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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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Constantin, J.; Raynal, H.; Casellas, E.; Hoffman, H.; Bindi, M.; Doro, L.; Eckersten, H.; Gaiser, T.; Grosz, B.; Haas, E.; Kersebaum, K.-C.; Klatt, S.; Kuhnert, M.; Lewan, E.; Maharjan, G.R.; Moriondo, M.; Nendel, C.; Roggero, P.P.; Specka, X.; Trombi, G.; Villa, A.; Wang, E.; Weihermueller, L.; Yeluripati, J.; Zhao, Z.; Ewert, F.; Bergez, J.-E. |
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Title |
Management and spatial resolution effects on yield and water balance at regional scale in crop models |
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Journal Article |
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Year |
2019 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
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Volume |
275 |
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184-195 |
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Drainage; Evapotranspiration; Aggregation; Decision rules; Scaling; winter-wheat yield; data aggregation; sowing dates; area index; input; data; carbon; growth; irrigation; productivity; assimilation |
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Due to the more frequent use of crop models at regional and national scale, the effects of spatial data input resolution have gained increased attention. However, little is known about the influence of variability in crop management on model outputs. A constant and uniform crop management is often considered over the simulated area and period. This study determines the influence of crop management adapted to climatic conditions and input data resolution on regional-scale outputs of crop models. For this purpose, winter wheat and maize were simulated over 30 years with spatially and temporally uniform management or adaptive management for North Rhine-Westphalia ((similar to)34 083 km(2)), Germany. Adaptive management to local climatic conditions was used for 1) sowing date, 2) N fertilization dates, 3) N amounts, and 4) crop cycle length. Therefore, the models were applied with four different management sets for each crop. Input data for climate, soil and management were selected at five resolutions, from 1 x 1 km to 100 x 100 km grid size. Overall, 11 crop models were used to predict regional mean crop yield, actual evapotranspiration, and drainage. Adaptive management had little effect (< 10% difference) on the 30-year mean of the three output variables for most models and did not depend on soil, climate, and management resolution. Nevertheless, the effect was substantial for certain models, up to 31% on yield, 27% on evapotranspiration, and 12% on drainage compared to the uniform management reference. In general, effects were stronger on yield than on evapotranspiration and drainage, which had little sensitivity to changes in management. Scaling effects were generally lower than management effects on yield and evapotranspiration as opposed to drainage. Despite this trend, sensitivity to management and scaling varied greatly among the models. At the annual scale, effects were stronger in certain years, particularly the management effect on yield. These results imply that depending on the model, the representation of management should be carefully chosen, particularly when simulating yields and for predictions on annual scale. |
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2020-02-14 |
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0168-1923 |
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CropM, ft_macsur |
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MA @ admin @ |
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5225 |
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Dono, G.; Cortignani, R.; Doro, L.; Giraldo, L.; Ledda, L.; Pasqui, M.; Roggero, P.P. |
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An integrated assessment of the impacts of changing climate variability on agricultural productivity and profitability in an irrigated Mediterranean catchment |
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Journal Article |
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2013 |
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Water Resource Management |
Abbreviated Journal |
Water Resource Manage. |
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27 |
Issue |
10 |
Pages |
3607-3622 |
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Keywords |
discrete stochastic programming; climate change variability; adaptation to climate change; net evapotranspiration and irrigation requirements; water availability; epic crops model; economic impact of climate change; precipitation; uncertainty; region; series; yield; model; scale; wheat; gis |
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Climate change is likely to have a profound effect on many agricultural variables, although the extent of its influence will vary over the course of the annual farm management cycle. Consequently, the effect of different and interconnected physical, technical and economic factors must be modeled in order to estimate the effects of climate change on agricultural productivity. Such modeling commonly makes use of indicators that summarize the among environmental factors that are considered when farmers plan their activities. This study uses net evapotranspiration (ETN), estimated using EPIC, as a proxy index for the physical factors considered by farmers when managing irrigation. Recent trends suggest that the probability distribution function of ETN may continue to change in the near future due to changes in the irrigation needs of crops. Also, water availability may continue to vary due to changes in the rainfall regime. The impacts of the uncertainties related to these changes on costs are evaluated using a Discrete Stochastic Programming model representing an irrigable Mediterranean area where limited water is supplied from a reservoir. In this context, adaptation to climate change can be best supported by improvements to the collective irrigation systems, rather than by measures aimed at individual farms such as those contained within the rural development policy. |
