944 resultados para potential nutrient use efficiency


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Attempts to estimate photosynthetic rate or gross primary productivity from remotely sensed absorbed solar radiation depend on knowledge of the light use efficiency (LUE). Early models assumed LUE to be constant, but now most researchers try to adjust it for variations in temperature and moisture stress. However, more exact methods are now required. Hyperspectral remote sensing offers the possibility of sensing the changes in the xanthophyll cycle, which is closely coupled to photosynthesis. Several studies have shown that an index (the photochemical reflectance index) based on the reflectance at 531 nm is strongly correlated with the LUE over hours, days and months. A second hyperspectral approach relies on the remote detection of fluorescence, which is a directly related to the efficiency of photosynthesis. We discuss the state of the art of the two approaches. Both have been demonstrated to be effective, but we specify seven conditions required before the methods can become operational.

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Near-isogenic lines (NILs) of winter wheat varying for alleles for reduced height (Rht), gibberellin (GA) response and photoperiod insensitivity (Ppd-D1a) in cv. Mercia background (rht (tall), Rht-B1b, Rht-D1b, Rht-B1c, Rht8c+Ppd-D1a, Rht-D1c, Rht12) and cv. Maris Widgeon (rht (tall), Rht-D1b, Rht-B1c) backgrounds were compared to investigate main effects and interactions with tillage (plough-based, minimum-, and zero-tillage) over two years. Both minimum- and zero- tillage were associated with reduced grain yields allied to reduced harvest index, biomass accumulation, interception of photosynthetically active radiation (PAR), and plant populations. Grain yields were optimized at mature crop heights of around 740mm because this provided the best compromise between harvest index which declined with height, and above ground biomass which increased with height. Improving biomass with height was due to improvements in both PAR interception and radiation-use efficiency. Optimum height for grain yield was unaffected by tillage system or GA-sensitivity. After accounting for effects of height, GA insensitivity was associated with increased grain yields due to increased grains per spike, which was more than enough to compensate for poorer plant establishment and lower mean grain weights compared to the GA-sensitive lines. Although better establishment was possible with GA-sensitive lines, there was no evidence that this effect interacted with tillage method. We find, therefore, little evidence to question the current adoption of wheats with reduced sensitivity to GA in the UK, even as tillage intensity lessens.

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Antiinflammatory compounds in the diet can alleviate excessive inflammation, a factor in the pathogenesis of common diseases such as rheumatoid arthritis, atherosclerosis and diabetes. This study examined three European herbs, chamomile (Matricaria chamomilla), meadowsweet (Filipendula ulmaria L.) and willow bark (Salix alba L.), which have been traditionally used to treat inflammation and their potential for use as antiinflammatory agents. Aqueous herbal extracts and isolated polyphenolic compounds (apigenin, quercetin and salicylic acid, 0–100 μM) were incubated with THP1 macrophages, and interleukin (IL)-1β, IL-6 and tumour necrosis factor-alpha (TNF-) were measured. At concentrations of 10 μM, both apigenin and quercetin reduced IL-6 significantly ( p < 0.05). Apigenin at 10 μM and quercetin at 25 μM reduced TNF- significantly ( p < 0.05). Amongst the herbal extracts, willow bark had the greatest antiinflammatory activity at reducing IL-6 and TNF- production. This was followed by meadowsweet and then chamomile. The lowest effective antiinflammatory concentrations were noncytotoxic (MTT mitochondrial activity assay). The Comet assay, which was used to study the protective effect of the isolated phenols against oxidative damage, showed positive results for all three polyphenols. These are the first findings that demonstrate the antiinflammatory capacity of these herbal extracts.

