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Author Nendel, C.; Wieland, R.; Mirschel, W.; Specka, X.; Guddat, C.; Kersebaum, K.C. url  doi
openurl 
  Title Simulating regional winter wheat yields using input data of different spatial resolution Type Journal Article
  Year 2013 Publication Field Crops Research Abbreviated Journal Field Crops Research  
  Volume 145 Issue Pages 67-77  
  Keywords monica; agro-ecosystem model; dynamic modelling; scaling; input data; climate-change; crop yield; nitrogen dynamics; food security; mineral nitrogen; soil-moisture; scaling-up; model; maize; water  
  Abstract (down) The success of using agro-ecosystem models for the high-resolution simulation of agricultural yields for larger areas is often hampered by a lack of input data. We investigated the effect of different spatially resolved soil and weather data used as input for the MONICA model on its ability to reproduce winter wheat yields in the Federal State of Thuringia, Germany (16,172 km(2)). The combination of one representative soil and one weather station was insufficient to reproduce the observed mean yield of 6.66 +/- 0.87 t ha(-1) for the federal state. Use of a 100 m x 100 m grid of soil and relief information combined with just one representative weather station yielded a good estimator (7.01 +/- 1.47 t ha(-1)). The soil and relief data grid used in combination with weather information from 14 weather stations in a nearest neighbour approach produced even better results (6.60 +/- 1.37 t ha(-1)); the same grid used with 39 additional rain gauges and an interpolation algorithm that included an altitude correction of temperature data slightly overpredicted the observed mean (7.36 +/- 1.17 t ha(-1)). It was concluded that the apparent success of the first two high-resolution approaches over the latter was based on two effects that cancelled each other out: the calibration of MONICA to match high-yield experimental data and the growth-defining and -limiting effect of weather data that is not representative for large parts of the region. At the county and farm level the MONICA model failed to reproduce the 1992-2010 time series of yields, which is partly explained by the fact that many growth-reducing factors were not considered in the model. (C) 2013 Elsevier B.V. All rights reserved.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0378-4290 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4498  
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Author Dumont, B.; Leemans, V.; Ferrandis, S.; Bodson, B.; Destain, J.-P.; Destain, M.-F. url  doi
openurl 
  Title Assessing the potential of an algorithm based on mean climatic data to predict wheat yield Type Journal Article
  Year 2014 Publication Precision Agriculture Abbreviated Journal Precision Agric.  
  Volume 15 Issue 3 Pages 255-272  
  Keywords stics model; yield prediction; real-time; proxy-sensing; stochastic weather generator; crop yield; mediterranean environment; simulation-model; variability; nitrogen; ensembles; forecasts; demeter; europe  
  Abstract (down) The real-time non-invasive determination of crop biomass and yield prediction is one of the major challenges in agriculture. An interesting approach lies in using process-based crop yield models in combination with real-time monitoring of the input climatic data of these models, but unknown future weather remains the main obstacle to reliable yield prediction. Since accurate weather forecasts can be made only a short time in advance, much information can be derived from analyzing past weather data. This paper presents a methodology that addresses the problem of unknown future weather by using a daily mean climatic database, based exclusively on available past measurements. It involves building climate matrix ensembles, combining different time ranges of projected mean climate data and real measured weather data originating from the historical database or from real-time measurements performed in the field. Used as an input for the STICS crop model, the datasets thus computed were used to perform statistical within-season biomass and yield prediction. This work demonstrated that a reliable predictive delay of 3-4 weeks could be obtained. In combination with a local micrometeorological station that monitors climate data in real-time, the approach also enabled us to (i) predict potential yield at the local level, (ii) detect stress occurrence and (iii) quantify yield loss (or gain) drawing on real monitored climatic conditions of the previous few days.  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1385-2256 1573-1618 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM Approved no  
  Call Number MA @ admin @ Serial 4621  
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Author Toscano, P.; Genesio, L.; Crisci, A.; Vaccari, F.P.; Ferrari, E.; La Cava, P.; Porter, J.R.; Gioli, B. url  doi
openurl 
  Title Empirical modelling of regional and national durum wheat quality Type Journal Article
  Year 2015 Publication Agricultural and Forest Meteorology Abbreviated Journal Agricultural and Forest Meteorology  
  Volume 204 Issue Pages 67-78  
  Keywords durum wheat; grain protein content; forecasting tool; modelling; gridded data; red winter-wheat; grain quality; climate-change; mediterranean conditions; interannual variability; protein-composition; co2 concentration; vapor-pressure; carbon-dioxide; crop yield  
  Abstract (down) The production of durum wheat in the Mediterranean basin is expected to experience increased variability in yield and quality as a consequence of climate change. To assess how environmental variables and agronomic practices affect grain protein content (GPC), a novel approach based on monthly gridded input data has been implemented to develop empirical model, and validated on historical time series to assess its capability to reproduce observed spatial and inter-annual GPC variability. The model was applied in four Italian regions and at the whole national scale and proved reliable and usable for operational purposes also in a forecast ‘real-time’ mode before harvesting. Precipitable water during autumn to winter and air temperature from anthesis to harvest were extremely important influences on GPC; these and additional variables, included in a linear model, were able to account for 95% of the variability in GPC that has occurred in the last 15 years in Italy. Our results are a unique example of the use of modelling as a predictive real-time platform and are a useful tool to understand better and forecast the impacts of future climate change projections on durum wheat production and quality.  
