Field evaluation of systemic inducing resistance chemicals at different growth stages for the control of apple (Venturia inaequalis) and pear (Venturia pirina) scab

Two field trials were conducted using established apple (Malus cv. Golden Delicious) and pear (Pyrus communis 'Williams' Bon Chretien') to assess the efficacy of three commercially available systemic inducing resistance (SIR) products, Messenger (a.i. Harpin protein), Phoenix (a.i. Potassium phosphite) and Rigel (a.i. Salicylic acid derivative) applied at four different growth stages of tree development (bud break, green cluster, 90% petal fall, early fruitlet) against the foliar pathogens Venturia inaequalis and Venturia pirina which cause apple and pear scab respectively. A conventional synthetic fungicide (penconazole) used within the UK for apple and pear scab control was included for comparison. Little efficacy as scab protectants was demonstrated when each SIR product and penconazole was applied at only two growth stages (bud break, green cluster). However when the above compounds were applied at three or more growth stages efficacy as scab protectants was confirmed. The synthetic fungicide penconazole provided greatest protection against apple and pear scab in both the 2006 and 2007 field trials. There was little difference in the magnitude of scab protection conferred by each SIR agent. Results suggest application of at least three sprays during bud break to early fruitlet formation with an appropriate SIR agent may provide a useful addition to existing methods of apple and pear scab management under field conditions. (C) 2009 Published by Elsevier Ltd.

Assessment of wheat cultivars for drought tolerance via osmotic stress imposed at early seedling growth stages

A study was conducted in the Department of Plant Breeding and Genetics,Sindh Agriculture University, Tandojam, Pakistan during the year 2009. Sixteen spring wheat cultivars (Triticum aestivum L.) were screened under osmotic stress with three treatments i.e. control-no PEG (polyethylene glycol), 15 percent and 25 percent PEG-6000 solution. The analysis of variance indicated significant differences among treatments for all seedling traits except seed germination percentage. Varieties also differed significantly in germination percentage, coleoptile length, shoot root length, shoot weight, root/shoot ratio and seed vigour index. However, shoot and root weights were non-significant. Significant interactions revealed that cultivars responded variably to osmotic stress treatments; hence provided better opportunity to select drought tolerant cultivars at seedling growth stages. The relative decrease over averages due to osmotic stress was 0.8 percent in seed germination, 53 percent in coleoptile length 62.9 percent in shoot length, 74.4 percent in root length, 50.6 percent in shoot weight, 45.1 percent in root weight, 30.2 percent in root/shoot ratio and 68.5 percent in seed vigour index. However, relative decrease of individual variety for various seedling traits could be more meaningful which indicated that cultivar TD-1 showed no reduction in coleoptile length, while minimum decline was noted in Anmol. For shoot length, cultivar Sarsabz expressed minimum reduction followed by Anmol. However, cultivars Anmol, Moomal, Inqalab-91, and Pavan gave almost equally lower reductions for root length suggesting their higher stress tolerance. In other words, cultivars Anmol, Moomal, Inqalab-91, Sarsabz, TD-1, ZA-77 and Pavan had relatively longer coleoptiles, shoots and roots, and were regarded as drought tolerant. Correlation coefficients among seedlings traits were significant and positive for all traits except germination percentage which had no significant correlation with any of other trait. The results indicated that increase in one trait may cause simultaneous increase in other traits; hence selection for any of these seedling attributes will lead to develop drought tolerant wheat cultivars.

Decimal growth stages for precision wheat production in changing environments?

The utility of the decimal growth stage (DGS) scoring system for cereals is reviewed. The DGS is the most widely used scale in academic and commercial applications because of its comprehensive coverage of cereal developmental stages, the ease of use and definition provided and adoption by official agencies. The DGS has demonstrable and established value in helping to optimise the timing of agronomic inputs, particularly with regard to plant growth regulators, herbicides, fungicides and soluble nitrogen fertilisers. In addition, the DGS is used to help parameterise crop models, and also in understanding the response and adaptation of crops to the environment. The value of the DGS for increasing precision relies on it indicating, to some degree, the various stages in the development of the stem apex and spike. Coincidence of specific growth stage scores with the transition of the apical meristem from a vegetative to a reproductive state, and also with the period of meiosis, is unreliable. Nonetheless, in pot experiments it is shown that the broad period of booting (DGS 41–49) appears adequate for covering the duration when the vulnerability of meiosis to drought and heat stress is exposed. Similarly, the duration of anthesis (61–69) is particularly susceptible to abiotic stresses: initially from a fertility perspective, but increasingly from a mean grain weight perspective as flowering progresses to DGS 69 and then milk development. These associations with DGS can have value at the crop level of organisation: for interpreting environmental effects, and in crop modelling. However, genetic, biochemical and physiological analysis to develop greater understanding of stress acclimation during the vegetative state, and tolerance at meiosis, does require more precision than DGS can provide. Similarly, individual floret analysis is needed to further understand the genetic basis of stress tolerance during anthesis.

