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Author |
De Pascale, S.; Orsini, F.; Caputo, R.; Palermo, M.A.; Barbieri, G.; Maggio, A. |
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Title |
Seasonal and multiannual effects of salinisation on tomato yield and fruit quality |
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Journal Article |
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Year |
2012 |
Publication |
Functional Plant Biology |
Abbreviated Journal |
Functional Plant Biology |
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Volume |
39 |
Issue |
8 |
Pages |
689-698 |
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Keywords |
fruit ions concentration; fruit lipophilic and hydrophilic antioxidant; capacities; leaf water potentials; leaf stomatal conductance; short- and; long-term salinisation; salinity tolerance; water-stress; antioxidant activity; irrigation; growth; plants; soils; carotenoids; responses; crops |
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Abstract |
The effects of short-and long-term salinisation were studied by comparing tomato growth on a soil exposed to one-season salinisation (short term) vs growth on a soil exposed to >20 years salinisation (long term). Remarkable differences were associated to substantial modifications of the soil physical-chemical characteristics in the root zone, including deteriorated structure, reduced infiltration properties and increased pH. Fresh yield, fruit number and fruit weight were similarly affected by short-and long-term salinisation. In contrast, the marketable yield was significantly lower in the long-term salinised soil-a response that was also associated to nutritional imbalance (mainly referred to P and K). As reported for plants growing under oxygen deprivation stress, the antioxidant capacity of the water soluble fraction of salinised tomato fruits was enhanced by short-term salinisation, also. Overall, long-term salinisation may cause physiological imbalances and yield reductions that cannot be solely attributed to hyperosmotic stress and ionic toxicity. Therefore, the ability of plants to cope with nutritional deficiency and withstand high pH and anoxia may be important traits that should be considered to improve plant tolerance to long-term salinised soils. |
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1445-4408 |
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CropM |
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MA @ admin @ |
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4583 |
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Author |
Hakala, K.; Jauhiainen, L.; Himanen, S.J.; RÖTter, R.; Salo, T.; Kahiluoto, H. |
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Title |
Sensitivity of barley varieties to weather in Finland |
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Journal Article |
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Year |
2012 |
Publication |
Journal of Agricultural Science |
Abbreviated Journal |
J. Agric. Sci. |
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Volume |
150 |
Issue |
02 |
Pages |
145-160 |
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Keywords |
climate-change; winter-wheat; spring wheat; reproductive growth; high-temperatures; changing climate; crop production; increased CO2; yield; tolerance |
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Global climate change is predicted to shift seasonal temperature and precipitation patterns. An increasing frequency of extreme weather events such as heat waves and prolonged droughts is predicted, but there are high levels of uncertainty about the nature of local changes. Crop adaptation will be important in reducing potential damage to agriculture. Crop diversity may enhance resilience to climate variability and changes that are difficult to predict. Therefore, there has to be sufficient diversity within the set of available cultivars in response to weather parameters critical for yield formation. To determine the scale of such ‘weather response diversity’ within barley (Hordeum vulgare L.), an important crop in northern conditions, the yield responses of a wide range of modern and historical varieties were analysed according to a well-defined set of critical agro-meteorological variables. The Finnish long-term dataset of MTT Official Variety Trials was used together with historical weather records of the Finnish Meteorological Institute. The foci of the analysis were firstly to describe the general response of barley to different weather conditions and secondly to reveal the diversity among varieties in the sensitivity to each weather variable. It was established that barley yields were frequently reduced by drought or excessive rain early in the season, by high temperatures at around heading, and by accelerated temperature sum accumulation rates during periods 2 weeks before heading and between heading and yellow ripeness. Low temperatures early in the season increased yields, but frost during the first 4 weeks after sowing had no effect. After canopy establishment, higher precipitation on average resulted in higher yields. In a cultivar-specific analysis, it was found that there were differences in responses to all but three of the studied climatic variables: waterlogging and drought early in the season and temperature sum accumulation rate before heading. The results suggest that low temperatures early in the season, delayed sowing, rain 3-7 weeks after sowing, a temperature change 3-4 weeks after sowing, a high temperature sum accumulation rate from heading to yellow ripeness and high temperatures (25 degrees C) at around heading could mostly be addressed by exploiting the traits found in the range of varieties included in the present study. However, new technology and novel genetic material are needed to enable crops to withstand periods of excessive rain or drought early in the season and to enhance performance under increased temperature sum accumulation rates prior to heading. |
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0021-8596 1469-5146 |
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MA @ admin @ |
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4586 |
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Legarrea, S.; Betancourt, M.; Plaza, M.; Fraile, A.; García-Arenal, F.; Fereres, A. |
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Title |
Dynamics of nonpersistent aphid-borne viruses in lettuce crops covered with UV-absorbing nets |
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Journal Article |
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Year |
2012 |
Publication |
Virus Research |
Abbreviated Journal |
Virus Res. |
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165 |
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1 |
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1-8 |
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Absorption; Animals; Aphids/growth & development/radiation effects/*virology; Insect Control/instrumentation/*methods; Insect Vectors/growth & development/radiation effects/*virology; Lettuce/parasitology/*virology; Plant Diseases/prevention & control/*virology; Plant Viruses/*physiology; Protective Devices/virology; Ultraviolet Rays |
