University of Hohenheim

About: University of Hohenheim is a education organization based out in Stuttgart, Germany. It is known for research contribution in the topics: Population & Soil water. The organization has 8585 authors who have published 16406 publications receiving 567377 citations.

Potential impact and cost-effectiveness of Golden Rice.

Abstract: Genetic engineering (GE) in agriculture is a controversial topic in science and society at large. While some oppose genetically modified crops as proxy of an agricultural system they consider unsustainable and inequitable, the question remains whether GE can benefit the poor within the existing system and what needs to be done to deliver these benefits? Golden Rice has been genetically engineered to produce provitamin A. The technology is still in the testing phase, but, once released, it is expected to address one consequence of poverty – vitamin A deficiency (VAD) – and its health implications. Current interventions to combat VAD rely mainly on pharmaceutical supplementation, which is costly in the long run and only partially successful. We develop a methodology for ex-ante evaluation, taking into account the whole sequence of effects between the cultivation of the crop and its ultimate health impacts. In doing so we build on a comprehensive, nationally representative data set of household food consumption in India. Using a refined disability-adjusted life year (DALY) framework and detailed health data, this study shows for India that under optimistic assumptions this country’s annual burden of VAD of 2.3 million DALYs lost can be reduced by 59.4% hence 1.4 million healthy life years could be saved each year if Golden Rice would be consumed widely. In a low impact scenario, where Golden Rice is consumed less frequently and produces less provitamin A, the burden of VAD could be reduced by 8.8%. However, in both scenarios the cost per DALY saved through Golden Rice (US$3.06-19.40) is lower than the cost of current supplementation efforts, and it outperforms international cost-effectiveness thresholds. Golden Rice should therefore be considered seriously as a complementary intervention to fight VAD in rice-eating populations in the medium term. JEL classifications: I0, I3, Q16, Q18.

Carbohydrate and amino acid composition of dissolved organic matter leached from soil

Abstract: Low molecular weight organic substances (LMWOS) in soil and soil solution include mainly amino acids, carboxylic acids, and carbohydrates. Due to their high bioavailability they play a crucial role in the cycles of C and nutrients in soils. The variety of soil processes that involve LMWOS requires identifying their composition to elucidate reactions and transformations. In most studies, LMWOS are extracted under artificial conditions, e.g. batch experiments, which may overestimate the actual concentrations. This study measures the composition of carbohydrates and amino acids in solution of a Haplic Luvisol leached in a column experiment. A combined system for simultaneous leaching and blowout of CO2 was used to estimate LMWOS decomposition. 14 C-labeled glucose was added as a highly sensitive tracer to control the efficiency of the LMWOS extraction by leaching and to estimate LMWOS decomposition during leaching. High performance liquid chromatography (HPLC), optimized for soil extracts, was used to analyze LMWOS composition. For HPLC optimization, different preparations of leached solutions (filtration vs. centrifugation, and drying vs. no-drying) were compared. For sugar determination, drying had no influence on the solution concentrations. In contrast, amino acid concentrations significantly decreased by drying LMWOS eluted substances. Combining the HPLC identification of eluted substances with 14 C tracer application revealed that about 5% of the glucose could be leached unchanged within 786 min (13.1 h), whereas about 84% remained in the soil, 9% were decomposed to CO2, and 2% were transformed to other LMWOS and recovered in the soil solution. The total amino acid concentration (TAC) in soil solution was about 8.2mmol l � 1 , dominated by alanine (14.4% of TAC), glycine (13.4%), glutamic acid (9.9%), serine (9.4%), and leucine (9.3%). The total carbohydrate concentration was about 2.4mM, dominated by glucose (29.9%), glucuronic acid (26.8%), and galacturonic acid (17.3%). Ratios of hexoses to pentoses, amino sugars glucosamine to galactosamine, and neutral sugars to uronic acids were determined. All three parameters pointed to the dominant influence of plants as the source of LMWOS in the leached soil solution. Within the small contribution of microorganisms, bacteria dominated over fungi. These used biomarker ratios as well as LMWOS concentrations differed widely from the ones obtained with conventional batch extraction. More research is necessary to evaluate the application of these biomarkers to soil solutions. r 2007 Elsevier Ltd. All rights reserved.

Current statistical issues in Weed Research

Abstract: Onofri A, Carbonell EA, Piepho H-P, Mortimer AM & Cousens RD (2010) Current statistical issues in Weed Research Weed Research50, 5–24 Summary The correct design of experimental studies, the selection of the appropriate statistical analysis of data and the efficient presentation of results are key to the good conduct and communication of science The last Guidance for the use and presentation of statistics in Weed Research was published in 1988 Since then, there have been developments in both the scope of research covered by the journal and in the statistical techniques available This paper addresses the changes in statistics and provides a reference work that will aid researchers in the design and analysis of their work It will also provide guidance for editors and reviewers The paper is organised into sections, which will aid the selection of relevant paragraphs, as we recognise that particular approaches require particular statistical analysis It also uses examples, questions and checklists, so that non-specialists can work towards the correct approach Statistics can be complex, so knowing when to seek specialist advice is important The structure and layout of this contribution should help weed scientists, but it cannot provide a comprehensive guide to every technique Therefore, we provide references to further reading We would like to reinforce the idea that statistical methods are not a set of recipes whose mindless application is required by convention; each experiment or study may involve subtleties that these guidelines cannot cover Nevertheless, we anticipate that this paper will help weed scientists in their initial designs for research, in the analysis of data and in the presentation of results for publication