946 resultados para Grass and vigour


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Focal symmetrical encephalomalacia (FSE) is the most prominent lesion seen in the chronic form of enterotoxemia by Clostridium perfringens type D. This paper reports FSE in sheep in Brazil. Six deaths occurred within a seven days period in a flock of 70, four to 30-month-old Santa Inês sheep in the state of Paraíba in the Brazilian semiarid. The flock was grazing a paddock of irrigated sprouting Cynodon dactylon (Tifton grass), and supplemented, ad libitum, with a concentrate of soybean, corn and wheat. Nervous signs included blindness and recumbence. A 19 month-old sheep was examined clinically and necropsied after a clinical course of three days. Gross lesions were herniation of the cerebellar vermis and multifocal, bilateral, symmetric brownish areas in the internal capsule, thalamus and cerebellar peduncles. Histologic lesions were multifocal, bilateral malacia with some neutrophils, swelling of blood vessels endothelium, perivascular edema, and hemorrhages. The flock was vaccinated, before the outbreak, with only one dose of Clostridium perfringens type D vaccine. Two factors are suggested to be important for the occurrence of the disease: insufficient immunity due to the incorrect vaccination; and high nutritional levels by the supplementation with highly fermentable carbohydrates.

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The present study focuses on the biochemical aspects of six islands belonging to Lakshadweep Archipelago – namely Kavaratti, Kadamath, Kiltan, Androth, Agathy and Minicoy. Lakshadweep, which is an area biologically significant due to isolation from the major coastline, remains as one of the least studied areas in Indian Ocean. The work, processed out the distributional pattern of trace metals among the biotic (corols, sea weeds and sea grass) and abiotic component (sediments) of ecosystem. An effort is made to picturise the spatial distribution pattern of different forms of nitrogen and phosphorus in the various sedimentary environments of the study area. Studies on the biogeochemical and nutrient aspects of the concerned study area scanty. In Lakshadweep, the local life is very dependent on reefs and its resources. The important stress which produce a threatening effort on the existence for coral reefs are anthropogenic-namely-organic and inorganic pollution from sewage, agricultural and industrial waters, sediment damage from excessive land cleaning, and over exploitation particularly through destructive fishing methods. In addition these one other more localized or less service anthropogenic stress: pollution by oil and other hydrocarbons, complex organic molecular and heavy metal pollution, and destructive engineering practices.

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In this present study macro benthos of minicoy island lakshadweep, an attempt has been made to study the distribution and community structure of benthos at different ecosystems. The main objectives of the study include the identification of benthic fauna, their distribution and composition, standing stock, qualitative and quantitative nature in relation to hydrography,seasons and sediment texture, community structure analysis and tropic relationships. This base line study at Minicoy,thus establishes that the benthos of sea grass and mangrove ecosystems(nursery grounds) determines the richness and diversity of demersal fish fauna at the nearby lagoon and reef areas to a great extent. Any serious stress on these ecosystems may lead to disappearance of certain fish species in the nearby future

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En este trabajo se describe la utilización de herramientas de software libre, básicamente GRASS y R, para obtener una serie de mapas de coberturas del suelo (1976-2006) a partir de imágenes de satélite Landsat MSS y Landsat TM. Se trata de un proyecto concedido a un año, por lo que se requería una metodología que permitiera realizar el análisis de forma rápida y sencilla, aún tratando de aplicar técnicas de clasificación avanzadas. Dada la complejidad del trabajo y la premura de tiempo, se ha tratado de automatizar gran parte del trabajo mediante diversos scripts con BASH y R. (...)

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Among shrubland- and young forest-nesting bird species in North America, Golden-winged Warblers (Vermivora chrysoptera) are one of the most rapidly declining partly because of limited nesting habitat. Creation and management of high quality vegetation communities used for nesting are needed to reduce declines. Thus, we examined whether common characteristics could be managed across much of the Golden-winged Warbler’s breeding range to increase daily survival rate (DSR) of nests. We monitored 388 nests on 62 sites throughout Minnesota, Wisconsin, New York, North Carolina, Pennsylvania, Tennessee, and West Virginia. We evaluated competing DSR models in spatial-temporal (dominant vegetation type, population segment, state, and year), intraseasonal (nest stage and time-within-season), and vegetation model suites. The best-supported DSR models among the three model suites suggested potential associations between daily survival rate of nests and state, time-within-season, percent grass and Rubus cover within 1 m of the nest, and distance to later successional forest edge. Overall, grass cover (negative association with DSR above 50%) and Rubus cover (DSR lowest at about 30%) within 1 m of the nest and distance to later successional forest edge (negative association with DSR) may represent common management targets across our states for increasing Golden-winged Warbler DSR, particularly in the Appalachian Mountains population segment. Context-specific adjustments to management strategies, such as in wetlands or areas of overlap with Blue-winged Warblers (Vermivora cyanoptera), may be necessary to increase DSR for Golden-winged Warblers.

