118 resultados para crop price only


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To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.

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Background: With the advances in DNA sequencer-based technologies, it has become possible to automate several steps of the genotyping process leading to increased throughput. To efficiently handle the large amounts of genotypic data generated and help with quality control, there is a strong need for a software system that can help with the tracking of samples and capture and management of data at different steps of the process. Such systems, while serving to manage the workflow precisely, also encourage good laboratory practice by standardizing protocols, recording and annotating data from every step of the workflow Results: A laboratory information management system (LIMS) has been designed and implemented at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that meets the requirements of a moderately high throughput molecular genotyping facility. The application is designed as modules and is simple to learn and use. The application leads the user through each step of the process from starting an experiment to the storing of output data from the genotype detection step with auto-binning of alleles; thus ensuring that every DNA sample is handled in an identical manner and all the necessary data are captured. The application keeps track of DNA samples and generated data. Data entry into the system is through the use of forms for file uploads. The LIMS provides functions to trace back to the electrophoresis gel files or sample source for any genotypic data and for repeating experiments. The LIMS is being presently used for the capture of high throughput SSR (simple-sequence repeat) genotyping data from the legume (chickpea, groundnut and pigeonpea) and cereal (sorghum and millets) crops of importance in the semi-arid tropics. Conclusions: A laboratory information management system is available that has been found useful in the management of microsatellite genotype data in a moderately high throughput genotyping laboratory. The application with source code is freely available for academic users and can be downloaded from http://www.icrisat.org/bt-software-d-lims.htm

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Adoption of conservation tillage practices on Red Ferrosol soils in the inland Burnett area of south-east Queensland has been shown to reduce runoff and subsequent soil erosion. However, improved infiltration resulting from these measures has not improved crop performance and there are suggestions of increased loss of soil water via deep drainage. This paper reports data monitoring soil water under real and artificial rainfall events in commercial fields and long-term tillage experiments, and uses the data to explore the rate and mechanisms of deep drainage in this soil type. Soils were characterised by large drainable porosities (≥0.10 m3/m3) in all parts of the profile to depths of 1.50 m, with drainable porosity similar to available water content (AWC) at 0.25 and 0.75 m, but >60% higher than AWC at 1.50 m. Hydraulic conductivity immediately below the tilled layer in both continuously cropped soils and those after a ley pasture phase was shown to decline with increasing soil moisture content, although the rate of decline was much greater in continuously cropped soil. At moisture contents approaching the drained upper limit (pore water pressure = -100cm H2O), estimates of saturated hydraulic conductivity after a ley pasture were 3-5 times greater than in continuously cropped soil, suggesting much greater rates of deep drainage in the former when soils are moist. Hydraulic tensiometers and fringe capacitance sensors monitored during real and artificial rainfall events showed evidence of soils approaching saturation in the surface layers (top 0.30-0.40 m), but there was no evidence of soil moistures exceeding the drained upper limit (i.e. pore water pressures ≤ -100 cm H2O) in deeper layers. Recovery of applied soil water within the top 1.00-1.20 m of the profile during or immediately after rainfall events declined as the starting profile moisture content increased. These effects were consistent with very rapid rates of internal drainage. Sensors deeper in the profile were unable to detect this drainage due to either non-uniformity of conducting macropores (i.e. bypass flow) or unsaturated conductivities in deeper layers that far exceed the saturated hydraulic conductivity of the infiltration throttle at the bottom of the cultivated layer. Large increases in unsaturated hydraulic conductivities are likely with only small increases in water content above the drained upper limit. Further studies with drainage lysimeters and large banks of hydraulic tensiometers are planned to quantify drainage risk in these soil types.