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Aphid-transmitted viruses frequently cause severe epidemics in lettuce grown under Mediterranean climates. Spatio-temporal dynamics of aphid-transmitted viruses and its vector were studied on lettuce (Lactuca sativa L.) grown under tunnels covered by two types of nets: a commercial UV-absorbing net (Bionet) and a Standard net. A group of plants infected by Cucumber mosaic virus (CMV, family Bromoviridae, genus Cucumovirus) and Lettuce mosaic virus (LMV, family Potyviridae, genus Potyvirus) was transplanted in each plot. The same virus-infected source plants were artificially infested by the aphid Macrosiphum euphorbiae (Thomas). Secondary spread of insects was weekly monitored and plants were sampled for the detection of viruses every two weeks. In 2008, the infection rate of both CMV and LMV were lower under the Bionet than under the Standard cover, probably due to the lower population density and lower dispersal rate achieved by M. euphorbiae. However, during spring of 2009, significant differences in the rate of infection between the two covers were only found for LMV six weeks after transplant. The spatial distribution of the viruses analysed by SADIE methodology was “at random”, and it was not associated to the spatial pattern of the vector. The results obtained are discussed analyzing the wide range of interactions that occurred among UV-radiation, host plant, viruses, insect vector and environmental conditions. Our results show that UV-absorbing nets can be recommended as a component of an integrated disease management program to reduce secondary spread of lettuce viruses, although not as a control measure on its own. |
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0168-1702 |
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CropM |
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MA @ admin @ |
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4475 |
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Author |
Cantelaube, P.; Jayet, P. |
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Geographical downscaling of outputs provided by an economic farm model calibrated at the regional level |
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Journal Article |
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Year |
2012 |
Publication |
Land Use Policy |
Abbreviated Journal |
Land Use Policy |
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29 |
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35-44 |
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Downscaling; Land use; Spatial statistics; Farm-groups; Farm Accountancy Data Network; FADN |
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There is a strong need for accurate and spatially referenced information regarding policy making and model linkage. This need has been expressed by land users, and policy and decision makers in order to estimate both spatially and locally the impacts of European policy (like the Common Agricultural Policy) and/or global changes on farm-groups. These entities are defined according to variables such as altitude, economic size and type of farming (referring to land uses). European farm-groups are provided through the Farm Accountancy Data Network (FADN) as statistical information delivered at regional level. The aim of the study is to map locally farm-group probabilities within each region. The mapping of the farm-groups is done in two steps: (1) by mapping locally the co-variables associated to the farm-groups, i.e. altitude and land uses; (2) by using regional FADN data as a priori knowledge for transforming land uses and altitude information into farm-groups location probabilities within each region. The downscaling process focuses on the land use mapping since land use data are originally point information located every 18 km. Interpolation of land use data is done at 100 m by using co-variables like land cover, altitude, climate and soil data which are continuous layers usually provided at fine resolution. Once the farm-groups are mapped, European Policy and global changes scenarios are run through an agro-economic model for assessing environmental impacts locally. |
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TradeM, ftnotmacsur |
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MA @ admin @ |
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4582 |
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Rötter, R.P.; Palosuo, T.; Kersebaum, K.-C.; Angulo, C.; Bindi, M.; Ewert, F.; Ferrise, R.; Hlavinka, P.; Moriondo, M.; Olesen, J.E.; Takáč, J.; Trnka, M. |
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Simulation of spring barley yield in different climatic zones of Northern and Central Europe: A comparison of nine crop models |
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Journal Article |
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Year |
2012 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
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Volume |
133 |
Issue |
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23-36 |
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Climate; Crop growth simulation; Model comparison; Spring barley; Yield variability; Uncertainty; change impacts; nitrogen dynamics; high-temperature; soil-moisture; elevated co2; ceres-wheat; data set; growth; drought; sensitivity |
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► We compared nine crop simulation models for spring barley at seven sites in Europe. ► Applying crop models with restricted calibration leads to high uncertainties. ► Multi-crop model mean yield estimates were in good agreement with observations. ► The degree of uncertainty for simulated grain yield of barley was similar to winter wheat. ► We need more suitable data enabling us to verify different processes in the models. In this study, the performance of nine widely used and accessible crop growth simulation models (APES-ACE, CROPSYST, DAISY, DSSAT-CERES, FASSET, HERMES, MONICA, STICS and WOFOST) was compared during 44 growing seasons of spring barley (Hordeum vulgare L) at seven sites in Northern and Central Europe. The aims of this model comparison were to examine how different process-based crop models perform at multiple sites across Europe when applied with minimal information for model calibration of spring barley at field scale, whether individual models perform better than the multi-model mean, and what the uncertainty ranges are in simulated grain yields. The reasons for differences among the models and how results for barley compare to winter wheat are discussed. Regarding yield estimation, best performing based on the root mean square error (RMSE) were models HERMES, MONICA and WOFOST with lowest values of 1124, 1282 and 1325 (kg ha(-1)), respectively. Applying the index of agreement (IA), models WOFOST, DAISY and HERMES scored best having highest values (0.632, 0.631 and 0.585, respectively). Most models systematically underestimated yields, whereby CROPSYST showed the highest deviation as indicated by the mean bias error (MBE) (-1159 kg ha(-1)). While the wide range of simulated yields across all sites and years shows the high uncertainties in model estimates with only restricted calibration, mean predictions from the nine models agreed well with observations. Results of this paper also show that models that were more accurate in predicting phenology were not necessarily the ones better estimating grain yields. Total above-ground biomass estimates often did not follow the patterns of grain yield estimates and, thus, harvest indices were also different. Estimates of soil moisture dynamics varied greatly. In comparison, even though the growing cycle for winter wheat is several months longer than for spring barley, using RMSE and IA as indicators, models performed slightly, but not significantly, better in predicting wheat yields. Errors in reproducing crop phenology were similar, which in conjunction with the shorter growth cycle of barley has higher effects on accuracy in yield prediction. |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4592 |
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