35 resultados para vinasse and weeds


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Four experiments conducted over three seasons (2002-05) at the Crops Research Unit, University of Reading, investigated effects of canopy management of autumn sown oilseed rape (Brassica napus L. ssp. oleifera var. biennis (DC.) Metzg.) on competition with grass weeds. Emphasis was placed on the effect of the crop on the weeds. Rape canopy size was manipulated using sowing date, seed rate and the application of autumn fertilizer. Lolium multiflorum Lam., L. x boucheanum Kunth and Alopecurus myosuroides Huds. were sown as indicative grass weeds. The effects of sowing date, seed rate and autumn nitrogen on crop competitive ability were correlated with rape biomass and fractional interception of photosynthetically active radiation (PAR) by the rape floral layer, to the extent that by spring there was good evidence of crop: weed replacement. An increase in seed rate up to the highest plant densities tested increased both rape biomass and competitiveness, e.g. in 2002/3, L. multiflorum head density was reduced from 539 to 245 heads/m(2) and spikelet density from 13 170 to 5960 spikelets/m(2) when rape plant density was increased from 16 to 81 plants/m(2). Spikelets/head of Lolium spp. was little affected by rape seed rate, but the length of heads of A. myosuroides was reduced by 9 % when plant density was increased from 29-51 plants/m(2). Autumn nitrogen increased rape biomass and reduced L. multiflorum head density (415 and 336 heads/m(2) without and with autumn nitrogen, respectively) and spikelet density (9990 and 8220 spikelets/m(2) without and with autumn nitrogen, respectively). The number of spikelets/head was not significantly affected by autumn nitrogen. Early sowing could increase biomass and competitiveness, but poor crop establishment sometimes overrode the effect. Where crop and weed establishment was similar for both sowing dates, a 2-week delay (i.e. early September to mid-September) increased L. multiflorum head density from 226 to 633 heads/m(2) and spikelet density from 5780 to 15 060 spikelets/m(2).

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As a result of the recent intensification of crop production, the abundance and diversity of UK arable weeds adapted to cultivated land have declined, with an associated reduction in farmland birds. A number of questions need to be addressed when considering how these declines can be reversed. Firstly, can the delivery of crop production and biodiversity be reconciled by spatially separating cropping from designated wildlife areas? A number of subsidised environmental schemes in the UK take this approach and are focused on establishing vegetation cover on uncropped land. However, because of the lack of regular disturbance in these habitats, they are dominated by perennials and they therefore have limited potential for promoting the recovery of annual weed populations. A number of farmland bird species also rely on the provision of resources in field centres, and it is therefore likely that the recovery of their populations will rely on weed management options targeted at the cropped areas of the field. This raises two further questions. Firstly, is it possible to identify beneficial weed species that are relatively poor competitors with the crop and also have biodiversity value? Secondly, are the tools available to manage these species at acceptable levels while controlling pernicious weeds? A number of approaches are being employed to answer these questions, including predicting yield loss from weed competition models and exploiting herbicide selectivity. The further development of these tools is crucial if farmer opposition to managing weeds in crops is to be overcome. (c) 2007 Society of Chemical Industry.

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With uncertainty concerning the future of set-aside, over-wintering stubble is an attractive management option within the agri-environment scheme. Over-wintering stubbles could be included as part of rotational set-aside, benefiting farmland biodiversity. However, there is little research on managing stubbles to maximise weed seed loss, so farmers may be reluctant to adopt this option for fear of increased weed infestation. The purpose of this investigation is to develop effective management of over-wintering stubbles to minimise pernicious grass weeds in sequential crops, whilst maintaining beneficial species diversity. Research has focused on four annual grass-weeds (Alopecurus myosuroides, Anisantha sterilis, Bromus commutatus and Lolium multiflorum) of increased occurrence and/or resistance to herbicides. Hitherto, work has concentrated on the effects of stubble manipulation on weed seed germination and mortality, in particular by straw spreading or removal after harvest. The dynamics of artificially inoculated weed populations were monitored from harvest until early spring. Results obtained indicate that where straw is retained on the soil surface, it provides a favourable microclimate for seed depletion of Anisantha sterilis and Bromus commutatus through germination. Conversely, greater depletion of Alopecurus myosuroides and Lolium multiflorum seed occurred from stubbles in which a straw layer was absent. Seed recovery work provided evidence that most seeds remaining ungerminated throughout the trial period were still viable, but a large proportion of the seeds sown were unaccounted for. As these species are not generally favoured as a food source, the as yet unknown fate of these seeds has implications for subsequent grass-weed infestations.

