Calotrope (Calotropis procera) control

Calotrope [Calotropis procera (Aiton) W.T.Aiton] is an exotic shrub or small tree species that is currently invading the tropical savannahs of northern Australia. A chemical trial involving 11 herbicides and four application methods (foliar, basal bark, cut stump and soil applied) was undertaken to identify effective chemicals to control calotrope. Of the foliar herbicides tested, imazapyr provided 100% mortality at the rates applied, and the higher rate of metsulfuron-methyl killed 100% of the treated plants. The herbicides 2,4-D butyl ester, fluroxypyr, triclopyr and triclopyr/picloram killed greater than 80% of the plants when applied by a basal bark or cut stump (when cut 5cm above ground level) method of application. Plants cut close to ground level (5cm) were controlled more effectively than plants cut 20cm above ground level. Chemical control (foliar and cut stump spraying) is a cost effective tool to treat calotrope densities <800plants/ha. Adoption of pasture management practices that promote perennial grasses, in conjunction with strategic chemical control, would further increase the effectiveness and reduce the costs of controlling vast areas of this weed.

Ruminococcus bromii, identification and isolation as a dominant community member in the rumen of cattle fed a barley diet

Aims: To identify dominant bacteria in grain (barley)-fed cattle for isolation and future use to increase the efficiency of starch utilization in these cattle. Methods and Results: Total DNA was extracted from samples of the rumen contents from eight steers fed a barley diet for 9 and 14 days. Bacterial profiles were obtained using denaturing gradient gel electrophoresis (DGGE) of the PCR-amplified V2/V3 region of the 16S rRNA genes from total bacterial DNA. Apparently dominant bands were excised and cloned, and the clone insert sequence was determined. One of the most common and dominant bacteria present was identified as Ruminococcus bromii. This species was subsequently isolated using traditional culture-based techniques and its dominance in the grain-fed cattle was confirmed using a real-time Taq nuclease assay (TNA) designed for this purpose. In some animals, the population of R. bromii reached densities above 1010R. bromii cell equivalents per ml or approximately 10% of the total bacterial population. Conclusions: Ruminococcus bromii is a dominant bacterial population in the rumen of cattle fed a barley-based diet. Significance and Impact of the Study: Ruminococcus bromii YE282 may be useful as a probiotic inoculant to increase the efficiency of starch utilization in barley-fed cattle. The combination of DGGE and real-time TNA has been an effective process for identifying and targeting for isolation, dominant bacteria in a complex ecosystem.

Stocking density and artificial habitat influence stock structure and yield from intensive nursery systems for mud crabs Scylla serrata (Forsskål 1775)

Intensive nursery systems are designed to culture mud crab postlarvae through a critical phase in preparation for stocking into growout systems. This study investigated the influence of stocking density and provision of artificial habitat on the yield of a cage culture system. For each of three batches of postlarvae, survival, growth and claw loss were assessed after each of three nursery phases ending at crab instars C1/C2, C4/C5 and C7/C8. Survival through the first phase was highly variable among batches with a maximum survival of 80% from megalops to a mean crab instar of 1.5. Stocking density between 625 and 2300 m-2 did not influence survival or growth in this first phase. Stocking densities tested in phases 2 and 3 were 62.5, 125 and 250 m -2. At the end of phases 2 and 3, there were five instar stages present, representing a more than 20-fold size disparity within the populations. Survival became increasingly density-sensitive following the first phase, with higher densities resulting in significantly lower survival (phase 2: 63% vs. 79%; phase 3: 57% vs. 64%). The addition of artificial habitat in the form of pleated netting significantly improved survival at all densities. The mean instar attained by the end of phase 2 was significantly larger at a lower stocking density and without artificial habitat. No significant effect of density or habitat on harvest size was detected in phase 3. The highest incidence of claw loss was 36% but was reduced by lowering stocking densities and addition of habitat. For intensive commercial production, yield can be significantly increased by addition of a simple net structure but rapidly decreases the longer crablets remain in the nursery.

Annual forecasting of the Australian macadamia crop - integrating tree census data with statistical climate-adjustment models

To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.

