89 resultados para Soil attributes


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Salinity, sodicity, acidity, and phytotoxic levels of chloride (Cl) in subsoils are major constraints to crop production in many soils of north-eastern Australia because they reduce the ability of crop roots to extract water and nutrients from the soil. The complex interactions and correlations among soil properties result in multi-colinearity between soil properties and crop yield that makes it difficult to determine which constraint is the major limitation. We used ridge-regression analysis to overcome colinearity to evaluate the contribution of soil factors and water supply to the variation in the yields of 5 winter crops on soils with various levels and combinations of subsoil constraints in the region. Subsoil constraints measured were soil Cl, electrical conductivity of the saturation extract (ECse), and exchangeable sodium percentage (ESP). The ridge regression procedure selected several of the variables used in a descriptive model, which included in-crop rainfall, plant-available soil water at sowing in the 0.90-1.10 m soil layer, and soil Cl in the 0.90-1.10 m soil layer, and accounted for 77-85% of the variation in the grain yields of the 5 winter crops. Inclusion of ESP of the top soil (0.0-0.10 m soil layer) marginally increased the descriptive capability of the models for bread wheat, barley and durum wheat. Subsoil Cl concentration was found to be an effective substitute for subsoil water extraction. The estimates of the critical levels of subsoil Cl for a 10% reduction in the grain yield were 492 mg cl/kg for chickpea, 662 mg Cl/kg for durum wheat, 854 mg Cl/kg for bread wheat, 980 mg Cl/kg for canola, and 1012 mg Cl/kg for barley, thus suggesting that chickpea and durum wheat were more sensitive to subsoil Cl than bread wheat, barley, and canola.

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The fate of nitrogen (N) applied in biosolids was investigated in a forage production system on an alluvial clay loam soil in south-eastern Queensland, Australia. Biosolids were applied in October 2002 at rates of 6, 12, 36, and 54dryt/ha for aerobically digested biosolids (AE) and 8, 16, 48, and 72dryt/ha for anaerobically digested biosolids (AN). Rates were based on multiples of the Nitrogen Limited Biosolids Application rate (0.5, 1, 3, and 4.5NLBAR) for each type of biosolid. The experiment included an unfertilised control and a fertilised control that received multiple applications of synthetic fertiliser. Forage sorghum was planted 1 week after biosolids application and harvested 4 times between December 2002 and May 2003. Dry matter production was significantly greater from the biosolids-treated plots (21-27t/ha) than from the unfertilised (16t/ha) and fertilised (18t/ha) controls. The harvested plant material removed an extra 148-488kg N from the biosolids-treated plots. Partial N budgets were calculated for the 1NLBAR and 4.5NLBAR treatments for each biosolids type at the end of the crop season. Crop removal only accounted for 25-33% of the applied N in the 1NLBAR treatments and as low as 8-15% with 4.5NLBAR. Residual biosolids N was predominantly in the form of organic N (38-51% of applied biosolids N), although there was also a significant proportion (10-23%) as NO3-N, predominantly in the top 0.90m of the soil profile. From 12 to 29% of applied N was unaccounted for, and presumed to be lost as gaseous nitrogen and/or ammonia, as a consequence of volatilisation or denitrification, respectively. In-season mineralisation of organic N in biosolids was 43-59% of the applied organic N, which was much greater than the 15% (AN)-25% (AE) expected, based on current NLBAR calculation methods. Excessive biosolids application produced little additional biomass but led to high soil mineral N concentrations that were vulnerable to multiple loss pathways. Queensland Guidelines need to account for higher rates of mineralisation and losses via denitrification and volatilisation and should therefore encourage lower application rates to achieve optimal plant growth and minimise the potential for detrimental impacts on the environment.

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The first larval instar has been identified as a critical stage for population mortality in Lepidoptera, yet due to the body size of these larvae, the factors that contribute to mortality under field conditions are still not clear. Dispersal behaviour has been suggested as a significant, but ignored factor contributing to mortality in first-instar lepidopteran larvae. The impact that leaving the host plant has on the mortality rate of Helicoverpa armigera neonates was examined in field crops and laboratory trials. In this study the following are examined: (1) the effects of soil surface temperature, and the level of shade within the crop, on the mortality of neonates on the soil after dropping off from the host plant; (2) the percentage of neonates that dropped off from a host plant and landed on the soil; and (3) the effects of exposure to different soil surface temperatures on the development and mortality of neonates. The findings of this study showed that: (1) on the soil, surface temperatures above 43°C were lethal for neonates, and exposure to these temperatures contributed greatly to the overall mortality rate observed; however, the fate of neonates on the soil varied significantly depending on canopy closure within the crop; (2) at least 15% of neonates dropped off from the host plant and landed on the soil, meaning that the proportion of neonates exposed to these condition is not trivial; and (3) 30 min exposure to soil surface temperatures approaching the lethal level (>43°C) has no significant negative effects on the development and mortality of larvae through to the second instar. Overall leaving the plant through drop-off contributes to first-instar mortality in crops with open canopies; however, survival of neonates that have lost contact with a host plant is possible, and becomes more likely later in the crop growing season.