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Four experiments conducted over three seasons (2002-05) at the Crops Research Unit, University of Reading, investigated effects of canopy management of autumn sown oilseed rape (Brassica napus L. ssp. oleifera var. biennis (DC.) Metzg.) on competition with grass weeds. Emphasis was placed on the effect of the crop on the weeds. Rape canopy size was manipulated using sowing date, seed rate and the application of autumn fertilizer. Lolium multiflorum Lam., L. x boucheanum Kunth and Alopecurus myosuroides Huds. were sown as indicative grass weeds. The effects of sowing date, seed rate and autumn nitrogen on crop competitive ability were correlated with rape biomass and fractional interception of photosynthetically active radiation (PAR) by the rape floral layer, to the extent that by spring there was good evidence of crop: weed replacement. An increase in seed rate up to the highest plant densities tested increased both rape biomass and competitiveness, e.g. in 2002/3, L. multiflorum head density was reduced from 539 to 245 heads/m(2) and spikelet density from 13 170 to 5960 spikelets/m(2) when rape plant density was increased from 16 to 81 plants/m(2). Spikelets/head of Lolium spp. was little affected by rape seed rate, but the length of heads of A. myosuroides was reduced by 9 % when plant density was increased from 29-51 plants/m(2). Autumn nitrogen increased rape biomass and reduced L. multiflorum head density (415 and 336 heads/m(2) without and with autumn nitrogen, respectively) and spikelet density (9990 and 8220 spikelets/m(2) without and with autumn nitrogen, respectively). The number of spikelets/head was not significantly affected by autumn nitrogen. Early sowing could increase biomass and competitiveness, but poor crop establishment sometimes overrode the effect. Where crop and weed establishment was similar for both sowing dates, a 2-week delay (i.e. early September to mid-September) increased L. multiflorum head density from 226 to 633 heads/m(2) and spikelet density from 5780 to 15 060 spikelets/m(2).

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Field experiments were conducted to quantify the natural levels of post-dispersal seed predation of arable weed species in spring barley and to identify the main groups of seed predators. Four arable weed species were investigated that were of high biodiversity value, yet of low to moderate competitive ability with the crop. These were Chenopodium album, Sinapis arvensis, Stellaria media and Polygonum aviculare. Exclusion treatments were used to allow selective access to dishes of seeds by different predator groups. Seed predation was highest early in the season, followed by a gradual decline in predation over the summer for all species. All species were taken by invertebrates. The activity of two phytophagous carabid genera showed significant correlations with seed predation levels. However, in general carabid activity was not related to seed predation and this is discussed in terms of the mainly polyphagous nature of many Carabid species that utilized the seed resource early in the season, but then switched to carnivory as prey populations increased. The potential relevance of post-dispersal seed predation to the development of weed management systems that maximize biological control through conservation and optimize herbicide use, is discussed.

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Although adult Rumex obtusifolius are problematic weeds, their seedlings are poor competitors against Lolium perenne, particularly in established swards. We investigated the possibility of using this weakness to augment control of R. obtusifolius seedlings with combinations of Gastrophysa viridula (Coleoptera: Chrysomelidae) and the rust fungus Uromyces rumicis. Rumex obtusifolius seedlings were grown in competition with L. perenne sown at different rates and times after R. obtusifolius: they competed successfully with L. perenne when sown 21 days before the grass. Sowing both species at the same time resulted in a dominant grass sward, with R. obtusifolius becoming dominant when sown 42 days prior to L. perenne. Grass sowing rate had no effect on R. obtusifolius growth or biomass. A second experiment investigated how competition from L. perenne sown 21 days after R. obtusifolius combined with damage from G. viridula and/or U. rumicis (applied at either the 3-4- or 10-13-leaf stage, or at both stages) affected the growth and final biomass of R. obtusifolius. Beetle grazing at the latter leaf stage was the only treatment that reduced R. obtusifolius biomass, although rust infection at the earlier application led to an increase in shoot and root weight. The results are discussed in terms of the potential for use of these agents in the field.