Probabilistic forecasts of the onset of the north Australian wet season

The amount and timing of early wet-season rainfall are important for the management of many agricultural industries in north Australia. With this in mind, a wet-season onset date is defined based on the accumulation of rainfall to a predefined threshold, starting from 1 September, for each square of a 1° gridded analysis of daily rainfall across the region. Consistent with earlier studies, the interannual variability of the onset dates is shown to be well related to the immediately preceding July-August Southern Oscillation index (SOI). Based on this relationship, a forecast method using logistic regression is developed to predict the probability that onset will occur later than the climatological mean date. This method is expanded to also predict the probabilities that onset will be later than any of a range of threshold dates around the climatological mean. When assessed using cross-validated hindcasts, the skill of the predictions exceeds that of climatological forecasts in the majority of locations in north Australia, especially in the Top End region, Cape York, and central Queensland. At times of strong anomalies in the July-August SOI, the forecasts are reliably emphatic. Furthermore, predictions using tropical Pacific sea surface temperatures (SSTs) as the predictor are also tested. While short-lead (July-August predictor) forecasts are more skillful using the SOI, long-lead (May-June predictor) forecasts are more skillful using Pacific SSTs, indicative of the longer-term memory present in the ocean.

Growth responses of sugarcane to mycorrhizal spore density and phosphorus rate

Arbuscular mycorrhizal (AM) fungi, commonly found in long-term cane-growing fields in northern Queensland, are linked with both negative and positive growth responses by sugarcane (Saccharum spp.), depending on P supply. A glasshouse trial was established to examine whether AM density might also have an important influence on these growth responses. Mycorrhizal spores (Glomus clarum), isolated from a long-term cane block in northern Queensland, were introduced into a pasteurised low-P cane soil at 5 densities (0, 0.06, 0.25, 1, 4 spores/g soil) and with 4 P treatments (0, 8.2, 25, and 47 mg/kg). At 83 days after planting, sugarcane tops responded positively to P fertilizer, although responses attributable to spore density were rarely observed. In one case, addition of 4 spores/g led to a 53% yield response over those without AM at 8 mgP/kg, or a relative benefit of 17 mg P/kg. Root colonisation was reduced for plants with nil or 74 mg P/kg. For those without AM, P concentration in the topmost visible dewlap (TVD) leaf increased significantly with fertiliser P (0.07 v. 0.15%). However, P concentration increased further with the presence of AM spores. Irrespective of AM, the critical P concentration in the TVD leaf was 0.18%. This study confirms earlier reports that sugarcane is poorly responsive to AM. Spore density, up to 4 spores/g soil, appears unable to influence this responsiveness, either positively or negatively. Attempts to gain P benefits by increasing AM density through rotation seem unlikely to lead to yield increases by sugarcane. Conversely, sugarcane grown in fields with high spore densities and high plant-available P, such as long-term cane-growing soils, is unlikely to suffer a yield reduction from mycorrhizal fungi.

A survey of management and economic impact of weeds in dryland cotton cropping systems of subtropical Australia

In dryland cotton cropping systems, the main weeds and effectiveness of management practices were identified, and the economic impact of weeds was estimated using information collected in a postal and a field survey of Southern Queensland and northern New South Wales. Forty-eight completed questionnaires were returned, and 32 paddocks were monitored in early and late summer for weed species and density. The main problem weeds were bladder ketmia (Hibiscus trionum), common sowthistle (Sonchus oleraceus), barnyard grasses (Echinochloa spp.), liverseed grass (Urochloa panicoides) and black bindweed (Fallopia convolvulus), but the relative importance of these differed with crops, fallows and crop rotations. The weed flora was diverse with 54 genera identified in the field survey. Control of weed growth in rotational crops and fallows depended largely on herbicides, particularly glyphosate in fallow and atrazine in sorghum, although effective control was not consistently achieved. Weed control in dryland cotton involved numerous combinations of selective herbicides, several non-selective herbicides, inter-row cultivation and some manual chipping. Despite this, residual weeds were found at 38-59% of initial densities in about 3-quarters of the survey paddocks. The on-farm financial costs of weeds ranged from $148 to 224/ha.year depending on the rotation, resulting in an estimated annual economic cost of $19.6 million. The approach of managing weed populations across the whole cropping system needs wider adoption to reduce the weed pressure in dryland cotton and the economic impact of weeds in the long term. Strategies that optimise herbicide performance and minimise return of weed seed to the soil are needed. Data from the surveys provide direction for research to improve weed management in this cropping system. The economic framework provides a valuable measure of evaluating likely future returns from technologies or weed management improvements.