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One of the pathways for transfer of cadmium (Cd) through the food chain is addition of urban wastewater solids (biosolids) to soil, and many countries have restrictions on biosolid use to minimize crop Cd contamination. The basis of these restrictions often lies in laboratory or glasshouse experimentation of soil-plant transfer of Cd, but these studies are confounded by artefacts from growing crops in controlled laboratory conditions. This study examined soil to plant (wheat grain) transfer of Cd under a wide range of field environments under typical agronomic conditions, and compared the solubility and bioavailability of Cd in biosolids to soluble Cd salts. Solubility of biosolid Cd (measured by examining Cd partitioning between soil and soil solution) was found to be equal to or greater than that of soluble Cd salts, possibly due to competing ions added with the biosolids. Conversely, bioavailability of Cd to wheat and transfer to grain was less than that of soluble Cd salts, possibly due to addition of Zn with the biosolids, causing reduced plant uptake or grain loading, or due to complexation of soluble Cd2+ by dissolved organic matter.

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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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Information on the effects of growing cotton (Gossypium hirsutum L.)-based crop rotations on soil quality of dryland Vertisols is sparse. The objective of this study was to quantify the effects of growing cereal and leguminous crops in rotation with dryland cotton on physical and chemical properties of a grey Vertisol near Warra, SE Queensland, Australia. The experimental treatments, selected after consultations with local cotton growers, were continuous cotton (T1), cotton-sorghum (Sorghum bicolor (L.) Moench.) (T2), cotton-wheat (Triticum aestivum L.) double cropped (T3), cotton-chickpea (Cicer arietinum L.) double cropped followed by wheat (T4) and cotton-wheat (T5). From 1993 to 1996 land preparation was by chisel ploughing to about 0.2 m followed by two to four cultivations with a Gyral tyne cultivator. Thereafter all crops were sown with zero tillage except for cultivation with a chisel plough to about 0.07-0.1 m after cotton picking to control heliothis moth pupae. Soil was sampled from 1996 to 2004 and physical (air-filled porosity of oven-dried soil, an indicator of soil compaction; plastic limit; linear shrinkage; dispersion index) and chemical (pH in 0.01 M CaCl2, organic carbon, exchangeable Ca, Mg, K and Na contents) properties measured. Crop rotation affected soil properties only with respect to exchangeable Na content and air-filled porosity. In the surface 0.15 m during 2000 and 2001 lowest air-filled porosity occurred with T1 (average of 34.6 m3/100 m3) and the highest with T3 (average of 38.9 m3/100 m3). Air-filled porosity decreased in the same depth between 1997 and 1998 from 45.0 to 36.1 m3/100 m3, presumably due to smearing and compaction caused by shallow cultivation in wet soil. In the subsoil, T1 and T2 frequently had lower air-filled porosity values in comparison with T3, T4 and T5, particularly during the early stages of the experiment, although values under T1 increased subsequently. In general, compaction was less under rotations which included a wheat crop (T3, T4, T5). For example, average air-filled porosity (in m3/100 m3) in the 0.15-0.30 m depth from 1996 to 1999 was 19.8 with both T1 and T2, and 21.2 with T3, 21.1 with T4 and 21.5 with T5. From 2000 to 2004, average air-filled porosity (in m3/100 m3) in the same depth was 21.3 with T1, 19.0 with T2, 19.8 with T3, 20.0 with T4 and 20.5 with T5. The rotation which included chickpea (T4) resulted in the lowest exchangeable Na content, although differences among rotations were small. Where only a cereal crop with a fibrous root system was sown in rotation with cotton (T2, T3, T5) linear shrinkage in the 0.45-0.60 m depth was lower than in rotations, which included tap-rooted crops such as chickpea (T4) or continuous cotton (T1). Dispersion index and organic carbon decreased, and plastic limit increased with time. Soil organic carbon stocks decreased at a rate of 1.2 Mg/ha/year. Lowest average cotton lint yield occurred with T2 (0.54 Mg/ha) and highest wheat yield with T3 (2.8 Mg/ha). Rotations which include a wheat crop are more likely to result in better soil structure and cotton lint yield than cotton-sorghum or continuous cotton.

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A low-altitude platform utilising a 1.8-m diameter tethered helium balloon was used to position a multispectral sensor, consisting of two digital cameras, above a fertiliser trial plot where wheat (Triticum spp.) was being grown. Located in Cecil Plains, Queensland, Australia, the plot was a long-term fertiliser trial being conducted by a fertiliser company to monitor the response of crops to various levels of nutrition. The different levels of nutrition were achieved by varying nitrogen application rates between 0 and 120 units of N at 40 unit increments. Each plot had received the same application rate for 10 years. Colour and near-infrared images were acquired that captured the whole 2 ha plot. These images were examined and relationships sought between the captured digital information and the crop parameters imaged at anthesis and the at-harvest quality and quantity parameters. The statistical analysis techniques used were correlation analysis, discriminant analysis and partial least squares regression. A high correlation was found between the image and yield (R2 = 0.91) and a moderate correlation between the image and grain protein content (R2 = 0.66). The utility of the system could be extended by choosing a more mobile platform. This would increase the potential for the system to be used to diagnose the causes of the variability and allow remediation, and/or to segregate the crop at harvest to meet certain quality parameters.

