19 resultados para Environments

em eResearch Archive - Queensland Department of Agriculture


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Variable-rate technologies and site-specific crop nutrient management require real-time spatial information about the potential for response to in-season crop management interventions. Thermal and spectral properties of canopies can provide relevant information for non-destructive measurement of crop water and nitrogen stresses. In previous studies, foliage temperature was successfully estimated from canopy-scale (mixed foliage and soil) temperatures and the multispectral Canopy Chlorophyll Content Index (CCCI) was effective in measuring canopy-scale N status in rainfed wheat (Triticum aestivum L.) systems in Horsham, Victoria, Australia. In the present study, results showed that under irrigated wheat systems in Maricopa, Arizona, USA, the theoretical derivation of foliage temperature unmixing produced relationships similar to those in Horsham. Derivation of the CCCI led to an r2 relationship with chlorophyll a of 0.53 after Zadoks stage 43. This was later than the relationship (r2 = 0.68) developed for Horsham after Zadoks stage 33 but early enough to be used for potential mid-season N fertilizer recommendations. Additionally, ground-based hyperspectral data estimated plant N (g kg)1) in Horsham with an r2 = 0.86 but was confounded by water supply and N interactions. By combining canopy thermal and spectral properties, varying water and N status can potentially be identified eventually permitting targeted N applications to those parts of a field where N can be used most efficiently by the crop.

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Wheat is one of the major food crops in the world. It is Australia's largest crop and most important agricultural commodity. In Australia the crop is grown under rainfed conditions with inherently important regional environmental differences; wheat growing areas are characterized by winter dominant rainfall in southern and western Australia and summer rainfall in northern Australia. Maximizing yield potential across these diverse regions is dependent upon managing, either genetically or agronomically, those factors in the environment that limit yield. The potential of synthetic backcross lines (SBLs) to increase yield in the diverse agroecological zones of Australia was investigated. Significant yield advantages were found for many of the SBLs across diverse environments. Depending on the environment, the yield of the SBLs ranged from 8% to 30% higher than the best local check in Australia. Apart from adaptation to semiarid water stressed conditions, some SBLs were also found to be significantly higher yielding under more optimal (irrigated) conditions. The four testing environments were classified into two groups, with the northern and southern environments being in separate groups. An elite group of SBLs was identified that exhibited broad adaptation across all diverse Australian environments included in this study. Other SBLs showed specific adaptation to either northern or southern Australia. This study showed that SBLs are likely to provide breeders with the opportunity to significantly improve wheat yield beyond what was previously possible in a number of diverse production environments.

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Synthetic backcrossed-derived bread wheats (SBWs) from CIMMYT were grown in the Northwest of Mexico at Centro de Investigaciones Agrícolas del Noroeste (CIANO) and sites across Australia during three seasons. During three consecutive years Australia received “shipments” of different SBWs from CIMMYT for evaluation. A different set of lines was evaluated each season, as new materials became available from the CIMMYT crop enhancement program. These consisted of approximately 100 advanced lines (F7) per year. SBWs had been top and backcrossed to CIMMYT cultivars in the first two shipments and to Australian wheat cultivars in the third one. At CIANO, the SBWs were trialled under receding soil moisture conditions. We evaluated both the performance of each line across all environments and the genotype-by-environment interaction using an analysis that fits a multiplicative mixed model, adjusted for spatial field trends. Data were organised in three groups of multienvironment trials (MET) containing germplasm from shipment 1 (METShip1), 2 (METShip2), and 3 (METShip3), respectively. Large components of variance for the genotype × environment interaction were found for each MET analysis, due to the diversity of environments included and the limited replication over years (only in METShip2, lines were tested over 2 years). The average percentage of genetic variance explained by the factor analytic models with two factors was 50.3% for METShip1, 46.7% for METShip2, and 48.7% for METShip3. Yield comparison focused only on lines that were present in all locations within a METShip, or “core” SBWs. A number of core SBWs, crossed to both Australian and CIMMYT backgrounds, outperformed the local benchmark checks at sites from the northern end of the Australian wheat belt, with reduced success at more southern locations. In general, lines that succeeded in the north were different from those in the south. The moderate positive genetic correlation between CIANO and locations in the northern wheat growing region likely reflects similarities in average temperature during flowering, high evaporative demand, and a short flowering interval. We are currently studying attributes of this germplasm that may contribute to adaptation, with the aim of improving the selection process in both Mexico and Australia.

