28 resultados para soil data requirements


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This is part of a GRDC funded project led by Dr Jeremy Whish of CSIRO Ecosystem Sciences. The project aims to build a root-lesion nematode module into the crop growth simulation program APSIM (Agricultural Production Systems Simulator). This will utilise existing nematode and crop data from field, glasshouse and laboratory research led by Dr John Thompson. New data will be collected to validate and extend the model.

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Macfadyena unguis-cati (L.) Gentry (Bignoniaceae) is a major environmental weed in coastal Queensland, Australia. There is a lack of quantitative data on its leaf chemistry and its impact on soil properties. Soils from infested vs uninfested areas, and leaves of M. unguis-cati and three co-occurring vine species (one exotic, two native) were collected at six sites (riparian and non-riparian) in south-eastern Queensland. Effects of invasion status, species, site and habitat type were examined using univariate and multivariate analyses. Habitat type had a greater effect on soil nutrients than on leaf chemistry. Invasion effect of M. unguis-cati on soil chemistry was more pronounced in non-riparian than in riparian habitat. Significantly higher values were obtained in M. unguis-cati infested (vs. uninfested) soils for ~50% of traits. Leaf ion concentrations differed significantly between exotic and native vines. Observed higher leaf-nutrient load (especially nitrogen, phosphorus and potassium) in exotic plants aligns with the preference of invasive plant species for disturbed habitats with higher nutrient input. Higher load of trace elements (aluminium, boron, cadmium and iron) in its leaves suggests that cycling of heavy-metal ions, many of which are potentially toxic at excess level, could be accelerated in soils of M. unguis-cati-invaded landscape. Although inferences from the present study are based on correlative data, the consistency of the patterns across many sites suggests that M. unguis-cati may improve soil fertility and influence nutrient cycling, perhaps through legacy effects of its own litter input.

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Loss of nitrogen in deep drainage from agriculture is an important issue for environmental and economic reasons, but limited field data is available for tropical crops. In this study, nitrogen (N) loads leaving the root zone of two major humid tropical crops in Australia, sugarcane and bananas, were measured. The two field sites, 57 km apart, had a similar soil type (a well drained Dermosol) and rainfall (∼2700 mm year -1) but contrasting crops and management. A sugarcane crop in a commercial field received 136-148 kg N ha -1 year -1 applied in one application each year and was monitored for 3 years (first to third ratoon crops). N treatments of 0-600 kg ha -1 year -1 were applied to a plant and following ratoon crop of bananas. N was applied as urea throughout the growing season in irrigation water through mini-sprinklers. Low-suction lysimeters were installed at a depth of 1 m under both crops to monitor loads of N in deep drainage. Drainage at 1 m depth in the sugarcane crops was 22-37% of rainfall. Under bananas, drainage in the row was 65% of rainfall plus irrigation for the plant crop, and 37% for the ratoon. Nitrogen leaching loads were low under sugarcane (<1-9 kg ha -1 year -1) possibly reflecting the N fertiliser applications being reasonably matched to crop requirements and at least 26 days between fertiliser application and deep drainage. Under bananas, there were large loads of N in deep drainage when N application rates were in excess of plant demand, even when applied fortnightly. The deep drainage loss of N attributable to N fertiliser, calculated by subtracting the loss from unfertilised plots, was 246 and 641 kg ha -1 over 2 crop cycles, which was equivalent to 37 and 63% of the fertiliser application for treatments receiving 710 and 1065 kg ha -1, respectively. Those rates of fertiliser application resulted in soil acidification to a depth of 0.6 m by as much as 0.6 of a unit at 0.1-0.2 m depth. The higher leaching losses from bananas indicated that they should be a priority for improved N management. Crown Copyright © 2012.

