"On-the-go" NIT technology to assess protein and moisture during harvest of wheat breeding trials.

In this study, we investigated the application of “on-the-go” assessment of wheat protein and moisture under a breeding trial situation.

Risk assessment and preventive strategies for herbicide resistance in NR (phase III)

The threat and management of glyphosate# resistant weeds are major issues facing northern region growers. At present five weeds are confirmed glyphosate-resistant: barnyard grass, liverseed grass, windmill grass, annual ryegrass and flaxleaf fleabane. This project used 25 experiments to investigate the ecology of the grass weeds, plus new or improved chemical and non-chemical control tactics for them. The refined glyphosate resistance model developed in this project used the experiments' findings to predict the long-term impacts on evolution of resistance and on seed bank numbers of resistant weeds. These data led to revised management and resistance avoidance strategies, which were published in the Reporter newsletter, and via an on-line risk assessment tool. - See more at: http://finalreports.grdc.com.au/UQ00054#sthash.oTkCN4Sk.dpuf

Non-destructive prediction of 'Hass' avocado dry matter via FT-NIR spectroscopy.

BACKGROUND: The inability to consistently guarantee internal quality of horticulture produce is of major importance to the primary producer, marketers and ultimately the consumer. Currently, commercial avocado maturity estimation is based on the destructive assessment of percentage dry matter (%DM), and sometimes percentage oil, both of which are highly correlated with maturity. In this study the utility of Fourier transform (FT) near-infrared spectroscopy (NIRS) was investigated for the first time as a non-invasive technique for estimating %DM of whole intact 'Hass' avocado fruit. Partial least squares regression models were developed from the diffuse reflectance spectra to predict %DM, taking into account effects of intra-seasonal variation and orchard conditions. RESULTS: It was found that combining three harvests (early, mid and late) from a single farm in the major production district of central Queensland yielded a predictive model for %DM with a coefficient of determination for the validation set of 0.76 and a root mean square error of prediction of 1.53% for DM in the range 19.4-34.2%. CONCLUSION: The results of the study indicate the potential of FT-NIRS in diffuse reflectance mode to non-invasively predict %DM of whole 'Hass' avocado fruit. When the FT-NIRS system was assessed on whole avocados, the results compared favourably against data from other NIRS systems identified in the literature that have been used in research applications on avocados.

Assessing the sustainability of wheat-based cropping systems using simulation modelling: sustainability

Concepts of agricultural sustainability and possible roles of simulation modelling for characterising sustainability were explored by conducting, and reflecting on, a sustainability assessment of rain-fed wheat-based systems in the Middle East and North Africa region. We designed a goal-oriented, model-based framework using the cropping systems model Agricultural Production Systems sIMulator (APSIM). For the assessment, valid (rather than true or false) sustainability goals and indicators were identified for the target system. System-specific vagueness was depicted in sustainability polygons-a system property derived from highly quantitative data-and denoted using descriptive quantifiers. Diagnostic evaluations of alternative tillage practices demonstrated the utility of the framework to quantify key bio-physical and chemical constraints to sustainability. Here, we argue that sustainability is a vague, emergent system property of often wicked complexity that arises out of more fundamental elements and processes. A 'wicked concept of sustainability' acknowledges the breadth of the human experience of sustainability, which cannot be internalised in a model. To achieve socially desirable sustainability goals, our model-based approach can inform reflective evaluation processes that connect with the needs and values of agricultural decision-makers. Hence, it can help to frame meaningful discussions, from which actions might emerge.

Baseline and greenhouse-gas emissions in extensive livestock enterprises, with a case study of feeding lipid to beef cattle

For accurate calculation of reductions in greenhouse-gas (GHG) emissions, methodologies under the Australian Government's Carbon Farming Initiative (CFI) depend on a valid assessment of the baseline and project emissions. Life-cycle assessments (LCAs) clearly show that enteric methane emitted from the rumen of cattle and sheep is the major source of GHG emissions from livestock enterprises. Where a historic baseline for a CFI methodology for livestock is required, the use of simulated data for cow-calf enterprises at six sites in southern Australia demonstrated that a 5-year rolling emission average will provide an acceptable trade off in terms of accuracy and stability, but this is a much shorter time period than typically used for LCA. For many CFI livestock methodologies, comparative or pair-wise baselines are potentially more appropriate than historic baselines. A case study of lipid supplementation of beef cows over winter is presented. The case study of a control herd of 250 cows used a comparative baseline derived from simple data on livestock numbers and class of livestock to quantify the emission abatement. Compared with the control herd, lipid supplementation to cows over winter increased livestock productivity, total livestock production and enterprise GHG emissions from 990 t CO2-e to 1022 t CO2-e. Energy embodied in the supplement and extra diesel used in transporting the supplement diminished the enteric-methane abatement benefit of lipid supplementation. Reducing the cow herd to 238 cows maintained the level of livestock production of the control herd and reduced enterprise emissions to 938 t CO2-e, but was not cost effective under the assumptions of this case study.