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Dumont, B.; Basso, B.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
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Title  |
Climatic risk assessment to improve nitrogen fertilisation recommendations: A strategic crop model-based approach |
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Journal Article |
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Year |
2015 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
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Volume |
65 |
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10-17 |
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Keywords |
climatic variability; stochastically generated weather; lars-wg; crop model; stics; nitrogen management; yield skewness; wheat yield; generic model; stics; management; variability; simulation; field; balances; impact |
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Abstract |
Within the context of nitrogen (N) management, since 1950, with the rapid intensification of agriculture, farmers have often applied much larger fertiliser quantities than what was required to reach the yield potential. However, to prevent pollution of surface and groundwater induced by nitrates, The European Community launched The European Nitrates Directive 91/6/76/EEC. In 2002, in Wallonia (Belgium), the Nitrates Directive has been transposed under the Sustainable Nitrogen Management in Agriculture Program (PGDA), with the aim of maintaining productivity and revenue for the country’s farmers, while reducing the environmental impact of excessive N application. A feasible approach for addressing climatic uncertainty lies in the use of crop models such as the one commonly known as STICS (simulateur multidisciplinaire pour les cultures standard). These models allow the impact on crops of the interaction between cropping systems and climatic records to be assessed. Comprehensive historical climatic records are rare, however, and therefore the yield distribution values obtained using such an approach can be discontinuous. In order to obtain better and more detailed yield distribution information, the use of a high number of stochastically generated climate time series was proposed, relying on the LARS-Weather Generator. The study focused on the interactions between varying N practices and climatic conditions. Historically and currently, Belgian farmers apply 180 kg N ha(-1), split into three equal fractions applied at the tillering, stem elongation and flag-leaf stages. This study analysed the effectiveness of this treatment in detail, comparing it to similar practices where only the N rates applied at the flag-leaf stage were modified. Three types of farmer decision-making were analysed. The first related to the choice of N strategy for maximising yield, the second to obtaining the highest net revenue, and the third to reduce the environmental impact of potential N leaching, which carries the likelihood of taxation if inappropriate N rates are applied. The results showed reduced discontinuity in the yield distribution values thus obtained. In general, the modulation of N levels to accord with current farmer practices showed considerable asymmetry. In other words, these practices maximised the probability of achieving yields that were at least superior to the mean of the distribution values, thus reducing risk for the farmers. The practice based on applying the highest amounts (60-60-100 kg N ha(-1)) produced the best yield distribution results. When simple economical criteria were computed, the 60-60-80 kg N ha(-1) protocol was found to be optimal for 80-90% of the time. There were no statistical differences, however, between this practice and Belgian farmers’ current practice. When the taxation linked to a high level of potentially leachable N remaining in the soil after harvest was considered, this methodology clearly showed that, in 3 years out of 4,30 kg N ha(-1) could systematically be saved in comparison with the usual practice. |
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1161-0301 |
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CropM, ft_macsur |
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MA @ admin @ |
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4646 |
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Sharif, B.; Makowski, D.; Plauborg, F.; Olesen, J.E. |
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Title |
Comparison of regression techniques to predict response of oilseed rape yield to variation in climatic conditions in Denmark |
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Journal Article |
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Year |
2017 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
Europ. J. Agron. |
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82 |
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11-20 |
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Winter oilseed rape; Statistical models; Yield; Climate; Regression |
