61 resultados para Oilseed crop

em eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry


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Background: Cultivated peanut or groundnut (Arachis hypogaea L.) is the fourth most important oilseed crop in the world, grown mainly in tropical, subtropical and warm temperate climates. Due to its origin through a single and recent polyploidization event, followed by successive selection during breeding efforts, cultivated groundnut has a limited genetic background. In such species, microsatellite or simple sequence repeat (SSR) markers are very informative and useful for breeding applications. The low level of polymorphism in cultivated germplasm, however, warrants a need of larger number of polymorphic microsatellite markers for cultivated groundnut. Results: A microsatellite- enriched library was constructed from the genotype TMV2. Sequencing of 720 putative SSR-positive clones from a total of 3,072 provided 490 SSRs. 71.2% of these SSRs were perfect type, 13.1% were imperfect and 15.7% were compound. Among these SSRs, the GT/CA repeat motifs were the most common (37.6%) followed by GA/CT repeat motifs (25.9%). The primer pairs could be designed for a total of 170 SSRs and were optimized initially on two genotypes. 104 (61.2%) primer pairs yielded scorable amplicon and 46 (44.2%) primers showed polymorphism among 32 cultivated groundnut genotypes. The polymorphic SSR markers detected 2 to 5 alleles with an average of 2.44 per locus. The polymorphic information content (PIC) value for these markers varied from 0.12 to 0.75 with an average of 0.46. Based on 112 alleles obtained by 46 markers, a phenogram was constructed to understand the relationships among the 32 genotypes. Majority of the genotypes representing subspecies hypogaea were grouped together in one cluster, while the genotypes belonging to subspecies fastigiata were grouped mainly under two clusters. Conclusion. Newly developed set of 104 markers extends the repertoire of SSR markers for cultivated groundnut. These markers showed a good level of PIC value in cultivated germplasm and therefore would be very useful for germplasm analysis, linkage mapping, diversity studies and phylogenetic relationships in cultivated groundnut as well as related Arachis species.

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Cultivated groundnut (Arachis hypogaea L.) is an agronomically and economically important oilseed crop grown extensively throughout the semi-arid tropics of Asia, Africa and Latin America. Rust (Puccinia arachidis) and late leaf spot (LLS, Phaseoisariopsis personata) are among the major diseases causing significant yield loss in groundnut. The development of varieties with high levels of resistance has been constrained by adaptation of disease isolates to resistance sources and incomplete resistance in resistant sources. Despite the wide range of morphological diversity observed in the cultivated groundnut gene pool, molecular marker analyses have thus far been unable to detect a parallel level of genetic diversity. However, the recent development of simple sequence repeat (SSR) markers presents new opportunities for molecular diversity analysis of cultivate groundnut. The current study was conducted to identify diverse disease resistant germplasm for the development of mapping populations and for their introduction into breeding programs. Twenty-three SSRs were screened across 22 groundnut genotypes with differing levels of resistance to rust and LLS. Overall, 135 alleles across 23 loci were observed in the 22 genotypes screened. Twelve of the 23 SSRs (52%) showed a high level of polymorphism, with PIC values ≥0.5. This is the first report detecting such high levels of genetic polymorphism in cultivated groundnut. Multi-dimensional scaling and cluster analyses revealed three well-separated groups of genotypes. Locus by locus AMOVA and Kruskal-Wallis one-way ANOVA identified candidate SSR loci that may be valuable for mapping rust and LLS resistance. The molecular diversity analysis presented here provides valuable information for groundnut breeders designing strategies for incorporating and pyramiding rust and late leaf spot resistances and for molecular biologists wishing to create recombinant inbred line populations to map these traits.

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Northern Australian dairy farms have a large area of tropical dryland grass pasture available for use as summer pastures. Late summer-autumn in sub-tropical Australia is traditionally a difficult period in which to produce milk because of the decline in both quality and quantity of tropical grasses (Ehrlich et al. 1994). Options to improve autumn feed on dairy farms include introducing forage crops and conservation, increasing concentrate feeding and introducing legumes. Perennial tropical legumes have not been successful at this time of year because of their inability to sustain stocking rates above one cow/ha. This experiment, conducted on farms, was designed to test if annual crop legumes could be successfully oversown into tropical grass areas using minimal till methods to measure the subsequent impact on milk production on farms. Previous experiments using annual legumes in plots at Mutdapilly Research Station had demonstrated yields up to 10 t/ha can be achieved using annual tropical legumes with protein levels as high as 20% in the whole legume plant. Animal production for a consuming world : proceedings of 9th Congress of the Asian-Australasian Association of Animal Production Societies [AAAP] and 23rd Biennial Conference of the Australian Society of Animal Production [ASAP] and 17th Annual Symposium of the University of Sydney, Dairy Research Foundation, [DRF]. 2-7 July 2000, Sydney, Australia.

