999 resultados para Plant Architecture
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Exploitation of arbuscular mycorrhizal fungi may be an important approach for development of reduced-input agriculture. We discuss the use of linear models to analyze variation in mycorrhiza response among diverse plant varieties in order to assess the value of mycorrhizas. Our approach allows elimination of variation linked to differences in plant performance in the absence of mycorrhizas and the selection of plant lines that might harbor genetic variation of use to improve the mycorrhizal symbiosis in agriculture. We illustrate our approach by applying it to previously published and to novel data. We suggest that in dealing with a relative trait such as mycorrhiza effect, the choice of measure used to quantify the trait greatly affects interpretation. In the plant populations under consideration, we find evidence for a greater potential to increase mycorrhiza benefit than previously suggested.
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Summary: Owncontrol directions in meat hygiene legislation and their practical implementation in the slaughterhouse and cutting plant of Snellman Ltd, part I
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This work proposes a parallel architecture for a motion estimation algorithm. It is well known that image processing requires a huge amount of computation, mainly at low level processing where the algorithms are dealing with a great numbers of data-pixel. One of the solutions to estimate motions involves detection of the correspondences between two images. Due to its regular processing scheme, parallel implementation of correspondence problem can be an adequate approach to reduce the computation time. This work introduces parallel and real-time implementation of such low-level tasks to be carried out from the moment that the current image is acquired by the camera until the pairs of point-matchings are detected
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This publication is designed to aid those involved in corn production to more fully understand how the corn plant develops. Includes numerous photos and illustrations.
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Plant growth analysis presents difficulties related to statistical comparison of growth rates, and the analysis of variance of primary data could guide the interpretation of results. The objective of this work was to evaluate the analysis of variance of data from distinct harvests of an experiment, focusing especially on the homogeneity of variances and the choice of an adequate ANOVA model. Data from five experiments covering different crops and growth conditions were used. From the total number of variables, 19% were originally homoscedastic, 60% became homoscedastic after logarithmic transformation, and 21% remained heteroscedastic after transformation. Data transformation did not affect the F test in one experiment, whereas in the other experiments transformation modified the F test usually reducing the number of significant effects. Even when transformation has not altered the F test, mean comparisons led to divergent interpretations. The mixed ANOVA model, considering harvest as a random effect, reduced the number of significant effects of every factor which had the F test modified by this model. Examples illustrated that analysis of variance of primary variables provides a tool for identifying significant differences in growth rates. The analysis of variance imposes restrictions to experimental design thereby eliminating some advantages of the functional growth analysis.
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We report the complete genome sequence of the free-living bacterium Pseudomonas protegens (formerly Pseudomonas fluorescens) CHA0, a model organism used in plant-microbe interactions, biological control of phytopathogens, and bacterial genetics.
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This publication is a guide to understanding the Iowa Department of Transportation’s roadside management programs. It offers descriptions of various landscape designs or planting styles used within or adjacent to Iowa’s highway rights-of-way, as well as various plant profiles. In addition, this guide will help you learn more about the value of plants and their contribution to our environment and society. This publication is written for persons having little or no formal training in botany, and technical terminology has been kept to the minimum necessary to maintain standards of accuracy and conciseness in the descriptions.
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Community-level patterns of functional traits relate to community assembly and ecosystem functioning. By modelling the changes of different indices describing such patterns - trait means, extremes and diversity in communities - as a function of abiotic gradients, we could understand their drivers and build projections of the impact of global change on the functional components of biodiversity. We used five plant functional traits (vegetative height, specific leaf area, leaf dry matter content, leaf nitrogen content and seed mass) and non-woody vegetation plots to model several indices depicting community-level patterns of functional traits from a set of abiotic environmental variables (topographic, climatic and edaphic) over contrasting environmental conditions in a mountainous landscape. We performed a variation partitioning analysis to assess the relative importance of these variables for predicting patterns of functional traits in communities, and projected the best models under several climate change scenarios to examine future potential changes in vegetation functional properties. Not all indices of trait patterns within communities could be modelled with the same level of accuracy: the models for mean and extreme values of functional traits provided substantially better predictive accuracy than the models calibrated for diversity indices. Topographic and climatic factors were more important predictors of functional trait patterns within communities than edaphic predictors. Overall, model projections forecast an increase in mean vegetation height and in mean specific leaf area following climate warming. This trend was important at mid elevation particularly between 1000 and 2000 m asl. With this study we showed that topographic, climatic and edaphic variables can successfully model descriptors of community-level patterns of plant functional traits such as mean and extreme trait values. However, which factors determine the diversity of functional traits in plant communities remains unclear and requires more investigations.
