206 research outputs found

    Alaska Public Policy: Current Problems and Issues, edited by Gordon Scott Harrison

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    Evaluating kernels on Xeon Phi to accelerate Gysela application

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    This work describes the challenges presented by porting parts ofthe Gysela code to the Intel Xeon Phi coprocessor, as well as techniques used for optimization, vectorization and tuning that can be applied to other applications. We evaluate the performance of somegeneric micro-benchmark on Phi versus Intel Sandy Bridge. Several interpolation kernels useful for the Gysela application are analyzed and the performance are shown. Some memory-bound and compute-bound kernels are accelerated by a factor 2 on the Phi device compared to Sandy architecture. Nevertheless, it is hard, if not impossible, to reach a large fraction of the peek performance on the Phi device,especially for real-life applications as Gysela. A collateral benefit of this optimization and tuning work is that the execution time of Gysela (using 4D advections) has decreased on a standard architecture such as Intel Sandy Bridge.Comment: submitted to ESAIM proceedings for CEMRACS 2014 summer school version reviewe

    Spectral soil analysis for fertilizer recommendations by coupling with QUEFTS for maize in East Africa: A sensitivity analysis

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    Laboratory analysis of soil properties is prohibitively expensive and difficult to scale across the soils in sub Saharan Africa. This results in a lack of soil-specific fertilizer recommendations, where recommendation can only be provided at a regional scale. This study aims to assess the feasibility of using spectral soil analysis to provide soil-specific fertilizer recommendations. Using a range of spectrometers [NeoSpectra Saucer (NIR), FieldSpec 4 (vis-NIR) with contact probe or mug light interface, FTIR Bruker Tensor 27 (MIR)], 346 archived soil samples (0–20 cm) with known soil chemical properties collected from Ethiopia, Kenya and Tanzania were scanned. Partial least square regression (PLSR) was used to develop prediction models for selected soil properties including pH, soil organic carbon (SOC), total nitrogen, Olsen P, and exchangeable K. These predicted properties, and associated uncertainty, were used to derive fertilizer recommendations for maize using the Quantitative Evaluation of the Fertility of Tropical Soils (QUEFTS) model parameters for sub-Saharan Africa. Most soil properties (pH, SOC, total nitrogen, and exchangeable K) were well predicted (Concordance Correlation Coefficient values between 0.88 and 0.96 and Ratio of Performance to Interquartile values between 1.4 and 5.9) by all the spectrometers but there were performance variations between soil properties and spec- trometers. Use of the predicted soil data for the development of fertilizer recommendations gave promising results when compared to the recommendations obtained with the conventional soil analysis. For example, the least performing NeoSpectra Saucer over/under-estimated up to 8 and 24 kg ha-1N and P, respectively, though there was insignificant variation in estimation of P fertilizer among spectrometers. We conclude that spectral technology can be used to determine major soil properties with satisfactory precision, sufficient for specific fertilizer decision making in East Africa, possibly even with portable equipment in the fiel

    The distribution of soil micro-nutrients and the effects on herbage micro-nutrient uptake and yield in three different pasture systems

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    Pasture micro-nutrient concentrations are often deficient for herbage productivity and the health of livestock. The aim of this study was to investigate soil and herbage micro-nutrient content and the effects on yield on the three pasture systems of the North Wyke Farm Platform (NWFP): high-sugar grass + legume mix minus nitrogen (N) fertilizer (blue/HSG + L); permanent pasture plus N fertilizer (green/P + N); high-sugar grass plus N fertilizer (red/HSG + N). The locations with high soil total micro-nutrient concentrations had a greater slope and higher soil organic matter (SOM) content. Herbage micro-nutrient concentrations were often greater at the locations with high soil total micro-nutrient concentrations. The concentration and uptake of nearly all mi-cro-nutrients was greatest in the herbage of the green/P + N system, which had the highest SOM content, whereas they were often lowest in the red/HSG + N system, which had the lowest SOM and the highest yield, indicating biomass dilution of micro-nutrients in the herbage. At the loca-tions with high soil micro-nutrient concentrations, yield was higher than at locations with low micro-nutrient concentrations, and was equal across the three pasture systems, regardless of fertilizer N treatment. Variation in micro-nutrient uptake/yield in the blue grass–legume system was predominantly explained by the soil molybdenum (Mo) concentration, possibly relating to the requirement for Mo in biological nitrogen fixation. There was, therefore, a trade-off in ploughing and re-seeding for higher yield, with the maintenance of SOM being important for herbage micro-nutrient content

    Predicting the growth of lettuce from soil infrared reflectance spectra: the potential for crop management

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    How well could one predict the growth of a leafy crop from reflectance spectra from the soil and how might a grower manage the crop in the light of those predictions? Two fields in the Cambridgeshire Fens in eastern England where farmers grow lettuce commercially were studied. Topsoil was sampled and analysed for various nutrients, particle-size distribution, and organic carbon concentration. Crop measurements (lettuce diameter) were derived by photogrammetry. Reflectance spectra were obtained in the laboratory from the soil in the near- and mid-infrared ranges, and these were used to predict crop performance by partial least squares regression (PLSR). Individual soil properties were also predicted from the spectra by PLSR. These estimated soil properties were used to predict lettuce diameter with a linear model (LM) and a linear mixed model (LMM): considering differences between lettuce varieties and the spatial correlation between data points. The PLSR predictions of the soil properties and lettuce diameter were close to observed values, with the latter showing a mean squared error (MSE) of 3.90 cm2 for Field 1 and 6.87 cm2 for Field 2. Prediction of lettuce diameter from the estimated soil properties with the LMs gave somewhat poorer results than those that used the soil spectra as predictor variables (difference in MSE for Field 1: 0.69 cm2 and Field 2: 2.12 cm2). Predictions from LMMs were more precise than those from the raw spectra (by PLSR alone) with a difference in mean squared error (MSE) of 2.12 cm2 for Field 1 and of 5.10 cm2 for Field 2. All model predictions improved when the effects of variety were taken into account. Predictions from the reflectance spectra, via the estimation of soil properties, can enable growers to decide what treatments to apply to grow lettuce and how to vary their treatments within their fields to maximize the net profit from the crop