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Light interception is a major factor influencing plant development and biomass production. Several methods have been proposed to determine this variable, but its calculation remains difficult in artificial environments with heterogeneous light. We propose a method that uses 3D virtual plant modelling and directional light characterisation to estimate light interception in highly heterogeneous light environments such as growth chambers and glasshouses. Intercepted light was estimated by coupling an architectural model and a light model for different genotypes of the rosette species Arabidopsis thaliana (L.) Heynh and a sunflower crop. The model was applied to plants of contrasting architectures, cultivated in isolation or in canopy, in natural or artificial environments, and under contrasting light conditions. The model gave satisfactory results when compared with observed data and enabled calculation of light interception in situations where direct measurements or classical methods were inefficient, such as young crops, isolated plants or artificial conditions. Furthermore, the model revealed that A. thaliana increased its light interception efficiency when shaded. To conclude, the method can be used to calculate intercepted light at organ, plant and plot levels, in natural and artificial environments, and should be useful in the investigation of genotype-environment interactions for plant architecture and light interception efficiency. This paper originates from a presentation at the 5th International Workshop on Functional–Structural Plant Models, Napier, New Zealand, November 2007.

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Better understanding of root system structure and function is critical to crop improvement in water-limited environments. The aims of this study were to examine root system characteristics of two wheat genotypes contrasting in tolerance to water limitation and to assess the functional implications on adaptation to water-limited environments of any differences found. The drought tolerant barley variety, Mackay, was also included to allow inter-species comparison. Single plants were grown in large, soil-filled root-observation chambers. Root growth was monitored by digital imaging and water extraction was measured. Root architecture differed markedly among the genotypes. The drought-tolerant wheat (cv. SeriM82) had a compact root system, while roots of barley cv. Mackay occupied the largest soil volume. Relative to the standard wheat variety (Hartog), SeriM82 had a more uniform rooting pattern and greater root length at depth. Despite the more compact root architecture of SeriM82, total water extracted did not differ between wheat genotypes. To quantify the value of these adaptive traits, a simulation analysis was conducted with the cropping system model APSIM, for a wide range of environments in southern Queensland, Australia. The analysis indicated a mean relative yield benefit of 14.5% in water-deficit seasons. Each additional millimetre of water extracted during grain filling generated an extra 55 kg ha-1 of grain yield. The functional implications of root traits on temporal patterns and total amount of water capture, and their importance in crop adaptation to specific water-limited environments, are discussed.

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Time to first root in cuttings varies under different environmental conditions and understanding these differences is critical for optimizing propagation of commercial forestry species. Temperature environment (15, 25, 30 or 35 +/- A 2A degrees C) had no effect on the cellular stages in root formation of the Slash x Caribbean Pine hybrid over 16 weeks as determined by histology. Initially callus cells formed in the cortex, then tracheids developed and formed primordia leading to external roots. However, speed of development followed a growth curve with the fastest development occurring at 25A degrees C and slowest at 15A degrees C with rooting percentages at week 12 of 80 and 0% respectively. Cutting survival was good in the three cooler temperature regimes (> 80%) but reduced to 59% at 35A degrees C. Root formation appeared to be dependant on the initiation of tracheids because all un-rooted cuttings had callus tissue but no tracheids, irrespective of temperature treatment and clone.

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Time to first root in cuttings varies under different environmental conditions and understanding these differences is critical for optimizing propagation of commercial forestry species. Temperature environment (15, 25, 30 or 352C) had no effect on the cellular stages in root formation of the Slash * Caribbean Pine hybrid over 16 weeks as determined by histology. Initially callus cells formed in the cortex, then tracheids developed and formed primordia leading to external roots. However, speed of development followed a growth curve with the fastest development occurring at 25C and slowest at 15C with rooting percentages at week 12 of 80 and 0% respectively. Cutting survival was good in the three cooler temperature regimes (>80%) but reduced to 59% at 35C. Root formation appeared to be dependant on the initiation of tracheids because all un-rooted cuttings had callus tissue but no tracheids, irrespective of temperature treatment and clone.