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Cereal grain is one of the main export commodities of Australian agriculture. Over the past decade, crop yield forecasts for wheat and sorghum have shown appreciable utility for industry planning at shire, state, and national scales. There is now an increasing drive from industry for more accurate and cost-effective crop production forecasts. In order to generate production estimates, accurate crop area estimates are needed by the end of the cropping season. Multivariate methods for analysing remotely sensed Enhanced Vegetation Index (EVI) from 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery within the cropping period (i.e. April-November) were investigated to estimate crop area for wheat, barley, chickpea, and total winter cropped area for a case study region in NE Australia. Each pixel classification method was trained on ground truth data collected from the study region. Three approaches to pixel classification were examined: (i) cluster analysis of trajectories of EVI values from consecutive multi-date imagery during the crop growth period; (ii) harmonic analysis of the time series (HANTS) of the EVI values; and (iii) principal component analysis (PCA) of the time series of EVI values. Images classified using these three approaches were compared with each other, and with a classification based on the single MODIS image taken at peak EVI. Imagery for the 2003 and 2004 seasons was used to assess the ability of the methods to determine wheat, barley, chickpea, and total cropped area estimates. The accuracy at pixel scale was determined by the percent correct classification metric by contrasting all pixel scale samples with independent pixel observations. At a shire level, aggregated total crop area estimates were compared with surveyed estimates. All multi-temporal methods showed significant overall capability to estimate total winter crop area. There was high accuracy at pixel scale (>98% correct classification) for identifying overall winter cropping. However, discrimination among crops was less accurate. Although the use of single-date EVI data produced high accuracy for estimates of wheat area at shire scale, the result contradicted the poor pixel-scale accuracy associated with this approach, due to fortuitous compensating errors. Further studies are needed to extrapolate the multi-temporal approaches to other geographical areas and to improve the lead time for deriving cropped-area estimates before harvest.

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The potential of beef producers to profitably produce 500-kg steers at 2.5 years of age in northern Australia's dry tropics to meet specifications of high-value markets, using a high-input management (HIM) system was examined. HIM included targeted high levels of fortified molasses supplementation, short seasonal mating and the use of growth promotants. Using herds of 300-400 females plus steer progeny at three sites, HIM was compared at a business level to prevailing best-practice, strategic low-input management (SLIM) in which there is a relatively low usage of energy concentrates to supplement pasture intake. The data presented for each breeding-age cohort within management system at each site includes: annual pregnancy rates (range: 14-99%), time of conception, mortalities (range: 0-10%), progeny losses between confirmed pregnancy and weaning (range: 0-29%), and weaning rates (range: 14-92%) over the 2-year observation. Annual changes in weight and relative net worth were calculated for all breeding and non-breeding cohorts. Reasons for outcomes are discussed. Compared with SLIM herds, both weaning weights and annual growth were >= 30 kg higher, enabling 86-100% of HIM steers to exceed 500 kg at 2.5 years of age. Very few contemporary SLIM steers reached this target. HIM was most profitably applied to steers. Where HIM was able to achieve high pregnancy rates in yearlings, its application was recommended in females. Well managed, appropriate HIM systems increased profits by around $15/adult equivalent at prevailing beef and supplement prices. However, a 20% supplement price rise without a commensurate increase in values for young slaughter steers would generally eliminate this advantage. This study demonstrated the complexity of pro. table application of research outcomes to commercial business, even when component research suggests that specific strategies may increase growth and reproductive efficiency and/or be more pro. table. Because of the higher level of management required, higher costs and returns, and higher susceptibility to market changes and disease, HIM systems should only be applied after SLIM systems are well developed. To increase profitability, any strategy must ultimately either increase steer growth and sale values and/or enable a shift to high pregnancy rates in yearling heifers.

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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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Marker ordering during linkage map construction is a critical component of QTL mapping research. In recent years, high-throughput genotyping methods have become widely used, and these methods may generate hundreds of markers for a single mapping population. This poses problems for linkage analysis software because the number of possible marker orders increases exponentially as the number of markers increases. In this paper, we tested the accuracy of linkage analyses on simulated recombinant inbred line data using the commonly used Map Manager QTX (Manly et al. 2001: Mammalian Genome 12, 930-932) software and RECORD (Van Os et al. 2005: Theoretical and Applied Genetics 112, 30-40). Accuracy was measured by calculating two scores: % correct marker positions, and a novel, weighted rank-based score derived from the sum of absolute values of true minus observed marker ranks divided by the total number of markers. The accuracy of maps generated using Map Manager QTX was considerably lower than those generated using RECORD. Differences in linkage maps were often observed when marker ordering was performed several times using the identical dataset. In order to test the effect of reducing marker numbers on the stability of marker order, we pruned marker datasets focusing on regions consisting of tightly linked clusters of markers, which included redundant markers. Marker pruning improved the accuracy and stability of linkage maps because a single unambiguous marker order was produced that was consistent across replications of analysis. Marker pruning was also applied to a real barley mapping population and QTL analysis was performed using different map versions produced by the different programs. While some QTLs were identified with both map versions, there were large differences in QTL mapping results. Differences included maximum LOD and R-2 values at QTL peaks and map positions, thus highlighting the importance of marker order for QTL mapping

