| Records |
| Author |
Zheng, B.; Chapman, S.C.; Christopher, J.T.; Frederiks, T.M.; Chenu, K. |
| Title |
Frost trends and their estimated impact on yield in the Australian wheatbelt |
Type |
Journal Article |
Year  |
2015 |
Publication |
Journal of Experimental Botany |
Abbreviated Journal |
J. Experim. Bot. |
| Volume |
66 |
Issue |
12 |
Pages |
3611-3623 |
| Keywords |
Adaptation, Physiological/genetics; Australia; Computer Simulation; Ecotype; *Freezing; Genotype; Geography; Seasons; Triticum/genetics/*growth & development/physiology; Breeding; climate change; crop adaptation; crop modelling; ideotype; post-head-emergence frost; reproductive frost; spring radiant frost |
| Abstract |
Radiant spring frosts occurring during reproductive developmental stages can result in catastrophic yield loss for wheat producers. To better understand the spatial and temporal variability of frost, the occurrence and impact of frost events on rain-fed wheat production was estimated across the Australian wheatbelt for 1957-2013 using a 0.05 ° gridded weather data set. Simulated yield outcomes at 60 key locations were compared with those for virtual genotypes with different levels of frost tolerance. Over the last six decades, more frost events, later last frost day, and a significant increase in frost impact on yield were found in certain regions of the Australian wheatbelt, in particular in the South-East and West. Increasing trends in frost-related yield losses were simulated in regions where no significant trend of frost occurrence was observed, due to higher mean temperatures accelerating crop development and causing sensitive post-heading stages to occur earlier, during the frost risk period. Simulations indicated that with frost-tolerant lines the mean national yield could be improved by up to 20% through (i) reduced frost damage (~10% improvement) and (ii) the ability to use earlier sowing dates (adding a further 10% improvement). In the simulations, genotypes with an improved frost tolerance to temperatures 1 °C lower than the current 0 °C reference provided substantial benefit in most cropping regions, while greater tolerance (to 3 °C lower temperatures) brought further benefits in the East. The results indicate that breeding for improved reproductive frost tolerance should remain a priority for the Australian wheat industry, despite warming climates. |
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| ISSN |
0022-0957 |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4580 |
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| Author |
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. |
| Title |
Analysis and classification of data sets for calibration and validation of agro-ecosystem models |
Type |
Journal Article |
| Year |
2015 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
| Volume |
72 |
Issue |
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Pages |
402-417 |
| 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 |
| 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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no |
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MA @ admin @ |
Serial |
4563 |
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Coucheney, E.; Buis, S.; Launay, M.; Constantin, J.; Mary, B.; García de Cortázar-Atauri, I.; Ripoche, D.; Beaudoin, N.; Ruget, F.; &rianarisoa, K.S.; Le Bas, C.; Justes, E.; Léonard, J. |
| Title |
Accuracy, robustness and behavior of the STICS soil–crop model for plant, water and nitrogen outputs: Evaluation over a wide range of agro-environmental conditions in France |
Type |
Journal Article |
| Year |
2015 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
| Volume |
64 |
Issue |
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Pages |
177-190 |
| Keywords |
soil-crop model; stics; model performances; plant biomass; soil nitrogen; soil water; remote-sensing data; goodness-of-fit; hydrological model; simulation-models; solar-radiation; regional-scale; climate-change; generic model; data set; validation |
| Abstract |
Soil-crop models are increasingly used as predictive tools to assess yield and environmental impacts of agriculture in a growing diversity of contexts. They are however seldom evaluated at a given time over a wide domain of use. We tested here the performances of the STICS model (v8.2.2) with its standard set of parameters over a dataset covering 15 crops and a wide range of agropedoclimatic conditions in France. Model results showed a good overall accuracy, with little bias. Relative RMSE was larger for soil nitrate (49%) than for plant biomass (35%) and nitrogen (33%) and smallest for soil water (10%). Trends induced by contrasted environmental conditions and management practices were well reproduced. Finally, limited dependency of model errors on crops or environments indicated a satisfactory robustness. Such performances make STICS a valuable tool for studying the effects of changes in agro-ecosystems over the domain explored. (C) 2014 Elsevier Ltd. All rights reserved. |
