990 resultados para Nitrogen effects on sugarcane
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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These rootstock and nitrogen fertiliser studies confirmed that rootstock race can significantly affect the development of postharvest disease and mineral nutrient accumulation in Hass avocado fruit. When Hass (Guatemalan race) was grafted to seedling Velvick (West Indian race) rootstock, the severity and incidence of anthracnose in fruit were significantly reduced by up to 64 and 37%, respectively, compared with seedling Duke 6 (Mexican race) rootstock. Stem-end rot was also influenced by rootstock in some seasons, and significant reductions (up to 87%) in the severity and incidence of stem-end rot were recorded in Hass fruit from Velvick compared with Duke 6 rootstock trees. These improvements in postharvest diseases were associated with significantly lower concentrations of nitrogen and potassium, higher concentrations of calcium and magnesium, lower ratios of nitrogen:calcium and higher ratios of calcium + magnesium:potassium in Hass leaves and fruit from Velvick compared with Duke 6 rootstock trees. Altering the rate of nitrogen fertiliser had minimal impact on postharvest disease development. However, in one season, reducing the rate of nitrogen fertiliser to nil significantly reduced the concentration of nitrogen in the fruit skin, decreased the nitrogen:calcium ratio and significantly reduced the severity and incidence of anthracnose in Hass fruit from both Velvick and Duke 6 rootstock trees. The form of nitrogen fertiliser (ammonium compared with nitrate) applied to the trees did not significantly affect the postharvest disease susceptibility of Hass avocado fruit on either Velvick or Duke 6 rootstock. The Guatemalan race rootstocks, Anderson 8 and Anderson 10, were also found to be superior to the Mexican race rootstock, Parida 1, for reducing anthracnose severity. This again, was associated with a better balance of mineral nutrients (significantly lower nitrogen:calcium and higher calcium + magnesium:potassium ratios) in the fruit. This rootstock effect, however, was only observed in the first season of a 3-year experiment, possibly because of a better balance between vegetative growth and fruit production in Parida 1 in the latter two seasons. Significant positive correlations between anthracnose severity and fruit skin nitrogen:calcium ratios were evident across all experiments.
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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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The promotion of controlled traffic (matching wheel and row spacing) in the Australian sugar industry is necessitating a widening of row spacing beyond the standard 1.5 m. As all cultivars grown in the Australian industry have been selected under the standard row spacing there are concerns that at least some cultivars may not be suitable for wider rows. To address this issue, experiments were established in northern and southern Queensland in which cultivars, with different growth characteristics, recommended for each region, were grown under a range of different row configurations. In the northern Queensland experiment at Gordonvale, cultivars Q187((sic)), Q200((sic)), Q201((sic)), and Q218((sic)) were grown in 1.5-m single rows, 1.8-m single rows, 1.8-m dual rows (50 cm between duals), and 2.3-m dual rows (80 cm between duals). In the southern Queensland experiment at Farnsfield, cvv. Q138, Q205((sic)), Q222((sic)) and Q188((sic)) were also grown in 1.5-m single rows, 1.8-m single rows, 1.8-m dual rows (50 cm between duals), while 1.8-m-wide throat planted single row and 2.0-m dual row (80 cm between duals) configurations were also included. There was no difference in yield between the different row configurations at Farnsfield but there was a significant row configuration x cultivar interaction at Gordonvale due to good yields in 1.8-m single and dual rows with Q201((sic)) and poor yields with Q200((sic)) at the same row spacings. There was no significant difference between the two cultivars in 1.5-m single and 2.3-m dual rows. The experiments once again demonstrated the compensatory capacity that exists in sugarcane to manipulate stalk number and individual stalk weight as a means of producing similar yields across a range of row configurations and planting densities. There was evidence of different growth patterns between cultivars in response to different row configurations (viz. propensity to tiller, susceptibility to lodging, ability to compensate between stalk number and stalk weight), suggesting that there may be genetic differences in response to row configuration. It is argued that there is a need to evaluate potential cultivars under a wider range of row configurations than the standard 1.5-m single rows. Cultivars that perform well in row configurations ranging from 1.8 to 2.0 m are essential if the adverse effects of soil compaction are to be managed through the adoption of controlled traffic.
