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Baker, A.; Ceasar, S.A.; Palmer, A.J.; Paterson, J.B.; Qi, W.; Muench, S.P.; Baldwin, S.A. |
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Replace, reuse, recycle: improving the sustainable use of phosphorus by plants |
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2015 |
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Journal of Experimental Botany |
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J. Experim. Bot. |
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66 |
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12 |
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3523-3540 |
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Conservation of Natural Resources; Crops, Agricultural/growth & development/metabolism; Gene Expression Regulation, Plant; Phosphorus/*metabolism; Plant Proteins/genetics/metabolism; Plants/genetics/*metabolism; Fertilizers; membrane transporters; nutrient recycling; phosphate; phosphate signalling; transcription factors |
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The ‘phosphorus problem’ has recently received strong interest with two distinct strands of importance. The first is that too much phosphorus (P) is entering into waste water, creating a significant economic and ecological problem. Secondly, while agricultural demand for phosphate fertilizer is increasing to maintain crop yields, rock phosphate reserves are rapidly declining. Unravelling the mechanisms by which plants sense, respond to, and acquire phosphate can address both problems, allowing the development of crop plants that are more efficient at acquiring and using limited amounts of phosphate while at the same time improving the potential of plants and other photosynthetic organisms for nutrient recapture and recycling from waste water. In this review, we attempt to synthesize these important but often disparate parts of the debate in a holistic fashion, since solutions to such a complex problem require integrated and multidisciplinary approaches that address both P supply and demand. Rapid progress has been made recently in our understanding of local and systemic signalling mechanisms for phosphate, and of expression and regulation of membrane proteins that take phosphate up from the environment and transport it within the plant. We discuss the current state of understanding of such mechanisms involved in sensing and responding to phosphate stress. We also discuss approaches to improve the P-use efficiency of crop plants and future direction for sustainable use of P, including use of photosynthetic organisms for recapture of P from waste waters. |
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0022-0957 1460-2431 |
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Review |
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CropM |
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MA @ admin @ |
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4548 |
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Sharif, B.; Mankowski, D.; Kersebaum, K.C.; Trnka, M.; Schelde, K.; Olsesen, J.E. |
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Title |
Empirical analysis on crop-weather relationships |
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Report |
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2015 |
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FACCE MACSUR Reports |
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6 |
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D-C2.5 |
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There have been several studies, where process-based crop models are developed, used and compared in order to project crop production and corresponding model uncertainties under climate change. Despite many advances in this field, there are some correlations between climate variables and crop growth, such as pest and diseases, that is often absent in process-based models. Such relationships can be simulated using empirical models. In this study, several statistical techniques were applied on winter oilseed rape data collected in some European countries. The empirical models were then used to predict yield of winter oilseed rape in the field experiments during more than 20 years, up to 2013. Results suggest that newly developed regression techniques such as shrinkage methods work well both in yield projections and finding the influential climatic variables. Many of regression techniques agree in terms of yield prediction; however, choice of significant climate variables is rather sensitive to the choice of regression technique. No Label |
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2092 |
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Bellocchi, G.; Sándor, R. |
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Model intercomparison |
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2015 |
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FACCE MACSUR Reports |
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6 |
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D-L2.4 |
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This deliverable focuses on some illustrative results obtained with different grassland- specific, grassland adapted crop and dynamic vegetation models selected out of the first list of models compiled in D-L2.1.1 to simulate biomass and flux data from grassland sites in Europe and peri-Mediterranean regions (D-L2.1.1 and D-L2.1.2). Results from uncalibrated simulations were documented in the D-L2.3 report as a blind exercise. Some model improvements are emphasized in this report due to the higher information level of the model calibrations. The complete set of results will include simulations from uncalibrated and calibrated models. No Label |
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MA @ admin @ |
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2108 |
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Janssen, S.; Houtkamp, J.; De Groot, H.; Schils, R. |
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Online web tool for data visualization |
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Report |
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2015 |
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FACCE MACSUR Reports |
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6 |
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D-C2.6 |
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This deliverable lays out the work as done as part of MACSUR CropM on data, with the focus on providing a web tool for visualization of model output. It was decided early on that not a specific MACSUR web tool would be developed as part of MACSUR for phase 1, and mostly results would be visualized in other available tools, such as the Global Yield Gap Atlas, which are recognised resources for visualizations. Only in relationship to the MACSUR Geonetwork data catalog hosted at Aarhus University some developments where started. Operationally speaking, most data was still being generated during phase 1, so there was not enough to visualize on specific websites and partners did not commit financial resources to their development, and only in kind was available. No Label |
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MA @ admin @ |
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2093 |
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Janssen, S.; Hansen, J.G.; Jorgensen, J.; Jørgensen, M.S. |
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Operational database for storing and extracting data |
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2015 |
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FACCE MACSUR Reports |
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6 |
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D-C2.2 |
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This deliverable lays out the work as done as part of MACSUR CropM on data, with the focus on improving data management and have shared data curation for future use. The issue was tackled with help from the MACSUR central hub coordination in the form of Jason Jargenson from University of Reading. The data management as proposed and implemented in this deliverable is very much a bottom up process, in which partners in a meeting in Spring 2013 in Aarhus investigated the best way forward for data management across activities in CropM.As a follow up to this, the work was mainly divided in three parts: 1. The Open Data Journal for Agricultural Research, mainly focused on long term data archival and citation of data sets, as input and outputs to the modelling work, as part of MACSUR, lead by Wageningen UR 2. The Geonetwork data catalog hosted at Aarhus Universitet, that allows for operational access and storage of data sets as part of the ongoing work, also for restricted access of the consortium, and as a first step to visualization, lead by Aarhus Universitet. 3. The work on rating data sets, that provides a tool for improving data set access in an early phase for connecting them to models, lead by Reading University. At the end of the deliverable some next steps are giving for data activities in the context of AgMIP and beyond. No Label |
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MA @ admin @ |
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2091 |
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