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More than 1200 wheat and 120 barley experiments conducted in Australia to examine yield responses to applied nitrogen (N) fertiliser are contained in a national database of field crops nutrient research (BFDC National Database). The yield responses are accompanied by various pre-plant soil test data to quantify plant-available N and other indicators of soil fertility status or mineralisable N. A web application (BFDC Interrogator), developed to access the database, enables construction of calibrations between relative crop yield ((Y0/Ymax) × 100) and N soil test value. In this paper we report the critical soil test values for 90% RY (CV90) and the associated critical ranges (CR90, defined as the 70% confidence interval around that CV90) derived from analysis of various subsets of these winter cereal experiments. Experimental programs were conducted throughout Australia’s main grain-production regions in different eras, starting from the 1960s in Queensland through to Victoria during 2000s. Improved management practices adopted during the period were reflected in increasing potential yields with research era, increasing from an average Ymax of 2.2 t/ha in Queensland in the 1960s and 1970s, to 3.4 t/ha in South Australia (SA) in the 1980s, to 4.3 t/ha in New South Wales (NSW) in the 1990s, and 4.2 t/ha in Victoria in the 2000s. Various sampling depths (0.1–1.2 m) and methods of quantifying available N (nitrate-N or mineral-N) from pre-planting soil samples were used and provided useful guides to the need for supplementary N. The most regionally consistent relationships were established using nitrate-N (kg/ha) in the top 0.6 m of the soil profile, with regional and seasonal variation in CV90 largely accounted for through impacts on experimental Ymax. The CV90 for nitrate-N within the top 0.6 m of the soil profile for wheat crops increased from 36 to 110 kg nitrate-N/ha as Ymax increased over the range 1 to >5 t/ha. Apparent variation in CV90 with seasonal moisture availability was entirely consistent with impacts on experimental Ymax. Further analyses of wheat trials with available grain protein (~45% of all experiments) established that grain yield and not grain N content was the major driver of crop N demand and CV90. Subsets of data explored the impact of crop management practices such as crop rotation or fallow length on both pre-planting profile mineral-N and CV90. Analyses showed that while management practices influenced profile mineral-N at planting and the likelihood and size of yield response to applied N fertiliser, they had no significant impact on CV90. A level of risk is involved with the use of pre-plant testing to determine the need for supplementary N application in all Australian dryland systems. In southern and western regions, where crop performance is based almost entirely on in-crop rainfall, this risk is offset by the management opportunity to split N applications during crop growth in response to changing crop yield potential. In northern cropping systems, where stored soil moisture at sowing is indicative of minimum yield potential, erratic winter rainfall increases uncertainty about actual yield potential as well as reducing the opportunity for effective in-season applications.

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Soil testing is the most widely used tool to predict the need for fertiliser phosphorus (P) application to crops. This study examined factors affecting critical soil P concentrations and confidence intervals for wheat and barley grown in Australian soils by interrogating validated data from 1777 wheat and 150 barley field treatment series now held in the BFDC National Database. To narrow confidence intervals associated with estimated critical P concentrations, filters for yield, crop stress, or low pH were applied. Once treatment series with low yield (<1 t/ha), severe crop stress, or pHCaCl2 <4.3 were screened out, critical concentrations were relatively insensitive to wheat yield (>1 t/ha). There was a clear increase in critical P concentration from early trials when full tillage was common compared with those conducted in 1995–2011, which corresponds to a period of rapid shift towards adoption of minimum tillage. For wheat, critical Colwell-P concentrations associated with 90 or 95% of maximum yield varied among Australian Soil Classification (ASC) Orders and Sub-orders: Calcarosol, Chromosol, Kandosol, Sodosol, Tenosol and Vertosol. Soil type, based on ASC Orders and Sub-orders, produced critical Colwell-P concentrations at 90% of maximum relative yield from 15 mg/kg (Grey Vertosol) to 47 mg/kg (Supracalcic Calcarosols), with other soils having values in the range 19–27 mg/kg. Distinctive differences in critical P concentrations were evident among Sub-orders of Calcarosols, Chromosols, Sodosols, Tenosols, and Vertosols, possibly due to differences in soil properties related to P sorption. However, insufficient data were available to develop a relationship between P buffering index (PBI) and critical P concentration. In general, there was no evidence that critical concentrations for barley would be different from those for wheat on the same soils. Significant knowledge gaps to fill to improve the relevance and reliability of soil P testing for winter cereals were: lack of data for oats; the paucity of treatment series reflecting current cropping practices, especially minimum tillage; and inadequate metadata on soil texture, pH, growing season rainfall, gravel content, and PBI. The critical concentrations determined illustrate the importance of recent experimental data and of soil type, but also provide examples of interrogation pathways into the BFDC National Database to extract locally relevant critical P concentrations for guiding P fertiliser decision-making in wheat and barley.