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Traps baited with synthetic aggregation pheromone and fermenting bread dough were used to monitor seasonal incidence and abundance of the ripening fruit pests, Carpophilus hemipterus (L.), C. mutilatus Erichson and C. davidsoni Dobson in stone fruit orchards in the Leeton district of southern New South Wales during five seasons (1991-96). Adult beetles were trapped from September-May, but abundance varied considerably between years with the amount of rainfall in December-January having a major influence on population size and damage potential during the canning peach harvest (late February-March). Below average rainfall in December-January was associated with mean trap catches of < 10 beetles/trap/week in low dose pheromone traps during the harvest period in 1991/92 and 1993/94 and no reported damage to ripening fruit. Rainfall in December-January 1992/93 was more than double the average and mean trap catches ranged from 8-27 beetles/week during the harvest period with substantial damage to the peach crop. December-January rainfall was also above average in 1994/95 and 1995/96 and means of 50-300 beetles/trap/week were recorded in high dose pheromone traps during harvest periods. Carpophilus spp. caused economic damage to peach crops in both seasons. These data indicate that it may be possible to predict the likelihood of Carpophilus beetle damage to ripening stone fruit in inland areas of southern Australia, by routine pheromone-based monitoring of beetle populations and summer temperatures and rainfall.

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Australian researchers have been developing robust yield estimation models, based mainly on the crop growth response to water availability during the crop season. However, knowledge of spatial distribution of yields within and across the production regions can be improved by the use of remote sensing techniques. Images of Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices, available since 1999, have the potential to contribute to crop yield estimation. The objective of this study was to analyse the relationship between winter crop yields and the spectral information available in MODIS vegetation index images at the shire level. The study was carried out in the Jondaryan and Pittsworth shires, Queensland , Australia . Five years (2000 to 2004) of 250m resolution, 16-day composite of MODIS Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) images were used during the winter crop season (April to November). Seasonal variability of the profiles of the vegetation index images for each crop season using different regions of interest (cropping mask) were displayed and analysed. Correlation analysis between wheat and barley yield data and MODIS image values were also conducted. The results showed high seasonal variability in the NDVI and EVI profiles, and the EVI values were consistently lower than those of the NDVI. The highest image values were observed in 2003 (in contrast to 2004), and were associated with rainfall amount and distribution. The seasonal variability of the profiles was similar in both shires, with minimum values in June and maximum values at the end of August. NDVI and EVI images showed sensitivity to seasonal variability of the vegetation and exhibited good association (e.g. r = 0.84, r = 0.77) with winter crop yields.

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Prediction of the initiation, appearance and emergence of leaves is critically important to the success of simulation models of crop canopy development and some aspects of crop ontogeny. Data on leaf number and crop ontogeny were collected on five cultivars of maize differing widely in maturity and genetic background grown under natural and extended photoperiods, and planted on seven sowing dates from October 1993 to March 1994 at Gatton, South-east Queensland. The same temperature coefficients were established for crop ontogeny before silking, and the rates of leaf initiation, leaf tip appearance and full leaf expansion, the base, optimum and maximum temperatures for each being 8, 34 and 40 degrees C. After silking, the base temperature for ontogeny was 0 degrees C, but the optimum and maximum temperatures remained unchanged. The rates of leaf initiation, appearance of leaf tips and full leaf expansion varied in a relatively narrow range across sowing times and photoperiod treatments, with average values of 0.040 leaves (degrees Cd)-1, 0.021 leaves (degrees Cd)-1, and 0.019 leaves (degrees Cd)-1, respectively. The relationships developed in this study provided satisfactory predictions of leaf number and crop ontogeny (tassel initiation to silking, emergence to silking and silking to physiological maturity) when assessed using independent data from Gatton (South eastern Queensland), Katherine and Douglas Daly (Northern Territory), Walkamin (North Queensland) and Kununurra (Western Australia).

