Final report on research project PS2010, proof of concept of automated mapping of weeds in arable fields

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).

Clinical potential and design of programmable mechanical impedances for orthotic applications

A person with a moderate or severe motor disability will often use specialised or adapted tools to assist their interaction with a general environment. Such tools can assist with the movement of a person's arms so as to facilitate manipulation, can provide postural supports, or interface to computers, wheelchairs or similar assistive technologies. Designing such devices with programmable stiffness and damping may offer a better means for the person to have effective control of their surroundings. This paper addresses the possibility of designing some assistive technologies using impedance elements that can adapt to the user and the circumstances. Two impedance elements are proposed. The first, based on magnetic particle brakes, allows control of the damping coefficient in a passive element. The second, based on detuning the P-D controller in a servo-motor mechanism, allows control of both stiffness and damping. Such a mechanical impedance can be modulated to the conditions imposed by the task in hand. The limits of linear theory are explored and possible uses of programmable impedance elements are proposed.

Cost733cat: a database of weather and circulation type classifications

A new database of weather and circulation type catalogs is presented comprising 17 automated classification methods and five subjective classifications. It was compiled within COST Action 733 "Harmonisation and Applications of Weather Type Classifications for European regions" in order to evaluate different methods for weather and circulation type classification. This paper gives a technical description of the included methods using a new conceptual categorization for classification methods reflecting the strategy for the definition of types. Methods using predefined types include manual and threshold based classifications while methods producing types derived from the input data include those based on eigenvector techniques, leader algorithms and optimization algorithms. In order to allow direct comparisons between the methods, the circulation input data and the methods' configuration were harmonized for producing a subset of standard catalogs of the automated methods. The harmonization includes the data source, the climatic parameters used, the classification period as well as the spatial domain and the number of types. Frequency based characteristics of the resulting catalogs are presented, including variation of class sizes, persistence, seasonal and inter-annual variability as well as trends of the annual frequency time series. The methodological concept of the classifications is partly reflected by these properties of the resulting catalogs. It is shown that the types of subjective classifications compared to automated methods show higher persistence, inter-annual variation and long-term trends. Among the automated classifications optimization methods show a tendency for longer persistence and higher seasonal variation. However, it is also concluded that the distance metric used and the data preprocessing play at least an equally important role for the properties of the resulting classification compared to the algorithm used for type definition and assignment.

The mechanical properties of amniotic membrane influence its effect as a biomaterial for ocular surface repair

The human amniotic membrane (AM) is a tissue of fetal origin and has proven to be clinically useful as a biomaterial in the management of various ocular surface disorders including corneal stem cell transplantation. However, its success rate displays a degree of clinical unpredictability. We suggest that the measured variability inAMstiffness offers an explanation for the poor clinical reproducibility when it is used as a substrate for stem cell expansion and transplantation. Corneal epithelial stem cells were expanded upon AM samples possessing different mechanical stiffness. To investigate further the importance of biological substrate stiffness on cell phenotype we replaced AM with type I collagen gels of known stiffness. Substrate stiffness was measured using shear rheometry and surface topography was characterized using scanning electron microscopy and atomic force microscopy. The differentiation status of epithelial cells was examined using RT-PCR, immunohistochemistry and Western blotting. The level of corneal stem cell differentiation was increased in cells expanded upon AM with a high dynamic elastic shear modulus and cell expansion on type I collagen gels confirmed that the level of corneal epithelial stem cell differentiation was related to the substrate’s mechanical properties. In this paper we provide evidence to show that the preparatory method of AM for clinical use can affect its mechanical properties and that these measured differences can influence the level of differentiation within expanded corneal epithelial stem cells.

On the quantum mechanical scattering statistics of many particles

The probability of a quantum particle being detected in a given solid angle is determined by the S-matrix. The explanation of this fact in time-dependent scattering theory is often linked to the quantum flux, since the quantum flux integrated against a (detector-) surface and over a time interval can be viewed as the probability that the particle crosses this surface within the given time interval. Regarding many particle scattering, however, this argument is no longer valid, as each particle arrives at the detector at its own random time. While various treatments of this problem can be envisaged, here we present a straightforward Bohmian analysis of many particle potential scattering from which the S-matrix probability emerges in the limit of large distances.