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Understanding the life-history attributes of aquatic species is integral to the development of environmental-flow strategies in regulated river systems. This is particularly important when species are under continual and increasing pressure from water-resource development. In this study, the water temperature and flow requirements for spawning of the Fitzroy River golden perch (Macquaria ambigua oriens) were investigated over 4 years at 22 sites in the Fitzroy River catchment. Eggs, larvae and young-of-year (YOY) M. ambigua oriens were sampled on a variety of flow events to determine the environmental requirements for spawning. Eggs and larvae of M. ambigua oriens were detected during natural flow events generally with a minimum of 1.5 m river rise and duration of 7 days. Spawning was associated with the peak and/or recession of the first or second post-winter flow event where water temperatures exceeded 248 degrees C. Our data suggests that it is important to protect a range of flows, not just flood flows, as previously documented for this species. The interaction of spawning flows with existing and future water-resource development should be considered to ensure maintenance of the population viability of M. ambigua oriens.

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The influence of grazing management on total soil organic carbon (SOC) and soil total nitrogen (TN) in tropical grasslands is an issue of considerable ecological and economic interest. Here we have used linear mixed models to investigate the effect of grazing management on stocks of SOC and TN in the top 0.5 m of the soil profile. The study site was a long-term pasture utilization experiment, 26 years after the experiment was established for sheep grazing on native Mitchell grass (Astrebla spp.) pasture in northern Australia. The pasture utilization rates were between 0% (exclosure) and 80%, assessed visually. We found that a significant amount of TN had been lost from the top 0.1 m of the soil profile as a result of grazing, with 80% pasture utilization resulting in a loss of 84 kg ha−1 over the 26-year period. There was no significant effect of pasture utilization rate on TN when greater soil depths were considered. There was no significant effect of pasture utilization rate on stocks of SOC and soil particulate organic carbon (POC), or the C:N ratio at any depth; however, visual trends in the data suggested some agreement with the literature, whereby increased grazing pressure appeared to: (i) decrease SOC and POC stocks; and, (ii) increase the C:N ratio. Overall, the statistical power of the study was limited, and future research would benefit from a more comprehensive sampling scheme. Previous studies at the site have found that a pasture utilization rate of 30% is sustainable for grazing production on Mitchell grass; however, given our results, we conclude that N inputs (possibly through management of native N2-fixing pasture legumes) should be made for long-term maintenance of soil health, and pasture productivity, within this ecosystem.

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A significantly increased water regime can lead to inundation of rivers, creeks and surrounding floodplains- and thus impact on the temporal dynamics of both the extant vegetation and the dormant, but viable soil-seed bank of riparian corridors. The study documented changes in the soil seed-bank along riparian corridors before and after a major flood event in January 2011 in southeast Queensland, Australia. The study site was a major river (the Mooleyember creek) near Roma, Central Queensland impacted by the extreme flood event and where baseline ecological data on riparian seed-bank populations have previously been collected in 2007, 2008 and 2009. After the major flood event, we collected further soil samples from the same locations in spring/summer (November–December 2011) and in early autumn (March 2012). Thereafter, the soils were exposed to adequate warmth and moisture under glasshouse conditions, and emerged seedlings identified taxonomically. Flooding increased seed-bank abundance but decreased its species richness and diversity. However, flood impact was less than that of yearly effect but greater than that of seasonal variation. Seeds of trees and shrubs were few in the soil, and were negatively affected by the flood; those of herbaceous and graminoids were numerous and proliferate after the flood. Seed-banks of weedy and/or exotic species were no more affected by the flood than those of native and/or non-invasive species. Overall, the studied riparian zone showed evidence of a quick recovery of its seed-bank over time, and can be considered to be resilient to an extreme flood event.