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Physiological and genetic studies of leaf growth often focus on short-term responses, leaving a gap to whole-plant models that predict biomass accumulation, transpiration and yield at crop scale. To bridge this gap, we developed a model that combines an existing model of leaf 6 expansion in response to short-term environmental variations with a model coordinating the development of all leaves of a plant. The latter was based on: (1) rates of leaf initiation, appearance and end of elongation measured in field experiments; and (2) the hypothesis of an independence of the growth between leaves. The resulting whole-plant leaf model was integrated into the generic crop model APSIM which provided dynamic feedback of environmental conditions to the leaf model and allowed simulation of crop growth at canopy level. The model was tested in 12 field situations with contrasting temperature, evaporative demand and soil water status. In observed and simulated data, high evaporative demand reduced leaf area at the whole-plant level, and short water deficits affected only leaves developing during the stress, either visible or still hidden in the whorl. The model adequately simulated whole-plant profiles of leaf area with a single set of parameters that applied to the same hybrid in all experiments. It was also suitable to predict biomass accumulation and yield of a similar hybrid grown in different conditions. This model extends to field conditions existing knowledge of the environmental controls of leaf elongation, and can be used to simulate how their genetic controls flow through to yield.

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The parasitic weed Orobanche crenata inflicts major damage on faba bean, lentil, pea and other crops in Mediterranean environments. The development of methods to control O. crenata is to a large extent hampered by the complexity of host-parasite systems. Using a model of host-parasite interactions can help to explain and understand this intricacy. This paper reports on the evaluation and application of a model simulating host-parasite competition as affected by environment and management that was implemented in the framework of the Agricultural Production Systems Simulator (APSIM). Model-predicted faba bean and O. crenata growth and development were evaluated against independent data. The APSIM-Fababean and -Parasite modules displayed a good capability to reproduce effects of pedoclimatic conditions, faba bean sowing date and O. crenata infestation on host-parasite competition. The r(2) values throughout exceeded 0.84 (RMSD: 5.36 days) for phenological, 0.85 (RMSD: 223.00 g m(-2)) for host growth and 0.78 (RMSD: 99.82 g m(-2)) for parasite growth parameters. Inaccuracies of simulated faba bean root growth that caused some bias of predicted parasite number and host yield loss may be dealt with by more flexibly simulating vertical root distribution. The model was applied in simulation experiments to determine optimum sowing windows for infected and non-infected faba bean in Mediterranean environments. Simulation results proved realistic and testified to the capability of APSIM to contribute to the development of tactical approaches in parasitic weed control.

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Background: Both sorghum (Sorghum bicolor) and sugarcane (Saccharum officinarum) are members of the Andropogoneae tribe in the Poaceae and are each other's closest relatives amongst cultivated plants. Both are relatively recent domesticates and comparatively little of the genetic potential of these taxa and their wild relatives has been captured by breeding programmes to date. This review assesses the genetic gains made by plant breeders since domestication and the progress in the characterization of genetic resources and their utilization in crop improvement for these two related species. Genetic Resources: The genome of sorghum has recently been sequenced providing a great boost to our knowledge of the evolution of grass genomes and the wealth of diversity within S. bicolor taxa. Molecular analysis of the Sorghum genus has identified close relatives of S. bicolor with novel traits, endosperm structure and composition that may be used to expand the cultivated gene pool. Mutant populations (including TILLING populations) provide a useful addition to genetic resources for this species. Sugarcane is a complex polyploid with a large and variable number of copies of each gene. The wild relatives of sugarcane represent a reservoir of genetic diversity for use in sugarcane improvement. Techniques for quantitative molecular analysis of gene or allele copy number in this genetically complex crop have been developed. SNP discovery and mapping in sugarcane has been advanced by the development of high-throughput techniques for ecoTILLING in sugarcane. Genetic linkage maps of the sugarcane genome are being improved for use in breeding selection. The improvement of both sorghum and sugarcane will be accelerated by the incorporation of more diverse germplasm into the domesticated gene pools using molecular tools and the improved knowledge of these genomes.

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Synthetic backcrossed-derived bread wheats (SBWs) from CIMMYT were grown in the north-west of Mexico (CIANO) and sites across Australia during 3 seasons. A different set of lines was evaluated each season, as new materials became available from the CIMMYT crop enhancement program. Previously, we have evaluated both the performance of genotypes across environments and the genotype x environment interaction (G x E). The objective of this study was to interpret the G x E for yield in terms of crop attributes measured at individual sites and to identify the potential environmental drivers of this interaction. Groups of SBWs with consistent yield performance were identified, often comprising closely related lines. However, contrasting performance was also relatively common among sister lines or between a recurrent parent and its SBWs. Early flowering was a common feature among lines with broad adaptation and/or high yield in the northern Australian wheatbelt, while yields in the southern region did not show any association with the maturity type. Lines with high yields in the southern and northern regions had cooler canopies during flowering and early grain filling. Among the SBWs with Australian genetic backgrounds, lines best adapted to CIANO were tall (>100 cm), with a slightly higher ground cover. These lines also displayed a higher concentration of water-soluble carbohydrates in the stem at flowering, which was negatively correlated with stem number per unit area when evaluated in southern Australia (Horsham). Possible reasons for these patterns are discussed. Selection for yield at CIANO did not specifically identify the lines best adapted to northern Australia, although they were not the most poorly adapted either. In addition, groups of lines with specific adaptation to the south would not have been selected by choosing the highest yielding lines at CIANO. These findings suggest that selection at CIMMYT for Australian environments may be improved by either trait based selection or yield data combined with trait information. Flowering date, canopy temperature around flowering, tiller density, and water-soluble carbohydrate concentration in the stem at flowering seem likely candidates.