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We present a benchmark system for global vegetation models. This system provides a quantitative evaluation of multiple simulated vegetation properties, including primary production; seasonal net ecosystem production; vegetation cover, composition and 5 height; fire regime; and runoff. The benchmarks are derived from remotely sensed gridded datasets and site-based observations. The datasets allow comparisons of annual average conditions and seasonal and inter-annual variability, and they allow the impact of spatial and temporal biases in means and variability to be assessed separately. Specifically designed metrics quantify model performance for each process, 10 and are compared to scores based on the temporal or spatial mean value of the observations and a “random” model produced by bootstrap resampling of the observations. The benchmark system is applied to three models: a simple light-use efficiency and water-balance model (the Simple Diagnostic Biosphere Model: SDBM), and the Lund-Potsdam-Jena (LPJ) and Land Processes and eXchanges (LPX) dynamic global 15 vegetation models (DGVMs). SDBM reproduces observed CO2 seasonal cycles, but its simulation of independent measurements of net primary production (NPP) is too high. The two DGVMs show little difference for most benchmarks (including the interannual variability in the growth rate and seasonal cycle of atmospheric CO2), but LPX represents burnt fraction demonstrably more accurately. Benchmarking also identified 20 several weaknesses common to both DGVMs. The benchmarking system provides a quantitative approach for evaluating how adequately processes are represented in a model, identifying errors and biases, tracking improvements in performance through model development, and discriminating among models. Adoption of such a system would do much to improve confidence in terrestrial model predictions of climate change 25 impacts and feedbacks.

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Purpose – The aim of this paper is to present a conceptual valuation framework to allow telecare service stakeholders to assess telecare devices in the home in terms of their social, psychological and practical effects. The framework enables telecare service operators to more effectively engage with the social and psychological issues resulting from telecare technology deployment in the home and to design and develop appropriate responses as a result. Design/methodology/approach – The paper provides a contextual background for the need for sociologically pitched tools that engage with the social and cultural feelings of telecare service users before presenting the valuation framework and how it could be used. Findings – A conceptual valuation framework is presented for potential development/use. Research limitations/implications – The valuation framework has yet to be extensively tested or verified. Practical implications – The valuation framework needs to be tested and deployed by a telecare service operator but the core messages of the paper are valid and interesting for readership. Social implications – In addressing the social and cultural perspectives of telecare service stakeholders, the paper makes a link between the technologies in the home, the feelings and orientations of service users (e.g. residents, emergency services, wardens, etc.) and the telecare service operator. Originality/value – The paper is an original contribution to the field as it details how the sociological orientations of telecare technology service users should be valued and addressed by service operators. It has a value through the conceptual arguments made and through valuation framework presented.

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The primary role of land surface models embedded in climate models is to partition surface available energy into upwards, radiative, sensible and latent heat fluxes. Partitioning of evapotranspiration, ET, is of fundamental importance: as a major component of the total surface latent heat flux, ET affects the simulated surface water balance, and related energy balance, and consequently the feedbacks with the atmosphere. In this context it is also crucial to credibly represent the CO2 exchange between ecosystems and their environment. In this study, JULES, the land surface model used in UK weather and climate models, has been evaluated for temperate Europe. Compared to eddy covariance flux measurements, the CO2 uptake by the ecosystem is underestimated and the ET overestimated. In addition, the contribution to ET from soil and intercepted water evaporation far outweighs the contribution of plant transpiration. To alleviate these biases, adaptations have been implemented in JULES, based on key literature references. These adaptations have improved the simulation of the spatio-temporal variability of the fluxes and the accuracy of the simulated GPP and ET, including its partitioning. This resulted in a shift of the seasonal soil moisture cycle. These adaptations are expected to increase the fidelity of climate simulations over Europe. Finally, the extreme summer of 2003 was used as evaluation benchmark for the use of the model in climate change studies. The improved model captures the impact of the 2003 drought on the carbon assimilation and the water use efficiency of the plants. It, however, underestimates the 2003 GPP anomalies. The simulations showed that a reduction of evaporation from the interception and soil reservoirs, albeit not of transpiration, largely explained the good correlation between the carbon and the water fluxes anomalies that was observed during 2003. This demonstrates the importance of being able to discriminate the response of individual component of the ET flux to environmental forcing.

