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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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Volume |
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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Abstract |
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 @ |
Serial |
4798 |
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Author |
Bindi, M.; Palosuo, T.; Trnka, M.; Semenov, M.A. |
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Title |
Modelling climate change impacts on crop production for food security INTRODUCTION |
Type |
Journal Article |
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Year |
2015 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
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Volume |
65 |
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Pages |
3-5 |
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Keywords |
Crop production; Climate change impact and adaptation assessments; Upscaling; Model ensembles |
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Abstract |
Process-based crop models that synthesise the latest scientific understanding of biophysical processes are currently the primary scientific tools available to assess potential impacts of climate change on crop production. Important obstacles are still present, however, and must be overcome for improving crop modelling application in integrated assessments of risk, of sustainability and of crop-production resilience in the face of climate change (e.g. uncertainty analysis, model integration, etc.). The research networks MACSUR and AGMIP organised the CropM International Symposium and Workshop in Oslo, on 10-12 February 2014, and present this CR Special, discussing the state-of-the-art-as well as future perspectives-of crop modelling applications in climate change risk assessment, including the challenges of integrated assessments for the agricultural sector. |
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2016-10-31 |
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0936-577x |
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Editorial Material |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4785 |
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Author |
Dietrich, J.P.; Schmitz, C.; Lotze-Campen, H.; Popp, A.; Muller, C. |
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Title |
Forecasting technological change in agriculture-An endogenous implementation in a global, and use model |
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Journal Article |
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Year |
2014 |
Publication |
Technological Forecasting and Social Change |
Abbreviated Journal |
Technological Forecasting and Social Change |
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Volume |
81 |
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236-249 |
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Keywords |
Technological change; Land use; Agricultural productivity; Land use; intensity; Research and development; land-use; research expenditures; productivity growth; impact; deforestation; forest; yield; Business & Economics; Public Administration |
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Abstract |
Technological change in agriculture plays a decisive role for meeting future demands for agricultural goods. However, up to now, agricultural sector models and models on land use change have used technological change as an exogenous input due to various information and data deficiencies. This paper provides a first attempt towards an endogenous implementation based on a measure of agricultural land use intensity. We relate this measure to empirical data on investments in technological change. Our estimated yield elasticity with respect to research investments is 029 and production costs per area increase linearly with an increasing yield level. Implemented in the global land use model MAgPIE (”Model of Agricultural Production and its Impact on the Environment”) this approach provides estimates of future yield growth. Highest future yield increases are required in Sub-Saharan Africa, the Middle East and South Asia. Our validation with FAO data for the period 1995-2005 indicates that the model behavior is in line with observations. By comparing two scenarios on forest conservation we show that protecting sensitive forest areas in the future is possible but requires substantial investments into technological change. (C) 2013 Elsevier Inc. All rights reserved. |
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2016-10-31 |
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ISSN |
0040-1625 |
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CropM |
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Call Number |
MA @ admin @ |
Serial |
4789 |
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Author |
Höglind, M.; Van Oijen, M.; Cameron, D.; Persson, T. |
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Title |
Process-based simulation of growth and overwintering of grassland using the BASGRA model |
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Journal Article |
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Year |
2016 |
Publication |
Ecological Modelling |
Abbreviated Journal |
Ecol. Model. |
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335 |
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Pages |
1-15 |
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Keywords |
Cold hardening; Frost injury; Phleum pratense L.; Process-based; modelling; Winter survival; Yield; low-temperature tolerance; perennial forage crops; dry-matter; production; climate-change; nutritive-value; snow-cover; bayesian; calibration; timothy regrowth; phleum-pratense; lolium-perenne |