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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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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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Single or multiple factors implicated in subsoil constraints including salinity, sodicity, and phytotoxic concentrations of chloride (Cl) are present in many Vertosols including those occurring in Queensland, Australia. The variable distribution and the complex interactions that exist between these constraints limit the agronomic or management options available to manage the soil with these subsoil constraints. The identification of crops and cultivars adapted to these adverse subsoil conditions and/or able to exploit subsoil water may be an option to maintain productivity of these soils. We evaluated relative performance of 5 winter crop species, in terms of grain yields, nutrient concentration, and ability to extract soil water, grown on soils with various levels and combinations of subsoil constraints in 19 field experiments over 2 years. Subsoil constraints were measured by levels of soil Cl, electrical conductivity of the saturation extract (ECse), and exchangeable sodium percentage (ESP). Increasing levels of subsoil constraints significantly decreased maximum depth of water extraction, grain yield, and plant-available water capacity for all the 5 crops and more so for chickpea and durum wheat than bread wheat, barley, or canola. Increasing soil Cl levels had a greater restricting effect on water availability than did ECse and ESP. We developed empirical relationships between soil Cl, ECse, and ESP and crop lower limit (CLL) for estimating subsoil water extraction by 5 winter crops. However, the presence of gypsum influenced the ability to predict CLL based on the levels of ECse. Stronger relationships between apparent unused plant-available water (CLL - LL15; LL15 is lower limit at -1.5 MPa) and soil Cl concentrations than ESP or ECse suggested that the presence of high Cl in these soils most likely inhibited the subsoil water extraction by the crops. This was supported by increased sodium (Na) and Cl concentration with a corresponding decrease in calcium (Ca) and potassium (K) in young mature leaf of bread wheat, durum wheat, and chickpea with increasing levels of subsoil constraints. Of the 2 ions, Na and Cl, the latter appears to be more damaging than the former, resulting in plant dieback and reduced grain yields.

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We tested the capacity of several published multispectral indices to estimate the nitrogen nutrition of wheat canopies grown under different levels of water supply and plant density and derived a simple canopy reflectance index that is greatly independent of those factors. Planar domain geometry was used to account for mixed signals from the canopy and soil when the ground cover was low. A nitrogen stress index was developed, which adjusts shoot %N for plant biomass and area, thereby accounting for environmental conditions that affect growth, such as crop water status. The canopy chlorophyll content index (CCCi) and the modified spectral ratio planar index (mSRPi) could explain 68 and 69% of the observed variability in the nitrogen nutrition of the crop as early as Zadoks 33, irrespective of water status or ground cover. The CCCi was derived from the combination of 3 wavebands 670, 720 and 790 nm, and the mSRPi from 445, 705 and 750 nm, together with broader bands in the NIR and RED. The potential for their spatial application over large fields/paddocks is discussed.

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Dwindling water supplies for irrigation are prompting alternative management choices by irrigators. Limited irrigation, where less water is applied than full crop demand, may be a viable approach. Application of limited irrigation to corn was examined in this research. Corn was grown in crop rotations with dryland, limited irrigation, or full irrigation management from 1985 to 1999. Crop rotations included corn following corn (continuous corn), corn following wheat, followed by soybean (wheat-corn-soybean), and corn following soybean (corn-soybean). Full irrigation was managed to meet crop evapotranspiration requirements (ETc). Limited irrigation was managed with a seasonal target of no more than 150 mm applied. Precipitation patterns influenced the outcomes of measured parameters. Dryland yields had the most variation, while fully irrigated yields varied the least. Limited irrigation yields were 80% to 90%> of fully irrigated yields, but the limited irrigation plots received about half the applied water. Grain yields were significantly different among irrigation treatments. Yields were not significantly different among rotation treatments for all years and water treatments. For soil water parameters, more statistical differences were detected among the water management treatments than among the crop rotation treatments. Economic projections of these management practices showed that full irrigation produced the most income if water was available. Limited irrigation increased income significantly from dryland management.