  Address 2016-10-31  
  Corporate Author Thesis  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0168-1923 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4818  
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Author Tao, F.; Zhang, S.; Zhang, Z.; Rötter, R.P. url  doi
openurl 
  Title Temporal and spatial changes of maize yield potentials and yield gaps in the past three decades in China Type Journal Article
  Year 2015 Publication Agriculture, Ecosystems and Environment Abbreviated Journal Agric. Ecosyst. Environ.  
  Volume 208 Issue Pages 12-20  
  Keywords agronomic management; climate change; food security; impact; water stress; yield potential; resource use efficiency; northeast china; climate-change; food security; environmental-quality; crop productivity; plain; agriculture; management; intensification  
  Abstract (down) The precise spatially explicit knowledge about crop yield potentials and yield gaps is essential to guide sustainable intensification of agriculture. In this study, the maize yield potentials from 1980 to 2008 across the major maize production regions of China were firstly estimated by county using ensemble simulation of a well-validated large scale crop model, i.e., MCWLA-Maize model. Then, the temporal and spatial patterns of maize yield potentials and yield gaps during 1980-2008 were presented and analyzed. The results showed that maize yields became stagnated at 32.4% of maize-growing areas during the period. In the major maize production regions, i.e., northeastern China, the North China Plain (NCP) and southwestern China, yield gap percentages were generally less than 40% and particularly less than 20% in some areas. By contrast, in northern and southern China, where actual yields were relatively lower, yield gap percentages were generally larger than 40%. The areas with yield gap percentages less than 20% and less than 40% accounted for 8.2% and 27.6% of maize-growing areas, respectively. During the period, yield potentials decreased in the NCP and southwestern China due to increase in temperature and decrease in solar radiation; by contrast, increased in northern, northeastern and southeastern China due to increases in both temperature and solar radiation. Yield gap percentages decreased generally by 2% per year across the major maize production regions, although increased in some areas in northern and northeastern China. The shrinking of yield gap was due to increases in actual yields and decreases in yield potentials in the NCP and southwestern China; and due to larger increases in actual yields than in yield potentials in northeastern and southeastern China. The results highlight the importance of sustainable intensification of agriculture to close yield gaps, as well as breeding new cultivars to increase yield potentials, to meet the increasing food demand. (C) 2015 Elsevier B.V. All rights reserved.  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0167-8809 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4715  
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Author Olesen, J.E.; Børgesen, C.D.; Elsgaard, L.; Palosuo, T.; Rötter, R.P.; Skjelvåg, A.O.; Peltonen-Sainio, P.; Börjesson, T.; Trnka, M.; Ewert, F.; Siebert, S.; Brisson, N.; Eitzinger, J.; van Asselt, E.D.; Oberforster, M.; van der Fels-Klerx, H.J. doi  openurl
  Title Changes in time of sowing, flowering and maturity of cereals in Europe under climate change Type Journal Article
  Year 2012 Publication Food Additives & Contaminants: Part A Abbreviated Journal Food Addit. Contam. Part A  
  Volume 29 Issue 10 Pages 1527-1542  
  Keywords Agriculture/*methods/trends; Avena/growth & development; *Climate Change; Crops, Agricultural/*growth & development; Edible Grain/*growth & development; Europe; Flowering Tops/growth & development; Forecasting/methods; Germination; Humans; Models, Biological; Models, Statistical; Seasons; Seeds/growth & development; Spatio-Temporal Analysis; Triticum/growth & development; Zea mays/growth & development  
  Abstract (down) The phenological development of cereal crops from emergence through flowering to maturity is largely controlled by temperature, but also affected by day length and potential physiological stresses. Responses may vary between species and varieties. Climate change will affect the timing of cereal crop development, but exact changes will also depend on changes in varieties as affected by plant breeding and variety choices. This study aimed to assess changes in timing of major phenological stages of cereal crops in Northern and Central Europe under climate change. Records on dates of sowing, flowering, and maturity of wheat, oats and maize were collected from field experiments conducted during the period 1985-2009. Data for spring wheat and spring oats covered latitudes from 46 to 64°N, winter wheat from 46 to 61°N, and maize from 47 to 58°N. The number of observations (site-year-variety combinations) varied with phenological phase, but exceeded 2190, 227, 2076 and 1506 for winter wheat, spring wheat, spring oats and maize, respectively. The data were used to fit simple crop development models, assuming that the duration of the period until flowering depends on temperature and day length for wheat and oats, and on temperature for maize, and that the duration of the period from flowering to maturity in all species depends on temperature only. Species-specific base temperatures were used. Sowing date of spring cereals was estimated using a threshold temperature for the mean air temperature during 10 days prior to sowing. The mean estimated temperature thresholds for sowing were 6.1, 7.1 and 10.1°C for oats, wheat and maize, respectively. For spring oats and wheat the temperature threshold increased with latitude. The effective temperature sums required for both flowering and maturity increased with increasing mean annual temperature of the location, indicating that varieties are well adapted to given conditions. The responses of wheat and oats were largest for the period from flowering to maturity. Changes in timing of cereal phenology by 2040 were assessed for two climate model projections according to the observed dependencies on temperature and day length. The results showed advancements of sowing date of spring cereals by 1-3 weeks depending on climate model and region within Europe. The changes were largest in Northern Europe. Timing of flowering and maturity were projected to advance by 1-3 weeks. The changes were largest for grain maize and smallest for winter wheat, and they were generally largest in the western and northern part of the domain. There were considerable differences in predicted timing of sowing, flowering and maturity between the two climate model projections applied.  
  Address  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1944-0049 1944-0057 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM Approved no  
  Call Number MA @ admin @ Serial 4590  
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