Needs for applied climate education in agriculture

This paper reports on a purposive survey study which aimed to identify needs for the development, delivery and evaluation of applied climate education for targeted groups, to improve knowledge and skills to better manage under variable climatic conditions. The survey sample consisted of 80 producers and other industry stakeholders in Australia (including representatives from consulting, agricultural extension and agricultural education sectors), with a 58% response rate to the survey. The survey included an assessment of (i) knowledge levels of the Southern Oscillation Index and sea surface temperatures, and (ii) skill and ability in interpreting weather and climate parameters. Results showed that despite many of the respondents having more than 20 years experience in their industry, the only formal climate education or training undertaken by most was a 1-day workshop. Over 80% of the applied climate skills listed in the survey were regarded by respondents as essential or important, but only 42% of educators, 30% of consultants and 28% of producers rated themselves as competent in applying such skills. Essential skills were deemed as those that would enable respondents or their clients to be better prepared for the next extended wet or dry meteorological event, and improved capability in identifying and capitalising on key decision points from climate information and a seasonal climate outlook. The complex issue of forecast accuracy is a confounding obstacle for many in the application of climate information and forecasts in management. Addressing this problem by describing forecast 'limitations and skill' can help to overcome this problem. The survey also highlighted specific climatic tactical and strategic information collated from grazing, cropping and agribusiness enterprises, and showed the value of such information from a users perspective.

Izmir subterranean clover (Trifolium subterraneum L. var. subterraneum)

Izmir is a hardseeded, early flowering, subterranean clover of var. subterraneum (Katz. et Morley) Zohary and Heller collected from Turkey and developed by the collaborating organisations of the National Annual Pasture Legume Improvement Program. It is a more hardseeded replacement for Nungarin and best suited to well-drained, moderately acidic soils in areas with a growing season of less than 4.5 months. Izmir seed production and regeneration densities in 3-year pasture phases were similar to Nungarin in 21 trials across southern Australia, but markedly greater in years following a crop or no seed set. Over all measurements, Izmir produced 10% more winter herbage and 7% more spring herbage than Nungarin. Its greater hardseededness and good seed production, makes it better suited to cropping rotations than Nungarin. Softening of Izmir hard seeds occurs later in the summer–autumn period than Nungarin, giving it slightly greater protection from seed losses following false breaks to the season. Izmir is recommended for sowing in Western Australia, New South Wales, Victoria, South Australia and Queensland. Izmir has been granted Plant Breeders Rights in Australia.

Defining and predicting the 'break of the season' for north-east Queensland grazing areas

For pasture growth in the semi-arid tropics of north-east Australia, where up to 80% of annual rainfall occurs between December and March, the timing and distribution of rainfall events is often more important than the total amount. In particular, the timing of the 'green break of the season' (GBOS) at the end of the dry season, when new pasture growth becomes available as forage and a live-weight gain is measured in cattle, affects several important management decisions that prevent overgrazing and pasture degradation. Currently, beef producers in the region use a GBOS rule based on rainfall (e. g. 40mm of rain over three days by 1 December) to define the event and make their management decisions. A survey of 16 beef producers in north-east Queensland shows three quarters of respondents use a rainfall amount that occurs in only half or less than half of all years at their location. In addition, only half the producers expect the GBOS to occur within two weeks of the median date calculated by the CSIRO plant growth days model GRIM. This result suggests that in the producer rules, either the rainfall quantity or the period of time over which the rain is expected, is unrealistic. Despite only 37% of beef producers indicating that they use a southern oscillation index (SOI) forecast in their decisions, cross validated LEPS (linear error in probability space) analyses showed both the average 3 month July-September SOI and the 2 month August-September SOI have significant forecast skill in predicting the probability of both the amount of wet season rainfall and the timing of the GBOS. The communication and implementation of a rigorous and realistic definition of the GBOS, and the likely impacts of anthropogenic climate change on the region are discussed in the context of the sustainable management of northern Australian rangelands.

Row spacing and planting density effects on the growth and yield of sugarcane. 1. Responses in fumigated and non-fumigated soil.

