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Kersebaum, K.C.; Boote, K.J.; Jorgenson, J.S.; Nendel, C.; Bindi, M.; Frühauf, C.; Gaiser, T.; Hoogenboom, G.; Kollas, C.; Olesen, J.E.; Rötter, R.P.; Ruget, F.; Thorburn, P.J.; Trnka, M.; Wegehenkel, M. |
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Title |
Analysis and classification of data sets for calibration and validation of agro-ecosystem models |
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Journal Article |
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Year |
2015 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
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Volume |
72 |
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Pages |
402-417 |
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Keywords |
field experiments; data quality; crop modelling; data requirement; minimum data; software; different climatic zones; soil-moisture sensors; spatial variability; nitrogen dynamics; crop models; systems simulation; wheat yields; elevated co2; growth; field |
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Abstract |
Experimental field data are used at different levels of complexity to calibrate, validate and improve agroecosystem models to enhance their reliability for regional impact assessment. A methodological framework and software are presented to evaluate and classify data sets into four classes regarding their suitability for different modelling purposes. Weighting of inputs and variables for testing was set from the aspect of crop modelling. The software allows users to adjust weights according to their specific requirements. Background information is given for the variables with respect to their relevance for modelling and possible uncertainties. Examples are given for data sets of the different classes. The framework helps to assemble high quality data bases, to select data from data bases according to modellers requirements and gives guidelines to experimentalists for experimental design and decide on the most effective measurements to improve the usefulness of their data for modelling, statistical analysis and data assimilation. (C) 2015 Elsevier Ltd. All rights reserved. |
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1364-8152 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
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4563 |
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Author |
Heinemann, A.B.; Barrios-Perez, C.; Ramirez-Villegas, J.; Arango-Londoño, D.; Bonilla-Findji, O.; Medeiros, J.C.; Jarvis, A. |
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Title |
Variation and impact of drought-stress patterns across upland rice target population of environments in Brazil |
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Journal Article |
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Year |
2015 |
Publication |
Journal of Experimental Botany |
Abbreviated Journal |
J. Experim. Bot. |
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Volume |
66 |
Issue |
12 |
Pages |
3625-3638 |
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Keywords |
Brazil; Climate; Computer Simulation; Crops, Agricultural/physiology; *Droughts; *Environment; Geography; Oryza/*physiology; Plant Transpiration; *Stress, Physiological; Water; Breeding; Oryza sativa; environment classification; modelling; water deficit. |
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The upland rice (UR) cropped area in Brazil has decreased in the last decade. Importantly, a portion of this decrease can be attributed to the current UR breeding programme strategy, according to which direct grain yield selection is targeted primarily to the most favourable areas. New strategies for more-efficient crop breeding under non-optimal conditions are needed for Brazil’s UR regions. Such strategies should include a classification of spatio-temporal yield variations in environmental groups, as well as a determination of prevalent drought types and their characteristics (duration, intensity, phenological timing, and physiological effects) within those environmental groups. This study used a process-based crop model to support the Brazilian UR breeding programme in their efforts to adopt a new strategy that accounts for the varying range of environments where UR is currently cultivated. Crop simulations based on a commonly grown cultivar (BRS Primavera) and statistical analyses of simulated yield suggested that the target population of environments can be divided into three groups of environments: a highly favorable environment (HFE, 19% of area), a favorable environment (FE, 44%), and least favourable environment (LFE, 37%). Stress-free conditions dominated the HFE group (69% likelihood) and reproductive stress dominated the LFE group (68% likelihood), whereas reproductive and terminal drought stress were found to be almost equally likely to occur in the FE group. For the best and worst environments, we propose specific adaptation focused on the representative stress, while for the FE, wide adaptation to drought is suggested. ‘Weighted selection’ is also a possible strategy for the FE and LFE environment groups. |
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0022-0957 1460-2431 |
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CropM |
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MA @ admin @ |
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4560 |
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Author |
Semenov, M.A.; Stratonovitch, P.; Alghabari, F.; Gooding, M.J. |
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Title |
Adapting wheat in Europe for climate change |
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Journal Article |
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Year |
2014 |
Publication |
Journal of Cereal Science |
Abbreviated Journal |
J. Ceareal Sci. |
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59 |
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3 |
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245-256 |