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Physical, cultural and biological methods for weed control have developed largely independently and are often concerned with weed control in different systems: physical and cultural control in annual crops and biocontrol in extensive grasslands. We discuss the strengths and limitations of four physical and cultural methods for weed control: mechanical, thermal, cutting, and intercropping, and the advantages and disadvantages of combining biological control with them. These physical and cultural control methods may increase soil nitrogen levels and alter microclimate at soil level; this may be of benefit to biocontrol agents, although physical disturbance to the soil and plant damage may be detrimental. Some weeds escape control by these methods; we suggest that these weeds may be controlled by biocontrol agents. It will be easiest to combine biological control with. re and cutting in grasslands; within arable systems it would be most promising to combine biological control (especially using seed predators and foliar pathogens) with cover-cropping, and mechanical weeding combined with foliar bacterial and possibly foliar fungal pathogens. We stress the need to consider the timing of application of combined control methods in order to cause least damage to the biocontrol agent, along with maximum damage to the weed and to consider the wider implications of these different weed control methods.

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Daphnia magna is a key invertebrate in the freshwater environment and is used widely as a model in ecotoxicological measurements and risk assessment. Understanding the genomic responses of D. magna to chemical challenges will be of value to regulatory authorities worldwide. Here we exposed D. magna to the insecticide methomyl and the herbicide propanil to compare phenotypic effects with changes in mRNA expression levels. Both pesticides are found in drainage ditches and surface water bodies standing adjacent to crops. Methomyl, a carbamate insecticide widely used in agriculture, inhibits acetylcholinesterase, a key enzyme in nerve transmission. Propanil, an acetanilide herbicide, is used to control grass and broad-leaf weeds. The phenotypic effects of single doses of each chemical were evaluated using a standard immobilisation assay. Immobilisation was linked to global mRNA expression levels using the previously estimated 48h-EC(1)s, followed by hybridization to a cDNA microarray with more than 13,000 redundant cDNA clones representing >5000 unique genes. Following exposure to methomyl and propanil, differential expression was found for 624 and 551 cDNAs, respectively (one-way ANOVA with Bonferroni correction, Pand up-regulation was prevalent for both test chemicals. Both pesticides promoted transcriptional changes in energy metabolism (e.g., mitochondrial proteins, ATP synthesis-related proteins), moulting (e.g., chitin-binding proteins, cuticular proteins) and protein biosynthesis (e.g., ribosomal proteins, transcription factors). Methomyl induced the transcription of genes involved in specific processes such as ion homeostasis and xenobiotic metabolism. Propanil highly promoted haemoglobin synthesis and up-regulated genes specifically related to defence mechanisms (e.g., innate immunity response systems) and neuronal pathways. Pesticide-specific toxic responses were found but there is little evidence for transcriptional responses purely restricted to genes associated with the pesticide target site or mechanism of toxicity.

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The project investigated whether it would be possible to remove the main technical hindrance to precision application of herbicides to arable crops in the UK, namely creating geo-referenced weed maps for each field. The ultimate goal is an information system so that agronomists and farmers can plan precision weed control and create spraying maps. The project focussed on black-grass in wheat, but research was also carried out on barley and beans and on wild-oats, barren brome, rye-grass, cleavers and thistles which form stable patches in arable fields. Farmers may also make special efforts to control them. Using cameras mounted on farm machinery, the project explored the feasibility of automating the process of mapping black-grass in fields. Geo-referenced images were captured from June to December 2009, using sprayers, a tractor, combine harvesters and on foot. Cameras were mounted on the sprayer boom, on windows or on top of tractor and combine cabs and images were captured with a range of vibration levels and at speeds up to 20 km h-1. For acceptability to farmers, it was important that every image containing black-grass was classified as containing black-grass; false negatives are highly undesirable. The software algorithms recorded no false negatives in sample images analysed to date, although some black-grass heads were unclassified and there were also false positives. The density of black-grass heads per unit area estimated by machine vision increased as a linear function of the actual density with a mean detection rate of 47% of black-grass heads in sample images at T3 within a density range of 13 to 1230 heads m-2. A final part of the project was to create geo-referenced weed maps using software written in previous HGCA-funded projects and two examples show that geo-location by machine vision compares well with manually-mapped weed patches. The consortium therefore demonstrated for the first time the feasibility of using a GPS-linked computer-controlled camera system mounted on farm machinery (tractor, sprayer or combine) to geo-reference black-grass in winter wheat between black-grass head emergence and seed shedding.

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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).