It has been reported that high-density planting of sugarcane can improve cane and sugar yield through promoting rapid canopy closure and increasing radiation interception earlier in crop growth. It is widely known that the control of adverse soil biota through fumigation (removes soil biological constraints and improves soil health) can improve cane and sugar yield. Whether the responses to high-density planting and improved soil health are additive or interactive has important implications for the sugarcane production system. Field experiments established at Bundaberg and Mackay, Queensland, Australia, involved all combinations of 2-row spacings (0.5 and 1.5 m), two planting densities (27 000 and 81 000 two-eyed setts/ha), and two soil fumigation treatments (fumigated and non-fumigated). The Bundaberg experiment had two cultivars (Q124, Q155), was fully irrigated, and harvested 15 months after planting. The Mackay experiment had one cultivar (Q117), was grown under rainfed conditions, and harvested 10 months after planting. High-density planting (81 000 setts/ha in 0.5-m rows) did not produce any more cane or sugar yield at harvest than low-density planting (27 000 setts/ha in 1.5-m rows) regardless of location, crop duration (15 v. 10 months), water supply (irrigated v. rainfed), or soil health (fumigated v. non-fumigated). Conversely, soil fumigation generally increased cane and sugar yields regardless of site, row spacing, and planting density. In the Bundaberg experiment there was a large fumigation x cultivar x density interaction (P<0.01). Cultivar Q155 responded positively to higher planting density in non-fumigated soil but not in fumigated soil, while Q124 showed a negative response to higher planting density in non-fumigated soil but no response in fumigated soil. In the Mackay experiment, Q117 showed a non-significant trend of increasing yield in response to increasing planting density in non-fumigated soil, similar to the Q155 response in non-fumigated soil at Bundaberg. The similarity in yield across the range of row spacings and planting densities within experiments was largely due to compensation between stalk number and stalk weight, particularly when fumigation was used to address soil health. Further, the different cultivars (Q124 and Q155 at Bundaberg and Q117 at Mackay) exhibited differing physiological responses to the fumigation, row spacing, and planting density treatments. These included the rate of tiller initiation and subsequent loss, changes in stalk weight, and propensity to lodging. These responses suggest that there may be potential for selecting cultivars suited to different planting configurations.

Row spacing and planting density effects on the growth and yield of sugarcane. 3. Responses with different cultivars.

The promotion of controlled traffic (matching wheel and row spacing) in the Australian sugar industry is necessitating a widening of row spacing beyond the standard 1.5 m. As all cultivars grown in the Australian industry have been selected under the standard row spacing there are concerns that at least some cultivars may not be suitable for wider rows. To address this issue, experiments were established in northern and southern Queensland in which cultivars, with different growth characteristics, recommended for each region, were grown under a range of different row configurations. In the northern Queensland experiment at Gordonvale, cultivars Q187((sic)), Q200((sic)), Q201((sic)), and Q218((sic)) were grown in 1.5-m single rows, 1.8-m single rows, 1.8-m dual rows (50 cm between duals), and 2.3-m dual rows (80 cm between duals). In the southern Queensland experiment at Farnsfield, cvv. Q138, Q205((sic)), Q222((sic)) and Q188((sic)) were also grown in 1.5-m single rows, 1.8-m single rows, 1.8-m dual rows (50 cm between duals), while 1.8-m-wide throat planted single row and 2.0-m dual row (80 cm between duals) configurations were also included. There was no difference in yield between the different row configurations at Farnsfield but there was a significant row configuration x cultivar interaction at Gordonvale due to good yields in 1.8-m single and dual rows with Q201((sic)) and poor yields with Q200((sic)) at the same row spacings. There was no significant difference between the two cultivars in 1.5-m single and 2.3-m dual rows. The experiments once again demonstrated the compensatory capacity that exists in sugarcane to manipulate stalk number and individual stalk weight as a means of producing similar yields across a range of row configurations and planting densities. There was evidence of different growth patterns between cultivars in response to different row configurations (viz. propensity to tiller, susceptibility to lodging, ability to compensate between stalk number and stalk weight), suggesting that there may be genetic differences in response to row configuration. It is argued that there is a need to evaluate potential cultivars under a wider range of row configurations than the standard 1.5-m single rows. Cultivars that perform well in row configurations ranging from 1.8 to 2.0 m are essential if the adverse effects of soil compaction are to be managed through the adoption of controlled traffic.

Row spacing and planting density effects on the growth and yield of sugarcane. 2. Strategies for the adoption of controlled traffic.