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Victoria Island lies at the north-western extremity of the region covered by the vast North American Laurentide Ice Sheet (LIS) in the Canadian Arctic Archipelago. This area is significant because it linked the interior of the LIS to the Arctic Ocean, probably via a number of ice streams. Victoria Island, however, exhibits a remarkably complex glacial landscape, with several successive generations of ice flow indicators superimposed on top of each other and often at abrupt (90 degrees) angles. This complexity represents a major challenge to those attempting to produce a detailed reconstruction of the glacial history of the region. This paper presents a map of the glacial geomorphology of Victoria Island. The map is based on analysis of Landsat Enhanced Thematic Plus (ETM+) satellite imagery and contains over 58,000 individual glacial features which include: glacial lineations, moraines (terminal, lateral, subglacial shear margin), hummocky moraine, ribbed moraine, eskers, glaciofluvial deposits, large meltwater channels, and raised shorelines. The glacial features reveal marked changes in ice flow direction and vigour over time. Moreover, the glacial geomorphology indicates a non-steady withdrawal of ice during deglaciation, with rapidly flowing ice streams focussed into the inter-island troughs and several successively younger flow patterns superimposed on older ones. It is hoped that detailed analysis of this map will lead to an improved reconstruction of the glacial history of this area which will provide other important insights, for example, with respect to the interactions between ice streaming, deglaciation and Arctic Ocean meltwater events.

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This paper considers the various complex changes that occur to nitrogen (N) containing compounds in forages through the processes of ensiling, rumen degradation and microbial synthesis, post-ruminal digestion and absorption and synthesis into milk protein. Particular emphasis is placed on reviewing recent data on the efficiency of utilisation of N-containing compounds in silages by rumen microbes, since low efficiency here is believed to be a major cause of large N losses to the environment on some silage-based diets. Data are reviewed which show that although rumen degradation of N compounds in silage is rapid and extensive, up to 10% of the soluble N can escape the rumen by being associated with the liquid phase. There is now firm evidence that the composition of the amino acids (AAs) absorbed is heavily dependent on the process of ensiling and that witting or use of certain silage additives conserve the initial amino acid profile of the forage. This provides an opportunity to manipulate the amino acid supply to better match demand thus potentially enhancing utilisation. This review confirms that utilisation of the N fractions in grass and legume silages in particular, is poor and the efficiency of microbial protein synthesis (EMPS) is consistently higher on maize silage-based diets. It is concluded that the way in which grass and legume silages in particular are produced and used in the future needs a radical rethink. New research needs to be aimed at enhancing the utilisation of N in the rumen through a better understanding of N/carbohydrate relationships and the ability of forages to supply degraded carbohydrate. Also more emphasis is needed on understanding of the potentially different role of the different N fractions that exist in silages. (C) 2004 Elsevier B.V. All rights reserved.

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Increased agricultural intensification has led to well-documented declines in the fauna and flora associated with intensive grasslands in the UK. We aimed to quantify the effectiveness of different field margin management strategies for putting bumblebee and butterfly biodiversity back into intensive grasslands. Using four intensive livestock farms in south-west England, we manipulated conventional management practices (addition of inorganic fertilizer, cutting frequency and height, and aftermath grazing) to generate seven grass-based treatments along a gradient of decreasing management intensity. We also tested two more interventionist treatments which introduced sown components into the sward: (i) a cereal, grass and legume mix, and (ii) a diverse conservation mix with kale, mixed cereals, linseed and legumes. These crop mixtures were intended to provide forage and structural resources for pollinators but were not intended to have agronomic value as livestock feed. Using a replicated block design, we monitored bumblebee and butterfly responses in 27 plots (10 x 50 m) in each farm from 2003 to 2006. Bumblebees were most abundant, species-rich and diverse in the sown treatments and virtually absent from the grass-based treatments. The diverse conservation mix treatment supported larger and more diverse bumblebee assemblages than the cereal, grass and legume mix treatment. The sown treatments, and the most extensively managed grass-based treatments, had the highest abundance, species richness and diversity of adult butterflies, whereas butterfly larvae were only found in the grass-based treatments. Bumblebee and butterfly assemblage structure was driven by floral abundance, floral richness, the availability of nectar resources, and sward structure. Only vegetation cover was correlated with butterfly larval abundance. Synthesis and applications. This study has identified management options in the margins of intensive grasslands which can enhance bumblebee and butterfly biodiversity. Extensification of conventional grass management by stopping fertilization, reducing cutting frequency and not grazing, benefits butterflies. However, to enhance bumblebees requires a more interventionist approach in the form of sowing flower-rich habitat. Both approaches are potentially suitable for adoption in agri-environment schemes in the UK and Europe.

