An improved simulation model to predict pre-harvest aflatoxin risk in maize

Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.

An improved simulation model to predict pre-harvest aflatoxin risk in maize

Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.

Responses of fruit flies (Tephritidae: Dacinae) to novel male attractants in north Queensland, Australia, and improved lures for some pest species

Male fruit fly attractants, cue-lure and methyl eugenol (ME), have been successfully used for the last 50 years in the monitoring and control of Dacini fruit flies (Bactrocera and Dacus species). However, over 50% of Dacini are non-responsive to either lure, including some pest species. A new lure, zingerone, has been found to weakly attract cue- and ME-responsive species in Malaysia. In Australia it attracted a weakly cue-responsive minor pest Bactrocera jarvisi (Tryon) and three non-responsive' species. Similar compounds were tested in Queensland and attracted cue- and ME-responsive species and two non-responsive' species. In this study, 14 novel compounds, including raspberry ketone formate (RKF) (Melolure) and zingerone, were field tested in comparison with cue-lure and ME at 17 sites in north Queensland. The most attractive novel lures were isoeugenol, methyl-isoeugenol, dihydroeugenol and zingerone. Several non-responsive' species responded to the new lures: Bactrocera halfordiae (Tryon), a species of some market access concern, was most attracted to isoeugenol; B.barringtoniae (Tryon), B.bidentata (May) and B.murrayi (Perkins) responded to isoeugenol, methyl-isoeugenol and dihydroeugenol; two new species of Dacus responded to zingerone. Bactrocera kraussi (Hardy), a cue-responsive minor pest in north Queensland, was significantly more attracted to isoeugenol than cue-lure. The cue-responsive D.absonifacies (May) and D.secamoneaeDrew were significantly more attracted to zingerone than cue-lure. Bactrocera yorkensisDrew & Hancock, a ME-responsive species was significantly more attracted to isoeugenol, methyl-isoeugenol and dihydroeugenol than ME. The preferential response to RKF or cue-lure was species specific. Six species were significantly more attracted to RKF, including the pests B.tryoni (Froggatt), B.frauenfeldi (Schiner) and minor pest B.bryoniae (Tryon); eight species were significantly more attracted to cue-lure including the pest B.neohumeralis (Hardy). These findings have significance in the search for optimal male lures for pest species elsewhere in the world.

A crop productivity research protocol for long wall mining

Springsure Creek Coal (SCC) intends to develop a coal mine using the long wall mining process under grain farming land near Emerald in Central Queensland (CQ). While this technology will result in some subsidence of the land surface, SCC wishes to maintain productivity of the grain cropping land in the precinct after coal mining. However, the impact of the surface subsidence resulting from that mining process on productivity of cropping land in any Australian landscape is currently unclear. A research protocol to investigate the impacts of subsidence on grain productivity for when the SCC project becomes operational is proposed. The protocol has wider application for other similar mining projects throughout the country. A copy of the full report is accessible on www.aginstitute.com.au.

Climate savvy grazing (Developing improved grazing and related practices to assist beef production enterprises across northern Australia to adapt to a changing and more variable climate)

There is uncertainty over the potential changes to rainfall across northern Australia under climate change. Since rainfall is a key driver of pasture growth, cattle numbers and the resulting animal productivity and beef business profitability, the ability to anticipate possible management strategies within such uncertainty is crucial. The Climate Savvy Grazing project used existing research, expert knowledge and computer modelling to explore the best-bet management strategies within best, median and worse-case future climate scenarios. All three scenarios indicated changes to the environment and resources upon which the grazing industry of northern Australia depends. Well-adapted management strategies under a changing climate are very similar to best practice within current climatic conditions. Maintaining good land condition builds resource resilience, maximises opportunities under higher rainfall years and reduces the risk of degradation during drought and failed wet seasons. Matching stocking rate to the safe long-term carrying capacity of the land is essential; reducing stock numbers in response to poor seasons and conservatively increasing stock numbers in response to better seasons generally improves profitability and maintains land in good condition. Spelling over the summer growing season will improve land condition under a changing climate as it does under current conditions. Six regions were included within the project. Of these, the Victoria River District in the Northern Territory, Gulf country of Queensland and the Kimberley region of Western Australia had projections of similar or higher than current rainfall and the potential for carrying capacity to increase. The Alice Springs, Maranoa-Balonne and Fitzroy regions had projections of generally drying conditions and the greatest risk of reduced pasture growth and carrying capacity. Encouraging producers to consider and act on the risks, opportunities and management options inherent in climate change was a key goal of the project. More than 60,000 beef producers, advisors and stakeholders are now more aware of the management strategies which build resource resilience, and that resilience helps buffer against the effects of variable and changing climatic conditions. Over 700 producers have stated they have improved confidence, skills and knowledge to attempt new practices to build resilience. During the course of the project, more than 165 beef producers reported they have implemented changes to build resource and business resilience.