24 resultados para root systems


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Background Plants form the base of the terrestrial food chain and provide medicines, fuel, fibre and industrial materials to humans. Vascular land plants rely on their roots to acquire the water and mineral elements necessary for their survival in nature or their yield and nutritional quality in agriculture. Major biogeochemical fluxes of all elements occur through plant roots, and the roots of agricultural crops have a significant role to play in soil sustainability, carbon sequestration, reducing emissions of greenhouse gasses, and in preventing the eutrophication of water bodies associated with the application of mineral fertilisers. ● Scope This article provides the context for a Special Issue of Annals of Botany on ‘Matching Roots to Their Environment’. It first examines how land plants and their roots evolved, describes how the ecology of roots and their rhizospheres contributes to the acquisition of soil resources, and discusses the influence of plant roots on biogeochemical cycles. It then describes the role of roots in overcoming the constraints to crop production imposed by hostile or infertile soils, illustrates root phenotypes that improve the acquisition of mineral elements and water, and discusses high-throughput methods to screen for these traits in the laboratory, glasshouse and field. Finally, it considers whether knowledge of adaptations improving the acquisition of resources in natural environments can be used to develop root systems for sustainable agriculture in the future.

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Most terrestrial plants form mutually beneficial symbioses with specific soil-borne fungi known as mycorrhiza. In a typical mycorrhizal association, fungal hyphae colonize plant roots, explore the soil beyond the rhizosphere and provide host plants with nutrients that might be chemically or physically inaccessible to root systems. Here, we combined nutritional, radioisotopic (33P) and genetic approaches to describe a plant growth promoting symbiosis between the basidiomycete fungus Austroboletus occidentalis and jarrah (Eucalyptus marginata), which has quite different characteristics. We show that the fungal partner does not colonize plant roots; hyphae are localized to the rhizosphere soil and vicinity and consequently do not transfer nutrients located beyond the rhizosphere. Transcript profiling of two high-affinity phosphate (Pi) transporter genes (EmPHT1;1 and EmPHT1;2) and hyphal-mediated 33Pi uptake suggest that the Pi uptake shifts from an epidermal to a hyphal pathway in ectomycorrhizal plants (Scleroderma sp.), similar to arbuscular mycorrhizal symbioses, whereas A. occidentalis benefits its host indirectly. The enhanced rhizosphere carboxylates are linked to growth and nutritional benefits in the novel symbiosis. This work is a starting point for detailed mechanistic studies on other basidiomycete–woody plant relationships, where a continuum between heterotrophic rhizosphere fungi and plant beneficial symbioses is likely to exist.

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Grass-based diets are of increasing social-economic importance in dairy cattle farming, but their low supply of glucogenic nutrients may limit the production of milk. Current evaluation systems that assess the energy supply and requirements are based on metabolisable energy (ME) or net energy (NE). These systems do not consider the characteristics of the energy delivering nutrients. In contrast, mechanistic models take into account the site of digestion, the type of nutrient absorbed and the type of nutrient required for production of milk constituents, and may therefore give a better prediction of supply and requirement of nutrients. The objective of the present study is to compare the ability of three energy evaluation systems, viz. the Dutch NE system, the agricultural and food research council (AFRC) ME system, and the feed into milk (FIM) ME system, and of a mechanistic model based on Dijkstra et al. [Simulation of digestion in cattle fed sugar cane: prediction of nutrient supply for milk production with locally available supplements. J. Agric. Sci., Cambridge 127, 247-60] and Mills et al. [A mechanistic model of whole-tract digestion and methanogenesis in the lactating dairy cow: model development, evaluation and application. J. Anim. Sci. 79, 1584-97] to predict the feed value of grass-based diets for milk production. The dataset for evaluation consists of 41 treatments of grass-based diets (at least 0.75 g ryegrass/g diet on DM basis). For each model, the predicted energy or nutrient supply, based on observed intake, was compared with predicted requirement based on observed performance. Assessment of the error of energy or nutrient supply relative to requirement is made by calculation of mean square prediction error (MSPE) and by concordance correlation coefficient (CCC). All energy evaluation systems predicted energy requirement to be lower (6-11%) than energy supply. The root MSPE (expressed as a proportion of the supply) was lowest for the mechanistic model (0.061), followed by the Dutch NE system (0.082), FIM ME system (0.097) and AFRCME system(0.118). For the energy evaluation systems, the error due to overall bias of prediction dominated the MSPE, whereas for the mechanistic model, proportionally 0.76 of MSPE was due to random variation. CCC analysis confirmed the higher accuracy and precision of the mechanistic model compared with energy evaluation systems. The error of prediction was positively related to grass protein content for the Dutch NE system, and was also positively related to grass DMI level for all models. In conclusion, current energy evaluation systems overestimate energy supply relative to energy requirement on grass-based diets for dairy cattle. The mechanistic model predicted glucogenic nutrients to limit performance of dairy cattle on grass-based diets, and proved to be more accurate and precise than the energy systems. The mechanistic model could be improved by allowing glucose maintenance and utilization requirements parameters to be variable. (C) 2007 Elsevier B.V. All rights reserved.

