999 resultados para Wheat trade.


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Two key quality traits in milling wheat are flour yield (FY) and water absorption (WA). Ideally, breeders would prefer to use markers to select promising lines rather than time consuming rheology tests. In this study, we measured FY and WA on a wheat mapping population (Lang/QT8766) of 162 individuals grown in two replicated field experiments at three locations over 2 years. We also carried out near infrared reflectance spectroscopy (NIRS) predictions on the grain for these traits to see if NIRS phenotypic data could provide useful mapping results when compared to the reference phenotypic data. Several common QTLs were identified for FY and WA by both sets of data. The QTL on chromosome 4D was a consistently recurring QTL region for both traits. The QTL on chromosome 2A was positively linked to protein content which was supported by genetic correlation data. The results also indicated it was possible to obtain useful phenotypic data for mapping FY and WA using NIRS data. This would save time and costs as NIRS is quicker and cheaper than current rheology methods.

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Conyza bonariensis is a major weed infesting zero-tilled cropping systems in subtropical Australia, particularly in wheat and winter fallows. Uncontrolled C.bonariensis survives to become a problem weed in the following crops or fallows. As no herbicide has been registered for C.bonariensis in wheat, the effectiveness of 11 herbicides, currently registered for other broad-leaved weeds in wheat, was evaluated in two pot and two field experiments. As previous research showed that the age of C.bonariensis, and to a lesser extent, the soil moisture at spraying affected herbicide efficacy, these factors also were investigated. The efficacy of the majority of herbicide treatments was reduced when large rosettes (5-15cm diameter) were treated, compared with small rosettes (<5cm diameter). However, for the majority of herbicide treatments, the soil moisture did not affect the herbicide efficacy in the pot experiments. In the field, a delay in herbicide treatment of 2 weeks reduced the herbicide efficacy consistently across herbicide treatments, which was related to weed age but not to soil moisture differences. Across all the experiments, four herbicides controlled C.bonariensis in wheat consistently (83-100%): 2,4-D; aminopyralid + fluroxypyr; picloram + MCPA + metsulfuron; and picloram + high rates of 2,4-D. Thus, this problem weed can be effectively and consistently controlled in wheat, particularly when small rosettes are treated, and therefore C.bonariensis will have a less adverse impact on the following fallow or crop.

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Concepts of agricultural sustainability and possible roles of simulation modelling for characterising sustainability were explored by conducting, and reflecting on, a sustainability assessment of rain-fed wheat-based systems in the Middle East and North Africa region. We designed a goal-oriented, model-based framework using the cropping systems model Agricultural Production Systems sIMulator (APSIM). For the assessment, valid (rather than true or false) sustainability goals and indicators were identified for the target system. System-specific vagueness was depicted in sustainability polygons-a system property derived from highly quantitative data-and denoted using descriptive quantifiers. Diagnostic evaluations of alternative tillage practices demonstrated the utility of the framework to quantify key bio-physical and chemical constraints to sustainability. Here, we argue that sustainability is a vague, emergent system property of often wicked complexity that arises out of more fundamental elements and processes. A 'wicked concept of sustainability' acknowledges the breadth of the human experience of sustainability, which cannot be internalised in a model. To achieve socially desirable sustainability goals, our model-based approach can inform reflective evaluation processes that connect with the needs and values of agricultural decision-makers. Hence, it can help to frame meaningful discussions, from which actions might emerge.

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The root-lesion nematode, Pratylenchus thornei, can reduce wheat yields by >50%. Although this nematode has a broad host range, crop rotation can be an effective tool for its management if the host status of crops and cultivars is known. The summer crops grown in the northern grain region of Australia are poorly characterised for their resistance to P. thornei and their role in crop sequencing to improve wheat yields. In a 4-year field experiment, we prepared plots with high or low populations of P. thornei by growing susceptible wheat or partially resistant canaryseed (Phalaris canariensis); after an 11-month, weed-free fallow, several cultivars of eight summer crops were grown. Following another 15-month, weed-free fallow, P. thornei-intolerant wheat cv. Strzelecki was grown. Populations of P. thornei were determined to 150 cm soil depth throughout the experiment. When two partially resistant crops were grown in succession, e.g. canaryseed followed by panicum (Setaria italica), P. thornei populations were <739/kg soil and subsequent wheat yields were 3245 kg/ha. In contrast, after two susceptible crops, e.g. wheat followed by soybean, P. thornei populations were 10 850/kg soil and subsequent wheat yields were just 1383 kg/ha. Regression analysis showed a linear, negative response of wheat biomass and grain yield with increasing P. thornei populations and a predicted loss of 77% for biomass and 62% for grain yield. The best predictor of wheat yield loss was P. thornei populations at 0-90 cm soil depth. Crop rotation can be used to reduce P. thornei populations and increase wheat yield, with greatest gains being made following two partially resistant crops grown sequentially.

