110 resultados para Cultivation without soil


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Thirty-seven surface (0-0.10 or 0-0.20 m) soils covering a wide range of soil types (16 Vertosols, 6 Ferrosols, 6 Dermosols, 4 Hydrosols, 2 Kandosols, 1 Sodosol, 1 Rudosol, and 1 Chromosol) were exhaustively cropped in 2 glasshouse experiments. The test species were Panicum maximum cv. Green Panic in Experiment A and Avena sativa cv. Barcoo in Experiment B. Successive forage harvests were taken until the plants could no longer grow in most soils because of severe potassium (K) deficiency. Soil samples were taken prior to cropping and after the final harvest in both experiments, and also after the initial harvest in Experiment B. Samples were analysed for solution K, exchangeable K (Exch K), tetraphenyl borate extractable K for extraction periods of 15 min (TBK15) and 60 min (TBK60), and boiling nitric acid extractable K (Nitric K). Inter-correlations between the initial levels of the various soil K parameters indicated that the following pools were in sequential equilibrium: solution K, Exch K, fast release fixed K [estimated as (TBK15-Exch K)], and slow release fixed K [estimated as (TBK60-TBK15)]. Structural K [estimated as (Nitric K-TBK60)] was not correlated with any of the other pools. However, following exhaustive drawdown of soil K by cropping, structural K became correlated with solution K, suggesting dissolution of K minerals when solution K was low. The change in the various K pools following cropping was correlated with K uptake at Harvest 1 ( Experiment B only) and cumulative K uptake ( both experiments). The change in Exch K for 30 soils was linearly related to cumulative K uptake (r = 0.98), although on average, K uptake was 35% higher than the change in Exch K. For the remaining 7 soils, K uptake considerably exceeded the change in Exch K. However, the changes in TBK15 and TBK60 were both highly linearly correlated with K uptake across all soils (r = 0.95 and 0.98, respectively). The slopes of the regression lines were not significantly different from unity, and the y-axis intercepts were very small. These results indicate that the plant is removing K from the TBK pool. Although the change in Exch K did not consistently equate with K uptake across all soils, initial Exch K was highly correlated with K uptake (r = 0.99) if one Vertosol was omitted. Exchangeable K is therefore a satisfactory diagnostic indicator of soil K status for the current crop. However, the change in Exch K following K uptake is soil-dependent, and many soils with large amounts of TBK relative to Exch K were able to buffer changes in Exch K. These soils tended to be Vertosols occurring on floodplains. In contrast, 5 soils (a Dermosol, a Rudosol, a Kandosol, and 2 Hydrosols) with large amounts of TBK did not buffer decreases in Exch K caused by K uptake, indicating that the TBK pool in these soils was unavailable to plants under the conditions of these experiments. It is likely that K fertiliser recommendations will need to take account of whether the soil has TBK reserves, and the availability of these reserves, when deciding rates required to raise exchangeable K status to adequate levels.

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Highly productive sown pasture systems can result in high growth rates of beef cattle and lead to increases in soil nitrogen and the production of subsequent crops. The nitrogen dynamics and growth of grain sorghum following grazed annual legume leys or a grass pasture were investigated in a no-till system in the South Burnett district of Queensland. Two years of the tropical legumes Macrotyloma daltonii and Vigna trilobata (both self regenerating annual legumes) and Lablab purpureus (a resown annual legume) resulted in soil nitrate N (0-0.9 m depth), at sorghum sowing, ranging from 35 to 86 kg/ha compared with 4 kg/ha after pure grass pastures. Average grain sorghum production in the 4 cropping seasons following the grazed legume leys ranged from 2651 to 4012 kg/ha. Following the grass pasture, grain sorghum production in the first and second year was < 1900 kg/ha and by the third year grain yield was comparable to the legume systems. Simulation studies utilising the farming systems model APSIM indicated that the soil N and water dynamics following 2-year ley phases could be closely represented over 4 years and the prediction of sorghum growth during this time was reasonable. In simulated unfertilised sorghum crops grown from 1954 to 2004, grain yield did not exceed 1500 kg/ha in 50% of seasons following a grass pasture, while following 2-year legume leys, grain exceeded 3000 kg/ha in 80% of seasons. It was concluded that mixed farming systems that utilise short term legume-based pastures for beef production in rotation with crop production enterprises can be highly productive.

