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Author |
Comadira, G.; Rasool, B.; Karpinska, B.; Morris, J.; Verrall, S.R.; Hedley, P.E.; Foyer, C.H.; Hancock, R.D. |
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Title |
Nitrogen deficiency in barley (Hordeum vulgare) seedlings induces molecular and metabolic adjustments that trigger aphid resistance |
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Journal Article |
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Year |
2015 |
Publication |
Journal of Experimental Botany |
Abbreviated Journal |
J. Experim. Bot. |
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Volume |
66 |
Issue |
12 |
Pages |
3639-3655 |
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Keywords |
Animals; Aphids/drug effects/*physiology; Biomass; Carbon/pharmacology; Chlorophyll/metabolism; Cluster Analysis; *Disease Resistance/drug effects; Gases/metabolism; Gene Expression Regulation, Plant/drug effects; Hordeum/drug effects/genetics/*parasitology; Nitrogen/*deficiency/metabolism/pharmacology; Oxidation-Reduction/drug effects; Photosynthesis/drug effects; Plant Diseases/genetics/*parasitology; Plant Leaves/drug effects/genetics/metabolism; Plant Proteins/genetics/metabolism; Plant Shoots/drug effects/metabolism; RNA, Messenger/genetics/metabolism; Secondary Metabolism/drug effects; Seedlings/drug effects/*metabolism/*parasitology; Signal Transduction/drug effects; Thylakoids/drug effects/metabolism/parasitology; Transcription Factors/metabolism; Transcriptome/genetics; Cross-tolerance; Myzus persicae; kinase cascades; metabolite profiles; nitrogen limitation; oxidative stress; sugar signalling |
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Abstract |
Agricultural nitrous oxide (N2O) pollution resulting from the use of synthetic fertilizers represents a significant contribution to anthropogenic greenhouse gas emissions, providing a rationale for reduced use of nitrogen (N) fertilizers. Nitrogen limitation results in extensive systems rebalancing that remodels metabolism and defence processes. To analyse the regulation underpinning these responses, barley (Horedeum vulgare) seedlings were grown for 7 d under N-deficient conditions until net photosynthesis was 50% lower than in N-replete controls. Although shoot growth was decreased there was no evidence for the induction of oxidative stress despite lower total concentrations of N-containing antioxidants. Nitrogen-deficient barley leaves were rich in amino acids, sugars and tricarboxylic acid cycle intermediates. In contrast to N-replete leaves one-day-old nymphs of the green peach aphid (Myzus persicae) failed to reach adulthood when transferred to N-deficient barley leaves. Transcripts encoding cell, sugar and nutrient signalling, protein degradation and secondary metabolism were over-represented in N-deficient leaves while those associated with hormone metabolism were similar under both nutrient regimes with the exception of mRNAs encoding proteins involved in auxin metabolism and responses. Significant similarities were observed between the N-limited barley leaf transcriptome and that of aphid-infested Arabidopsis leaves. These findings not only highlight significant similarities between biotic and abiotic stress signalling cascades but also identify potential targets for increasing aphid resistance with implications for the development of sustainable agriculture. |
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2016-10-31 |
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0022-0957 1460-2431 |
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CropM |
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Call Number |
MA @ admin @ |
Serial |
4787 |
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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 |
Type |
Journal Article |
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Year |
2016 |
Publication |
Ecological Modelling |
Abbreviated Journal |
Ecol. Model. |
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Volume |
335 |
Issue |
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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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Abstract |
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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Call Number |
MA @ admin @ |
Serial |
4764 |
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Author |
Savary, S.; Jouanin, C.; Félix, I.; Gourdain, E.; Piraux, F.; Brun, F.; Willocquet, L. |
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Title |
Assessing plant health in a network of experiments on hardy winter wheat varieties in France: patterns of disease-climate associations |
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Journal Article |
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Year |
2016 |
Publication |
European Journal of Plant Pathology |
Abbreviated Journal |
Eur. J. Plant Pathol. |
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Volume |
146 |
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Pages |
741-755 |
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Keywords |
Puccinia triticina; Puccinia striiformis; Fusarium graminearum; Fusarium culmorum; Fusarium avenaceum; Blumeria graminis; Zymoseptoria tritici; Categorical data; Risk factor; Multiple pathosystem; Correspondence analysis; Logistic regression |
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Abstract |
A data set generated by a multi-year (2003–2010) and multi-site network of experiments on winter wheat varieties grown at different levels of crop management is analysed in order to assess the importance of climate on the variability of wheat health. Wheat health is represented by the multiple pathosystem involving five components: leaf rust, yellow rust, fusarium head blight, powdery mildew, and septoria tritici blotch. An overall framework of associations between multiple diseases and climate variables is developed. This framework involves disease levels in a binary form (i.e. epidemic vs. non-epidemic) and synthesis variables accounting for climate over spring and early summer. The multiple disease-climate pattern of associations of this framework conforms to disease-specific knowledge of climate effects on the components of the pathosystem. It also concurs with a (climate-based) risk factor approach to wheat diseases. This report emphasizes the value of large scale data in crop health assessment and the usefulness of a risk factor approach for both tactical and strategic decisions for crop health management. |