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Process-based models (PBM) for simulation of weather dependent grass growth can assist farmers and plant breeders in addressing the challenges of climate change by simulating alternative roads of adaptation. They can also provide management decision support under current conditions. A drawback of existing grass models is that they do not take into account the effect of winter stresses, limiting their use for full-year simulations in areas where winter survival is a key factor for yield security. Here, we present a novel full-year PBM for grassland named BASGRA. It was developed by combining the LINGRA grassland model (Van Oijen et al., 2005a) with models for cold hardening and soil physical winter processes. We present the model and show how it was parameterized for timothy (Phleum pratense L.), the most important forage grass in Scandinavia and parts of North America and Asia. Uniquely, BASGRA simulates the processes taking place in the sward during the transition from summer to winter, including growth cessation and gradual cold hardening, and functions for simulating plant injury due to low temperatures, snow and ice affecting regrowth in spring. For the calibration, we used detailed data from five different locations in Norway, covering a wide range of agroclimatic regions, day lengths (latitudes from 59 degrees to 70 degrees N) and soil conditions. The total dataset included 11 variables, notably above-ground dry matter, leaf area index, tiller density, content of C reserves, and frost tolerance. All data were used in the calibration. When BASGRA was run with the maximum a-posteriori (MAP) parameter vector from the single, Bayesian calibration, nearly all measured variables were simulated to an overall normalized root mean squared error (NRMSE) <0.5. For many site x experiment combinations, NRMSE was <0.3. The temporal dynamics were captured well for most variables, as evaluated by comparing simulated time courses versus data for the individual sites. The results may suggest that BASGRA is a reasonably robust model, allowing for simulation of growth and several important underlying processes with acceptable accuracy for a range of agroclimatic conditions. However, the robustness of the model needs to be tested further using independent data from a wide range of growing conditions. Finally we show an example of application of the model, comparing overwintering risks in two climatically different sites, and discuss future model applications. Further development work should include improved simulation of the dynamics of C reserves, and validation of winter tiller dynamics against independent data. (C) 2016 Elsevier B.V. All rights reserved. |
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2016-07-28 |
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0304-3800 |
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CropM, LiveM, ft_macsur |
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MA @ admin @ |
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4764 |
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Author |
Yin, X.; Olesen, J.E.; Wang, M.; Öztürk, I.; Zhang, H.; Chen, F. |
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Title |
Impacts and adaptation of the cropping systems to climate change in the Northeast Farming Region of China |
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Journal Article |
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Year |
2016 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
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78 |
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60-72 |
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Keywords |
Climate change; Vulnerability; Impact; Adaptation; Cropping systems; The Northeast Farming Region of China; maize production; high-temperature; growth period; yield; rice; drought; management; nitrogen; crops; pests |
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Abstract |
The Northeast Farming Region of China (NFR) is a very important crop growing area, comprising seven sub-regions: Xing’anling (XA), Sanjiang (SJ), Northwest Songliao (NSL), Central Songliao (CSL), Southwest Songliao (SSL), Changbaishan (CB) and Liaodong (LD), which has been severely affected by extreme climate events and climatic change. Therefore, a set of expert survey has been done to identify current and project future climate limitations to crop production and explore appropriate adaptation measures in NFR. Droughts have been the largest limitation for maize (Zea mays L.) in NSL and SSL, and for soybean (Glycine max L Merr.) in SSL. Chilling damage has been the largest limitation for rice (Oryza sativa L) production in XA, SJ and CB. Projected climate change is expected to be beneficial for expanding the crop growing season, and to provide more suitable conditions for sowing and harvest. Autumn frost will occur later in most parts of NFR, and chilling damage will also decrease, particularly for rice production in XA and SJ. Drought and heat stress are expected to become more severe for maize and soybean production in most parts of NFR. Also, plant diseases, pests and weeds are considered to become more severe for crop production under climate change. Adaptation measures that have already been implemented in recent decades to cope with current climatic limitations include changes in timing of cultivation, variety choice, soil tillage practices, crop protection, irrigation and use of plastic film for soil cover. With the projected climate change and increasing risk of climatic extremes, additional adaptation measures will become relevant for sustaining and improving productivity of crops in NFR to ensure food security in China. (C) 2016 Elsevier B.V. All rights reserved. |
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1161-0301 |
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CropM, ft_macsur |
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MA @ admin @ |
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4772 |
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