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1364-8152 |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4554 |
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| Author |
Ewert, F.; Rötter, R.P.; Bindi, M.; Webber, H.; Trnka, M.; Kersebaum, K.C.; Olesen, J.E.; van Ittersum, M.K.; Janssen, S.; Rivington, M.; Semenov, M.A.; Wallach, D.; Porter, J.R.; Stewart, D.; Verhagen, J.; Gaiser, T.; Palosuo, T.; Tao, F.; Nendel, C.; Roggero, P.P.; Bartošová, L.; Asseng, S. |
| Title |
Crop modelling for integrated assessment of risk to food production from climate change |
Type |
Journal Article |
| Year |
2015 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
| Volume |
72 |
Issue |
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Pages |
287-303 |
| Keywords |
uncertainty; scaling; integrated assessment; risk assessment; adaptation; crop models; agricultural land-use; change adaptation strategies; farming systems simulation; agri-environmental systems; enrichment face experiment; high-temperature stress; change impacts; nitrogen dynamics; atmospheric co2; spring wheat |
| Abstract |
The complexity of risks posed by climate change and possible adaptations for crop production has called for integrated assessment and modelling (IAM) approaches linking biophysical and economic models. This paper attempts to provide an overview of the present state of crop modelling to assess climate change risks to food production and to which extent crop models comply with IAM demands. Considerable progress has been made in modelling effects of climate variables, where crop models best satisfy IAM demands. Demands are partly satisfied for simulating commonly required assessment variables. However, progress on the number of simulated crops, uncertainty propagation related to model parameters and structure, adaptations and scaling are less advanced and lagging behind IAM demands. The limitations are considered substantial and apply to a different extent to all crop models. Overcoming these limitations will require joint efforts, and consideration of novel modelling approaches. |
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1364-8152 |
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Article |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4521 |
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| Author |
Dumont, B.; Basso, B.; Leemans, V.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
| Title |
Systematic analysis of site-specific yield distributions resulting from nitrogen management and climatic variability interactions |
Type |
Journal Article |
| Year |
2015 |
Publication |
Precision Agriculture |
Abbreviated Journal |
Precision Agric. |
| Volume |
16 |
Issue |
4 |
Pages |
361-384 |
| Keywords |
nitrogen management; climatic variability; lars-wg weather generator; stics soil-crop model; pearson system; probability risk assessment; crop model stics; fertilizer nitrogen; generic model; wheat yield; maize; simulation; skewness; field; agriculture; scenarios |
| Abstract |
At the plot level, crop simulation models such as STICS have the potential to evaluate risk associated with management practices. In nitrogen (N) management, however, the decision-making process is complex because the decision has to be taken without any knowledge of future weather conditions. The objective of this paper is to present a general methodology for assessing yield variability linked to climatic uncertainty and variable N rate strategies. The STICS model was coupled with the LARS-Weather Generator. The Pearson system and coefficients were used to characterise the shape of yield distribution. Alternatives to classical statistical tests were proposed for assessing the normality of distributions and conducting comparisons (namely, the Jarque-Bera and Wilcoxon tests, respectively). Finally, the focus was put on the probability risk assessment, which remains a key point within the decision process. The simulation results showed that, based on current N application practice among Belgian farmers (60-60-60 kgN ha(-1)), yield distribution was very highly significantly non-normal, with the highest degree of asymmetry characterised by a skewness value of -1.02. They showed that this strategy gave the greatest probability (60 %) of achieving yields that were superior to the mean (10.5 t ha(-1)) of the distribution. |
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Edition |
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1385-2256 |
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CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4519 |
| Permanent link to this record |
