990 resultados para plant biology


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Nucleopolyhedrovirus (NPV) has become an integral part of integrated pest management (IPM) in many Australian agricultural and horticultural crops. This is the culmination of years of work conducted by researchers at the Queensland Department of Primary Industries and Fisheries (QDPI&F) and Ag Biotech Australia Pty Ltd. In the early 1970’s researchers at QDPI&F identified and isolated a virus in Helicoverpa armigera populations in the field. This NPV was extensively studied and shown to be highly specific to Helicoverpa and Heliothis species. Further work showed that when used appropriately the virus could be used effectively to manage these insects in crops such as sorghum, cotton, chickpea and sweet corn. A similar virus was first commercially produced in the USA in the 1970’s. This product, Elcar®, was introduced into Australia in the late 1970’s by Shell Chemicals with limited success. A major factor contributing to the poor adoption of Elcar was the concurrent enormous success of the synthetic pyrethroids. The importance of integrated pest management was probably also not widely accepted at that time. Gradual development of insect resistance to synthetic pyrethroids and other synthetic insecticides in Australia and the increased awareness of the importance of IPM meant that researchers once again turned their attentions to environmentally friendly pest management tools such NPV and beneficial insects. In the 1990’s a company called Rhone-Poulenc registered an NPV for use in Australian sorghum, chickpea and cotton. This product, Gemstar®, was imported from the USA. In 2000 Ag Biotech Australia established an in-vivo production facility in Australia to produce commercial volumes of a product similar to the imported product. This product was branded, ViVUS®, and was first registered and sold commercially in Australia in 2003. The initial production of ViVUS used a virus identical to the American product but replicating it in an Australian Helicoverpa species, H. armigera. Subsequent research collaboration between QDPI&F and Ag Biotech reinvigorated interest in the local virus strain. This was purified and the production system adapted to produce it on a commercial scale. This new version of ViVUS, which was branded ViVUS Gold®, was first registered and sold commercially in 2004. Widespread insect resistance to insecticides and a greater understanding of integrated pest management is leading to increased adoption of technologies such NPV in Australian agriculture.

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• Premise of the study: Here we propose a staining protocol using TBO and Ruthenium red in order to reliably identify secondary compounds in the leaves of some species of Myrtaceae. • Methods and results: Leaves of 10 species representing 10 different genera of Myrtaceae were processed and stained using five different combinations of Ruthenium red and TBO. Optimal staining conditions were determined as 1 min of Ruthenium red (0.05% aqueous) and 45 sec of TBO (0.1% aqueous). Secondary compounds clearly identified under this treatment include mucilage in mesophyll, polyphenols in cuticle, lignin in fibers and xylem, tannins and carboxylated polysaccharides in epidermis and pectic substances in primary cell walls. • Conclusions: Potential applications of this protocol include systematic, phytochemical and ecological investigations in Myrtaceae. It might be applicable to other plant families rich in secondary compounds and could be used as preliminary screening method for extraction of these elements.

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Premise of the study: Plant invasiveness can be promoted by higher values of adaptive traits (e.g., photosynthetic capacity, biomass accumulation), greater plasticity and coordination of these traits, and by higher and positive relative influence of these functionalities on fitness, such as increasing reproductive output. However, the dataset for this premise rarely include linkages between epidermal-stomatal traits, leaf internal anatomy, and physiological performance. Methods: Three ecological pairs of invasive vs non-invasive (native) woody vine species of South-East Queensland, Australia were investigated for trait differences in leaf morphology and anatomy under varying light intensity. The linkages of these traits with physiological performance (e.g. water use efficiency, photosynthesis, and leaf construction cost) and plant adaptive traits of specific leaf area, biomass, and relative growth rates were also explored. Key results: Mean leaf anatomical trait differed significantly between the two groups, except for stomatal size. Plasticity of traits, and to a very limited extent, their phenotypic integration were higher in the invasive relative to the native species. ANOVA, ordination, and analysis of similarity suggest that for leaf morphology and anatomy, the three functional strategies contribute to the differences between the two groups in the order phenotypic plasticity > trait means > phenotypic integration. Conclusions: The linkages demonstrated in the study between stomatal complex/gross anatomy and physiology are scarce in the ecological literature of plant invasiveness, but the findings suggest that leaf anatomical traits need to be considered routinely as part of weed species assessment and in the worldwide leaf economic spectrum.

