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Fereres, A. (2012). Insect behaviour and management options under UV-deficient enclosures..
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Elsgaard, L., Børgesen, C. D., Olesen, J. E., Siebert, S., Ewert, F., Peltonen-Sainio, P., et al. (2012). Shifts in comparative advantages for maize, oat and wheat cropping under climate change in Europe. Food Addit. Contam. Part A, 29(10), 1514–1526.
Abstract: Climate change is anticipated to affect European agriculture, including the risk of emerging or re-emerging feed and food hazards. Indirectly, climate change may influence such hazards (e.g. the occurrence of mycotoxins) due to geographic shifts in the distribution of major cereal cropping systems and the consequences this may have for crop rotations. This paper analyses the impact of climate on cropping shares of maize, oat and wheat on a 50-km square grid across Europe (45-65°N) and provides model-based estimates of the changes in cropping shares in response to changes in temperature and precipitation as projected for the time period around 2040 by two regional climate models (RCM) with a moderate and a strong climate change signal, respectively. The projected cropping shares are based on the output from the two RCMs and on algorithms derived for the relation between meteorological data and observed cropping shares of maize, oat and wheat. The observed cropping shares show a south-to-north gradient, where maize had its maximum at 45-55°N, oat had its maximum at 55-65°N, and wheat was more evenly distributed along the latitudes in Europe. Under the projected climate changes, there was a general increase in maize cropping shares, whereas for oat no areas showed distinct increases. For wheat, the projected changes indicated a tendency towards higher cropping shares in the northern parts and lower cropping shares in the southern parts of the study area. The present modelling approach represents a simplification of factors determining the distribution of cereal crops, and also some uncertainties in the data basis were apparent. A promising way of future model improvement could be through a systematic analysis and inclusion of other variables, such as key soil properties and socio-economic conditions, influencing the comparative advantages of specific crops.
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Dumont, B., Vancutsem, F., Seutin, B., Bodson, B., Destain, J. - P., & Destain, M. - F. (2012). Simulation de la croissance du blé à l’aide de modèles écophysiologiques: Synthèse bibliographique des méthodes, potentialités et limitations. Biotechnologie, Agronomie, Société et Environnement, 163, 376–386.
Abstract: Crop models describe the growth and development of a crop interacting with its surrounding agro-environmental conditions (soil, climate and the close conditions of the plant). However, the implementation of such models remains difficult because of the high number of explanatory variables and parameters. It often happens that important discrepancies appear between measured and simulated values. This article aims to highlight the different sources of uncertainty related to the use of crop models, as well as the actual methods that allow a compensation for or, at least, a consideration of these sources of error during analysis of the model results. This article presents a literature review, which firstly synthesises the general mathematical structure of crop models. The main criteria for evaluating crop models are then described. Finally, several methods used for improving models are given. Parameter estimation methods, including frequentist and Bayesian approaches, are presented and data assimilation methods are reviewed.
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Dumont, B., Leemans, V., Ferrandis Vallterra, S., Vancutsem, F., Seutin, B., Bodson, B., et al. (2012). Assessing the potential of an algorithm based on mean climatic data to predict wheat yield..
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Dumont, B., Leemans, V., Ferrandis Vallterra, S., Vancutsem, F., Seutin, B., Bodson, B., et al. (2012). A first step towards a real-time predictive yield support system..
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