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The role of different sky conditions on diffuse PAR fraction (ϕ), air temperature (Ta), vapor pressure deficit (vpd) and GPP in a deciduous forest is investigated using eddy covariance observations of CO2 fluxes and radiometer and ceilometer observations of sky and PAR conditions on hourly and growing season timescales. Maximum GPP response occurred under moderate to high PAR and ϕ and low vpd. Light response models using a rectangular hyperbola showed a positive linear relation between ϕ and effective quantum efficiency (α = 0.023ϕ + 0.012, r2 = 0.994). Since PAR and ϕ are negatively correlated, there is a tradeoff between the greater use efficiency of diffuse light and lower vpd and the associated decrease in total PAR available for photosynthesis. To a lesser extent, light response was also modified by vpd and Ta. The net effect of these and their relation with sky conditions helped enhance light response under sky conditions that produced higher ϕ. Six sky conditions were classified from cloud frequency and ϕ data: optically thick clouds, optically thin clouds, mixed sky (partial clouds within hour), high, medium and low optical aerosol. The frequency and light responses of each sky condition for the growing season were used to predict the role of changing sky conditions on annual GPP. The net effect of increasing frequency of thick clouds is to decrease GPP, changing low aerosol conditions has negligible effect. Increases in the other sky conditions all lead to gains in GPP. Sky conditions that enhance intermediate levels of ϕ, such as thin or scattered clouds or higher aerosol concentrations from volcanic eruptions or anthropogenic emissions, will have a positive outcome on annual GPP, while an increase in cloud cover will have a negative impact. Due to the ϕ/PAR tradeoff and since GPP response to changes in individual sky conditions differ in sign and magnitude, the net response of ecosystem GPP to future sky conditions is non-linear and tends toward moderation of change.

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We present a benchmark system for global vegetation models. This system provides a quantitative evaluation of multiple simulated vegetation properties, including primary production; seasonal net ecosystem production; vegetation cover; composition and height; fire regime; and runoff. The benchmarks are derived from remotely sensed gridded datasets and site-based observations. The datasets allow comparisons of annual average conditions and seasonal and inter-annual variability, and they allow the impact of spatial and temporal biases in means and variability to be assessed separately. Specifically designed metrics quantify model performance for each process, and are compared to scores based on the temporal or spatial mean value of the observations and a "random" model produced by bootstrap resampling of the observations. The benchmark system is applied to three models: a simple light-use efficiency and water-balance model (the Simple Diagnostic Biosphere Model: SDBM), the Lund-Potsdam-Jena (LPJ) and Land Processes and eXchanges (LPX) dynamic global vegetation models (DGVMs). In general, the SDBM performs better than either of the DGVMs. It reproduces independent measurements of net primary production (NPP) but underestimates the amplitude of the observed CO2 seasonal cycle. The two DGVMs show little difference for most benchmarks (including the inter-annual variability in the growth rate and seasonal cycle of atmospheric CO2), but LPX represents burnt fraction demonstrably more accurately. Benchmarking also identified several weaknesses common to both DGVMs. The benchmarking system provides a quantitative approach for evaluating how adequately processes are represented in a model, identifying errors and biases, tracking improvements in performance through model development, and discriminating among models. Adoption of such a system would do much to improve confidence in terrestrial model predictions of climate change impacts and feedbacks.

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It is well known that atmospheric concentrations of carbon dioxide (CO2) (and other greenhouse gases) have increased markedly as a result of human activity since the industrial revolution. It is perhaps less appreciated that natural and managed soils are an important source and sink for atmospheric CO2 and that, primarily as a result of the activities of soil microorganisms, there is a soil-derived respiratory flux of CO2 to the atmosphere that overshadows by tenfold the annual CO2 flux from fossil fuel emissions. Therefore small changes in the soil carbon cycle could have large impacts on atmospheric CO2 concentrations. Here we discuss the role of soil microbes in the global carbon cycle and review the main methods that have been used to identify the microorganisms responsible for the processing of plant photosynthetic carbon inputs to soil. We discuss whether application of these techniques can provide the information required to underpin the management of agro-ecosystems for carbon sequestration and increased agricultural sustainability. We conclude that, although crucial in enabling the identification of plant-derived carbon-utilising microbes, current technologies lack the high-throughput ability to quantitatively apportion carbon use by phylogentic groups and its use efficiency and destination within the microbial metabolome. It is this information that is required to inform rational manipulation of the plant–soil system to favour organisms or physiologies most important for promoting soil carbon storage in agricultural soil.