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1. Accumulating evidence indicates that plant resistance against above-ground herbivores can be affected by the presence of arbuscular mycorrhizal fungi (AMF) in association with the host plant. Little is known, however, about how AMF composition can influence herbivore choice to feed on a particular plant. 2. Unravelling the preference-performance hypothesis in a multitrophic context is needed to expand our knowledge of complex multitrophic interactions in natural systems. If given mycorrhizal fungal genotypes increase attractiveness for a herbivore (reduced plant resistance), then the benefits of increased unpalatability provided by the mycorrhizal fungi (increased plant resistance) might be outweighed by the increased herbivore recruitment. 3. This was addressed by designing three experiments to test the effects of different AMF genotypes, inoculated either alone or in combination, to measure intraspecific AMF effects on plant resistance and insect herbivore preference. Using strawberry (Fragaria vesca L.) plants that were colonised by eight different combinations of Rhizophagus irregularis isolates, we measured effects on plant growth, insect growth and survival, as well as feeding preferences of a generalist herbivore caterpillar (Spodoptera littoralis Boisduval). 4. Overall, it was found that: (i) AMF influenced plant resistance in an AMF genotype-specific manner; (ii) some AMF inoculations decreased insect performance; (iii) insects preferentially chose to feed more on leaves originating from non-mycorrhizal plants; but also that (iv) in a whole plant bioassay, insects preferentially chose the biggest plant, regardless of their mycorrhizal status. 5. Therefore, AMF-mediated trade-offs between growth and resistance against herbivores have been shown. Such trade-offs, particularly driven by plant attractiveness to herbivores, buffer the positive effects of the mycorrhizal symbiosis on enhanced plant growth.
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Antiresorptive agents such as bisphosphonates induce a rapid increase of BMD during the 1st year of treatment and a partial maintenance of bone architecture. Trabecular Bone Score (TBS), a new grey-level texture measurement that can be extracted from the DXA image, correlates with 3D parameters of bone micro-architecture. Aim: To evaluate the longitudinal effect of antiresorptive agents on spine BMD and on site-matched spine microarchitecture as assessed by TBS. Methods: From the BMD database for Province of Manitoba, Canada, we selected women age >50 with paired baseline and follow up spine DXA examinations who had not received any prior HRT or other antiresorptive drug.Women were divided in two subgroups: (1) those not receiving any HRT or antiresorptive drug during follow up (=non-users) and (2) those receiving non-HRT antiresorptive drug during follow up (=users) with high adherence (medication possession ratio >75%) from a provincial pharmacy database system. Lumbar spine TBS was derived by the Bone Disease Unit, University of Lausanne, for each spine DXA examination using anonymized files (blinded from clinical parameters and outcomes). Effects of antiresorptive treatment for users and non-users on TBS and BMD at baseline and during mean 3.7 years follow-up were compared. Results were expressed % change per year. Results: 1150 non-users and 534 users met the inclusion criteria. At baseline, users and non-users had a mean age and BMI of [62.2±7.9 vs 66.1±8.0 years] and [26.3±4.7 vs 24.7±4.0 kg/m²] respectively. Antiresorptive drugs received by users were bisphosphonates (86%), raloxifene (10%) and calcitonin (4%). Significant differences in BMD change and TBS change were seen between users and nonusers during follow-up (p<0.0001). Significant decreases in mean BMD and TBS (−0.36± 0.05% per year; −0.31±0.06% per year) were seen for non-users compared with baseline (p<0.001). A significant increase in mean BMD was seen for users compared with baseline (+1.86±0.0% per year, p<0.0018). TBS of users also increased compared with baseline (+0.20±0.08% per year, p<0.001), but more slowly than BMD. Conclusion: We observed a significant increase in spine BMD and a positive maintenance of bone micro-architecture from TBS with antiresorptive treatment, whereas the treatment naïve group lost both density and micro-architecture. TBS seems to be responsive to treatment and could be suitable for monitoring micro-architecture. This article is part of a Special Issue entitled ECTS 2011. Disclosure of interest: M.-A. Krieg: None declared, A. Goertzen: None declared, W. Leslie: None declared, D. Hans Consulting fees from Medimaps.
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Nitrogen supply and plant population are basic parameters for cereal-legume intercropping. In order to study plant population and nitrogen fertilizer effects on yield and yield efficiency of maize-bean intercropping, a field experiment was established. Three bean plant populations and three nitrogen levels were used. Maize dry matter accumulation decreased with increases in bean plant population. Competitive effect of intercrop beans on maize yields was high at higher plant populations, being decreased by nitrogen fertilizer; application of 50 kg ha-1 N was very efficient in increasing maize cob yield. Intercropping significantly decreased harvest index of beans in all plant population and nitrogen fertilizer situations. The efficiency of intercropping, compared to sole cropping, was evidenced by the values obtained for Land Equivalent Ratio (LER) for biomass, cob and pod yields that increased with increases in bean plant populations and nitrogen fertilizer levels.
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The objective of this study was to evaluate the efficiency of spatial statistical analysis in the selection of genotypes in a plant breeding program and, particularly, to demonstrate the benefits of the approach when experimental observations are not spatially independent. The basic material of this study was a yield trial of soybean lines, with five check varieties (of fixed effect) and 110 test lines (of random effects), in an augmented block design. The spatial analysis used a random field linear model (RFML), with a covariance function estimated from the residuals of the analysis considering independent errors. Results showed a residual autocorrelation of significant magnitude and extension (range), which allowed a better discrimination among genotypes (increase of the power of statistical tests, reduction in the standard errors of estimates and predictors, and a greater amplitude of predictor values) when the spatial analysis was applied. Furthermore, the spatial analysis led to a different ranking of the genetic materials, in comparison with the non-spatial analysis, and a selection less influenced by local variation effects was obtained.