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Author |
Dumont, B.; Basso, B.; Leemans, V.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
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Title |
Systematic analysis of site-specific yield distributions resulting from nitrogen management and climatic variability interactions |
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Journal Article |
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Year |
2015 |
Publication |
Precision Agriculture |
Abbreviated Journal |
Precision Agric. |
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Volume |
16 |
Issue |
4 |
Pages |
361-384 |
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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 |
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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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1385-2256 |
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CropM, ft_macsur |
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MA @ admin @ |
Serial |
4519 |
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Author |
Kraus, D.; Weller, S.; Klatt, S.; Haas, E.; Wassmann, R.; Kiese, R.; Butterbach-Bahl, K. |
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Title |
A new LandscapeDNDC biogeochemical module to predict CH4 and N2O emissions from lowland rice and upland cropping systems |
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Journal Article |
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Year |
2015 |
Publication |
Plant and Soil |
Abbreviated Journal |
Plant Soil |
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Volume |
386 |
Issue |
1-2 |
Pages |
125-149 |
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Keywords |
methane; nitrous oxide; paddy rice; maize; model; nitrous-oxide emissions; process-based model; methane transport capacity; process-oriented model; pnet-n-dndc; forest soils; paddy soils; sensitivity-analysis; residue management; organic-matter |
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Abstract |
Replacing paddy rice by upland systems such as maize cultivation is an on-going trend in SE Asia caused by increasing water scarcity and higher demand for meat. How such land management changes will feedback on soil C and N cycles and soil greenhouse gas emissions is not well understood at present. A new LandscapeDNDC biogeochemical module was developed that allows the effect of land management changes on soil C and N cycle to be simulated. The new module is applied in combination with further modules simulating microclimate and crop growth and evaluated against observations from field experiments. The model simulations agree well with observed dynamics of CH (4) emissions in paddy rice depending on changes in climatic conditions and agricultural management. Magnitude and peak emission periods of N (2) O from maize cultivation are simulated correctly, though there are still deficits in reproducing day-to-day dynamics. These shortcomings are most likely related to simulated soil hydrology and may only be resolved if LandscapeDNDC is coupled to more complex hydrological models. LandscapeDNDC allows for simulation of changing land management practices in SE Asia. The possibility to couple LandscapeDNDC to more complex hydrological models is a feature needed to better understand related effects on soil-atmosphere-hydrosphere interactions. |
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0032-079x |
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CropM, ft_macsur |
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MA @ admin @ |
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4530 |
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Watson, J.; Challinor, A.J.; Fricker, T.E.; Ferro, C.A.T. |
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Title |
Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model |
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Journal Article |
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Year |
2015 |
Publication |
Climatic Change |
Abbreviated Journal |
Clim. Change |
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132 |
Issue |
1 |
Pages |
93-109 |
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Keywords |
maize; yield; ensemble; impacts; design; heat |
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Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve. |
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0165-0009 1573-1480 |
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CropM, ft_macsur |
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MA @ admin @ |
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4546 |
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Author |
Perego, A.; Sanna, M.; Giussani, A.; Chiodini, M.E.; Fumagalli, M.; Pilu, S.R.; Bindi, M.; Moriondo, M.; Acutis, M. |
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Title |
Designing a high-yielding maize ideotype for a changing climate in Lombardy plain (northern Italy) |
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Journal Article |
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Year |
2014 |
Publication |
Science of The Total Environment |
Abbreviated Journal |
Science of The Total Environment |
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499 |
Issue |
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Pages |
497-509 |
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Keywords |
Agriculture/*methods/standards; *Climate Change; Droughts; Italy; Nitrogen/analysis; Soil; Water Supply/statistics & numerical data; Zea mays/*growth & development/standards; Climate change; Crop model; Maize; Water use adaptation |
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The expected climate change will affect the maize yields in view of air temperature increase and scarce water availability. The application of biophysical models offers the chance to design a drought-resistant ideotype and to assist plant breeders and agronomists in the assessment of its suitability in future scenarios. The aim of the present work was to perform a model-based estimation of the yields of two hybrids, current vs ideotype, under future climate scenarios (2030-2060 and 2070-2100) in Lombardy (northern Italy), testing two options of irrigation (small amount at fixed dates vs optimal water supply), nitrogen (N) fertilization (300 vs 400 kg N ha(-1)), and crop cycle durations (current vs extended). For the designing of the ideotype we set several parameters of the ARMOSA process-based crop model: the root elongation rate and maximum depth, stomatal resistance, four stage-specific crop coefficients for the actual transpiration estimation, and drought tolerance factor. The work findings indicated that the current hybrid ensures good production only with high irrigation amount (245-565 mm y(-1)). With respect to the current hybrid, the ideotype will require less irrigation water (-13%, p<0.01) and it resulted in significantly higher yield under water stress condition (+15%, p<0.01) and optimal water supply (+2%, p<0.05). The elongated cycle has a positive effect on yield under any combination of options. Moreover, higher yields projected for the ideotype implicate more crop residues to be incorporated into the soil, which are positively correlated with the SOC sequestration and negatively with N leaching. The crop N uptake is expected to be adequate in view of higher rate of soil mineralization; the N fertilization rate of 400 kg N ha(-1) will involve significant increasing of grain yield, and it is expected to involve a higher rate of SOC sequestration. |
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2016-10-31 |
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0048-9697 |
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CropM |
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MA @ admin @ |
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4798 |
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Author |
Tao, F.; Zhang, Z.; Zhang, S.; Rötter, R.P.; Shi, W.; Xiao, D.; Liu, Y.; Wang, M.; Liu, F.; Zhang, H. |
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Historical data provide new insights into response and adaptation of maize production systems to climate change/variability in China |
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Journal Article |
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2016 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
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185 |
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1-11 |
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Keywords |
china; climate variability; grain yield; impact; maize; northeast china; tropical maize; wheat yields; heat-stress; crop yields; temperature; impacts; sensitivities; hybrids; trends |
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Extensive studies had been conducted to investigate the impacts of climate change on maize growth and yield in recent decades; however, the dynamics of crop husbandry in response and adaptation to climate change were not taken into account. Based on field observations spanning from 1981 to 2009 at 167 agricultural meteorological stations across China, we found that solar radiation and temperature over the observed maize growth period had decreasing trends during 1981-2009, and maize yields were positively correlated with these climate variables in major production regions. The decreasing trends in solar radiation and temperature during maize growth period were mainly ascribed to the adoption of late maturity cultivars with longer reproductive growth period (RGP). The adoption of late maturing cultivars with longer RGP contributed substantially to grain yield increase during the last three decades. The climate trends during maize growth period varied among different production areas. During 1981-2009, decreases in mean temperature, precipitation and solar radiation over maize growth period jointly reduced yield most by 13.2-17.3% in southwestern China, by contrast in northwestern China increases in mean temperature, precipitation and solar radiation jointly increased yield most by 12.9-14.4%. Our findings highlight that the adaptations of maize production system to climate change through shifts of sowing date and genotypes are underway and should be taken into accounted when evaluating climate change impacts. (C) 2015 Elsevier B.V. All rights reserved. |
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2016-10-31 |
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0378-4290 |
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CropM, ft_macsur |
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MA @ admin @ |
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4816 |
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