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Growing agricultural crops in wide row spacings has been widely adopted to conserve water, to control pests and diseases, and to minimise problems associated with sowing into stubble. The development of herbicide resistance combined with the advent of precision agriculture has resulted in a further reason for wide row spacings to be adopted: weed control. Increased row spacing enables two different methods of weed control to be implemented with non-selective chemical and physical control methods utilised in the wide inter-row zone, with or without selective chemicals used on the on-row only. However, continual application of herbicides and tillage on the inter-row zone brings risks of herbicide resistance, species shifts and/or changes in species dominance, crop damage, increased costs, yield losses, and more expensive weed management technology.

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Much research in understanding plant diseases has been undertaken, but there has been insufficient attention given to dealing with coordinated approaches to preventing and managing diseases. A global management approach is essential to the long-term sustainability of banana production. This approach would involve coordinated surveys, capacity building in developing countries, development of disease outbreak contingency plans and coordinated quarantine awareness, including on-line training in impact risk assessment and web-based diagnostic software. Free movement of banana plants and products between some banana-producing countries is causing significant pressure on the ability to manage diseases in banana. The rapid spread of Fusarium oxysporum f. sp. cubense 'tropical race 4' in Asia, bacterial wilts in Africa and Asia and black leaf streak [Mycosphaerella fijiensis] in Brazil and elsewhere are cases in point. The impact of these diseases is devastating, severely cutting family incomes and jeopardising food security around the globe. Agreements urgently need to be reached between governments to halt the movement of banana plants and products between banana-producing countries before it is too late and global food security is irreparably harmed. Black leaf streak, arguably the most serious banana disease, has become extremely difficult to control in commercial plantations in various parts of the world. Sometimes in excess of 50 fungicide sprays have to be applied each year. Disease eradication and effective disease control is not possible because there is no control of disease inoculum in non-commercial plantings in these locations. Additionally, there have been enormous sums of money invested in international banana breeding programmes over many years only to see the value of hybrid products lost too soon. 'Goldfinger' (AAAB, syn. 'FHIA-01'), for example, has recently been observed severely affected by black leaf streak in Samoa. Resistant cultivars alone cannot be relied upon in the fight against this disease. Real progress in control may only come when the local communities are engaged and become actively involved in regional programmes. Global recommendations are long overdue and urgently needed to help ensure the long-term sustainable utilisation of the products of the breeding programmes.

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Background and Aims: The evolution of resistance to herbicides is a substantial problem in contemporary agriculture. Solutions to this problem generally consist of the use of practices to control the resistant population once it evolves, and/or to institute preventative measures before populations become resistant. Herbicide resistance evolves in populations over years or decades, so predicting the effectiveness of preventative strategies in particular relies on computational modelling approaches. While models of herbicide resistance already exist, none deals with the complex regional variability in the northern Australian sub-tropical grains farming region. For this reason, a new computer model was developed. Methods: The model consists of an age- and stage-structured population model of weeds, with an existing crop model used to simulate plant growth and competition, and extensions to the crop model added to simulate seed bank ecology and population genetics factors. Using awnless barnyard grass (Echinochloa colona) as a test case, the model was used to investigate the likely rate of evolution under conditions expected to produce high selection pressure. Key Results: Simulating continuous summer fallows with glyphosate used as the only means of weed control resulted in predicted resistant weed populations after approx. 15 years. Validation of the model against the paddock history for the first real-world glyphosate-resistant awnless barnyard grass population shows that the model predicted resistance evolution to within a few years of the real situation. Conclusions: This validation work shows that empirical validation of herbicide resistance models is problematic. However, the model simulates the complexities of sub-tropical grains farming in Australia well, and can be used to investigate, generate and improve glyphosate resistance prevention strategies.