Modelling the partitioning of evapotranspiration in a maize-sunflower intercrop

The primary purpose of this study was to model the partitioning of evapotranspiration in a maize-sunflower intercrop at various canopy covers. The Shuttleworth-Wallace (SW) model was extended for intercropping systems to include both crop transpiration and soil evaporation and allowing interaction between the two. To test the accuracy of the extended SW model, two field experiments of maize-sunflower intercrop were conducted in 1998 and 1999. Plant transpiration and soil evaporation were measured using sap flow gauges and lysimeters, respectively. The mean prediction error (simulated minus measured values) for transpiration was zero (which indicated no overall bias in estimation error), and its accuracy was not affected by the plant growth stages, but simulated transpiration during high measured transpiration rates tended to be slightly underestimated. Overall, the predictions for daily soil evaporation were also accurate. Model estimation errors were probably due to the simplified modelling of soil water content, stomatal resistances and soil heat flux as well as due to the uncertainties in characterising the 2 micrometeorological conditions. The SW’s prediction of transpiration was most sensitive to parameters most directly related to the canopy characteristics such as the partitioning of captured solar radiation, canopy resistance, and bulk boundary layer resistance.

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).

Digestion, rumen fermentation and circulating concentrations of insulin, growth hormone and IGF-1 in steers given maize silages harvested at three stages of maturity

Advancing maturity of forage maize is associated with increases in the proportion of dry matter (DM) and starch and decreases in the proportions of structural carbohydrates in the ensiled crop. Three maize silages (286 (low, L), 329 (medium, M) and 379 (high, H) g DM per kg fresh weight) plus a concentrate formulated to give isonitrogenous intakes were offered to Holstein-Friesian steers fitted with a cannula in the dorsal sac of the rumen and a 'T' piece cannula in the proximal duodenum in an experiment with a cross-over design that allowed four collection periods. Nutrient flow to the duodenum was estimated using chromium-EDTA. Steers consumed approximately 0(.)6 kg DM per day less of diet L compared with the other two diets (P=0(.)026), resulting in less DM being digested (P=0(.)005) but digestibility did not differ between diets. Similar results were obtained for organic matter. There were no differences between diets in the intake or digestibility of neutral-detergent fibre. Intake, duodenal flow and faecal output of starch were greater for steers offered diets M and H compared with those given diet L (P < 0(.)05). In all diets rumen digestion contributed to over 90% of total digestion of starch, although rumen digestibility declined significantly with advancing maize maturity (P=0(.)002). Molar proportions of acetic acid were higher in diet H (P < 0(.)05) whilst proportions of propionic acid and n-butyric acid were higher in diets M and L. There were no significant differences between diets in mean rumen pH or ammonia concentrations. Mean circulating concentrations of insulin were higher (P=0(.)009) in cattle given diets L and M compared with diet H. There were no differences between diets in the mean circulating concentration of growth hormone, or the frequency, amplitude and duration of growth hormone pulses, or the mean circulating concentrations of IGF-1. Changes in forage composition that accompany advancing maize maturity affect overall silage digestion and circulating concentrations of insulin.

Oxidation of polycrystalline Ni studied by spectromicroscopy: Phase separation in the early stages of crystallite growth

Low-energy and photoemission electron microscopy enables the determination of facet planes of polycrystalline surfaces and the study of their chemical composition at the sub-m scale. Using these techniques the early oxidation stages of nickel were studied. After exposing the surface to 20 L of oxygen at 373 K a uniform layer of chemisorbed oxygen was found on all facets. After oxygen exposure at 473–673 K, small NiO crystallites are formed on all facets but not in the vicinity of all grain boundaries. The crystallites are separated by areas of bare Ni without significant oxygen coverage.

Stages of organizational transformation in transition economies: A dynamic capabilities approach

How do organizations previously dominated by the state develop dynamic capabilities that would support their growth in a competitive market economy? We develop a theoretical framework of organizational transformation that explains the processes by which organizations learn and develop dynamic capabilities in transition economies. Specifically, the framework theorizes about the importance of, and inter-relationships between, leadership, organizational learning, dynamic capabilities, and performance over three stages of transformation. Propositions derived from this framework explain the pre-conditions enabling organizational learning, the linkages between types of learning and functions of dynamic capabilities, and the feedback from dynamic capabilities to organizational learning that allows firms in transition economies to regain their footing and build long-term competitive advantage. We focus on transition contexts, where these processes have been magnified and thus offer new insights into strategizing in radically altered environments.