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0920-4741 |
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TradeM |
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MA @ admin @ |
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4487 |
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Webber, H.; Gaiser, T.; Oomen, R.; Teixeira, E.; Zhao, G.; Wallach, D.; Zimmermann, A.; Ewert, F. |
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Title |
Uncertainty in future irrigation water demand and risk of crop failure for maize in Europe |
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Journal Article |
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Year |
2016 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
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Keywords |
crop model; impact assessment; crop water use; evapotranspiration; irrigation; drought; uncertainty |
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While crop models are widely used to assess the change in crop productivity with climate change, their skill in assessing irrigation water demand or the risk of crop failure in large area impact assessments is relatively unknown. The objective of this study is to investigate which aspects of modeling crop water use (reference crop evapotranspiration (ET0), soil water extraction, soil evaporation, soil water balance and root growth) contributes most to the variability in estimates of maize crop water use and the risk of crop failure, and demonstrate the resulting uncertainty in a climate change impact study for Europe. The SIMPLACE crop modeling framework was used to couple the LINTUL5 crop model in factorial combinations of 2-3 different approaches for simulating the 5 aspects of crop water use, resulting in 51 modeling approaches. Using experiments in France and New Zeland, analysis of total sensitivity revealed that ET0 explained the most variability in both irrigated maize water use and rainfed grain yield levels, with soil evaporation also imporatant in the French experiment. In the European impact study, net irrigation requirement differed by 36% between the Penman and Hargreaves ET0 methods in the baseline period. Average EU grain yields were similar between models, but differences approached 1-2 tonnes in parts of France and Southern Europe. EU wide esimates of crop failure in the historical period ranged between 5.4 years for Priestley-Taylor to every 7.9 years for the Penman ET0 methods. While the uncertainty in absolute values between models was significant, estimates of relative changes were similar between models, confirming the utility of crop models in assessing climate change impacts. If ET0 estimates in crop models can be improved, through the use of appropriate methods, uncertainty in irrigation water demand as well as in yield estimates under drought can be reduced. |
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2016-09-13 |
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Newsletter July |
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CropM; wos; ft=macsur; |
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MA @ admin @ |
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4778 |
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Zhao, G.; Webber, H.; Hoffmann, H.; Wolf, J.; Siebert, S.; Ewert, F. |
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The implication of irrigation in climate change impact assessment: a European-wide study |
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Journal Article |
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2015 |
Publication |
Global Change Biology |
Abbreviated Journal |
Glob. Chang. Biol. |
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21 |
Issue |
11 |
Pages |
4031-4048 |
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Keywords |
CO2 effects; Lintul; Simplace; climate change; crop model; irrigation; water availability; yield change |
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This study evaluates the impacts of projected climate change on irrigation requirements and yields of six crops (winter wheat, winter barley, rapeseed, grain maize, potato, and sugar beet) in Europe. Furthermore, the uncertainty deriving from consideration of irrigation, CO2 effects on crop growth and transpiration, and different climate change scenarios in climate change impact assessments is quantified. Net irrigation requirement (NIR) and yields of the six crops were simulated for a baseline (1982-2006) and three SRES scenarios (B1, B2 and A1B, 2040-2064) under rainfed and irrigated conditions, using a process-based crop model, SIMPLACE <LINTUL5, DRUNIR, HEAT>. We found that projected climate change decreased NIR of the three winter crops in northern Europe (up to 81 mm), but increased NIR of all the six crops in the Mediterranean regions (up to 182 mm yr(-1)). Climate change increased yields of the three winter crops and sugar beet in middle and northern regions (up to 36%), but decreased their yields in Mediterranean countries (up to 81%). Consideration of CO2 effects can alter the direction of change in NIR for irrigated crops in the south and of yields for C3 crops in central and northern Europe. Constraining the model to rainfed conditions for spring crops led to a negative bias in simulating climate change impacts on yields (up to 44%), which was proportional to the irrigation ratio of the simulation unit. Impacts on NIR and yields were generally consistent across the three SRES scenarios for the majority of regions in Europe. We conclude that due to the magnitude of irrigation and CO2 effects, they should both be considered in the simulation of climate change impacts on crop production and water availability, particularly for crops and regions with a high proportion of irrigated crop area. |
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1354-1013 |
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CropM, ft_macsur |
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MA @ admin @ |
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4716 |
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