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An extensive set of machine learning and pattern classification techniques trained and tested on KDD dataset failed in detecting most of the user-to-root attacks. This paper aims to provide an approach for mitigating negative aspects of the mentioned dataset, which led to low detection rates. Genetic algorithm is employed to implement rules for detecting various types of attacks. Rules are formed of the features of the dataset identified as the most important ones for each attack type. In this way we introduce high level of generality and thus achieve high detection rates, but also gain high reduction of the system training time. Thenceforth we re-check the decision of the user-to- root rules with the rules that detect other types of attacks. In this way we decrease the false-positive rate. The model was verified on KDD 99, demonstrating higher detection rates than those reported by the state- of-the-art while maintaining low false-positive rate.

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A nonlinear general predictive controller (NLGPC) is described which is based on the use of a Hammerstein model within a recursive control algorithm. A key contribution of the paper is the use of a novel, one-step simple root solving procedure for the Hammerstein model, this being a fundamental part of the overall tuning algorithm. A comparison is made between NLGPC and nonlinear deadbeat control (NLDBC) using the same one-step nonlinear components, in order to investigate NLGPC advantages and disadvantages.

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Root nodule symbiosis (RNS) is one of the most efficient biological systems for nitrogen fixation and it occurs in 90% of genera in the Papilionoideae, the largest subfamily of legumes. Most papilionoid species show evidence of a polyploidy event occurred approximately 58 million years ago. Although polyploidy is considered to be an important evolutionary force in plants, the role of this papilionoid polyploidy event, especially its association with RNS, is not understood. In this study, we explored this role using an integrated comparative genomic approach and conducted gene expression comparisons and gene ontology enrichment analyses. The results show the following: (1) approximately a quarter of the papilionoid-polyploidy-derived duplicate genes are retained; (2) there is a striking divergence in the level of expression of gene duplicate pairs derived from the polyploidy event; and (3) the retained duplicates are frequently involved in the processes crucial for RNS establishment, such as symbiotic signalling, nodule organogenesis, rhizobial infection and nutrient exchange and transport. Thus, we conclude that the papilionoid polyploidy event might have further refined RNS and induced a more robust and enhanced symbiotic system. This conclusion partly explains the widespread occurrence of the Papilionoideae.

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Roots are important to plants for a wide variety of processes, including nutrient and water uptake, anchoring and mechanical support, storage functions, and as the major interface between the plant and various biotic and abiotic factors in the soil environment. Therefore, understanding the development and architecture of roots holds potential for the manipulation of root traits to improve the productivity and sustainability of agricultural systems and to better understand and manage natural ecosystems. While lateral root development is a traceable process along the primary root and different stages can be found along this longitudinal axis of time and development, root system architecture is complex and difficult to quantify. Here, we comment on assays to describe lateral root phenotypes and propose ways to move forward regarding the description of root system architecture, also considering crops and the environment.

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Background and Aims Root traits can be selected for crop improvement. Techniques such as soil excavations can be used to screen root traits in the field, but are limited to genotypes that are well-adapted to field conditions. The aim of this study was to compare a low-cost, high-throughput root phenotyping (HTP) technique in a controlled environment with field performance, using oilseed rape (OSR; Brassica napus) varieties. Methods Primary root length (PRL), lateral root length and lateral root density (LRD) were measured on 14-d-old seedlings of elite OSR varieties (n = 32) using a ‘pouch and wick’ HTP system (∼40 replicates). Six field experiments were conducted using the same varieties at two UK sites each year for 3 years. Plants were excavated at the 6- to 8-leaf stage for general vigour assessments of roots and shoots in all six experiments, and final seed yield was determined. Leaves were sampled for mineral composition from one of the field experiments. Key Results Seedling PRL in the HTP system correlated with seed yield in four out of six (r = 0·50, 0·50, 0·33, 0·49; P < 0·05) and with emergence in three out of five (r = 0·59, 0·22, 0·49; P < 0·05) field experiments. Seedling LRD correlated positively with leaf concentrations of some minerals, e.g. calcium (r = 0·46; P < 0·01) and zinc (r = 0·58; P < 0·001), but did not correlate with emergence, general early vigour or yield in the field. Conclusions Associations between PRL and field performance are generally related to early vigour. These root traits might therefore be of limited additional selection value, given that vigour can be measured easily on shoots/canopies. In contrast, LRD cannot be assessed easily in the field and, if LRD can improve nutrient uptake, then it may be possible to use HTP systems to screen this trait in both elite and more genetically diverse, non-field-adapted OSR.