Growth of the lava dome and extrusion rates at Soufrière Hills Volcano, Montserrat, West Indies: 2005–2008

The third episode of lava dome growth at Soufrière Hills Volcano began 1 August 2005 and ended 20 April 2007. Volumes of the dome and talus produced were measured using a photo-based method with a calibrated camera for increased accuracy. The total dense rock equivalent (DRE) volume of extruded andesite magma (306 ± 51 Mm3) was similar within error to that produced in the earlier episodes but the average extrusion rate was 5.6 ± 0.9 m3s−1 (DRE), higher than the previous episodes. Extrusion rates varied in a pulsatory manner from <0.5 m3s−1 to ∼20 m3s−1. On 18 May 2006, the lava dome had reached a volume of 85 Mm3 DRE and it was removed in its entirety during a massive dome collapse on 20 May 2006. Extrusion began again almost immediately and built a dome of 170 Mm3 DRE with a summit height 1047 m above sea level by 4 April 2007. There were few moderate-sized dome collapses (1–10 Mm3) during this extrusive episode in contrast to the first episode of dome growth in 1995–8 when they were numerous. The first and third episodes of dome growth showed a similar pattern of low (<0.5 m3s−1) but increasing magma flux during the early stages, with steady high flux after extrusion of ∼25 Mm3

Effect of plant density and initial crown size on growth, development and yield in strawberry cultivars Elsanta and Bolero

The effects of density (plant spacing) and initial plant size on vegetative growth, flowering and fruiting were studied in the strawberry cultivars Elsanta and Bolero in their first and second years of cropping. The influence of these factors on light use and dry-matter partitioning was investigated. The size of planting material in 'Elsanta' and 'Bolero' slightly affected plant growth and yield, but this effect was not consistent and radiation use efficiency (RUE) and harvest index were unaltered. Plant spacing did not significantly affect the early stages of crop growth, but was important in determining growth and yield later in the season, this effect being more significant in the second year of cropping. Plant growth and yield per plant increased as plant spacing increased from 20 to 30 cm in both 'Elsanta' and 'Bolero', but the highest harvest index and yield per square metre were obtained at the closest spacing. Increased plant spacing also resulted in a greater leaf area and leaf area index. However, light was used less efficiently resulting in a lower RUE and lower harvest index (HI).

Effect of plant density and initial crown size on growth, development and yield in strawberry cultivars Elsanta and Bolero

The effects of density (plant spacing) and initial plant size on vegetative growth, flowering and fruiting were studied in the strawberry cultivars Elsanta and Bolero in their first and second years of cropping. The influence of these factors on light use and dry-matter partitioning was investigated. The size of planting material in 'Elsanta' and 'Bolero' slightly affected plant growth and yield, but this effect was not consistent and radiation use efficiency (RUE) and harvest index were unaltered. Plant spacing did not significantly affect the early stages of crop growth, but was important in determining growth and yield later in the season, this effect being more significant in the second year of cropping. Plant growth and yield per plant increased as plant spacing increased from 20 to 30 cm in both 'Elsanta' and 'Bolero', but the highest harvest index and yield per square metre were obtained at the closest spacing. Increased plant spacing also resulted in a greater leaf area and leaf area index. However, light was used less efficiently resulting in a lower RUE and lower harvest index (HI).

Rooting cuttings of Syringa vulgaris cv. Charles Joly and Corylus avellana cv. Aurea: the influence of stock plant pruning and shoot growth

The relationship between shoot growth and rooting was examined in two, 'difficult-to root' amenity trees, Syringa vulgaris L. cv. Charles Joly and Corylus avellana L. cv. Aurea. A range of treatments reflecting severity of pruning was imposed on field-grown stock prior to bud break. To minimise variation due to the numbers of buds that developed under different treatments, bud number was restricted to 30 per plant. Leafy cuttings were harvested at different stages of the active growth phase of each species. With Syringa, rooting decreased with later harvests, but loss of rooting potential was delayed in cuttings collected from the most severe pruning treatment. Rooting potential was associated with the extent of post-excision shoot growth on the cutting but regression analyses indicated that this relationship could not entirely explain the loss of rooting with time, nor the effects due to pruning. Similarly, in Corylus rooting was promoted by severe pruning, but the relationship between apical growth on the cutting and rooting was weaker than in Syringa, and only at the last harvest did growth play a critical role in determining rooting. Another unusual factor of the last harvest of Corylus was a bimodal distribution of roots per cutting, with very few rooted cuttings having less than five roots. This implies that, for this harvest at least, the potential of an individual cutting to root is probably not limited by the number of potential rooting sites.

Biomass partitioning and growth efficiency in four naturally regenerated forest tree species

Current forest growth models and yield tables are almost exclusively based on data from mature trees, reducing their applicability to young and developing stands. To address this gap, young European beech, sessile oak, Scots pine and Norway spruce trees approximately 0 to 10 years old were destructively sampled in a range of naturally regenerated forest stands in Central Europe. Diameter at base and height were first measured in situ for up to 175 individuals per species. Subsequently, the trees were excavated and dry biomass of foliage, branches, stems and roots was measured. Allometric relations were then used to calculate biomass allocation coefficients (BAC) and growth efficiency (GE) patterns in young trees. We found large differences in BAC and GE between broadleaves and conifers, but also between species within these categories. Both BAC and GE are strongly age-specific in young trees, their rapidly changing values reflecting different growth strategies in the earliest stages of growth. We show that linear relationships describing biomass allocation in older trees are not applicable in young trees. To accurately predict forest biomass and carbon stocks, forest growth models need to include species and age specific parameters of biomass allocation patterns.