Controlled traffic (matching wheel and row spacing) is being promoted as a means to manage soil compaction in the Australian sugar industry. However, machinery limitations dictate that wider row spacings than the standard 1.5-m single row will need to be adopted to incorporate controlled traffic and many growers are reluctant to widen row spacing for fear of yield penalties. To address these concerns, contrasting row configuration and planting density combinations were investigated for their effect on cane and sugar yield in large-scale experiments in the Gordonvale, Tully, Ingham, Mackay, and Bingera (near Bundaberg) sugarcane-growing regions of Queensland, Australia. The results showed that sugarcane possesses a capacity to compensate for different row configurations and planting densities through variation in stalk number and individual stalk weight. Row configurations ranging from 1.5-m single rows (the current industry standard) to 1.8-m dual rows (50 cm between duals), 2.1-m dual (80 cm between duals) and triple ( 65 cm between triples) rows, and 2.3-m triple rows (65 cm between triples) produced similar yields. Four rows (50 cm apart) on a 2.1-m configuration (quad rows) produced lower yields largely due to crop lodging, while a 1.8-m single row configuration produced lower yields in the plant crop, probably due to inadequate resource availability (water stress/limited radiation interception). The results suggest that controlled traffic can be adopted in the Australian sugar industry by changing from a 1.5-m single row to 1.8-m dual row configuration without yield penalty. Further, the similar yields obtained with wider row configurations (2 m or greater with multiple rows) in these experiments emphasise the physiological and environmental plasticity that exists in sugarcane. Controlled traffic can be implemented with these wider row configurations (>2 m), although it will be necessary to carry out expensive modifications to the current harvester and haul-out equipment. There were indications from this research that not all cultivars were suited to configurations involving multiple rows. The results suggest that consideration be given to assessing clones with different growth habits under a range of row configurations to find the most suitable plant types for controlled traffic cropping systems.

Evaluating progress in weed eradication programs

Evaluating progress towards eradication is critically important because weed eradication programs are very expensive and may take more than 10 years to complete. The degree of confidence that can be placed in any measure of eradication progress is a function of the effort that has been invested in finding new infestations and in monitoring known infestations. Determining eradication endpoints is particularly difficult, since plants may be extremely difficult to detect when at low densities and it is virtually impossible to demonstrate seed bank exhaustion. Recent work suggests that an economic approach to this problem should be adopted. They propose some rules of thumb to determine whether to continue an eradication program or switch to an alternative management strategy.

Inter-seasonal population dynamics and pest status of Bemisia tabaci (Gennadius) biotype B in an Australian cropping system

Bemisia tabaci, biotype B, commonly known as the silverleaf whitefly (SLW) is an alien species that invaded Australia in the mid-90s. This paper reports on the invasion ecology of SLW and the factors that are likely to have contributed to the first outbreak of this major pest in an Australian cotton cropping system, population dynamics of SLW within whitefly-susceptible crop (cotton and cucurbit) and non-crop vegetation (sowthistle, Sonchus spp.) components of the cropping system were investigated over four consecutive growing seasons (September-June) 2001/02-2004/05 in the Emerald Irrigation Area (EIA) of Queensland, Australia. Based on fixed geo-referenced sampling sites, variation in spatial and temporal abundance of SLW within each system component was quantified to provide baseline data for the development of ecologically sustainable pest management strategies. Parasitism of large (3rd and 4th instars) SLW nymphs by native aphelinid wasps was quantified to determine the potential for natural control of SLW populations. Following the initial outbreak in 2001/02, SLW abundance declined and stabilised over the next three seasons. The population dynamics of SLW is characterised by inter-seasonal population cycling between the non-crop (weed) and cotton components of the EIA cropping system. Cotton was the largest sink for and source of SLW during the study period. Over-wintering populations dispersed from weed host plant sources to cotton in spring followed by a reverse dispersal in late summer and autumn to broad-leaved crops and weeds. A basic spatial source-sink analysis showed that SLW adult and nymph densities were higher in cotton fields that were closer to over-wintering weed sources throughout spring than in fields that were further away. Cucurbit fields were not significant sources of SLW and did not appear to contribute significantly to the regional population dynamics of the pest. Substantial parasitism of nymphal stages throughout the study period indicates that native parasitoid species and other natural enemies are important sources of SLW mortality in Australian cotton production systems. Weather conditions and use of broad-spectrum insecticides for pest control are implicated in the initial outbreak and on-going pest status of SLW in the region.