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Highlights • Regularization techniques for regression outperformed the classical regression techniques in predicting crop yields. • Different regression techniques with similar prediction accuracy showed different responses of major climatic variables to crop yield. • The regression models showed some responses of crop yield to climatic conditions that is mostly absent in process based crop models. Abstract Statistical regression models represent alternatives to process-based dynamic models for predicting the response of crop yields to variation in climatic conditions. Regression models can be used to quantify the effect of change in temperature and precipitation on yields. However, it is difficult to identify the most relevant input variables that should be included in regression models due to the high number of candidate variables and to their correlations. This paper compares several regression techniques for modeling response of winter oilseed rape yield to a high number of correlated input variables. Several statistical regression methods were fitted to a dataset including 689 observations of winter oilseed rape yield from replicated field experiments conducted in 239 sites in Denmark, covering nearly all regions of the country from 1992 to 2013. Regression methods were compared by cross-validation. The regression methods leading to the most accurate yield predictions were Lasso and Elastic Net, and the least accurate methods were ordinary least squares and stepwise regression. Partial least squares and ridge regression methods gave intermediate results. The estimated relative yield change for a +1°C temperature increase during flowering was estimated to range between 0 and +6 %, depending on choice of regression method. Precipitation was found to have an adverse effect on yield during autumn and winter. It was estimated that an increase in precipitation of +1 mm/day would result in a relative yield change ranging from 0 to −4 %. Soil type was also important for crop yields with lower yields on sandy soils compared to loamy soils. Later sowing was found to result in increased crop yield. The estimated effect of climate on yield was highly sensitive to the chosen regression method. Regression models showing similar performance led in some cases to different conclusions with respect to effect of temperature and precipitation. Hence, it is recommended to apply an ensemble of regression models, in order to account for the sensitivity of the data driven models for projecting crop yield under climate change. |
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1161-0301 |
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CropM, ft_macsur |
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MA @ admin @ |
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4966 |
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Kollas, C.; Kersebaum, K.C.; Nendel, C.; Manevski, K.; Müller, C.; Palosuo, T.; Armas-Herrera, C.M.; Beaudoin, N.; Bindi, M.; Charfeddine, M.; Conradt, T.; Constantin, J.; Eitzinger, J.; Ewert, F.; Ferrise, R.; Gaiser, T.; Cortazar-Atauri, I.G. de; Giglio, L.; Hlavinka, P.; Hoffmann, H.; Hoffmann, M.P.; Launay, M.; Manderscheid, R.; Mary, B.; Mirschel, W.; Moriondo, M.; Olesen, J.E.; Öztürk, I.; Pacholski, A.; Ripoche-Wachter, D.; Roggero, P.P.; Roncossek, S.; Rötter, R.P.; Ruget, F.; Sharif, B.; Trnka, M.; Ventrella, D.; Waha, K.; Wegehenkel, M.; Weigel, H.-J.; Wu, L. |
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Title |
Crop rotation modelling—A European model intercomparison |
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Journal Article |
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Year |
2015 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
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70 |
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98-111 |
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Model ensemble; Crop simulation models; Catch crop; Intermediate crop; Treatment; Multi-year; long-term experiment; climate-change; wheat production; n-fertilization; systems simulation; nitrogen dynamics; tillage intensity; winter-wheat; soil carbon; growth |
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• First model inter-comparison on crop rotations. • Continuous simulation of multi-year crop rotations yields outperformed single-year simulation. • Low accuracy of yield predictions in less commonly modelled crops such as potato, radish, grass vegetation. • Multi-model mean prediction was found to minimise the likely error arising from single-model predictions. • The representation of intermediate crops and carry-over effects in the models require further research efforts.
Diversification of crop rotations is considered an option to increase the resilience of European crop production under climate change. So far, however, many crop simulation studies have focused on predicting single crops in separate one-year simulations. Here, we compared the capability of fifteen crop growth simulation models to predict yields in crop rotations at five sites across Europe under minimal calibration. Crop rotations encompassed 301 seasons of ten crop types common to European agriculture and a diverse set of treatments (irrigation, fertilisation, CO2 concentration, soil types, tillage, residues, intermediate or catch crops). We found that the continuous simulation of multi-year crop rotations yielded results of slightly higher quality compared to the simulation of single years and single crops. Intermediate crops (oilseed radish and grass vegetation) were simulated less accurately than main crops (cereals). The majority of models performed better for the treatments of increased CO2 and nitrogen fertilisation than for irrigation and soil-related treatments. The yield simulation of the multi-model ensemble reduced the error compared to single-model simulations. The low degree of superiority of continuous simulations over single year simulation was caused by (a) insufficiently parameterised crops, which affect the performance of the following crop, and (b) the lack of growth-limiting water and/or nitrogen in the crop rotations under investigation. In order to achieve a sound representation of crop rotations, further research is required to synthesise existing knowledge of the physiology of intermediate crops and of carry-over effects from the preceding to the following crop, and to implement/improve the modelling of processes that condition these effects. |
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1161-0301 |
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CropM, ft_macsur |