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QTL mapping methods for complex traits are challenged by new developments in marker technology, phenotyping platforms, and breeding methods. In meeting these challenges, QTL mapping approaches will need to also acknowledge the central roles of QTL by environment interactions (QEI) and QTL by trait interactions in the expression of complex traits like yield. This paper presents an overview of mixed model QTL methodology that is suitable for many types of populations and that allows predictive modeling of QEI, both for environmental and developmental gradients. Attention is also given to multi-trait QTL models which are essential to interpret the genetic basis of trait correlations. Biophysical (crop growth) model simulations are proposed as a complement to statistical QTL mapping for the interpretation of the nature of QEI and to investigate better methods for the dissection of complex traits into component traits and their genetic controls.

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Sperm chromatin status was assessed in 565 Zebu and Zebu crossbred beef bulls in extensive tropical environments using the sperm chromatin structure assay (SCSA). The SCSA involved exposure of sperm to acid hydrolysis for 0.5 or 5.0 minutes, followed by flow cytometry to ascertain relative amounts of double-stranded (normal) and single-stranded (denatured) DNA, which was used to generate a DNA fragmentation index (%DFI). With conventional SCSA (0.5-minute SCSA), 513 bulls (91%) had <15 %DFI, 24 bulls (4%) had 15 to 27 %DFI, and 28 bulls (5%) had >27 %DFI. In 5.0-minute SCSA, 432 bulls (76%) had <15 %DFI, 68 bulls (12%) had 15 to 27 %DFI and 65 bulls (12%) had >27 %DFI. For most bulls, the SCSA was repeatable on two to four occasions; however, because most bulls had <15 %DFI, repeatability of the SCSA will need to be determined in a larger number of bulls in the 15 to 27 %DFI and >27 %DFI categories. The %DFI was negatively correlated with several bull semen parameters and the strongest negative correlation was with normal sperm. There was a strong positive correlation between %DFI and sperm head abnormalities. Based on these findings, most Zebu beef bulls in extensive tropical environments had relatively stable sperm chromatin. Based on the apparent negative correlations with conventional semen parameters, we inferred that the SCSA measured a unique feature of sperm quality, which has also been suggested for other species. Further studies on the relationships between sperm chromatin stability and fertility are required in beef bulls before chromatin status can be used as an additional predictor of the siring capacity of individual bulls in extensive multiple-sire herds. (C) 2013 Elsevier Inc. All rights reserved.

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Recurring water stresses are a major risk factor for rainfed maize cropping across the highly diverse agro-ecological environments of Queensland (Qld) and northern New South Wales (NNSW). Enhanced understanding of such agro-ecological diversity is necessary to more consistently sample target production environments for testing and targeting release of improved germplasm, and to improve the efficiency of the maize pre-breeding and breeding programs of Qld and New South Wales. Here, we used the Agricultural Production Systems Simulator (APSIM) – a well validated maize crop model to characterize the key distinctive water stress patterns and risk to production across the main maize growing regions of Qld and NNSW located between 15.8° and 31.5°S, and 144.5° and 151.8°E. APSIM was configured to simulate daily water supply demand ratios (SDRs) around anthesis as an indicator of the degree of water stress, and the final grain yield. Simulations were performed using daily climatic records during the period between 1890 and 2010 for 32 sites-soils in the target production regions. The runs were made assuming adequate nitrogen supply for mid-season maize hybrid Pioneer 3153. Hierarchical complete linkage analyses of the simulated yield resulted in five major clusters showing distinct probability distribution of the expected yields and geographic patterns. The drought stress patterns and their frequencies using SDRs were quantified using multivariate statistical methods. The identified stress patterns included no stress, mid-season (flowering) stress, and three terminal stresses differing in terms of severity. The combined frequency of flowering and terminal stresses was highest (82.9%), mainly in sites-soils combinations in the west of Qld and NNSW. Yield variability across the different sites-soils was significantly related to the variability in frequencies of water stresses. Frequencies of water stresses within each yield cluster tended to be similar, but different across clusters. Sites-soils falling within each yield cluster therefore could be treated as distinct maize production environments for testing and targeting newly developed maize cultivars and hybrids for adaptation to water stress patterns most common to those environments.