Protease-activated receptor 2 sensitizes the transient receptor potential vanilloid 4 ion channel to cause mechanical hyperalgesia in mice

Exacerbated sensitivity to mechanical stimuli that are normally innocuous or mildly painful (mechanical allodynia and hyperalgesia) occurs during inflammation and underlies painful diseases. Proteases that are generated during inflammation and disease cleave protease-activated receptor 2 (PAR2) on afferent nerves to cause mechanical hyperalgesia in the skin and intestine by unknown mechanisms. We hypothesized that PAR2-mediated mechanical hyperalgesia requires sensitization of the ion channel transient receptor potential vanilloid 4 (TRPV4). Immunoreactive TRPV4 was coexpressed by rat dorsal root ganglia (DRG) neurons with PAR2, substance P (SP) and calcitonin gene-related peptide (CGRP), mediators of pain transmission. In PAR2-expressing cell lines that either naturally expressed TRPV4 (bronchial epithelial cells) or that were transfected to express TRPV4 (HEK cells), pretreatment with a PAR2 agonist enhanced Ca2+ and current responses to the TRPV4 agonists phorbol ester 4alpha-phorbol 12,13-didecanoate (4alphaPDD) and hypotonic solutions. PAR2-agonist similarly sensitized TRPV4 Ca2+ signals and currents in DRG neurons. Antagonists of phospholipase Cbeta and protein kinases A, C and D inhibited PAR2-induced sensitization of TRPV4 Ca2+ signals and currents. 4alphaPDD and hypotonic solutions stimulated SP and CGRP release from dorsal horn of rat spinal cord, and pretreatment with PAR2 agonist sensitized TRPV4-dependent peptide release. Intraplantar injection of PAR2 agonist caused mechanical hyperalgesia in mice and sensitized pain responses to the TRPV4 agonists 4alphaPDD and hypotonic solutions. Deletion of TRPV4 prevented PAR2 agonist-induced mechanical hyperalgesia and sensitization. This novel mechanism, by which PAR2 activates a second messenger to sensitize TRPV4-dependent release of nociceptive peptides and induce mechanical hyperalgesia, may underlie inflammatory hyperalgesia in diseases where proteases are activated and released.

Geo-Engineering to Confine Climate Change: Is it at all Feasible?

Paul Crutzen (2006) has suggested a research initiative to consider whether it would be feasible to artificially enhance the albedo of the planet Earth to counteract greenhouse warming. The enhancement of albedo would be achieved by intentionally injecting sulfur into the stratosphere. The rational for proposing the experiment is the observed cooling of the atmosphere following the recent major volcanic eruptions by El Chichon in 1984 and Mount Pinatubo in 1991 (Hansen et al., 1992). Although I am principally not against a research initiative to study such a potential experiment, I do have important reservations concerning its general feasibility. And its potential feasibility, I believe, must be the key motivation for embarking on such a study. Here I will bring up three major issues, which must be more thoroughly understood before any geo-engineering of climate could be considered, if at all. The three issues are (i) the lack of accuracy in climate prediction, (ii) the huge difference in timescale between the effect of greenhouse gases and the effect of aerosols and (iii) serious environmental problems which may be caused by high carbon dioxide concentration irrespective of the warming of the climate.

The importance of surface pressure changes in the response of the atmosphere to zonally-symmetric thermal and mechanical forcing

he classical problem of the response of a balanced, axisymmetric vortex to thermal and mechanical forcing is re-examined, paying special attention to the lower boundary condition. The correct condition is DΦ/Dt = 0, where Φ is the geopotential and D/Dt the material derivative, which explicitly accounts for a mass redistribution as part of the mean-flow response. This redistribution is neglected when using the boundary condition Dp/Dt = 0, which has conventionally been applied in this problem. It is shown that applying the incorrect boundary condition, and thereby ignoring the surface pressure change, leads to a zonal wind acceleration δū/δt that is too strong, especially near the surface. The effect is significant for planetary-scale forcing even when applied at tropopause level. A comparison is made between the mean-flow evolution in a baroclinic life-cycle, as simulated in a fully nonlinear, primitive-equation model, and that predicted by using the simulated eddy fluxes in the zonally-symmetric response problem. Use of the correct lower boundary condition is shown to lead to improved agreement.