    Projecting the Contribution of Provitamin A Maize Biofortification and Other Nutrition Interventions to the Nutritional Adequacy and Cost of Diets in Rural Zimbabwe

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    Background Evidence of the effectiveness of biofortified maize with higher provitamin A (PVA) to address vitamin A deficiency in rural Africa remains scant. Objectives This study projects the impact of adopting PVA maize for a diversity of households in an area typical of rural Zimbabwe and models the cost and composition of diets adequate in vitamin A. Methods Household-level weighed food records were generated from 30 rural households during a week in April and November 2021. Weekly household intakes were calculated, as well as indicative costs of diets using data from market surveys. The impact of PVA maize adoption was modeled assuming all maize products contained observed vitamin A concentrations. The composition and cost of the least expensive indicative diets adequate in vitamin A were calculated using linear programming. Results Very few households would reach adequate intake of vitamin A with the consumption of PVA maize. However, from a current situation of 33%, 50%–70% of households were projected to reach ≤50% of their requirements (the target of PVA), even with the modest vitamin A concentrations achieved on-farm (mean of 28.3 μg RAE per 100 g). This proportion would increase if higher concentrations recorded on-station were achieved. The estimated daily costs of current diets (mean ± standard deviation) were USD 1.43 ± 0.59 in the wet season and USD 0.96 ± 0.40 in the dry season. By comparison, optimization models suggest that diets adequate in vitamin A could be achieved at daily costs of USD 0.97 and USD 0.79 in the wet and dry seasons, respectively. Conclusions The adoption of PVA maize would bring a substantial improvement in vitamin A intake in rural Zimbabwe but should be combined with other interventions (e.g., diet diversification) to fully address vitamin A deficienc

    Construction of a generalised farm typology to aid selection, targeting and scaling of on farm research

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    Farm typologies are often used to reduce the complexity in categorising diverse farming systems, particularly in sub-Saharan Africa. The resulting typologies can then be used in multiple ways including designing efficient sampling schemes that capture the diversity in smallholder farms, prescribing the selection of certain farm types to which interventions can be targeted or upscaled, or to give context into derived relationships. However, the construction of farm typologies consists of many subjective decisions that are not always obvious or evident to the end-user. By developing a generalized framework for constructing farm typologies, we clarify where these subjective decisions are and quantify the impact they have on the resulting typologies. Further, this framework has been encapsulated in the open source RShiny App: TypologyGenerator to enable users to focus on the decisions and not the underlying implementation

    Plant Available Zinc Is Influenced by Landscape Position in the Amhara Region, Ethiopia

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    Zinc (Zn) is an important element determining the grain quality of staple food crops and deficient in many Ethiopian soils. However, farming systems are highly variable in Ethiopia due to different soil types and landscape cropping positions. Zinc availability and uptake by plants from soil and fertilizer sources are governed by the retention and release potential of the soil, usually termed as adsorption and desorption, respectively. The aim of this study was to characterize the amount of plant available Zn at different landscape positions. During the 2018/19 cropping season, adsorption-desorption studies were carried out on soil samples collected from on-farm trials conducted at Aba Gerima, Debre Mewi and Markuma in the Amhara Region. In all locations and landscape positions, adsorption and desorption increased with increasing Zn additions. The amount of adsorption and desorption was highly associated with the soil pH, the soil organic carbon concentration and cation exchange capacity, and these factors are linked to landscape positions. The Freundlich isotherm fitted very well to Zn adsorption (r2 0.87–0.99) and desorption (r2 0.92–0.99), while the Langmuir isotherm only fitted to Zn desorption (r2 0.70–0.93). Multiple regression models developed by determining the most influential soil parameters for Zn availability could be used to inform Zn fertilizer management strategies for different locations and landscape positions in this region, and thereby improve plant Zn use efficienc

    Liming impacts barley yield over a wide concentration range of soil exchangeable cations

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    Liming has widespread and significant impacts on soil processes and crop responses. The aim of this study was to describe the relationships between exchangeable cation concentrations in soil and the relative yield of spring barley. The hypothesis was that yield is restricted by the concentration of a single exchangeable cation in the soil. For simplicity, we focused on spring barley which was grown in nine years of a long-term experiment at two sites (Rothamsted and Woburn). Four liming rates were applied and in each year the relative yield (RY) and the concentrations of exchangeable cations were assessed. Liming had highly significant effects on the concentrations of most exchangeable cations, except for Cu and K. There were significant negative relationships (either linear or exponential) between the exchangeable concentrations of Mn, Cd, Cr, Al, Fe, Cu, Co, Zn and Ni in soil and soil pH. The relationships between RY and the concentrations of selected exchangeable cations (Mn, Ca and Al) were described well using log-logistic relationships. For these cations a significant site effect was probably due to fundamental differences in soil properties. At both sites the concentrations of exchangeable soil Al were excessive ([ 7.5 mg kg-1) and were most likely responsible for reduced barley yields (where RY B 0.5) with soil acidification. At Rothamsted barley yield was nonlimited (where RY C 1) at soil exchangeable Mn concentrations (up to 417 mg kg-1) greater than previously considered toxic, which requires further evaluation of critical Mn concentrations
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