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Milk supply from Mexican dairy farms does not meet demand and small-scale farms can contribute toward closing the gap. Two multi-criteria programming techniques, goal programming and compromise programming, were used in a study of small-scale dairy farms in central Mexico. To build the goal and compromise programming models, 4 ordinary linear programming models were also developed, which had objective functions to maximize metabolizable energy for milk production, to maximize margin of income over feed costs, to maximize metabolizable protein for milk production, and to minimize purchased feedstuffs. Neither multicriteria approach was significantly better than the other; however, by applying both models it was possible to perform a more comprehensive analysis of these small-scale dairy systems. The multi-criteria programming models affirm findings from previous work and suggest that a forage strategy based on alfalfa, rye-grass, and corn silage would meet nutrient requirements of the herd. Both models suggested that there is an economic advantage in rescheduling the calving season to the second and third calendar quarters to better synchronize higher demand for nutrients with the period of high forage availability.

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This study investigates the function of non-cropped field margins in arable farming systems for enhancing the biodiversity value of beetle communities. Three different sown seed mixtures were used to establish field margins, a Countryside Stewardship mix, a fine grass and forbs mix and a tussock grass and forbs mix. The structure of beetle communities in the first full year of establishment was found to show no difference between the tussock grass and Countryside Stewardship margins. However, both differed from the fine grass margins, which supported lower overall abundance and species richness of beetles. This was attributed to small-scale architectural differences between species of fine and tussock grasses, rather than differences in plant composition. Body size distributions of beetles showed distinct similarities between the Countryside Stewardship and tussock margins. A greater abundance of large beetles was found in fine grass margins, although in all cases these body size distributions were attributed to a small number of species or a taxonomically distinct group. All three margin types included beetle species of conservation value. The importance of these results was discussed in the context of the value of these seed mixtures for invertebrate conversation. (c) 2004 Elsevier B.V. All rights reserved.