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ISSN |
0929-1873 1573-8469 |
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CropM |
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CropMwp;wos; ftnot_macsur; |
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MA @ admin @ |
Serial |
4755 |
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Author |
Zhao, G.; Siebert, S.; Enders, A.; Rezaei, E.E.; Yan, C.; Ewert, F. |
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Title |
Demand for multi-scale weather data for regional crop modeling |
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Journal Article |
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Year |
2015 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
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Volume |
200 |
Issue |
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Pages |
156-171 |
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Keywords |
multi-scale; spatial heterogeneity; spatial resolution; crop model; climate variability; climate-change scenarios; integrated assessment; large-scale; phenological development; agricultural systems; spatial-resolution; data aggregation; european-union; winter-wheat; input data |
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Abstract |
A spatial resolution needs to be determined prior to using models to simulate crop yields at a regional scale, but a dilemma exists in compromising between different demands. A fine spatial resolution demands extensive computation load for input data assembly, model runs, and output analysis. A coarse spatial resolution could result in loss of spatial detail in variability. This paper studied the impact of spatial resolution, data aggregation and spatial heterogeneity of weather data on simulations of crop yields, thus providing guidelines for choosing a proper spatial resolution for simulations of crop yields at regional scale. Using a process-based crop model SIMPLACE (LINTUL2) and daily weather data at 1 km resolution we simulated a continuous rainfed winter wheat cropping system at the national scale of Germany. Then we aggregated the weather data to four resolutions from 10 to 100 km, repeated the simulation, compared them with the 1 km results, and correlated the difference with the intra-pixel heterogeneity quantified by an ensemble of four semivariogram models. Aggregation of weather data had small effects over regions with a flat terrain located in northern Germany, but large effects over southern regions with a complex topography. The spatial distribution of yield bias at different spatial resolutions was consistent with the intra-pixel spatial heterogeneity of the terrain and a log-log linear relationship between them was established. By using this relationship we demonstrated the way to optimize the model resolution to minimize both the number of simulation runs and the expected loss of spatial detail in variability due to aggregation effects. We concluded that a high spatial resolution is desired for regions with high spatial environmental heterogeneity, and vice versa. This calls for the development of multi-scale approaches in regional and global crop modeling. The obtained results require substantiation for other production situations, crops, output variables and for different crop models. (C) 2014 Elsevier B.V. All rights reserved. |
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0168-1923 |
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CropM, ft_macsur |
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MA @ admin @ |
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4753 |
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Author |
Gabaldón-Leal, C.; Lorite, I.J.; Mínguez, M.I.; Lizaso, J.I.; Dosio, A.; Sanchez, E.; Ruiz-Ramos, M. |
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Title |
Strategies for adapting maize to climate change and extreme temperatures in Andalusia, Spain |
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Journal Article |
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Year |
2015 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
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Volume |
65 |
Issue |
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Pages |
159-173 |
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Keywords |
climate change; impact; adaptation; maize; crop model; regional climate model; extreme temperature; elevated carbon-dioxide; iberian peninsula; future climate; mediterranean environment; crop productivity; model simulations; pollen viability; european climate; bias correction; change impacts |
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Abstract |
Climate projections indicate that rising temperatures will affect summer crops in the southern Iberian Peninsula. The aim of this study was to obtain projections of the impacts of rising temperatures, and of higher frequency of extreme events on irrigated maize, and to evaluate some adaptation strategies. The study was conducted at several locations in Andalusia using the CERES-Maize crop model, previously calibrated/validated with local experimental datasets. The simulated climate consisted of projections from regional climate models from the ENSEMBLES project; these were corrected for daily temperature and precipitation with regard to the E-OBS observational dataset. These bias-corrected projections were used with the CERES-Maize model to generate future impacts. Crop model results showed a decrease in maize yield by the end of the 21st century from 6 to 20%, a decrease of up to 25% in irrigation water requirements, and an increase in irrigation water productivity of up to 22%, due to earlier maturity dates and stomatal closure caused by CO2 increase. When adaptation strategies combining earlier sowing dates and cultivar changes were considered, impacts were compensated, and maize yield increased up to 14%, compared with the baseline period (1981-2010), with similar reductions in crop irrigation water requirements. Effects of extreme maximum temperatures rose to 40% at the end of the 21st century, compared with the baseline. Adaptation resulted in an overall reduction in extreme T-max damages in all locations, with the exception of Granada, where losses were limited to 8%. |
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2016-06-01 |
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0936-577x 1616-1572 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
4738 |
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