Driving better vegetable irrigation through profitable practice change

The availability and quality of irrigation water has become an issue limiting productivity in many Australian vegetable regions. Production is also under competitive pressure from supply chain forces. Producers look to new technologies, including changing irrigation infrastructure, exploring new water sources, and more complex irrigation management, to survive these stresses. Often there is little objective information investigating which improvements could improve outcomes for vegetable producers, and external communities (e.g. meeting NRM targets). This has led to investment in inappropriate technologies, and costly repetition of errors, as business independently discover the worth of technologies by personal experience. In our project, we investigated technology improvements for vegetable irrigation. Through engagement with industry and other researchers, we identified technologies most applicable to growers, particularly those that addressed priority issues. We developed analytical tools for ‘what if’ scenario testing of technologies. We conducted nine detailed experiments in the Lockyer Valley and Riverina vegetable growing districts, as well as case studies on grower properties in southern Queensland. We investigated root zone monitoring tools (FullStop™ wetting front detectors and Soil Solution Extraction Tubes - SSET), drip system layout, fertigation equipment, and altering planting arrangements. Our project team developed and validated models for broccoli, sweet corn, green beans and lettuce, and spreadsheets for evaluating economic risks associated with new technologies. We presented project outcomes at over 100 extension events, including irrigation showcases, conferences, field days, farm walks and workshops. The FullStops™ were excellent for monitoring root zone conditions (EC, nitrate levels), and managing irrigation with poor quality water. They were easier to interpret than the SSET. The SSET were simpler to install, but required wet soil to be reliable. SSET were an option for monitoring deeper soil zones, unsuitable for FullStop™ installations. Because these root zone tools require expertise, and are labour intensive, we recommend they be used to address specific problems, or as a periodic auditing strategy, not for routine monitoring. In our research, we routinely found high residual N in horticultural soils, with subsequently little crop yield response to additional nitrogen fertiliser. With improved irrigation efficiency (and less leaching), it may be timely to re-examine nitrogen budgets and recommendations for vegetable crops. Where the drip irrigation tube was located close to the crop row (i.e. within 5-8 cm), management of irrigation was easier. It improved nitrogen uptake, water use efficiency, and reduced the risk of poor crop performance through moisture stress, particularly in the early crop establishment phases. Close proximity of the drip tube to the crop row gives the producer more options for managing salty water, and more flexibility in taking risks with forecast rain. In many vegetable crops, proximate drip systems may not be cost-effective. The next best alternative is to push crop rows closer to the drip tube (leading to an asymmetric row structure). The vegetable crop models are good at predicting crop phenology (development stages, time to harvest), input use (water, fertiliser), environmental impacts (nutrient, salt movement) and total yields. The two immediate applications for the models are understanding/predicting/manipulating harvest dates and nitrogen movements in vegetable cropping systems. From the economic tools, the major influences on accumulated profit are price and yield. In doing ‘what if’ analyses, it is very important to be as accurate as possible in ascertaining what the assumed yield and price ranges are. In most vegetable production systems, lowering the required inputs (e.g. irrigation requirement, fertiliser requirement) is unlikely to have a major influence on accumulated profit. However, if a resource is constraining (e.g. available irrigation water), it is usually most profitable to maximise return per unit of that resource.

Processing Tomato Production in the Burdekin: Opportunities and Risks for Growers

The research undertaken here was in response to a decision by a major food producer in about 2009 to consider establishing processing tomato production in northern Australia. This was in response to a lack of water availability in the Goulburn Valley region following the extensive drought that continued until 2011. The high price of water and the uncertainty that went with it was important in making the decision to look at sites within Queensland. This presented an opportunity to develop a tomato production model for the varieties used in the processing industry and to use this as a case study along with rice and cotton production. Following some unsuccessful early trials and difficulties associated with the Global Financial Crisis, large scale studies by the food producer were abandoned. This report uses the data that was collected prior to this decision and contrasts the use of crop modelling with simpler climatic analyses that can be undertaken to investigate the impact of climate change on production systems. Crop modelling can make a significant contribution to our understanding of the impacts of climate variability and climate change because it harnesses the detailed understanding of physiology of the crop in a way that statistical or other analytical approaches cannot do. There is a high overhead, but given that trials are being conducted for a wide range of crops for a variety of purposes, breeding, fertiliser trials etc., it would appear to be profitable to link researchers with modelling expertise with those undertaking field trials. There are few more cost-effective approaches than modelling that can provide a pathway to understanding future climates and their impact on food production.

Evaluation of rumen fatty acid hydrogenation intermediates and differences in bacterial communities after feeding wheat- or corn-based dried distillers grains to feedlot cattle

The effect of partially replacing rolled barley (86.6% of control diet) with 20% wheat dried distillers grains plus solubles (DDGS), 40% wheat DDGS, 20% corn DDGS, or 40% corn DDGS (dietary DM basis) on rumen fluid fatty acid (FA) composition and some rumen bacterial communities was evaluated using 100 steers (20 per treatment). Wheat DDGS increased the 11t-to 10t-18:1 ratio (P < 0.05) in rumen fluid and there was evidence that the conversion of trans-18:1 to 18:0 was reduced in the control and wheat DDGS diets but not in the corn DDGS diet. Bacterial community profiles obtained using denaturing gradient gel electrophoresis and evaluated by Pearson correlation similarity matrices were not consistent for diet and, therefore, these could not be linked to different specific rumen FA. This inconsistency may be related to the nature of diets fed (dominant effect of barley), limited change in dietary composition as the result of DDGS inclusion, large animal-to-animal variation, and possibly additional stress as a result of transport just before slaughter. Ruminal densities of a key fiber-digesting bacteria specie that produces 11t-18:1 from linoleic and linolenic acids (Butyrivibrio fibrisolvens), and a lactate producer originally thought responsible for production of 10t, 12c-18:2 (Megasphaera elsdenii) were not influenced by diet (P > 0.05).

