost–benefit analysis.

Statistical methods for analysis of multi-harvest data from perennial pasture variety selection trials

Variety selection in perennial pasture crops involves identifying best varieties from data collected from multiple harvest times in field trials. For accurate selection, the statistical methods for analysing such data need to account for the spatial and temporal correlation typically present. This paper provides an approach for analysing multi-harvest data from variety selection trials in which there may be a large number of harvest times. Methods are presented for modelling the variety by harvest effects while accounting for the spatial and temporal correlation between observations. These methods provide an improvement in model fit compared to separate analyses for each harvest, and provide insight into variety by harvest interactions. The approach is illustrated using two traits from a lucerne variety selection trial. The proposed method provides variety predictions allowing for the natural sources of variation and correlation in multi-harvest data.