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Background Increased disease resistance is a key target of cereal breeding programs, with disease outbreaks continuing to threaten global food production, particularly in Africa. Of the disease resistance gene families, the nucleotide-binding site plus leucine-rich repeat (NBS-LRR) family is the most prevalent and ancient and is also one of the largest gene families known in plants. The sequence diversity in NBS-encoding genes was explored in sorghum, a critical food staple in Africa, with comparisons to rice and maize and with comparisons to fungal pathogen resistance QTL. Results In sorghum, NBS-encoding genes had significantly higher diversity in comparison to non NBS-encoding genes and were significantly enriched in regions of the genome under purifying and balancing selection, both through domestication and improvement. Ancestral genes, pre-dating species divergence, were more abundant in regions with signatures of selection than in regions not under selection. Sorghum NBS-encoding genes were also significantly enriched in the regions of the genome containing fungal pathogen disease resistance QTL; with the diversity of the NBS-encoding genes influenced by the type of co-locating biotic stress resistance QTL. Conclusions NBS-encoding genes are under strong selection pressure in sorghum, through the contrasting evolutionary processes of purifying and balancing selection. Such contrasting evolutionary processes have impacted ancestral genes more than species-specific genes. Fungal disease resistance hot-spots in the genome, with resistance against multiple pathogens, provides further insight into the mechanisms that cereals use in the “arms race” with rapidly evolving pathogens in addition to providing plant breeders with selection targets for fast-tracking the development of high performing varieties with more durable pathogen resistance.

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Yield in cultivated cotton (Gossypium spp.) is affected by the number and distribution of fibres initiated on the seed surface but, apart from simple statistical summaries, little has been done to assess this phenotype quantitatively. Here we use two types of spatial statistics to describe and quantify differences in patterning of cotton ovule fibre initials (FI). The following five different species of Gossypium were analysed: G. hirsutum L., G. barbadense L., G. arboreum, G. raimondii Ulbrich. and G. trilobum (DC.) Skovsted. Scanning electron micrographs of FIs were taken on the day of anthesis. Cell centres for fibre and epidermal cells were digitised and analysed by spatial statistics methods appropriate for marked point processes and tessellations. Results were consistent with previously published reports of fibre number and spacing. However, it was shown that the spatial distributions of FIs in all of species examined exhibit regularity, and are not completely random as previously implied. The regular arrangement indicates FIs do not appear independently of each other and we surmise there may be some form of mutual inhibition specifying fibre-initial development. It is concluded that genetic control of FIs differs from that of stomata, another well studied plant idioblast. Since spatial statistics show clear species differences in the distribution of FIs within this genus, they provide a useful method for phenotyping cotton. © CSIRO 2007.