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Vegetable cropping systems are often characterised by high inputs of nitrogen fertiliser. Elevated emissions of nitrous oxide (N2O) can be expected as a consequence. In order to mitigate N2O emissions from fertilised agricultural fields, the use of nitrification inhibitors, in combination with ammonium based fertilisers, has been promoted. However, no data is currently available on the use of nitrification inhibitors in sub-tropical vegetable systems. A field experiment was conducted to investigate the effect of the nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP) on N2O emissions and yield from broccoli production in sub-tropical Australia. Soil N2O fluxes were monitored continuously (3 h sampling frequency) with fully automated, pneumatically operated measuring chambers linked to a sampling control system and a gas chromatograph. Cumulative N2O emissions over the 5 month observation period amounted to 298 g-N/ha, 324 g-N/ha, 411 g-N/ha and 463 g-N/ha in the conventional fertiliser (CONV), the DMPP treatment (DMPP), the DMMP treatment with a 10% reduced fertiliser rate (DMPP-red) and the zero fertiliser (0N), respectively. The temporal variation of N2O fluxes showed only low emissions over the broccoli cropping phase, but significantly elevated emissions were observed in all treatments following broccoli residues being incorporated into the soil. Overall 70–90% of the total emissions occurred in this 5 weeks fallow phase. There was a significant inhibition effect of DMPP on N2O emissions and soil mineral N content over the broccoli cropping phase where the application of DMPP reduced N2O emissions by 75% compared to the standard practice. However, there was no statistical difference between the treatments during the fallow phase or when the whole season was considered. This study shows that DMPP has the potential to reduce N2O emissions from intensive vegetable systems, but also highlights the importance of post-harvest emissions from incorporated vegetable residues. N2O mitigation strategies in vegetable systems need to target these post-harvest emissions and a better evaluation of the effect of nitrification inhibitors over the fallow phase is needed.

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Sustainable management of native pastures requires an understanding of what the bounds of pasture composition, cover and soil surface condition are for healthy pastoral landscapes to persist. A survey of 107 Aristida/Bothriochloa pasture sites in inland central Queensland was conducted. The sites were chosen for their current diversity of tree cover, apparent pasture condition and soil type to assist in setting more objective bounds on condition ‘states’ in such pastures. Assessors’ estimates of pasture condition were strongly correlated with herbage mass (r = 0.57) and projected ground cover (r = 0. 58), and moderately correlated with pasture crown cover (r = 0.35) and tree basal area (r = 0.32). Pasture condition was not correlated with pasture plant density or the frequency of simple guilds of pasture species. The soil type of Aristida/Bothriochloa pasture communities was generally hard-setting, low in cryptogam cover but moderately covered with litter and projected ground cover (30–50%). There was no correlation between projected ground cover of pasture and estimated ground-level cover of plant crowns. Tree basal area was correlated with broad categories of soil type, probably because greater tree clearing has occurred on the more fertile, heavy-textured clay soils. Of the main perennial grasses, some showed strong soil preferences, for example Tripogon loliiformis for hard-setting soils and Dichanthium sericeum for clays. Common species, such as Chrysopogon fallax and Heteropogon contortus, had no strong soil preference. Wiregrasses (Aristida spp.) tended to be uncommon at both ends of the estimated pasture condition scale whereas H. contortus was far more common in pastures in good condition. Sedges (Cyperaceae) were common on all soil types and for all pasture condition ratings. Plants identified as increaser species were Tragus australianus, daisies (Asteraceae) and potentially toxic herbaceous legumes such as Indigofera spp. and Crotalaria spp. Pasture condition could not be reliably predicted based on the abundance of a single species or taxon but there may be scope for using integrated data for four to five ecologically contrasting plants such as Themeda triandra with daisies, T. loliiformis and flannel weeds (Malvaceae).