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The effects of inorganic amendments (fertilisers and pesticides) on soil biota that are reported in the scientific literature are, to say the least, variable. Though there is clear evidence that certain products can have significant impacts, the effects can be positive or negative. This is not surprising when you consider the number of organisms and amount of different functional groups, the number of products and various rates at which they could be applied, the methods of application and the environmental differences that occur in soil at a micro scale (within centimetres) in a paddock, let alone between paddocks, farms, catchments, regions etc. It therefore becomes extremely difficult to draw definitive conclusions from the reported results in order to summarise the impacts of these inputs. Several research trials and review papers have been published on this subject and most similarly conclude that the implications of many of the effects are still uncertain.

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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.

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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.

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Measurement or accurate simulation of soil temperature is important for improved understanding and management of peanuts (Arachis hypogaea L.), due to their geocarpic habit. A module of the Agricultural Production Systems Simulator Model (APSIM), APSIM-soiltemp, which uses input of ambient temperature, rainfall and solar radiation in conjunction with other APSIM modules, was evaluated for its ability to simulate surface 5 cm soil temperature in 35 peanut on-farm trials conducted between 2001 and 2005 in the Burnett region (25°36'S to 26°41'S, 151°39'E to 151°53'E). Soil temperature simulated by the APSIM-soiltemp module, from 30 days after sowing until maturity, closely matched the measured values (R2 ≥ 0.80)in the first three seasons (2001-04). However, a slightly poorer relationship (R2 = 0.55) between the observed and the simulated temperatures was observed in 2004-05, when the crop was severely water stressed. Nevertheless, over all the four seasons, which were characterised by a range of ambient temperature, leaf area index, radiation and soil water, each of which was found to have significant effects on soil temperature, a close 1:1 relationship (R2 = 0.85) between measured and simulated soil temperatures was observed. Therefore, the pod zone soil temperature simulated by the module can be generally relied on in place of measured input of soil temperature in APSIM applications, such as quantifying climatic risk of aflatoxin accumulation.

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Soils with high levels of chloride and/or sodium in their subsurface layers are often referred to as having subsoil constraints (SSCs). There is growing evidence that SSCs affect wheat yields by increasing the lower limit of a crop's available soil water (CLL) and thus reducing the soil's plant-available water capacity (PAWC). This proposal was tested by simulation of 33 farmers' paddocks in south-western Queensland and north-western New South Wales. The simulated results accounted for 79% of observed variation in grain yield, with a root mean squared deviation (RMSD) of 0.50 t/ha. This result was as close as any achieved from sites without SSCs, thus providing strong support for the proposed mechanism that SSCs affect wheat yields by increasing the CLL and thus reducing the soil's PAWC. In order to reduce the need to measure CLL of every paddock or management zone, two additional approaches to simulating the effects of SSCs were tested. In the first approach the CLL of soils was predicted from the 0.3-0.5 m soil layer, which was taken as the reference CLL of a soil regardless of its level of SSCs, while the CLL values of soil layers below 0.5 m depth were calculated as a function of these soils' 0.3-0.5 m CLL values as well as of soil depth plus one of the SSC indices EC, Cl, ESP, or Na. The best estimates of subsoil CLL values were obtained when the effects of SSCs were described by an ESP-dependent function. In the second approach, depth-dependent CLL values were also derived from the CLL values of the 0.3-0.5 m soil layer. However, instead of using SSC indices to further modify CLL, the default values of the water-extraction coefficient (kl) of each depth layer were modified as a function of the SSC indices. The strength of this approach was evaluated on the basis of correlation of observed and simulated grain yields. In this approach the best estimates were obtained when the default kl values were multiplied by a Cl-determined function. The kl approach was also evaluated with respect to simulated soil moisture at anthesis and at grain maturity. Results using this approach were highly correlated with soil moisture results obtained from simulations based on the measured CLL values. This research provides strong evidence that the effects of SSCs on wheat yields are accounted for by the effects of these constraints on wheat CLL values. The study also produced two satisfactory methods for simulating the effects of SSCs on CLL and on grain yield. While Cl and ESP proved to be effective indices of SSCs, EC was not effective due to the confounding effect of the presence of gypsum in some of these soils. This study provides the tools necessary for investigating the effects of SSCs on wheat crop yields and natural resource management (NRM) issues such as runoff, recharge, and nutrient loss through simulation studies. It also facilitates investigation of suggested agronomic adaptations to SSCs.