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The present study set out to test the hypothesis through field and simulation studies that the incorporation of short-term summer legumes, particularly annual legume lablab (Lablab purpureus cv. Highworth), in a fallow-wheat cropping system will improve the overall economic and environmental benefits in south-west Queensland. Replicated, large plot experiments were established at five commercial properties by using their machineries, and two smaller plot experiments were established at two intensively researched sites (Roma and St George). A detailed study on various other biennial and perennial summer forage legumes in rotation with wheat and influenced by phosphorus (P) supply (10 and 40 kg P/ha) was also carried out at the two research sites. The other legumes were lucerne (Medicago sativa), butterfly pea (Clitoria ternatea) and burgundy bean (Macroptilium bracteatum). After legumes, spring wheat (Triticum aestivum) was sown into the legume stubble. The annual lablab produced the highest forage yield, whereas germination, establishment and production of other biennial and perennial legumes were poor, particularly in the red soil at St George. At the commercial sites, only lablab-wheat rotations were experimented, with an increased supply of P in subsurface soil (20 kg P/ha). The lablab grown at the commercial sites yielded between 3 and 6 t/ha forage yield over 2-3 month periods, whereas the following wheat crop with no applied fertiliser yielded between 0.5 to 2.5 t/ha. The wheat following lablab yielded 30% less, on average, than the wheat in a fallow plot, and the profitability of wheat following lablab was slightly higher than that of the wheat following fallow because of greater costs associated with fallow management. The profitability of the lablab-wheat phase was determined after accounting for the input costs and additional costs associated with the management of fallow and in-crop herbicide applications for a fallow-wheat system. The economic and environmental benefits of forage lablab and wheat cropping were also assessed through simulations over a long-term climatic pattern by using economic (PreCAPS) and biophysical (Agricultural Production Systems Simulation, APSIM) decision support models. Analysis of the long-term rainfall pattern (70% in summer and 30% in winter) and simulation studies indicated that ~50% time a wheat crop would not be planted or would fail to produce a profitable crop (grain yield less than 1 t/ha) because of less and unreliable rainfall in winter. Whereas forage lablab in summer would produce a profitable crop, with a forage yield of more than 3 t/ha, ~90% times. Only 14 wheat crops (of 26 growing seasons, i.e. 54%) were profitable, compared with 22 forage lablab (of 25 seasons, i.e. 90%). An opportunistic double-cropping of lablab in summer and wheat in winter is also viable and profitable in 50% of the years. Simulation studies also indicated that an opportunistic lablab-wheat cropping can reduce the potential runoff+drainage by more than 40% in the Roma region, leading to improved economic and environmental benefits.

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The variation in liveweight gain in grazing beef cattle as influenced by pasture type, season and year effects has important economic implications for mixed crop-livestock systems and the ability to better predict such variation would benefit beef producers by providing a guide for decision making. To identify key determinants of liveweight change of Brahman-cross steers grazing subtropical pastures, measurements of pasture quality and quantity, and diet quality in parallel with liveweight were made over two consecutive grazing seasons (48 and 46 weeks, respectively), on mixed Clitoria ternatea/grass, Stylosanthes seabrana/grass and grass swards (grass being a mixture of Bothriochloa insculpta cv. Bisset, Dichanthium sericeum and Panicum maximum var. trichoglume cv. Petrie). Steers grazing the legume-based pastures had the highest growth rate and gained between 64 and 142 kg more than those grazing the grass pastures in under 12 months. Using an exponential model, green leaf mass, green leaf %, adjusted green leaf % (adjusted for inedible woody legume stems), faecal near infrared reflectance spectroscopy predictions of diet crude protein and diet dry matter digestibility, accounted for 77, 74, 80, 63 and 60%, respectively, of the variation in daily weight gain when data were pooled across pasture types and grazing seasons. The standard error of the regressions indicated that 95% prediction intervals were large (+/- 0.42-0.64 kg/head.day) suggesting that derived regression relationships have limited practical application for accurately estimating growth rate. In this study, animal factors, especially compensatory growth effects, appeared to have a major influence on growth rate in relation to pasture and diet attributes. It was concluded that predictions of growth rate based only on pasture or diet attributes are unlikely to be accurate or reliable. Nevertheless, key pasture attributes such as green leaf mass and green leaf% provide a robust indication of what proportion of the potential growth rate of the grazing animals can be achieved.

