9 resultados para Nitrogen analysis

em eResearch Archive - Queensland Department of Agriculture


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Cyperus iria is a weed of rice with widespread occurrence throughout the world. Because of concerns about excessive and injudicious use of herbicides, cultural weed management approaches that are safe and economical are needed. Developing such approaches will require a better understanding of weed biology and ecology, as well as of weed response to increases in crop density and nutrition. Knowledge of the effects of nitrogen (N) fertilizer on crop-weed competitive interactions could also help in the development of integrated weed management strategies. The present study was conducted in a screenhouse to determine the effects of rice planting density (0, 5, 10, and 20 plants pot−1) and N rate (0, 50, 100, and 150 kg ha−1) on the growth of C. iria. Tiller number per plant decreased by 73–88%, leaf number by 85–94%, leaf area by 85–98%, leaf biomass by 92–99%, and inflorescence biomass by 96–99% when weed plants were grown at 20 rice plants pot−1 (i.e., 400 plants m−2) compared with weed plants grown alone. All of these parameters increased when N rates were increased. On average, weed biomass increased by 118–389% and rice biomass by 121–275% with application of 50–150 kg N ha−1, compared to control. Addition of N favored weed biomass production relative to rice biomass. Increased N rates reduced the root-to-shoot weight ratio of C. iria. Rice interference reduced weed growth and biomass and completely suppressed C. iria when no N was applied at high planting densities (i.e., 20 plants pot−1). The weed showed phenotypic plasticity in response to N application, and the addition of N increased the competitive ability of the weed over rice at densities of 5 and 10 rice plants pot−1 compared with 20 plants pot−1. The results of the present study suggest that high rice density (i.e., 400 plants m−2) can help suppress C. iria growth even at high N rates (150 kg ha−1).

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Nitrogen (N) is the largest agricultural input in many Australian cropping systems and applying the right amount of N in the right place at the right physiological stage is a significant challenge for wheat growers. Optimizing N uptake could reduce input costs and minimize potential off-site movement. Since N uptake is dependent on soil and plant water status, ideally, N should be applied only to areas within paddocks with sufficient plant available water. To quantify N and water stress, spectral and thermal crop stress detection methods were explored using hyperspectral, multispectral and thermal remote sensing data collected at a research field site in Victoria, Australia. Wheat was grown over two seasons with two levels of water inputs (rainfall/irrigation) and either four levels (in 2004; 0, 17, 39 and 163 kg/ha) or two levels (in 2005; 0 and 39 kg/ha N) of nitrogen. The Canopy Chlorophyll Content Index (CCCI) and modified Spectral Ratio planar index (mSRpi), two indices designed to measure canopy-level N, were calculated from canopy-level hyperspectral data in 2005. They accounted for 76% and 74% of the variability of crop N status, respectively, just prior to stem elongation (Zadoks 24). The Normalised Difference Red Edge (NDRE) index and CCCI, calculated from airborne multispectral imagery, accounted for 41% and 37% of variability in crop N status, respectively. Greater scatter in the airborne data was attributable to the difference in scale of the ground and aerial measurements (i.e., small area plant samples against whole-plot means from imagery). Nevertheless, the analysis demonstrated that canopy-level theory can be transferred to airborne data, which could ultimately be of more use to growers. Thermal imagery showed that mean plot temperatures of rainfed treatments were 2.7 °C warmer than irrigated treatments (P < 0.001) at full cover. For partially vegetated fields, the two-Dimensional Crop Water Stress Index (2D CWSI) was calculated using the Vegetation Index-Temperature (VIT) trapezoid method to reduce the contribution of soil background to image temperature. Results showed rainfed plots were consistently more stressed than irrigated plots. Future work is needed to improve the ability of the CCCI and VIT methods to detect N and water stress and apply both indices simultaneously at the paddock scale to test whether N can be targeted based on water status. Use of these technologies has significant potential for maximising the spatial and temporal efficiency of N applications for wheat growers. ‘Ground–breaking Stuff’- Proceedings of the 13th Australian Society of Agronomy Conference, 10-14 September 2006, Perth, Western Australia.