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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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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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Cultivation and cropping of soils results in a decline in soil organic carbon and soil nitrogen, and can lead to reduced crop yields. The CENTURY model was used to simulate the effects of continuous cultivation and cereal cropping on total soil organic matter (C and N), carbon pools, nitrogen mineralisation, and crop yield from 6 locations in southern Queensland. The model was calibrated for each replicate from the original datasets, allowing comparisons for each replicate rather than site averages. The CENTURY model was able to satisfactorily predict the impact of long-term cultivation and cereal cropping on total organic carbon, but was less successful in simulating the different fractions and nitrogen mineralisation. The model firstly over-predicted the initial (pre-cropping) soil carbon and nitrogen concentration of the sites. To account for the unique shrinking and swelling characteristics of the Vertosol soils, the default annual decomposition rates of the slow and passive carbon pools were doubled, and then the model accurately predicted initial conditions. The ability of the model to predict carbon pool fractions varied, demonstrating the difficulty inherent in predicting the size of these conceptual pools. The strength of the model lies in the ability to closely predict the starting soil organic matter conditions, and the ability to predict the impact of clearing, cultivation, fertiliser application, and continuous cropping on total soil carbon and nitrogen.

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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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This paper is the first of a series that investigates whether new cropping systems with permanent raised beds (PRBs) or Flat land could be successfully used to increase farmers' incomes from rainfed crops in Lombok in Eastern Indonesia. This paper discusses the rice phase of the cropping system. Low grain yields of dry-seeded rice (Oryza sativa) grown on Flat land on Vertisols in the rainfed region of southern Lombok, Eastern Indonesia, are probably mainly due to (a) erratic rainfall (870-1220 mm/yr), with water often limiting at sensitive growth stages, (b) consistently high temperatures (average maximum - 31 C), and (c) low solar radiation. Farmers are therefore poor, and labour is hard and costly, as all operations are manual. Two replicated field experiments were run at Wakan (annual rainfall = 868 mm) and Kawo (1215 mm) for 3 years (2001/2002 to 2003/2004) on Vertisols in southern Lombok. Dry-seeded rice was grown in 4 treatments with or without manual tillage on (a) PRBs, 1.2 m wide, 200 mm high, separated by furrows 300 mm wide, 200 mill deep, with no rice sown in the well-graded furrows, and (b) well-graded Flat land. Excess surface water was harvested from each treatment and used for irrigation after the vegetative stage of the rice. All operations were manual. There were no differences between treatments in grain yield of rice (mean grain yield = 681 g/m(2)) which could be partly explained by total number of tillers/hill and mean panicle length, but not number of productive tillers/hill, plant height or weight of 1000 grains. When the data from both treatments on PRBs and from both treatments on Flat land, each year at each site were analysed, there were also no differences in grain yield of rice (g/m(2)). When rainfall in the wet season up to harvest was over 1000 mm (Year 2; Wakan, Kawo), or plants were water-stressed during crop establishment (Year 1; Wakan) or during grain-fill (Year 3: Kawo), there were significant differences in grain yield (g/1.5 m(2)) between treatments; generally the grain yield (g/1.5 m(2)) on PRBs with or without tillage was less than that on Flat land with or without tillage. However, when the data from both treatments on PRBs and from both treatments on Flat land, each year at each site, were analysed, the greater grain yield of dry-seeded rice on Flat land (mean yield 1 092 g/1.5 m(2)) than that on PRBs (mean 815 g/1.5 m(2)) was mainly because there were 25% more plants on Flat land. Overall when the data in the 2 outer rows and the 2 inner rows on PRBs were each combined, there was a higher number of productive tillers in the combined outer rows (mean 20.7 tillers/hill) compared with that in the combined inner rows on each PRB (mean 18.2 tillers/hill). However, there were no differences in grain yield between combined rows (mean 142 g/m row). Hence with a gap of 500 mm (the distance between the outer rows of plants on adjacent raised beds), plants did not compensate in grain yield for missing plants in furrows. This suggests that rice (a) also sown in furrows, or (b) sown in 7 rows with narrower row-spacing, or (c) sown in 6 rows with slightly wider row-spacing, and narrower gap between outer rows on adjacent beds, may further increase grain yield (g/1.5 m(2)) in this system of PRBs. The growth and the grain yield (y in g/m(2)) of rainfed rice (with rainfall on-site the only source of water for irrigation) depended mainly on the rainfall (x in mm) in the wet season up to harvest (due either to site or year) with y = 1. 1x -308; r(2) = 0.54; p < 0.005. However, 280 mm (i.e. 32%) of the rainfall was not directly used to produce grain (i.e. when y = 0 g/m(2)). Manual tillage did not affect growth and grain yield of rice (g/m(2); g/1.5 m(2)), either on PRB or on Flat land.

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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.