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In irrigated cropping, as with any other industry, profit and risk are inter-dependent. An increase in profit would normally coincide with an increase in risk, and this means that risk can be traded for profit. It is desirable to manage a farm so that it achieves the maximum possible profit for the desired level of risk. This paper identifies risk-efficient cropping strategies that allocate land and water between crop enterprises for a case study of an irrigated farm in Southern Queensland, Australia. This is achieved by applying stochastic frontier analysis to the output of a simulation experiment. The simulation experiment involved changes to the levels of business risk by systematically varying the crop sowing rules in a bioeconomic model of the case study farm. This model utilises the multi-field capability of the process based Agricultural Production System Simulator (APSIM) and is parameterised using data collected from interviews with a collaborating farmer. We found sowing rules that increased the farm area sown to cotton caused the greatest increase in risk-efficiency. Increasing maize area also improved risk-efficiency but to a lesser extent than cotton. Sowing rules that increased the areas sown to wheat reduced the risk-efficiency of the farm business. Sowing rules were identified that had the potential to improve the expected farm profit by ca. $50,000 Annually, without significantly increasing risk. The concept of the shadow price of risk is discussed and an expression is derived from the estimated frontier equation that quantifies the trade-off between profit and risk.

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Pratylenchus thornei is a major pathogen of wheat crops in the northern grain region of Eastern Australia with an estimated annual yield loss of $38 million. Damaged crops show symptoms of water and nutrient stress that suggest uptake is significantly affected. In order to understand the mechanisms involved in reducing water uptake and consequently plant yield, detailed measurements of water extraction and leaf area were conducted on a range of wheat cultivars with differing levels of tolerance and resistance to P. thornei.

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Climate projections over the next two to four decades indicate that most of Australia’s wheat-belt is likely to become warmer and drier. Here we used a shire scale, dynamic stress-index model that accounts for the impacts of rainfall and temperature on wheat yield, and a range of climate change projections from global circulation models to spatially estimate yield changes assuming no adaptation and no CO2 fertilisation effects. We modelled five scenarios, a baseline climate (climatology, 1901–2007), and two emission scenarios (“low” and “high” CO2) for two time horizons, namely 2020 and 2050. The potential benefits from CO2 fertilisation were analysed separately using a point level functional simulation model. Irrespective of the emissions scenario, the 2020 projection showed negligible changes in the modelled yield relative to baseline climate, both using the shire or functional point scale models. For the 2050-high emissions scenario, changes in modelled yield relative to the baseline ranged from −5 % to +6 % across most of Western Australia, parts of Victoria and southern New South Wales, and from −5 to −30 % in northern NSW, Queensland and the drier environments of Victoria, South Australia and in-land Western Australia. Taking into account CO2 fertilisation effects across a North–south transect through eastern Australia cancelled most of the yield reductions associated with increased temperatures and reduced rainfall by 2020, and attenuated the expected yield reductions by 2050.

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Key message: QTLidentified for seedling and adult plant crown rot resistance in four partially resistant hexaploid wheat sources. PCR-based markers identified for use in marker-assisted selection. Abstract: Crown rot, caused by Fusarium pseudograminearum, is an important disease of wheat in many wheat-growing regions globally. Complete resistance to infection by F. pseudograminearum has not been observed in a wheat host, but germplasm with partial resistance to this pathogen has been identified. The partially resistant wheat hexaploid germplasm sources 2-49, Sunco, IRN497 and CPI133817 were investigated in both seedling and adult plant field trials to identify markers associated with the resistance which could be used in marker-assisted selection programs. Thirteen different quantitative trait loci (QTL) conditioning crown rot resistance were identified in the four different sources. Some QTL were only observed in seedling trials whereas others appeared to be adult plant specific. For example while the QTL on chromosomes 1AS, 1BS, and 4BS contributed by 2-49 and on 2BS contributed by Sunco were detected in both seedling and field trials, the QTL on 1DL present in 2-49 and the QTL on 3BL in IRN497 were only detected in seedling trials. Genetic correlations between field trials of the same population were strong, as were correlations between seedling trials of the same population. Low to moderate correlations were observed between seedling and field trials. Flanking markers, most of which are less than 10 cM apart, have now been identified for each of the regions associated with crown rot resistance.