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This paper reports on the use of APSIM - Maize for retrospective analysis of performance of a high input, high yielding maize crop and analysis of predicted performance of maize grown with high inputs over the long-term (>100 years) for specified scenarios of environmental conditions (temperature and radiation) and agronomic inputs (sowing date, plant population, nitrogen fertiliser and irrigation) at Boort, Victoria, Australia. It uses a high yielding (17 400 kg/ha dry grain, 20 500 kg/ha at 15% water) commercial crop grown in 2004-05 as the basis of the study. Yield for the agronomic and environmental conditions of 2004-05 was predicted accurately, giving confidence that the model could be used for the detailed analyses undertaken. The analysis showed that the yield achieved was close to that possible with the conditions and agronomic inputs of 2004-05. Sowing dates during 21 September to 26 October had little effect on predicted yield, except when combined with reduced temperature. Single year and long-term analyses concluded that a higher plant population (11 plants/m2) is needed to optimise yield, but that slightly lower N and irrigation inputs are appropriate for the plant population used commercially (8.4 plants/m2). Also, compared with changes in agronomic inputs increases in temperature and/or radiation had relatively minor effects, except that reduced temperature reduces predicted yield substantially. This study provides an approach for the use of models for both retrospective analysis of crop performance and assessment of long-term variability of crop yield under a wide range of agronomic and environmental conditions.

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Stay-green, an important trait for grain yield of sorghum grown under water limitation, has been associated with a high leaf nitrogen content at the start of grain filling. This study quantifies the N demand of leaves and stems and explores effects of N stress on the N balance of vegetative plant parts of three sorghum hybrids differing in potential crop height. The hybrids were grown under well-watered conditions at three levels of N supply. Vertical profiles of biomass and N% of leaves and stems, together with leaf size and number, and specific leaf nitrogen (SLN), were measured at regular intervals. The hybrids had similar minimum but different critical and maximum SLN, associated with differences in leaf size and N partitioning, the latter associated with differences in plant height. N demand of expanding new leaves was represented by critical SLN, and structural stem N demand by minimum stem N%. The fraction of N partitioned to leaf blades increased under N stress. A framework for N dynamics of leaves and stems is developed that captures effects of N stress and genotype on N partitioning and on critical and maximum SLN.

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Interest in cashew production in Australia has been stimulated by domestic and export market opportunities and suitability of large areas of tropical Australia. Economic models indicate that cashew production is profitable at 2.8 t ha-1 nut-in-shell (NIS). Balanced plant nutrition is essential to achieve economic yields in Australia, with nitrogen (N) of particular importance because of its capacity to modify growth, affect nut yield and cause environmental degradation through soil acidification and off-site contamination. The study on a commercial cashew plantation at Dimbulah, Australia, investigated the effect of N rate and timing on cashew growth, nut production, N leaching and soil chemical properties over five growth cycles (1995-1999). Nitrogen was applied during the main periods of vegetative (December-April) and reproductive (June-October) growth. Commercial NIS yields (up to 4.4 t ha-1 from individual trees) that exceeded the economic threshold of 2.8 t ha-1 were achieved. The yield response was mainly determined by canopy size as mean nut weight, panicle density and nuts per panicle were largely unaffected by N treatments. Nitrogen application confined to the main period of vegetative growth (December-April) produced a seasonal growth pattern that corresponded most consistently with highest NIS yield. This N timing also reduced late season flowering and undesirable post-November nut drop. Higher yields were not produced at N rates greater than 17 g m-2 of canopy surface area (equating to 210 kg N ha-1 for mature size trees). High yields were attained when N concentrations in Mveg leaves in May-June were about 2%, but this assessment occurs at a time when it is not feasible to correct N deficiency. The Mflor leaf of the preceding November, used in conjunction with the Mveg leaf, was proposed as a diagnostic tool to guide N rate decisions. Leaching of nitrate-N and acidification of the soil profile was recorded to 0.9 m. This is an environmental and sustainability hazard, and demonstrates that improved methods of N management are required.