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Increasing organic carbon inputs to agricultural soils through the use of pastures or crop residues has been suggested as a means of restoring soil organic carbon lost via anthropogenic activities, such as land use change. However, the decomposition and retention of different plant residues in soil, and how these processes are affected by soil properties and nitrogen fertiliser application, is not fully understood. We evaluated the rate and extent of decomposition of 13C-pulse labelled plant material in response to nitrogen addition in four pasture soils of varying physico-chemical characteristics. Microbial respiration of buffel grass (Cenchrus ciliaris L.), wheat (Triticum aestivum L.) and lucerne (Medicago sativa L.) residues was monitored over 365-days. A double exponential model fitted to the data suggested that microbial respiration occurred as an early rapid and a late slow stage. A weighted three-compartment mixing model estimated the decomposition of both soluble and insoluble plant 13C (mg C kg−1 soil). Total plant material decomposition followed the alkyl C: O-alkyl C ratio of plant material, as determined by solid-state 13C nuclear magnetic resonance spectroscopy. Urea-N addition increased the decomposition of insoluble plant 13C in some soils (≤0.1% total nitrogen) but not others (0.3% total nitrogen). Principal components regression analysis indicated that 26% of the variability of plant material decomposition was explained by soil physico-chemical characteristics (P = 0.001), which was primarily described by the C:N ratio. We conclude that plant species with increasing alkyl C: O-alkyl C ratio are better retained as soil organic matter, and that the C:N stoichiometry of soils determines whether N addition leads to increases in soil organic carbon stocks.

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The Brigalow Belt bioregion of southern and central Queensland supports a large percentage of northern Australia's sown pastures and beef herd. The Brigalow soils were widely thought to have adequate phosphorus (P) for cropping, sown pastures and grazing animals, which has led to almost no use of P fertiliser on sown pastures. The majority of pastures established in the region were sown with tropical grasses only (i.e. no legumes were sown). Under grass-only pastures, nitrogen (N) mineralisation rates decline with time since establishment as N is 'tied-up' in soil organic matter. This process leads to a significant decline in pasture and animal productivity and is commonly called 'pasture rundown'. Incorporating pasture legumes has been identified as the best long-term solution to improve the productivity of rundown sown grass pastures. Pasture legumes require adequate P to grow well and fix large amounts of N to increase the productivity of rundown sown grass pastures. Producers and farm advisors have traditionally thought that P fertiliser is not cost-effective for legume-based improved pastures growing on inland areas of Queensland despite there being little, if any, data on production responses or their economic outcomes. Recent studies show large and increasing areas of low plant available soil P and large responses by pasture legumes to P fertiliser on Brigalow soils. The economic analysis in this scoping study indicates potential returns of 9–15% on extra funds invested from the application of P fertiliser, when establishing legumes into grass pastures on low P soils (i.e. lower than the critical P requirement of the legume grown). Higher returns of 12–24% may be possible when adding P fertiliser to already established grass/legume pastures on such soils. As these results suggest potential for significant returns from applying P fertiliser on legume pastures, it is recommended that research be conducted to better quantify the impacts of P fertiliser on productivity and profit. Research priorities include: quantifying the animal production and economic impact of fertilising legume-based pastures in the sub-tropics for currently used legumes; quantifying the comparative P requirements and responses of available legume varieties; understanding clay soil responses to applied P fertiliser; testing the P status of herds grazing in the Brigalow Belt; and quantifying the extent of other nutrient deficiencies (e.g. sulphur and potassium) for legume based pastures. Development and extension activities are required to demonstrate the commercial impacts of applying P fertiliser to legume based pastures.

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Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising methodology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.