Multivalency in healable supramolecular polymers: the effect of supramolecular cross-link density on the mechanical properties and healing of noncovalent polymer networks

Polymers with the ability to heal themselves could provide access to materials with extended lifetimes in a wide range of applications such as surface coatings, automotive components and aerospace composites. Here we describe the synthesis and characterisation of two novel, stimuli-responsive, supramolecular polymer blends based on π-electron-rich pyrenyl residues and π-electron-deficient, chain-folding aromatic diimides that interact through complementary π–π stacking interactions. Different degrees of supramolecular “cross-linking” were achieved by use of divalent or trivalent poly(ethylene glycol)-based polymers featuring pyrenyl end-groups, blended with a known diimide–ether copolymer. The mechanical properties of the resulting polymer blends revealed that higher degrees of supramolecular “cross-link density” yield materials with enhanced mechanical properties, such as increased tensile modulus, modulus of toughness, elasticity and yield point. After a number of break/heal cycles, these materials were found to retain the characteristics of the pristine polymer blend, and this new approach thus offers a simple route to mechanically robust yet healable materials.

Enhancing the recovery of tiger nut (Cyperus esculentus) oil by mechanical pressing: moisture content, particle size, high pressure and enzymatic pre-treatment effects

Tiger nut (Cyperus esculentus) tuber contains oil that is high in monounsaturated fatty acids, and this oil makes up about 23% of the tuber. The study aimed at evaluating the impact of several factors and enzymatic pre-treatment on the recovery of pressed tiger nut oil. Smaller particles were more favourable for pressing. High pressure pre-treatment did not increase oil recovery but enzymatic treatment did. The highest yield obtained by enzymatic treatment prior to mechanical extraction was 33 % on a dry defatted basis, which represents a recovery of 90 % of the oil. Tiger nut oil consists mainly of oleic acid; its acid and peroxide values reflect the high stability of the oil.

Edible oil from Tiger nut (Cyperus esculentus L.): mechanical pressing and aqueous enzymatic extraction methods

The tiger nut tuber of the Cyperus esculentus L. plant is an unusual storage system with similar amounts of starch and lipid. The extraction of its oil employing both mechanical pressing and aqueous enzymatic extraction (AEE) methods was investigated and an examination of the resulting products was carried out. The effects of particle size and moisture content of the tuber on the yield of tiger nut oil with pressing were initially studied. Smaller particles were found to enhance oil yields while a range of moisture content was observed to favour higher oil yields. When samples were first subjected to high pressures up to 700 MPa before pressing at 38 MPa there was no increase in the oil yields. Ground samples incubated with a mixture of α- Amylase, Alcalase, and Viscozyme (a mixture of cell wall degrading enzyme) as a pre-treatment, increased oil yield by pressing and 90% of oil was recovered as a result. When aqueous enzymatic extraction was carried out on ground samples, the use of α- Amylase, Alcalase, and Celluclast independently improved extraction oil yields compared to oil extraction without enzymes by 34.5, 23.4 and 14.7% respectively. A mixture of the three enzymes further augmented the oil yield and different operational factors were individually studied for their effects on the process. These include time, total mixed enzyme concentration, linear agitation speed, and solid-liquid ratio. The largest oil yields were obtained with a solid-liquid ratio of 1:6, mixed enzyme concentration of 1% (w/w) and 6 h incubation time although the longer time allowed for the formation of an emulsion. Using stationary samples during incubation surprisingly gave the highest oil yields, and this was observed to be as a result of gravity separation occurring during agitation. Furthermore, the use of high pressure processing up to 300 MPa as a pre-treatment enhanced oil yields but additional pressure increments had a detrimental effect. The quality of oils recovered from both mechanical and aqueous enzymatic extraction based on the percentage free fatty acid (% FFA) and peroxide values (PV) all reflected the good stabilities of the oils with the highest % FFA of 1.8 and PV of 1.7. The fatty acid profiles of all oils also remained unchanged. The level of tocopherols in oils were enhanced with both enzyme aided pressing (EAP) and high pressure processing before AEE. Analysis on the residual meals revealed DP 3 and DP 4 oligosaccharides present in EAP samples but these would require further assessment on their identity and quality.