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Reducing crop row spacing and delaying time of weed emergence may provide crops a competitive edge over weeds. Field experiments were conducted to evaluate the effects of crop row spacing (11, 15, and 23-cm) and weed emergence time (0, 20, 35, 45, 55, and 60 days after wheat emergence; DAWE) on Galium aparine and Lepidium sativum growth and wheat yield losses. Season-long weed-free and crop-free treatments were also established to compare wheat yield and weed growth, respectively. Row spacing and weed emergence time significantly affected the growth of both weed species and wheat grain yields. For both weed species, the maximum plant height, shoot biomass, and seed production were observed in the crop-free plots, and delayed emergence decreased these variables. In weed-crop competition plots, maximum weed growth was observed when weeds emerged simultaneously with the crop in rows spaced 23-cm apart. Less growth of both weed species was observed in narrow row spacing (11-cm) of wheat as compared with wider rows (15 and 23-cm). These weed species produced less than 5 seeds plant-1 in 11-cm wheat rows when they emerged at 60 DAWE. Presence of weeds in the crop especially at early stages was devastating for wheat yields. Therefore, maximum grain yield (4.91tha-1) was recorded in the weed-free treatment at 11-cm row spacing. Delay in time of weed emergence and narrow row spacing reduced weed growth and seed production and enhanced wheat grain yield, suggesting that these strategies could contribute to weed management in wheat.

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Pratylenchus thornei is a major pathogen of wheat in Australia. Two glasshouse experiments with four wheat cultivars that had different final populations (Pf) of P. thornei in the field were used to optimise conditions for assessing resistance. With different initial populations (Pi) ranging up to 5250 P. thornei/kg soil, Pf of P. thornei increased to 16 weeks after sowing, and then decreased at 20 weeks in some cultivar x Pi combinations. The population dynamics of P. thornei up to 16 weeks were best described by a modified exponential equation P f (t) = aP i e kt where P f (t) is the final population density at time t, P i is the initial population density, a is the proportion of P i that initiates population development, and k is the intrinsic rate of increase of the population. The cultivar GS50a had very low k values at Pi of 5250 and 1050 indicating its resistance, Suneca and Potam had high k values indicating susceptibility, whereas intolerant Gatcher had a low value at the higher Pi and a high value at the lower Pi. Nitrate fertiliser increased plant growth and Pf values of susceptible cultivars, but in unplanted soil it decreased Pf. Nematicide (aldicarb 5 mg/kg soil) killed P. thornei more effectively in planted than in unplanted soil and increased plant growth particularly in the presence of N fertiliser. In both experiments, the wheat cultivars Suneca and Potam were more susceptible than the cultivar GS50a reflecting field results. The method chosen to discriminate wheat cultivars was to assess Pf after growth for 16 weeks in soil with Pi ~1050–5250 P. thornei/kg soil and fertilised with 200 mg NO3–N/kg soil.

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Assessing the impacts of climate variability on agricultural productivity at regional, national or global scale is essential for defining adaptation and mitigation strategies. We explore in this study the potential changes in spring wheat yields at Swift Current and Melfort, Canada, for different sowing windows under projected climate scenarios (i.e., the representative concentration pathways, RCP4.5 and RCP8.5). First, the APSIM model was calibrated and evaluated at the study sites using data from long term experimental field plots. Then, the impacts of change in sowing dates on final yield were assessed over the 2030-2099 period with a 1990-2009 baseline period of observed yield data, assuming that other crop management practices remained unchanged. Results showed that the performance of APSIM was quite satisfactory with an index of agreement of 0.80, R2 of 0.54, and mean absolute error (MAE) and root mean square error (RMSE) of 529 kg/ha and 1023 kg/ha, respectively (MAE = 476 kg/ha and RMSE = 684 kg/ha in calibration phase). Under the projected climate conditions, a general trend in yield loss was observed regardless of the sowing window, with a range from -24 to -94 depending on the site and the RCP, and noticeable losses during the 2060s and beyond (increasing CO2 effects being excluded). Smallest yield losses obtained through earlier possible sowing date (i.e., mid-April) under the projected future climate suggested that this option might be explored for mitigating possible adverse impacts of climate variability. Our findings could therefore serve as a basis for using APSIM as a decision support tool for adaptation/mitigation options under potential climate variability within Western Canada.