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MA @ admin @ |
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4660 |
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Cirillo, V.; Masin, R.; Maggio, A.; Zanin, G. |
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Title |
Crop-weed interactions in saline environments |
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Journal Article |
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2018 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
Europ. J. Agron. |
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99 |
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51-61 |
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Salinity; Weeds; Abiotic stress; Crop management; Salt stress; Echinochloa-Crus-Galli; Portulaca Oleracea L.; Seed-Germination; Soil-Salinity; Salt Tolerance; Stress Tolerance; Chenopodium-Album; Chemical-Composition; Southern Australia; Microbial Biomass |
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Soil salinization is one of the most critical environmental factors affecting crop yield. It is estimated that 20% of cultivated land and 33% of irrigated agricultural land are affected by salinity. In the last decades, considerable effort to manage saline agro-ecosystems has focused on 1) controlling soil salinity to minimize/reduce the accumulation of salts in the root zone and 2) improving plants ability to cope with osmotic and ionic stress. Less attention has been given to other components of the agro-ecosystem including weed populations, which also react and adapt to soil salinization and indirectly affect plant growth and yield. Weeds represent an increasing challenge for crop systems since they have high genetic resilience and adaptation ability to adverse environmental conditions such as soil salinization. In this review, we assess current knowledge on salinity tolerance of weeds in agricultural contexts and discuss critical components of crop-weed interactions that may increase weeds competitiveness under salinity. Compared to crop species, weeds generally exhibit greater salt tolerance due to high intraspecific variability, associated with diverse physiological adaptation mechanisms (e.g. phenotipic plasticity, seed heteromorphism, allelopathy). Weed competitiveness in saline soils may be enhanced by their earlier emergence, faster growth rates and synergies occurring between soil salts and allelochemicals released by weeds. In the future, a better understanding of crop-weed relationships and molecular, physiological and agronomic stress responses under salinity is essential to design efficient strategies to achieve weed control under altered climatic and environmental conditions. |
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2018-09-20 |
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CropM, ft_macsur |
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MA @ admin @ |
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5209 |
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Himanen, S.J.; Ketoja, E.; Hakala, K.; Rötter, R.P.; Salo, T.; Kahiluoto, H. |
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Title |
Cultivar diversity has great potential to increase yield for feed barley |
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Journal Article |
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Year |
2013 |
Publication |
Agronomy for Sustainable Development |
Abbreviated Journal |
Agron. Sust. Developm. |
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33 |
Issue |
3 |
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519-530 |
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Crop cultivar; Diversity; Environmental responses; Regional yields; Yield security |
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This study shows an average yield increase of 415–1,338 kg ha−1 per unit increase of the Shannon diversity index for feed barley cultivar use. There is a global quest to increase food production sustainably. Therefore, judicious farmer choices such as selection of crop cultivars are increasingly important. Cultivar diversity is limited and, as a consequence, corresponding crop yields are highly impacted by local weather variations and global climate change. Actually, there is little knowledge on the relationships between yields of regional crops and cultivar diversity, that is evenness and richness in cultivar use. Here, we hypothesized that higher cultivar diversity is related to higher regional yield. We also assumed that the diversity-yield relationship depends on weather during the growing season. Our data were based on farm yield surveys of feed and malting barley, Hordeum vulgare L.; spring wheat, Triticum aestivum L.; and spring turnip rape, Brassica rapa L. ssp. oleifera, from 1998 to 2009, representing about 4,500–5,500 farms annually. We modeled the relationships between regional yields and Shannon diversity indices in high-yielding (south-west) and low-yielding (central-east) regions of Finland using linear mixed models. Our results show that an increase of Shannon diversity index increases yield of feed barley. Feed barley had also the greatest cultivar diversity. In contrast, an average yield decrease of 1,052 kg ha−1 per unit increase in Shannon index was found for spring rape in 2006 and 2008. Our findings show that cultivar diversification has potential to raise mean regional yield of feed barley. Increasing cultivar diversity thus offers a novel, sustainability-favoring means to promote higher yields. |
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1774-0746 1773-0155 |
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MA @ admin @ |
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4603 |
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