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Many weeds occur in patches but farmers frequently spray whole fields to control the weeds in these patches. Given a geo-referenced weed map, technology exists to confine spraying to these patches. Adoption of patch spraying by arable farmers has, however, been negligible partly due to the difficulty of constructing weed maps. Building on previous DEFRA and HGCA projects, this proposal aims to develop and evaluate a machine vision system to automate the weed mapping process. The project thereby addresses the principal technical stumbling block to widespread adoption of site specific weed management (SSWM). The accuracy of weed identification by machine vision based on a single field survey may be inadequate to create herbicide application maps. We therefore propose to test the hypothesis that sufficiently accurate weed maps can be constructed by integrating information from geo-referenced images captured automatically at different times of the year during normal field activities. Accuracy of identification will also be increased by utilising a priori knowledge of weeds present in fields. To prove this concept, images will be captured from arable fields on two farms and processed offline to identify and map the weeds, focussing especially on black-grass, wild oats, barren brome, couch grass and cleavers. As advocated by Lutman et al. (2002), the approach uncouples the weed mapping and treatment processes and builds on the observation that patches of these weeds are quite stable in arable fields. There are three main aspects to the project. 1) Machine vision hardware. Hardware component parts of the system are one or more cameras connected to a single board computer (Concurrent Solutions LLC) and interfaced with an accurate Global Positioning System (GPS) supplied by Patchwork Technology. The camera(s) will take separate measurements for each of the three primary colours of visible light (red, green and blue) in each pixel. The basic proof of concept can be achieved in principle using a single camera system, but in practice systems with more than one camera may need to be installed so that larger fractions of each field can be photographed. Hardware will be reviewed regularly during the project in response to feedback from other work packages and updated as required. 2) Image capture and weed identification software. The machine vision system will be attached to toolbars of farm machinery so that images can be collected during different field operations. Images will be captured at different ground speeds, in different directions and at different crop growth stages as well as in different crop backgrounds. Having captured geo-referenced images in the field, image analysis software will be developed to identify weed species by Murray State and Reading Universities with advice from The Arable Group. A wide range of pattern recognition and in particular Bayesian Networks will be used to advance the state of the art in machine vision-based weed identification and mapping. Weed identification algorithms used by others are inadequate for this project as we intend to collect and correlate images collected at different growth stages. Plants grown for this purpose by Herbiseed will be used in the first instance. In addition, our image capture and analysis system will include plant characteristics such as leaf shape, size, vein structure, colour and textural pattern, some of which are not detectable by other machine vision systems or are omitted by their algorithms. Using such a list of features observable using our machine vision system, we will determine those that can be used to distinguish weed species of interest. 3) Weed mapping. Geo-referenced maps of weeds in arable fields (Reading University and Syngenta) will be produced with advice from The Arable Group and Patchwork Technology. Natural infestations will be mapped in the fields but we will also introduce specimen plants in pots to facilitate more rigorous system evaluation and testing. Manual weed maps of the same fields will be generated by Reading University, Syngenta and Peter Lutman so that the accuracy of automated mapping can be assessed. The principal hypothesis and concept to be tested is that by combining maps from several surveys, a weed map with acceptable accuracy for endusers can be produced. If the concept is proved and can be commercialised, systems could be retrofitted at low cost onto existing farm machinery. The outputs of the weed mapping software would then link with the precision farming options already built into many commercial sprayers, allowing their use for targeted, site-specific herbicide applications. Immediate economic benefits would, therefore, arise directly from reducing herbicide costs. SSWM will also reduce the overall pesticide load on the crop and so may reduce pesticide residues in food and drinking water, and reduce adverse impacts of pesticides on non-target species and beneficials. Farmers may even choose to leave unsprayed some non-injurious, environmentally-beneficial, low density weed infestations. These benefits fit very well with the anticipated legislation emerging in the new EU Thematic Strategy for Pesticides which will encourage more targeted use of pesticides and greater uptake of Integrated Crop (Pest) Management approaches, and also with the requirements of the Water Framework Directive to reduce levels of pesticides in water bodies. The greater precision of weed management offered by SSWM is therefore a key element in preparing arable farming systems for the future, where policy makers and consumers want to minimise pesticide use and the carbon footprint of farming while maintaining food production and security. The mapping technology could also be used on organic farms to identify areas of fields needing mechanical weed control thereby reducing both carbon footprints and also damage to crops by, for example, spring tines. Objective i. To develop a prototype machine vision system for automated image capture during agricultural field operations; ii. To prove the concept that images captured by the machine vision system over a series of field operations can be processed to identify and geo-reference specific weeds in the field; iii. To generate weed maps from the geo-referenced, weed plants/patches identified in objective (ii).

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Declines of farmland birds have been pronounced in landscapes dominated by lowland livestock production and densities of seed-eating birds are particularly low in such areas. Modern livestock production often entails a simple cropping system dominated by ley grassland and maize grown for animal feed. These crops often lack invertebrate and seed resources for foraging birds and can be hostile nesting environments. Cereal-based wholecrop silages (CBWCS) offer potential benefits for farmland birds because they can be grown with minimal herbicide applications and can be spring-sown with following winter stubbles. We compared the biodiversity benefits and agronomic yields of winter-sown wheat and spring-sown barley as alternatives to grass and maize silage in intensive dairy livestock systems. Seed-eating birds foraged mainly in CBWCS fields during summer, and mainly on barley stubbles during winter and this reflected the higher densities of seed-bearing plants therein. Maize and grass fields lacked seed-bearing vegetation and were strongly avoided by most seed-eating birds. Production costs of CBWCS are similar to those of maize and lower than those of grass silage. Selective (rather than broad-spectrum) herbicide application on spring barley crops increased forb cover, reduced yields (by 11%) but caused only a small (<4%) increase in production costs. CBWCS grown with selective herbicide and with following winter stubbles offer a practical conservation measure for seed-eating farmland birds in landscapes dominated by intensively-managed grassland and maize. However, the relatively early harvesting of CBWCS could destroy a significant proportion of breeding attempts of late-nesting species like corn bunting (Emberiza calandra) or yellow wagtail (Motocilla flava). Where late-breeding species are likely to nest in CBWCS fields, harvesting should be delayed until most nesting attempts have been completed (e.g. until after 1st August in southern Britain). (C) 2010 Elsevier Ltd. All rights reserved.