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A, maximum area of flag leaf area; ABA, abscisic acid; CV, coefficient of variation; Crop improvement; Crop modelling; FC, field capacity; GMT, Greenwich mean time; GS, growth stage; Gf, grain filling duration; HI, harvest index; HSP, heat shock protein; Heat and drought tolerance; Impact assessment; LAI, leaf area index; Ph, phylochron; Pp, photoperiod response; Ru, root water uptake; S, duration of leaf senescence; SF, drought stress factor; Sirius; Wheat ideotype |
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Increasing cereal yield is needed to meet the projected increased demand for world food supply of about 70% by 2050. Sirius, a process-based model for wheat, was used to estimate yield potential for wheat ideotypes optimized for future climatic projections for ten wheat growing areas of Europe. It was predicted that the detrimental effect of drought stress on yield would be decreased due to enhanced tailoring of phenology to future weather patterns, and due to genetic improvements in the response of photosynthesis and green leaf duration to water shortage. Yield advances could be made through extending maturation and thereby improve resource capture and partitioning. However the model predicted an increase in frequency of heat stress at meiosis and anthesis. Controlled environment experiments quantify the effects of heat and drought at booting and flowering on grain numbers and potential grain size. A current adaptation of wheat to areas of Europe with hotter and drier summers is a quicker maturation which helps to escape from excessive stress, but results in lower yields. To increase yield potential and to respond to climate change, increased tolerance to heat and drought stress should remain priorities for the genetic improvement of wheat. |
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0733-5210 |
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Review |
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CropM, ft_macsur |
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MA @ admin @ |
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4543 |
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Ventrella, D.; Charfeddine, M.; Moriondo, M.; Rinaldi, M.; Bindi, M. |
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Agronomic adaptation strategies under climate change for winter durum wheat and tomato in southern Italy: irrigation and nitrogen fertilization |
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Journal Article |
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Year |
2012 |
Publication |
Regional Environmental Change |
Abbreviated Journal |
Reg Environ Change |
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12 |
Issue |
3 |
Pages |
407-419 |
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Modelling; Climate change; Agronomic adaptation strategies; Yield; Tomato; Winter durum wheat; air co2 enrichment; change scenarios; cropping systems; change impacts; simulation; agriculture; variability; increase; model; responses; Environmental Sciences & Ecology |
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Agricultural crops are affected by climate change due to the relationship between crop development, growth, yield, CO2 atmospheric concentration and climate conditions. In particular, the further reduction in existing limited water resources combined with an increase in temperature may result in higher impacts on agricultural crops in the Mediterranean area than in other regions. In this study, the cropping system models CERES-Wheat and CROPGRO-Tomato of the Decision Support System for Agrotechnology Transfer (DSSAT) were used to analyse the response of winter durum wheat (Triticum aestivum L.) and tomato (Lycopersicon esculentum Mill.) crops to climate change, irrigation and nitrogen fertilizer managements in one of most productive areas of Italy (i.e. Capitanata, Puglia). For this analysis, three climatic datasets were used: (1) a single dataset (50 km x 50 km) provided by the JRC European centre for the period 1975-2005; two datasets from HadCM3 for the IPCC A2 GHG scenario for time slices with +2A degrees C (centred over 2030-2060) and +5A degrees C (centred over 2070-2099), respectively. All three datasets were used to generate synthetic climate series using a weather simulator (model LARS-WG). Adaptation strategies, such as irrigation and N fertilizer managements, have been investigated to either avoid or at least reduce the negative impacts induced by climate change impacts for both crops. Warmer temperatures were primarily shown to accelerate wheat and tomato phenology, thereby resulting in decreased total dry matter accumulation for both tomato and wheat under the +5A degrees C future climate scenario. Under the +2A degrees C scenario, dry matter accumulation and resulting yield were also reduced for tomato, whereas no negative yield effects were observed for winter durum wheat. In general, limiting the global mean temperature change of 2A degrees C, the application of adaptation strategies (irrigation and nitrogen fertilization) showed a positive effect in minimizing the negative impacts of climate change on productivity of tomato cultivated in southern Italy. |
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1436-3798 1436-378x |
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CropM |
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MA @ admin @ |
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4480 |
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Author |
Nendel, C.; Wieland, R.; Mirschel, W.; Specka, X.; Guddat, C.; Kersebaum, K.C. |
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Simulating regional winter wheat yields using input data of different spatial resolution |
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Journal Article |
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2013 |
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Field Crops Research |
Abbreviated Journal |
Field Crops Research |
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145 |
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67-77 |
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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 |
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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. |
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0378-4290 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4498 |
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