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The nitrogen-driven trade-off between nitrogen utilisation efficiency (yield per unit nitrogen uptake) and water use efficiency (yield per unit evapotranspiration) is widespread and results from well established, multiple effects of nitrogen availability on the water, carbon and nitrogen economy of crops. Here we used a crop model (APSIM) to simulate the yield, evapotranspiration, soil evaporation and nitrogen uptake of wheat, and analysed yield responses to water, nitrogen and climate using a framework analogous to the rate-duration model of determinate growth. The relationship between modelled grain yield (Y) and evapotranspiration (ET) was fitted to a linear-plateau function to derive three parameters: maximum yield (Ymax), the ET break-point when yield reaches its maximum (ET#), and the rate of yield response in the linear phase ([Delta]Y/[Delta]ET). Against this framework, we tested the hypothesis that nitrogen deficit reduces maximum yield by reducing both the rate ([Delta]Y/[Delta]ET) and the range of yield response to evapotranspiration, i.e. ET# - Es, where Es is modelled median soil evaporation. Modelled data reproduced the nitrogen-driven trade-off between nitrogen utilisation efficiency and water use efficiency in a transect from Horsham (36°S) to Emerald (23°S) in eastern Australia. Increasing nitrogen supply from 50 to 250 kg N ha-1 reduced yield per unit nitrogen uptake from 29 to 12 kg grain kg-1 N and increased yield per unit evapotranspiration from 6 to 15 kg grain ha-1 mm-1 at Emerald. The same increment in nitrogen supply reduced yield per unit nitrogen uptake from 30 to 25 kg grain kg-1 N and increased yield per unit evapotranspiration from 6 to 25 kg grain ha-1 mm-1 at Horsham. Maximum yield ranged from 0.9 to 6.4 t ha-1. Consistent with our working hypothesis, reductions in maximum yield with nitrogen deficit were associated with both reduction in the rate of yield response to ET and compression of the range of yield response to ET. Against the notion of managing crops to maximise water use efficiency in low rainfall environments, we emphasise the trade-off between water use efficiency and nitrogen utilisation efficiency, particularly under conditions of high nitrogen-to-grain price ratio. The rate-range framework to characterise the relationship between yield and evapotranspiration is useful to capture this trade-off as the parameters were responsive to both nitrogen supply and climatic factors.

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Global trends in human population and agriculture dictate that future calls made on the resources (physical, human, financial) and systems involved in producing food will be increasingly more demanding and complex. Both plant breeding and improved agronomy lift the potential yield of crops, a key component in progressing farm yield, so society can reasonably expect both agronomy as a science and agronomists as practitioners to contribute to the successful delivery of necessary change. By reflecting on current trends in agricultural production (diversification, intensification, integration, industrialisation, automation) and deconstructing a futuristic scenario of attempting agricultural production on Mars, it seems the skills agronomists will require involve not only the mandatory elements of their discipline but also additional skills that enable engagement with, even leadership of, teams who integrate (in sum or part) engineering, (agri-)business, economics and operational management, and build the social capital required to create and maintain a diverse array of enhanced and new ethical production systems and achieve increasing efficiencies within them.

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Sonchus oleraceus (common sowthistle) is a dominant weed and has increased in prevalence in conservation cropping systems of the subtropical grain region of Australia. Four experiments were undertaken to define the environmental factors that favor its germination, emergence, and seed persistence. Seeds were germinated at constant temperatures between 5 and 35C and water potentials between 0 and -1.4 MPa. The maximum germination rate of 86-100% occurred at 0 and -0.2 MPa, irrespective of the temperature when exposed to light (12 h photoperiod light/dark), but the germination rate was reduced by 72% without light. At water potentials of -0.6 to -0.8 MPa, the germination rate was reduced substantially by higher temperatures; no seed germinated at a water potential >-1.0 MPa. Emergence and seed persistence were measured over 30 months following seed burial at 0 (surface), 1, 2, 5, and 10 cm depths in large pots that were buried in a south-eastern Queensland field. Seedlings emerged readily from the surface and 1 cm depth, with no emergence from below the 2 cm depth. The seedlings emerged during any season following rain but, predominantly, within 6 months of planting. Seed persistence was short-term on the soil surface, with 2% of seeds remaining after 6 months, but it increased with the burial depth, with 12% remaining after 30 months at 10 cm. Thus, a minimal seed burial depth with reduced tillage and increased surface soil water with stubble retention has favored the proliferation of this weed in any season in a subtropical environment. However, diligent management without seed replenishment will greatly reduce this weed problem within a short period.