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To protect terrestrial ecosystems and humans from contaminants many countries and jurisdictions have developed soil quality guidelines (SQGs). This study proposes a new framework to derive SQGs and guidelines for amended soils and uses a case study based on phytotoxicity data of copper (Cu) and zinc (Zn) from field studies to illustrate how the framework could be applied. The proposed framework uses normalisation relationships to account for the effects of soil properties on toxicity data followed by a species sensitivity distribution (SSD) method to calculate a soil added contaminant limit (soil ACL) for a standard soil. The normalisation equations are then used to calculate soil ACLs for other soils. A soil amendment availability factor (SAAF) is then calculated as the toxicity and bioavailability of pure contaminants and contaminants in amendments can be different. The SAAF is used to modify soil ACLs to ACLs for amended soils. The framework was then used to calculate soil ACLs for copper (Cu) and zinc (Zn). For soils with pH of 4-8 and OC content of 1-6%, the ACLs range from 8 mg/kg to 970 mg/kg added Cu. The SAAF for Cu was pH dependant and varied from 1.44 at pH 4 to 2.15 at pH 8. For soils with pH of 4-8 and OC content of 1-6%, the ACLs for amended soils range from 11 mg/kg to 2080 mg/kg added Cu. For soils with pH of 4-8 and a CEC from 5-60, the ACLs for Zn ranged from 21 to 1470 mg/kg added Zn. A SAAF of one was used for Zn as it concentrations in plant tissue and soil to water partitioning showed no difference between biosolids and soluble Zn salt treatments, indicating that Zn from biosolids and Zn salts are equally bioavailable to plants.

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An experiment using herds of similar to 20 cows (farmlets) assessed the effects of high stocking rates on production and profitability of feeding systems based on dryland and irrigated perennial ryegrass-based pastures in a Mediterranean environment in South Australia over 4 years. A target level of milk production of 7000 L/cow.year was set, based on predicted intakes of 2.7 t DM/cow.year as concentrates, pasture intakes from 1.5 to 2.7 t/cow.year and purchased fodder. In years 1 and 2, up to 1.5 t DM/cow.year of purchased fodder was used and in years 3 and 4 the amounts were increased if necessary to enable levels of milk production per cow to be maintained at target levels. Cows in dryland farmlets calved in March to May inclusive and were stocked at 2.5, 2.9, 3.3, 3.6 and 4.1 cows/ha, while those in irrigated farmlets calved in August to October inclusive and were stocked at 4.1, 5.2, 6.3 and 7.4 cows/ha. In the first 2 years, when inputs of purchased fodder were limited, milk production per cow was reduced with higher stocking rates (P < 0.01), but in years 3 and 4 there were no differences. Mean production was 7149 kg/cow.year in years 1 and 2, and 8162 kg/cow.year in years 3 and 4. Production per hectare was very closely related to stocking rate in all years (P < 0.01), increasing from 18 to 34 t milk/ha.year for dryland farmlets (1300 to 2200 kg milk solids/ha) and from 30 to 60 t milk/ha.year for irrigated farmlets (2200 to 4100 kg milk solids/ha). Almost all of these increases were attributed to the increases in grain and purchased fodder inputs associated with the increases in stocking rate. Net pasture accumulation rates and pasture harvest were generally not altered with stocking rate, though as stocking rate increased there was a change to more of the pasture being grazed and less conserved in both dryland and irrigated farmlets. Total pasture harvest averaged similar to 8 and 14 t DM/ha.year for dryland and irrigated pastures, respectively. An exception was at the highest stocking rate under irrigation, where pugging during winter was associated with a 14% reduction in annual pasture growth. There were several indications that these high stocking rates may not be sustainable without substantial changes in management practice. There were large and positive nutrient balances and associated increases in soil mineral content (P < 0.01), especially for phosphorus and nitrate nitrogen, with both stocking rate and succeeding years. Levels under irrigation were considerably higher (up to 90 and 240 mg/kg of soil for nitrate nitrogen and phosphorus, respectively) than under dryland pastures (60 and 140 mg/kg, respectively). Soil organic carbon levels did not change with stocking rate, indicating a high level of utilisation of forage grown. Weed ingress was also high (to 22% DM) in all treatments and especially in heavily stocked irrigated pastures during winter. It was concluded the higher stocking rates used exceeded those that are feasible for Mediterranean pastures in this environment and upper levels of stocking are suggested to be 2.5 cows/ha for dryland pastures and 5.2 cows/ha for irrigated pastures. To sustain these suggested stocking rates will require further development of management practices to avoid large increases in soil minerals and weed invasion of pastures.