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Sustainable Intensification (SI) of agriculture has recently received widespread political attention, in both the UK and internationally. The concept recognises the need to simultaneously raise yields, increase input use efficiency and reduce the negative environmental impacts of farming systems to secure future food production and to sustainably use the limited resources for agriculture. The objective of this paper is to outline a policy-making tool to assess SI at a farm level. Based on the method introduced by Kuosmanen and Kortelainen (2005), we use an adapted Data Envelopment Analysis (DEA) to consider the substitution possibilities between economic value and environmental pressures generated by farming systems in an aggregated index of Eco-Efficiency. Farm level data, specifically General Cropping Farms (GCFs) from the East Anglian River Basin Catchment (EARBC), UK were used as the basis for this analysis. The assignment of weights to environmental pressures through linear programming techniques, when optimising the relative Eco-Efficiency score, allows the identification of appropriate production technologies and practices (integrating pest management, conservation farming, precision agriculture, etc.) for each farm and therefore indicates specific improvements that can be undertaken towards SI. Results are used to suggest strategies for the integration of farming practices and environmental policies in the framework of SI of agriculture. Paths for improving the index of Eco-Efficiency and therefore reducing environmental pressures are also outlined.

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Climate projections show Australia becoming significantly warmer during the 21st century, and precipitation decreasing over much of the continent. Such changes are conventionally considered to increase wildfire risk. Nevertheless, we show that burnt area increases in southern Australia, but decreases in northern Australia. Overall the projected increase in fire is small (0.72–1.31% of land area, depending on the climate scenario used), and does not cause a decrease in carbon storage. In fact, carbon storage increases by 3.7–5.6 Pg C (depending on the climate scenario used). Using a process-based model of vegetation dynamics, vegetation–fire interactions and carbon cycling, we show increased fire promotes a shift to more fire-adapted trees in wooded areas and their encroachment into grasslands, with an overall increase in forested area of 3.9–11.9%. Both changes increase carbon uptake and storage. The increase in woody vegetation increases the amount of coarse litter, which decays more slowly than fine litter hence leading to a relative reduction in overall heterotrophic respiration, further reducing carbon losses. Direct CO2 effects increase woody cover, water-use efficiency and productivity, such that carbon storage is increased by 8.5–14.8 Pg C compared to simulations in which CO2 is held constant at modern values. CO2 effects tend to increase burnt area, fire fluxes and therefore carbon losses in arid areas, but increase vegetation density and reduce burnt area in wooded areas.

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Adult neural crest related-stem cells persist in adulthood, making them an ideal and easily accessible source of multipotent cells for potential clinical use. Recently, we reported the presence of neural crest-related stem cells within adult palatal ridges, thus raising the question of their localization in their endogenous niche. Using immunocytochemistry, reverse transcription-polymerase chain reaction, and correlative fluorescence and transmission electron microscopy, we identified myelinating Schwann cells within palatal ridges as a putative neural crest stem cell source. Palatal Schwann cells expressed nestin, p75(NTR), and S100. Correlative fluorescence and transmission electron microscopy revealed the exclusive nestin expression within myelinating Schwann cells. Palatal neural crest stem cells and nestin-positive Schwann cells isolated from adult sciatic nerves were able to grow under serum-free conditions as neurospheres in presence of FGF-2 and EGF. Spheres of palatal and sciatic origin showed overlapping expression pattern of neural crest stem cell and Schwann cell markers. Expression of the pluripotency factors Sox2, Klf4, c-Myc, Oct4, the NF-κB subunits p65, p50, and the NF-κB-inhibitor IκB-β were up-regulated in conventionally cultivated sciatic nerve Schwann cells and in neurosphere cultures. Finally, neurospheres of palatal and sciatic origin were able to differentiate into ectodermal, mesodermal, and endodermal cell types emphasizing their multipotency. Taken together, we show that nestin-positive myelinating Schwann cells can be reprogrammed into multipotent adult neural crest stem cells under appropriate culture conditions.

