Optimising plant bed performance through adaptive research with the Australian sweetpotato industry

A key driver of Australian sweetpotato productivity improvements and consumer demand has been industry adoption of disease-free planting material systems. On a farm isolated from main Australian sweetpotato areas, virus-free germplasm is annually multiplied, with subsequent 'pathogen-tested' (PT) sweetpotato roots shipped to commercial Australian sweetpotato growers. They in turn plant their PT roots into specially designated plant beds, commencing in late winter. From these beds, they cut sprouts as the basis for their commercial fields. Along with other intense agronomic practices, this system enables Australian producers to achieve worldRSQUOs highest commercial yields (per hectare) of premium sweetpotatoes. Their industry organisation, ASPG (Australian Sweetpotato Growers Inc.), has identified productivity of mother plant beds as a key driver of crop performance. Growers and scientists are currently collaborating to investigate issues such as catastrophic plant beds losses; optimisation of irrigation and nutrient addition; rapidity and uniformity of initial plant bed harvests; optimal plant bed harvest techniques; virus re-infection of plant beds; and practical longevity of plant beds. A survey of 50 sweetpotato growers in Queensland and New South Wales identified a substantial diversity in current plant bed systems, apparently influenced by growing district, scale of operation, time of planting, and machinery/labour availability. Growers identified key areas for plant bed research as: optimising the size and grading specifications of PT roots supplied for the plant beds; change in sprout density, vigour and performance through sequential cuttings of the plant bed; optimal height above ground level to cut sprouts to maximise commercial crop and plant bed performance; and use of structures and soil amendments in plant bed systems. Our ongoing multi-disciplinary research program integrates detailed agronomic experiments, grower adaptive learning sites, product quality and consumer research, to enhance industry capacity for inspired innovation and commercial, sustainable practice change.

Leadership training and regular communication identified as key strategies for the development of the Australian pineapple industry

Changes in the circumstances of the Australian pineapple industry left growers with a leadership vacuum, limited technical support and no funds for conducting research and marketing. Inspirational leadership training together with regular district farm meetings were used to assist the Australian pineapple industry to successfully adapt to these challenges. All growers were assigned to one of a number of regional grower study groups and regular on-farm meetings commenced to facilitate communication between growers, transfer of technology, awareness of industry affairs and an opportunity to become involved in industry business. A leader was appointed within each study group and these leaders attended a leadership course consisting of three, three-day modules. These original course graduates formed the nucleus of a new grower representative group which subsequently instigated levies to fund research and marketing. Two more courses have since been conducted to provide the depth of leadership to satisfy the growers' desire to rotate industry leadership on a regular basis.

'Abnormal vertical growth' : A disorder threatening the viability of the Australian macadamia industry

'Abnormal vertical growth' (AVG) was recognised in Australia as a dysfunction of macadamia (Macadamia spp.) in the mid-1990s. Affected trees displayed unusually erect branching, and poor flowering and yield. Since 2002, the commercial significance of AVG, its cause, and strategies to alleviate its affects, has been studied. The cause is still unknown, and AVG remains a serious threat to orchard viability. AVG affects both commercial and urban macadamia. It occurs predominantly in the warmer-drier production regions of Queensland and New South Wales. An estimated 100,000 orchard trees are affected, equating to an annual loss of $ 10.5 M. In orchards, AVG occurs as aggregations of affected trees, affected tree number can increase by 4.5% per year, and yield reduction can exceed 30%. The more upright cultivars 'HAES 344' and '741' are highly susceptible, while the more spreading cultivars 'A4', 'A16' and 'A268' show tolerance. Incidence is higher (p<0.05) in soils of high permeability and good drainage. No soil chemical anomaly has been found. Fine root dry weight of AVG trees (0-15 cm depth) was found lower (p<0.05) than non-AVG. Next generation sequencing has led to the discovery of a new Bacillus sp. and a bipartite Geminivirus, which may have a role in the disease. Trunk cinctures will increase (p<0.05) yield of moderately affected trees. Further research is needed to clarify whether a pathogen is the cause, the role of soil moisture in AVG, and develop a varietal solution.

Statistical forecasting of the Australian macadamia crop

Three types of forecasts of the total Australian production of macadamia nuts (t nut-in-shell) have been produced early each year since 2001. The first is a long-term forecast, based on the expected production from the tree census data held by the Australian Macadamia Society, suitably scaled up for missing data and assumed new plantings each year. These long-term forecasts range out to 10 years in the future, and form a basis for industry and market planning. Secondly, a statistical adjustment (termed the climate-adjusted forecast) is made annually for the coming crop. As the name suggests, climatic influences are the dominant factors in this adjustment process, however, other terms such as bienniality of bearing, prices and orchard aging are also incorporated. Thirdly, industry personnel are surveyed early each year, with their estimates integrated into a growers and pest-scouts forecast. Initially conducted on a 'whole-country' basis, these models are now constructed separately for the six main production regions of Australia, with these being combined for national totals. Ensembles or suites of step-forward regression models using biologically-relevant variables have been the major statistical method adopted, however, developing methodologies such as nearest-neighbour techniques, general additive models and random forests are continually being evaluated in parallel. The overall error rates average 14% for the climate forecasts, and 12% for the growers' forecasts. These compare with 7.8% for USDA almond forecasts (based on extensive early-crop sampling) and 6.8% for coconut forecasts in Sri Lanka. However, our somewhatdisappointing results were mainly due to a series of poor crops attributed to human reasons, which have now been factored into the models. Notably, the 2012 and 2013 forecasts averaged 7.8 and 4.9% errors, respectively. Future models should also show continuing improvement, as more data-years become available.