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A guide to better soil, water and nutrient management practices for the south east Queensland strawberry industry.

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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.

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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.

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To investigate the effects of soil type on seed persistence in a manner that controlled for location and climate variables, three weed species—Gomphocarpus physocarpus (swan plant), Avena sterilis ssp. ludoviciana (wild oat) and Ligustrum lucidum (broadleaf privet)—were buried for 21 months in three contrasting soils at a single location. Soil type had a significant effect on seed persistence and seedling vigour, but soil water content and temperature varied between soils due to differences in physical and chemical properties. Warmer, wetter conditions favoured shorter persistence. A laboratory-based test was developed to accelerate the rate of seed ageing within soils, using controlled superoptimal temperature and moisture conditions (the soil-specific accelerated ageing test, SSAAT). The SSAAT demonstrated that soil type per se did not influence seed longevity. Moreover, the order in which seeds aged was the same whether aged in the field or SSAAT, with L. lucidum being shortest-lived and A. sterilis being longest-lived of the three species.

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We investigated aspects of the reproductive ecology of Ochna serrulata (Hochst.) Walp., an invasive plant in eastern Australia. O. serrulata drupes were similar in size to fleshy fruits of other local invasive plants, but showed some distinct differences in quality, with a very high pulp lipid content (32.8% of dry weight), and little sugar and water. Seeds were dispersed by figbirds, Sphecotheres viridis Vieillot, a locally abundant frugivore, and comprised between 10 and 50% of all non-Ficus spp. fruit consumed during October and November. The rate of removal of O. serrulata drupes was greater in bushland than suburban habitats, indicating that control in bushland habitats should be a priority, but also that suburban habitats are likely to act as significant seed sources for reinvasion of bushland. Germination occurred under all seed-processing treatments (with and without pulp, and figbird gut passage), suggesting that although frugivores are important for dispersal, they are not essential for germination. Recruitment of buried and surface-sown seed differed between greenhouse and field experiments, with minimal recruitment of surface-sown seed in the field. Seed persistence was low, particularly under field conditions, with 0.75% seed viability after 6 months and 0% at 12 months. This provides an opportunity to target control efforts in south-eastern Queensland in spring before fruit set, when there is predicted to be few viable seeds in the soil.

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An assessment of the relative influences of management and environment on the composition of floodplain grasslands of north-western New South Wales was made using a regional vegetation survey sampling a range of land tenures (e. g. private property, travelling stock routes and nature reserves). A total of 364 taxa belonging to 55 different plant families was recorded. Partitioning of variance with redundancy analysis determined that environmental variables accounted for a greater proportion (61.3%) of the explained variance in species composition than disturbance-related variables (37.6%). Soil type (and fertility), sampling time and rainfall had a strong influence on species composition and there were also east-west variations in composition across the region. Of the disturbance-related variables, cultivation, stocking rate and flooding frequency were all influential. Total, native, forb, shrub and subshrub richness were positively correlated with increasing time since cultivation. Flood frequency was positively correlated with graminoid species richness and was negatively correlated with total and forb species richness. Site species richness was also influenced by environmental variables (e. g. soil type and rainfall). Despite the resilience of these grasslands, some forms of severe disturbance (e. g. several years of cultivation) can result in removal of some dominant perennial grasses (e. g. Astrebla spp.) and an increase in disturbance specialists. A simple heuristic transitional model is proposed that has conceptual thresholds for plant biodiversity status. This knowledge representation may be used to assist in the management of these grasslands by defining four broad levels of community richness and the drivers that change this status.