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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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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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Maize (Zea mays L.) is a chill-susceptible crop cultivated in northern latitude environments. The detrimental effects of cold on growth and photosynthetic activity have long been established. However, a general overview of how important these processes are with respect to the reduction of productivity reported in the field is still lacking. In this study, a model-assisted approach was used to dissect variations in productivity under suboptimal temperatures and quantify the relative contributions of light interception (PARc) and radiation use efficiency (RUE) from emergence to flowering. A combination of architectural and light transfer models was used to calculate light interception in three field experiments with two cold-tolerant lines and at two sowing dates. Model assessment confirmed that the approach was suitable to infer light interception. Biomass production was strongly affected by early sowings. RUE was identified as the main cause of biomass reduction during cold events. Furthermore, PARc explained most of the variability observed at flowering, its relative contributions being more or less important according to the climate experienced. Cold temperatures resulted in lower PARc, mainly because final leaf length and width were significantly reduced for all leaves emerging after the first cold occurrence. These results confirm that virtual plants can be useful as fine phenotyping tools. A scheme of action of cold on leaf expansion, light interception and radiation use efficiency is discussed with a view towards helping breeders define relevant selection criteria. 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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Background: Sorghum genome mapping based on DNA markers began in the early 1990s and numerous genetic linkage maps of sorghum have been published in the last decade, based initially on RFLP markers with more recent maps including AFLPs and SSRs and very recently, Diversity Array Technology (DArT) markers. It is essential to integrate the rapidly growing body of genetic linkage data produced through DArT with the multiple genetic linkage maps for sorghum generated through other marker technologies. Here, we report on the colinearity of six independent sorghum component maps and on the integration of these component maps into a single reference resource that contains commonly utilized SSRs, AFLPs, and high-throughput DArT markers. Results: The six component maps were constructed using the MultiPoint software. The lengths of the resulting maps varied between 910 and 1528 cM. The order of the 498 markers that segregated in more than one population was highly consistent between the six individual mapping data sets. The framework consensus map was constructed using a "Neighbours" approach and contained 251 integrated bridge markers on the 10 sorghum chromosomes spanning 1355.4 cM with an average density of one marker every 5.4 cM, and were used for the projection of the remaining markers. In total, the sorghum consensus map consisted of a total of 1997 markers mapped to 2029 unique loci ( 1190 DArT loci and 839 other loci) spanning 1603.5 cM and with an average marker density of 1 marker/0.79 cM. In addition, 35 multicopy markers were identified. On average, each chromosome on the consensus map contained 203 markers of which 58.6% were DArT markers. Non-random patterns of DNA marker distribution were observed, with some clear marker-dense regions and some marker-rare regions. Conclusion: The final consensus map has allowed us to map a larger number of markers than possible in any individual map, to obtain a more complete coverage of the sorghum genome and to fill a number of gaps on individual maps. In addition to overall general consistency of marker order across individual component maps, good agreement in overall distances between common marker pairs across the component maps used in this study was determined, using a difference ratio calculation. The obtained consensus map can be used as a reference resource for genetic studies in different genetic backgrounds, in addition to providing a framework for transferring genetic information between different marker technologies and for integrating DArT markers with other genomic resources. DArT markers represent an affordable, high throughput marker system with great utility in molecular breeding programs, especially in crops such as sorghum where SNP arrays are not publicly available.

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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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Sorghum (Sorghum bicolor (L.) Moench) is grown as a dryland crop in semiarid subtropical and tropical environments where it is often exposed to high temperatures around flowering. Projected climate change is likely to increase the incidence of exposure to high temperature, with potential adverse effects on growth, development and grain yield. The objectives of this study were to explore genetic variability for the effects of high temperature on crop growth and development, in vitro pollen germination and seed-set. Eighteen diverse sorghum genotypes were grown at day : night temperatures of 32 : 21 degrees C (optimum temperature, OT) and 38 : 21 degrees C (high temperature, HT during the middle of the day) in controlled environment chambers. HT significantly accelerated development, and reduced plant height and individual leaf size. However, there was no consistent effect on leaf area per plant. HT significantly reduced pollen germination and seed-set percentage of all genotypes; under HT, genotypes differed significantly in pollen viability percentage (17-63%) and seed-set percentage (7-65%). The two traits were strongly and positively associated (R-2 = 0.93, n = 36, P < 0.001), suggesting a causal association. The observed genetic variation in pollen and seed-set traits should be able to be exploited through breeding to develop heat-tolerant varieties for future climates.

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Field evaluation of germplasm for performance under water and heat stress is challenging. Field environments are variable and unpredictable, and genotype x environment interactions are difficult to interpret if environments are not well characterised. Numerous traits, genes and quantitative trait loci have been proposed for improving performance but few have been used in variety development. This reflects the limited capacity of commercial breeding companies to screen for these traits and the absence of validation in field environments relevant to breeding companies, and because little is known about the economic benefit of selecting one particular trait over another. The value of the proposed traits or genes is commonly not demonstrated in genetic backgrounds of value to breeding companies. To overcome this disconnection between physiological trait breeding and uptake by breeding companies, three field sites representing the main environment types encountered across the Australian wheatbelt were selected to form a set of managed environment facilities (MEFs). Each MEF manages soil moisture stress through irrigation, and the effects of heat stress through variable sowing dates. Field trials are monitored continuously for weather variables and changes in soil water and canopy temperature in selected probe genotypes, which aids in decisions guiding irrigation scheduling and sampling times. Protocols have been standardised for an essential core set of measurements so that phenotyping yield and other traits are consistent across sites and seasons. MEFs enable assessment of a large number of traits across multiple genetic backgrounds in relevant environments, determine relative trait value, and facilitate delivery of promising germplasm and high value traits into commercial breeding programs.