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Full-waveform laser scanning data acquired with a Riegl LMS-Q560 instrument were used to classify an orange orchard into orange trees, grass and ground using waveform parameters alone. Gaussian decomposition was performed on this data capture from the National Airborne Field Experiment in November 2006 using a custom peak-detection procedure and a trust-region-reflective algorithm for fitting Gauss functions. Calibration was carried out using waveforms returned from a road surface, and the backscattering coefficient c was derived for every waveform peak. The processed data were then analysed according to the number of returns detected within each waveform and classified into three classes based on pulse width and c. For single-peak waveforms the scatterplot of c versus pulse width was used to distinguish between ground, grass and orange trees. In the case of multiple returns, the relationship between first (or first plus middle) and last return c values was used to separate ground from other targets. Refinement of this classification, and further sub-classification into grass and orange trees was performed using the c versus pulse width scatterplots of last returns. In all cases the separation was carried out using a decision tree with empirical relationships between the waveform parameters. Ground points were successfully separated from orange tree points. The most difficult class to separate and verify was grass, but those points in general corresponded well with the grass areas identified in the aerial photography. The overall accuracy reached 91%, using photography and relative elevation as ground truth. The overall accuracy for two classes, orange tree and combined class of grass and ground, yielded 95%. Finally, the backscattering coefficient c of single-peak waveforms was also used to derive reflectance values of the three classes. The reflectance of the orange tree class (0.31) and ground class (0.60) are consistent with published values at the wavelength of the Riegl scanner (1550 nm). The grass class reflectance (0.46) falls in between the other two classes as might be expected, as this class has a mixture of the contributions of both vegetation and ground reflectance properties.

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Sainfoin is a non-bloating temperate forage legume with a moderate-to-high condensed tannin (CT) content. This study investigated whether the diversity of sainfoin accessions in terms of CT structures and contents could be related to rumen in vitro gas and methane (CH4) production and fermentation characteristics. The aim was to identify promising accessions for future investigations. Accessions differed (P < 0·0001) in terms of total gas and CH4 productions. Fermentation kinetics (i.e. parameters describing the shape of the gas production curve and half-time gas production) for CH4 production were influenced by accession (P ≤ 0·038), but not by PEG. Accession, PEG and time affected (P < 0·001) CH4 production, but accession and PEG interaction showed only a tendency (P = 0·08). Increase in CH4 due to PEG addition was not related to CT content. Further analysis of the relationships among multiple traits (nutritional composition, CT structure and CH4 production) using principal component analysis (PCA) based on optimally weighted variables revealed differences among accessions. The first two principal component axes, PC1 (57·6%) and PC2 (18·4%), explained 76·0% of the total variation among accessions. Loading of biplots derived from both PCAs made it possible to establish a relationship between the ratio of prodelphinidin:procyanidin (PD:PC) tannins and CH4 production in some accessions. The PD:PC ratio seems to be an important source of variation that is negatively related to CH4 production. These results suggested that sainfoin accessions collected from across the world exhibited substantial variation in terms of their effects on rumen in vitro CH4 production, revealing some promising accessions for future investigations.

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European grassland-based livestock production systems face the challenge of producing more meat and milk to meet increasing world demands and to achieve this using fewer resources. Legumes offer great potential for achieving these objectives. They have numerous features that can act together at different stages in the soil–plant–animal–atmosphere system, and these are most effective in mixed swards with a legume proportion of 30–50%. The resulting benefits include reduced dependence on fossil energy and industrial N-fertilizer, lower quantities of harmful emissions to the environment (greenhouse gases and nitrate), lower production costs, higher productivity and increased protein self-sufficiency. Some legume species offer opportunities for improving animal health with less medication, due to the presence of bioactive secondary metabolites. In addition, legumes may offer an adaptation option to rising atmospheric CO2 concentrations and climate change. Legumes generate these benefits at the level of the managed land-area unit and also at the level of the final product unit. However, legumes suffer from some limitations, and suggestions are made for future research to exploit more fully the opportunities that legumes can offer. In conclusion, the development of legume-based grassland–livestock systems undoubtedly constitutes one of the pillars for more sustainable and competitive ruminant production systems, and it can be expected that forage legumes will become more important in the future.