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Root architecture traits in wheat are important in deep soil moisture acquisition and may be used to improve adaptation to water-limited environments. The genetic architecture of two root traits, seminal root angle and seminal root number, were investigated using a doubled haploid population derived from SeriM82 and Hartog. Multiple novel quantitative trait loci (QTL) were identified, each one having a modest effect. For seminal root angle, four QTL (-log10(P) >3) were identified on 2A, 3D, 6A and 6B, and two suggestive QTL (-log10(P) >2) on 5D and 6B. For root number, two QTL were identified on 4A and 6A with four suggestive QTL on 1B, 3A, 3B and 4A. QTL for root angle and root number did not co-locate. Transgressive segregation was found for both traits. Known major height and phenology loci appear to have little effect on root angle and number. Presence or absence of the T1BL.1RS translocation did not significantly influence root angle. Broad sense heritability (h 2) was estimated as 50 % for root angle and 31 % for root number. Root angle QTL were found to be segregating between wheat cultivars adapted to the target production region indicating potential to select for root angle in breeding programs. © 2013 Springer-Verlag Berlin Heidelberg.

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The stay-green drought adaptation mechanism has been widely promoted as a way of improving grain yield and lodging resistance in sorghum [Sorghum bicolor (L.) Moench] and as a result has been the subject of many physiological and genetic studies. The relevance of these studies to elite sorghum hybrids is not clear given that they sample a limited number of environments and were conducted using inbred lines or relatively small numbers of experimental F-1 hybrids. In this study we investigated the relationship between stay-green and yield using data from breeding trials that sampled 1668 unique hybrid combinations and 23 environments whose mean yields varied from 2.3 to 10.5 t ha(-1). The strength and direction of the association between stay-green and grain yield varied with both environment and genetic background (male tester). The majority of associations were positive, particularly in environments with yields below 6 t ha(-1). As trial mean yield increased above 6 t ha(-1) there was a trend toward an increased number of negative associations; however, the number and magnitude of the positive associations were larger. Given that post-flowering drought is very commonly experienced by sorghum crops world wide and average yields are 1.2 and 2.5 t ha(-1) for the world and Australia, respectively, our results indicate that selection for stay-green in elite sorghum hybrids may be broadly beneficial for increasing yield in a wide range of environments.

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Do alien invasive species exhibit life history characteristics that are similar to those of native species that have become pests in their continent of origin? We compared eucalypt specialists that have become pests in Australian plantations (natives) to those that have established overseas (aliens) using 13 life history traits and found that although traits that support rapid population build-up were shared, overall, aliens and native colonisers differed significantly. Distance from source (New Zealand vs. other) had no significant effect, but species that established more than 50 years ago exhibited different life history traits from those that established within the last 50 years, possibly because of more effective quarantine. Native and alien eucalypt insect invaders differed predominantly in traits that facilitate long-distance movement (pathway traits), compared to traits that facilitate establishment and spread. Aliens had longer adult flight seasons, were smaller and more closely host-associated (cryptic eggs and larvae), had lower incidence of diapause (i.e. were more seasonally plastic) and more generations per year than natives. Thus, studies of species invasive within their country of origin can shed light on alien invasions.

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Climatic variability in dryland production environments (E) generates variable yield and crop production risks. Optimal combinations of genotype (G) and management (M) depend strongly on E and thus vary among sites and seasons. Traditional crop improvement seeks broadly adapted genotypes to give best average performance under a standard management regime across the entire production region, with some subsequent manipulation of management regionally in response to average local environmental conditions. This process does not search the full spectrum of potential G × M × E combinations forming the adaptation landscape. Here we examine the potential value (relative to the conventional, broad adaptation approach) of exploiting specific adaptation arising from G × M × E. We present an in-silico analysis for sorghum production in Australia using the APSIM sorghum model. Crop design (G × M) is optimised for subsets of locations within the production region (specific adaptation) and is compared with the optimum G across all environments with locally modified M (broad adaptation). We find that geographic subregions that have frequencies of major environment types substantially different from that for the entire production region show greatest advantage for specific adaptation. Although the specific adaptation approach confers yield and production risk advantages at industry scale, even greater benefits should be achievable with better predictors of environment-type likelihood than that conferred by location alone.