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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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Extensive cattle grazing is the dominant land use in northern Australia. It has been suggested that grazing intensity and rainfall have profound effects on the dynamics of soil nutrients in northern Australia’s semi-arid rangelands. Previous studies have found positive, neutral and negative effects of grazing pressure on soil nutrients. These inconsistencies could be due to short-term experiments that do not capture the slow dynamics of some soil nutrients and the effects of interannual variability in rainfall. In a long-term cattle grazing trial in northern Australia on Brown Sodosol–Yellow Kandosol complex, we analysed soil organic matter and mineral nitrogen in surface soils (0–10 cm depth) 11, 12 and 16 years after trial establishment on experimental plots representing moderate stocking (stocked at the long-term carrying capacity for the region) and heavy stocking (stocked at twice the long-term carrying capacity). Higher soil organic matter was found under heavy stocking, although grazing treatment had little effect on mineral and total soil nitrogen. Interannual variability had a large effect on soil mineral nitrogen, but not on soil organic matter, suggesting that soil nitrogen levels observed in this soil complex may be affected by other indirect pathways, such as climate. The effect of interannual variability in rainfall and the effects of other soil types need to be explored further.
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AIN/CrN multilayer hard coatings with various bilayer thicknesses were fabricated by a reactive sputtering process. The microstructural and mechanical characterizations of multilayer coatings were investigated through transmission electron microscope (TEM) observations and the hardness measurements by nano indentation. In particular, the variation of chemical bonding states of the bilayer nitrides was elucidated by near edge X-ray absorption fine structure (NEXAFS) spectroscopy. Many broken nitrogen bonds were formed by decreasing the bilayer thickness of AIN/CrN multilayer coatings. Existence of optimum AIN/CrN multilayer coatings thickness for maximum hardness could be explained by the competition of softening by the formation of broken nitrogen bonds and strengthening induced by decreasing bilayer thickness.
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Professionals who are responsible for coastal environmental and natural resource planning and management have a need to become conversant with new concepts designed to provide quantitative measures of the environmental benefits of natural resources. These amenities range from beaches to wetlands to clean water and other assets that normally are not bought and sold in everyday markets. At all levels of government — from federal agencies to townships and counties — decisionmakers are being asked to account for the costs and benefits of proposed actions. To non-specialists, the tools of professional economists are often poorly understood and sometimes inappropriate for the problem at hand. This handbook is intended to bridge this gap. The most widely used organizing tool for dealing with natural and environmental resource choices is benefit-cost analysis — it offers a convenient way to carefully identify and array, quantitatively if possible, the major costs, benefits, and consequences of a proposed policy or regulation. The major strength of benefit-cost analysis is not necessarily the predicted outcome, which depends upon assumptions and techniques, but the process itself, which forces an approach to decision-making that is based largely on rigorous and quantitative reasoning. However, a major shortfall of benefit-cost analysis has been the difficulty of quantifying both benefits and costs of actions that impact environmental assets not normally, nor even regularly, bought and sold in markets. Failure to account for these assets, to omit them from the benefit-cost equation, could seriously bias decisionmaking, often to the detriment of the environment. Economists and other social scientists have put a great deal of effort into addressing this shortcoming by developing techniques to quantify these non-market benefits. The major focus of this handbook is on introducing and illustrating concepts of environmental valuation, among them Travel Cost models and Contingent Valuation. These concepts, combined with advances in natural sciences that allow us to better understand how changes in the natural environment influence human behavior, aim to address some of the more serious shortcomings in the application of economic analysis to natural resource and environmental management and policy analysis. Because the handbook is intended for non-economists, it addresses basic concepts of economic value such as willingness-to-pay and other tools often used in decision making such as costeffectiveness analysis, economic impact analysis, and sustainable development. A number of regionally oriented case studies are included to illustrate the practical application of these concepts and techniques.