Production of Australian freshwater crayfish in earthen-based systems using pelleted diets and forage crops as food

Juvenile Cherax destructor (commonly called theyabby) were cultured in earthen-based ponds and tanks for 70–105d, and were fed pellets and/or a forage crop of the perennialwhiteclover, Trifolium repens. Three supplementary feedingstrategies were evaluated. Yabby growth on pellets consistently exceeded (by67–159%) that obtained on clover. Base-line yields for extensiveproduction systems are around 400 kg ha^–1. Thesupplementary addition of T. repens produced yields of 635kg ha^–1 (in ponds) to 1086 kgha^–1 (in tanks). The sequential addition of cut-cloverto tanks stimulated growth to levels approaching those achieved on pellets.Yabbies stocked into ponds at 17 m^–2 and fed 33%protein pellets for 100 d, resulted in a yield of 1117 kgha^–1.Pellet inputs at a rate of 129–249 g m^–2(dry matter) and 38–83 g m^–2 (protein) over70–100 d resulted in acceptable growth and feed utilisationindices. Clover inputs of 534–682 g m–2 (asdry matter) or 84–177 g m^–2 (as protein)produced reasonable growth rates but poor feed utilisation indices. Aconsiderable quantity of the dry matter and protein content of clover waseitherinefficiently utilised or directed into other production pathways. In tanks,clover inputs from 113–296 g m^–2 (drymatter) and 24–54 g m^–2 (protein) weresufficient to maintain high growth rates for 4 weeks, while in ponds, inputs of21 g m^–2 (dry matter) and 4.3 gm^–2 (protein) were sufficient for 3 weeks. During theearly weeks of production no growth advantage was gained by providing pelletstoanimals cultured in forage-based systems. Forage depletion occurred after3–4 weeks and was probably a major growth limiting factor.

Evaluation of fixed sample-size plans for Plutella xylostella (Lepidoptera: Plutellidae) on broccoli crops in Australia

Fixed sample-size plans for monitoring Plutella xylostella (L.) (Lepidoptera: Plutellidae) on broccoli and other Brassica vegetable crops are popular in Australia for their simplicity and ease of application. But the sample sizes used are often small, ≈10–25 plants per crop, and it may be that they fail to provide sufficient information upon which to base pest control decisions. We tested the performance of seven fixed sample-size plans (10, 15, 20, 30, 35, 40, and 45 plants) by resampling a large data set on P. xylostella in commercial broccoli crops. For each sample size, enumerative and presence-absence plans were assessed. The precision of the plans was assessed in terms of the ratio of the standard error to the mean; and at least 45 and 35 samples were necessary for the enumerative and presence-absence plans, respectively, to attain the generally accepted benchmark of ≤0.3. Sample sizes of 10–20 were highly imprecise. We also assessed the consequences of classifications based on action thresholds (ATs) of 0.2 and 0.8 larvae per plant for the enumerative case, and 0.15 and 0.45 proportion of plants of infested for the presence-absence case. Operating characteristic curves and investigations of the frequency of correct decisions suggest improvements in the performance of plans with increased sample size. In both the enumerative and presence-absence cases, the proportion of incorrect decisions was much higher for the lower of the two ATs assessed, and type II errors (i.e., failure to suggest pest control upon the AT is exceeded) generally accounted for the majority of this error. Type II errors are the most significant from a producer’s standpoint. Further consideration is necessary to determine what is an acceptable type II error rate.

Deterministic versus stochastic quantitative microbial Risk Assessment models for wastewater irrigation of food crops

Reuse of wastewater to irrigate food crops is being practiced in many parts of the world and is becoming more commonplace as the competition for, and stresses on, freshwater resources intensify. But there are risks associated with wastewater irrigation, including the possibility of transmission of pathogens causing infectious disease, to both workers in the field and to consumers buying and eating produce irrigated with wastewater. To manage these risks appropriately we need objective and quantitative estimates of them. This is typically achieved through one of two modelling approaches: deterministic or stochastic. Each parameter in a deterministic model is represented by a single value, whereas in stochastic models probability functions are used. Stochastic models are theoretically superior because they account for variability and uncertainty, but they are computationally demanding and not readily accessible to water resource and public health managers. We constructed models to estimate risk of enteric virus infection arising from the consumption of wastewater-irrigated horticultural crops (broccoli, cucumber and lettuce), and compared the resultant levels of risk between the deterministic and stochastic approaches. Several scenarios were tested for each crop, accounting for different concentrations of enteric viruses and different lengths of environmental exposure (i.e. the time between the last irrigation event and harvest, when the viruses are liable to decay or inactivation). In most situations modelled the two approaches yielded similar estimates of risk (within 1 order-of-magnitude). The two methods diverged most markedly, up to around 2 orders-of-magnitude, when there was large uncertainty associated with the estimate of virus concentration and the exposure period was short (1 day). Therefore, in some circumstances deterministic modelling may offer water resource managers a pragmatic alternative to stochastic modelling, but its usefulness as a surrogate will depend upon the level of uncertainty in the model parameters.

Nanostructured liquid crystalline particle assisted delivery of 2,4-dichlorophenoxyacetic acid to weeds, crops and model plants

Routine agricultural practices are heavily dependent on the use of surfactants, many of which are toxic to humans and detrimental to the environment. In proof of concept work we have previously shown the potential of nanostructured liquid crystalline particles (NLCP) to safely interact with plant leaf cuticular surfaces with minimal impact on epicuticular waxes. Here we demonstrate the use of NLCP to effectively deliver the auxin herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) to plant leaves in laboratory and field studies. In the laboratory, the physiological stress responses of lupin, Lupinus angustifolius (L.) (Fabaceae) towards NLCP spray applications were shown to be much reduced in comparison with application of two common surfactants. Phytotoxicity assays of 2,4-D loaded NLCP were used to validate the herbicidal effects on Arabidopsis thaliana (L.) Heynth. (Brassicaceae) and established a similarity with that of surfactant assisted 2,4-D delivery when tested at a concentration of 0.1%. Field trials were conducted to test the efficacy of NLCP-assisted delivery of 2,4-D in comparison with commercial surfactants for the control of the invasive weed wild radish, Raphanus raphanistrum (L.) (Brassicaceae), in wheat, Triticum aestivum (L.) (Poaceae) crop fields. Compared against Estercide 800, a commercially available 2,4-D formulation, NLCP assisted delivery of 2,4-D was effective at low concentrations of 0.03% and 0.06%. The crop yield remained similar for all the tested concentrations and formulations of 2,4-D loaded NLCP and Estercide 800. This is the first report to directly show that, as an alternative to conventional methods, NLCP can be used under both laboratory and field conditions to successfully delivery an agrochemical.

Root-depth profiles of important agricultural crops

Based on a literature review we describe root density profiles in terms of a logistic dose-response function for important global agricultural crops (wheat, maize, rice, barley, soybean, pulses, cotton, potato, sunflower, rye, rapeseed, and sugarbeet). These root density profiles can be used in 1-D macroscopic root water uptake models. For use in 1-D microscopic root water uptake models, we analyze root density data in terms of the half mean distance between roots. Based on the database there is little support for a predictive relationship between parameters of the root density distribution of agricultural crops and climate or management factors. Constancy of the shape of the root density distribution with time is shown not to hold in some experiments, but evidence is anecdotical. At present the basis to describe rooting profiles with depth only seems to allow profiles which are constant in time and with depth. The correlation between half mean distance and drought sensitivity is investigated and conclusions will be presented.