Institution
University of Hohenheim
Education•Stuttgart, Germany•
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.
Papers published on a yearly basis
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TL;DR: The results indicate that breeders averted the narrowing of the wheat germplasm base and subsequently increased the genetic diversity through the introgression of novel materials.
Abstract: It has been claimed that plant breeding reduces genetic diversity in elite germplasm which could seriously jeopardize the continued ability to improve crops. The main objective of this study was to examine the loss of genetic diversity in spring bread wheat during (1) its domestication, (2) the change from traditional landrace cultivars (LCs) to modern breeding varieties, and (3) 50 years of international breeding. We studied 253 CIMMYT or CIMMYT-related modern wheat cultivars, LCs, and Triticum tauschii accessions, the D-genome donor of wheat, with 90 simple sequence repeat (SSR) markers dispersed across the wheat genome. A loss of genetic diversity was observed from T. tauschii to the LCs, and from the LCs to the elite breeding germplasm. Wheat’s genetic diversity was narrowed from 1950 to 1989, but was enhanced from 1990 to 1997. Our results indicate that breeders averted the narrowing of the wheat germplasm base and subsequently increased the genetic diversity through the introgression of novel materials. The LCs and T. tauschii contain numerous unique alleles that were absent in modern spring bread wheat cultivars. Consequently, both the LCs and T. tauschii represent useful sources for broadening the genetic base of elite wheat breeding germplasm.
393 citations
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Blaise Pascal University1, Institut national de la recherche agronomique2, University of Florida3, University of Bonn4, Goddard Institute for Space Studies5, Commonwealth Scientific and Industrial Research Organisation6, International Water Management Institute7, Michigan State University8, Agro ParisTech9, CGIAR10, University of Leeds11, University of Tübingen12, University of Alberta13, International Atomic Energy Agency14, University of Reading15, University of Guelph16, University of Hohenheim17, University of Maryland, College Park18, Potsdam Institute for Climate Impact Research19, Indian Agricultural Research Institute20, Department of Environment and Primary Industries21, Aarhus University22, Rothamsted Research23, Food and Agriculture Organization24, Washington State University25, Wageningen University and Research Centre26, Chinese Academy of Sciences27, International Trademark Association28, United States Department of Agriculture29
TL;DR: It is concluded that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics, and argued that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.
Abstract: Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.
392 citations
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TL;DR: It is suggested that dietary fructose intake, increased intestinal translocation of bacterial endotoxin, and PAI-1 may contribute to the development of NAFLD in humans.
Abstract: Results of animal experiments suggest that consumption of refined carbohydrates (e.g. fructose) can result in small intestinal bacterial overgrowth and increased intestinal permeability, thereby contributing to the development of nonalcoholic fatty liver disease (NAFLD). Furthermore, increased plasminogen activator inhibitor (PAI)-1 has been linked to liver damage of various etiologies (e.g. alcohol, endotoxin, nonalcoholic). The aim of the present pilot study was to compare dietary factors, endotoxin, and PAI-1 concentrations between NAFLD patients and controls. We assessed the dietary intake of 12 patients with NAFLD and 6 control subjects. Plasma endotoxin and PAI-1 concentrations as well as hepatic expression of PAI-1 and toll-like receptor (TLR) 4 mRNA were determined. Despite similar total energy, fat, protein, and carbohydrate intakes, patients with NAFLD consumed significantly more fructose than controls. Endotoxin and PAI-1 plasma concentrations as well as hepatic TLR4 and PAI-1 mRNA expression of NAFLD patients were significantly higher than in controls. The plasma PAI-1 concentration was positively correlated with the plasma endotoxin concentration (Spearman r = 0.83; P < 0.005) and hepatic TLR4 mRNA expression (Spearman r = 0.54; P < 0.05). Hepatic mRNA expression of PAI-1 was positively associated with dietary intakes of carbohydrates (Spearman r = 0.67; P < 0.01), glucose (Spearman r = 0.58; P < 0.01), fructose (Spearman r = 0.58; P < 0.01), and sucrose (Spearman r = 0.70; P < 0.01). In conclusion, our results suggest that dietary fructose intake, increased intestinal translocation of bacterial endotoxin, and PAI-1 may contribute to the development of NAFLD in humans.
391 citations
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TL;DR: The results of these experiments support the idea of an enzymic reduction of Fe(III) on the plasmalemma of cortical cells of roots.
Abstract: Iron deficiency in peanuts (Arachis hypogeae L.) caused an increase in release of caffeic acid, a higher rate of Fe(III) reduction, and increased rates of both Fe(III) chelate splitting and iron uptake.Experiments on Fe(III) reduction by phenolics (in vitro experiments) and by roots of Fe-deficient peanuts exclude the direct involvement of released phenolics in Fe(III) reduction by roots: Fe(III) reduction by phenolics had a pH optimum higher than 8.0 and was strongly dependent on the concentration and the stability of the supplied Fe(III) chelates. In contrast, Fe(III) reduction by roots of Fe-deficient peanuts had a pH optimum of about 5.0 and was less dependent on the stability of the supplied Fe(III) chelates. Furthermore, the observed release of phenolics into nutrient solution would have to be at least 200 times higher to attain the reduction rates of roots of Fe-deficient peanuts. The results of these experiments support the idea of an enzymic reduction of Fe(III) on the plasmalemma of cortical cells of roots.
386 citations
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TL;DR: In this article, an in vitro enzymatic starch digestion method was applied in order to estimate the expected glycemic index in vivo based on the kinetics of starch hydrolysis in vitro.
383 citations
Authors
Showing all 8665 results
Name | H-index | Papers | Citations |
---|---|---|---|
Robert J. Lefkowitz | 214 | 860 | 147995 |
Patrick O. Brown | 183 | 755 | 200985 |
Mark Stitt | 132 | 456 | 60800 |
Wolf B. Frommer | 105 | 345 | 30918 |
Muhammad Imran | 94 | 3053 | 51728 |
Muhammad Farooq | 92 | 1341 | 37533 |
Yakov Kuzyakov | 87 | 667 | 37050 |
Werner Goebel | 85 | 367 | 26106 |
Ismail Cakmak | 84 | 249 | 25991 |
Reinhold Carle | 84 | 418 | 24858 |
Michael Wink | 83 | 938 | 32658 |
Albrecht E. Melchinger | 83 | 398 | 23140 |
Tilman Grune | 82 | 479 | 30327 |
Volker Römheld | 79 | 231 | 20763 |
Klaus Becker | 79 | 320 | 27494 |