Food-borne pathogens - a key issue for all food animal industries

The modern consumer has an attitude that food safety is non-negotiable issue – the consumer simply demands food to be safe. Yet, at the same time, the modern consumer has an expectation that the food safety is the responsibility of others – the primary producer, the processing company, the supermarket, commercial food handlers and so on. Given this environment, all food animal industries have little choice but to regard food safety as a key issue. As an example, the chicken meat industry, via the two main industry funding bodies – the Rural Industries Research and Development Corporation (Chicken Meat) and the Poultry CRC – has a comprehensive research program that seeks to focus on reducing the risks of food-borne diseases at all points of the food processing chain – from the farm to the processing plant. The scale of the issue for all industries can be illustrated by an analysis of the problem of campylobacterosis – a major food-borne disease. It has been estimated that there are around 230,000 cases of campylobacterosis per year. In 1995, it was estimated that each case of food-borne campylobacterosis in the USA was costing between $(US) 350-580. Hence, a reasonable conservative estimate is that each Australian case in 2010 would result in a cost of around $500 (this includes hospital, medication and lost productivity costs). Hence, this single food-borne agent could be costing Australian society around $115 million annually. In the light of these types of estimated costs for just one food-borne pathogen, it is easy to understand the importance that all food animal industries place on food safety.

Estimating an Aggregate Economic Genotype to Facilitate Breeding and Selection of Strawberry Genotypes in Southeast Queensland

The Queensland strawberry (Fragaria ×ananassa) breeding program in subtropical Australia aims to improve sustainable profitability for the producer. Selection must account for the relative economic importance of each trait and the genetic architecture underlying these traits in the breeding population. Our study used estimates of the influence of a trait on production costs and profitability to develop a profitability index (PI) and an economic weight (i.e., change in PI for a unit change in level of trait) for each trait. The economic weights were then combined with the breeding values for 12 plant and fruit traits on over 3000 genotypes that were represented in either the current breeding population or as progenitors in the pedigree of these individuals. The resulting linear combination (i.e., sum of economic weight × breeding value for all 12 traits) estimated the overall economic worth of each genotype as H, the aggregate economic genotype. H values were validated by comparisons among commercial cultivars and were also compared with the estimated gross margins. When the H value of ‘Festival’ was set as zero, the H values of genotypes in the pedigree ranged from –0.36 to +0.28. H was highly correlated (R2 = 0.77) with the year of selection (1945–98). The gross margins were highly linearly related (R2 > 0.98) to H values when the genotype was planted on less than 50% of available area, but the relationship was non-linear [quadratic with a maximum (R2 > 0.96)] when the planted area exceeded 50%. Additionally, with H values above zero, the variation in gross margin increased with increasing H values as the percentage of area planted to a genotype increased. High correlations among some traits allowed the omission of any one of three of the 12 traits with little or no effect on ranking (Spearman’s rank correlation 0.98 or greater). Thus, these traits may be dropped from the aggregate economic genotype, leading to either cost reductions in the breeding program or increased selection intensities for the same resources. H was efficient in identifying economically superior genotypes for breeding and deployment, but because of the non-linear relationship with gross margin, calculation of a gross margin for genotypes with high H is also necessary when cultivars are deployed across more than 50% of the available area.

Priority list of endemic diseases for the red meat industries

This report provides a systematic review of the most economically damaging endemic diseases and conditions for the Australian red meat industry (cattle, sheep and goats). A number of diseases for cattle, sheep and goats have been identified and were prioritised according to their prevalence, distribution, risk factors and mitigation. The economic cost of each disease as a result of production losses, preventive costs and treatment costs is estimated at the herd and flock level, then extrapolated to a national basis using herd/flock demographics from the 2010-11 Agricultural Census by the Australian Bureau of Statistics. Information shortfalls and recommendations for further research are also specified. A total of 17 cattle, 23 sheep and nine goat diseases were prioritised based on feedback received from producer, government and industry surveys, followed by discussions between the consultants and MLA. Assumptions of disease distribution, in-herd/flock prevalence, impacts on mortality/production and costs for prevention and treatment were obtained from the literature where available. Where these data were not available, the consultants used their own expertise to estimate the relevant measures for each disease. Levels of confidence in the assumptions for each disease were estimated, and gaps in knowledge identified. The assumptions were analysed using a specialised Excel model that estimated the per animal, herd/flock and national costs of each important disease. The report was peer reviewed and workshopped by the consultants and experts selected by MLA before being finalised. Consequently, this report is an important resource that will guide and prioritise future research, development and extension activities by a variety of stakeholders in the red meat industry. This report completes Phase I and Phase II of an overall four-Phase project initiative by MLA, with identified data gaps in this report potentially being addressed within the later phases. Modelling the economic costs using a consistent approach for each disease ensures that the derived estimates are transparent and can be refined if improved data on prevalence becomes available. This means that the report will be an enduring resource for developing policies and strategies for the management of endemic diseases within the Australian red meat industry.