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We used a light-use efficiency model of photosynthesis coupled with a dynamic carbon allocation and tree-growth model to simulate annual growth of the gymnosperm Callitris columellaris in the semi-arid Great Western Woodlands, Western Australia, over the past 100 years. Parameter values were derived from independent observations except for sapwood specific respiration rate, fine-root turnover time, fine-root specific respiration rate and the ratio of fine-root mass to foliage area, which were estimated by Bayesian optimization. The model reproduced the general pattern of interannual variability in radial growth (tree-ring width), including the response to the shift in precipitation regimes that occurred in the 1960s. Simulated and observed responses to climate were consistent. Both showed a significant positive response of tree-ring width to total photosynthetically active radiation received and to the ratio of modeled actual to equilibrium evapotranspiration, and a significant negative response to vapour pressure deficit. However, the simulations showed an enhancement of radial growth in response to increasing atmospheric CO2 concentration (ppm) ([CO2]) during recent decades that is not present in the observations. The discrepancy disappeared when the model was recalibrated on successive 30-year windows. Then the ratio of fine-root mass to foliage area increases by 14% (from 0.127 to 0.144 kg C m-2) as [CO2] increased while the other three estimated parameters remained constant. The absence of a signal of increasing [CO2] has been noted in many tree-ring records, despite the enhancement of photosynthetic rates and water-use efficiency resulting from increasing [CO2]. Our simulations suggest that this behaviour could be explained as a consequence of a shift towards below-ground carbon allocation.

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Groundnuts cultivated in the semiarid tropics are often exposed to water stress (mid-season and end season) and high temperature (> 34 °C) during the critical stages of flowering and pod development. This study evaluated the effects of both water stress and high temperature under field conditions at ICRISAT, India. Treatments included two irrigations (full irrigation, 100 % of crop evapotranspiration; and water stress, 40 % of crop evapotranspiration), four temperature treatments from a combination of two sowing dates and heat tunnels with mean temperatures from sowing to maturity of 26.3° (T1), 27.3° (T2), 29.0° (T3) and 29.7 °C (T4) and two genotypes TMV2 and ICGS 11. The heat tunnels were capable of raising the day temperature by > 10 °C compared to ambient. During the 20-day high-temperature treatment at flowering, mean temperatures were 33.8° (T1), 41.6° (T2), 38.7° (T3) and 43.5°C (T4). The effects of water stress and high temperature were additive and temporary for both vegetative and pod yield, and disappeared as soon as high-temperature stress was removed. Water use efficiency was significantly affected by the main effects of temperature and cultivar and not by water stress treatments. Genotypic differences for tolerance to high temperature can be attributed to differences in flowering pattern, flower number, peg-set and harvest index. It can be inferred from this study that genotypes that are tolerant to water stress are also tolerant to high temperature under field conditions. In addition, genotypes with an ability to establish greater biomass and with a significantly greater partitioning of biomass to pod yield would be suitable for sustaining higher yields in semiarid tropics with high temperature and water stress.

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Change in morphological and physiological parameters in response to phosphorus (P) supply was studied in 11 perennial herbaceous legume species, six Australian native (Lotus australis, Cullen australasicum, Kennedia prorepens, K. prostrata, Glycine canescens, C. tenax) and five exotic species (Medicago sativa, Lotononis bainesii, Bituminaria bituminosa var albomarginata, Lotus corniculatus, Macroptilium bracteatum). We aimed to identify mechanisms for P acquisition from soil. Plants were grown in sterilised washed river sand; eight levels of P as KH2PO4 ranging from 0 to 384 μg P g−1 soil were applied. Plant growth under low-P conditions strongly correlated with physiological P-use efficiency and/or P-uptake efficiency. Taking all species together, at 6 μg P g−1 soil there was a good correlation between P uptake and both root surface area and total root length. All species had higher amounts of carboxylates in the rhizosphere under a low level of P application. Six of the 11 species increased the fraction of rhizosphere citrate in response to low P, which was accompanied by a reduction in malonate, except L. corniculatus. In addition, species showed different plasticity in response to P-application levels and different strategies in response to P deficiency. Our results show that many of the 11 species have prospects for low-input agroecosystems based on their high P-uptake and P-use efficiency.