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Nitrogen (N) is an essential nutrient in mango, influencing both productivity and fruit quality. In Australia, tree N is traditionally assessed once a year in the dormant pre-flowering stage by laboratory analysis of leaf N. This single assessment is insufficient to determine tree N status at all stages of the annual phenological cycle. Development of a field-based rapid N test would allow more frequent monitoring of tree N status and improved fertiliser management. This experiment examined the accuracy and useability of several devices used in other horticultural crops to rapidly assess mango leaf N in the field; the Konica Minolta 'SPAD-502 chlorophyll meter', Horiba 'Cardy Meter' and the Merck 'RQflex 10'. Regression and correlation analyses were used to determine the relationship between total leaf N and the measurements from the rapid test devices. The relationship between the chlorophyll index measured by the SPAD-502 meter and leaf N is highly significant at late fruit set (R 2=0.72, n=40) and post-harvest (R2=0.81, n=40) stages in the mango cultivar 'Kensington Pride' and significant (R2=0.51, n=40) at the flowering stage, indicating the device can be used to rapidly assess mango leaf N in the field. Correlation analysis indicated the relationship between petiole sap measured with the Cardy or Merck devices and leaf N is non-significant. © 2013 ISHS.

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Nitrogen (N) is an essential nutrient in mango, influencing both productivity and fruit quality. In Australian mango orchards, tree N is traditionally assessed once a year at the dormant pre-flowering stage using laboratory analysis of leaf N. This single assessment is insufficient to determine tree N status at all stages of the annual phenological cycle. Development of a field-based rapid N test would allow more frequent monitoring of tree N status and improved fertiliser management. These experiments examined the accuracy and useability of several devices used in other horticultural crops to rapidly assess mango leaf N in the field; the Konica Minolta 'SPAD-502 chlorophyll meter', Horiba 'Cardy Meter' and the Merck 'RQflex 10.' Regression and correlation analyses were used to determine the relationship between total leaf N and the measurements from the rapid test devices. The relationship between the chlorophyll index measured by the SPAD-502 meter and leaf N was highly significant at late fruit set (R 2=0.72, n=40) and post-harvest (R 2=0.81, n=40) stages and significant at the flowering stage (R 2=0.51, n=40) in the cultivar 'Kensington Pride', indicating the device can be used to rapidly assess mango leaf N in the field. Correlation analysis indicated the relationship between petiole sap measured with the Cardy or Merck devices and leaf N was non-significant.

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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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Carbon (C) sequestration in soils is a means for increasing soil organic carbon (SOC) stocks and is a potential tool for climate change mitigation. One recommended management practice to increase SOC stocks is nitrogen (N) fertilisation, however examples of positive, negative or null SOC effects in response to N addition exist. We evaluated the relative importance of plant molecular structure, soil physical properties and soil ecological stoichiometry in explaining the retention of SOC with and without N addition. We tracked the transformation of 13C pulse-labelled buffel grass (Cenchrus ciliaris L.), wheat (Triticum aestivum L.) and lucerne (Medicago sativa L.) material to the <53 μm silt + clay soil organic C fraction, hereafter named “humus”, over 365-days of incubation in four contrasting agricultural soils, with and without urea-N addition. We hypothesised that: a) humus retention would be soil and litter dependent; b) humus retention would be litter independent once litter C:N ratios were standardised with urea-N addition; and c) humus retention would be improved by urea-N addition. Two and three-way factorial analysis of variance indicated that 13C humus was consistently soil and litter dependent, even when litter C:N ratios were standardised, and that the effect of urea-N addition on 13C humus was also soil and litter dependent. A boosted regression analysis of the effect of 44 plant and soil explanatory variables demonstrated that soil biological and chemical properties had the greatest relative influence on 13C humus. Regression tree analyses demonstrated that the greatest gains in 13C humus occurred in soils of relatively low total organic C, dissolved organic C and microbial biomass C (MBC), or with a combination of relatively high MBC and low C:N ratio. The greatest losses in 13C humus occurred in soils with a combination of relatively high MBC and low total N or increasing C:N ratio. We conclude that soil variables involved in soil ecological stoichiometry exert a greater relative influence on incorporating organic matter as humus compared to plant molecular structure and soil physical properties. Furthermore, we conclude that the effect of N fertilisation on humus retention is dependent upon soil ecological stoichiometry.