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Leogrande, R.; Lopedota, O.; Vitti, C.; Ventrella, D.; Montemurro, F. |
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Title |
Saline water and municipal solid waste compost application on tomato crop: Effects on plant and soil |
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Journal Article |
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Year |
2016 |
Publication |
Journal of Plant Nutrition |
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39 |
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4 |
Pages |
491-501 |
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ftnotmacsur |
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Abstract |
A field experiment was conducted in Southern Italy to evaluate the effects of different water quality and fertilizers on yield performance of tomato crop. In mineral nitrogen (N) fertilizer and irrigation with fresh water (Electrical Conductivity, EC, = 0.9 dS m⁻¹) (FWF); mineral N fertilizer and irrigation with saline water (EC = 6.0 dS m⁻¹) (SWF); municipal solid waste (MSW) compost and irrigation with fresh water (EC = 0.9 dS m⁻¹) (FWC); MSW compost and irrigation with saline water (EC = 6.0 dS m⁻¹) (SWC). At harvest, weight and number of fruits and refractometric index (°Brix) were measured, total and marketable yield and dry matter of fruit were calculated. The results indicated that MSW compost, applied as amendment, could substitute the mineral fertilizer. In fact, in the treatments based on compost application, the tomato average marketable yield increased by 9% compared with treatments with mineral fertilizer. The marketable yield in the SWF and SWC treatments (with an average soil EC in two years to about 3.5 dS m⁻¹) decreased respectively of 20 and 10%, in respect to fresh water treatments. At the end of the experiment, application of compost significantly decreased the sodium absorption rate (SAR) of SWC treatment in respect of SWF (−29.9%). Significant differences were observed among the four treatments both on soil solution cations either exchangeable cations. In particular compost application increased the calcium (Ca) and potassium (K) contents in saturated soil paste respect to the SWF ones (31.4% and 59.5%, respectively). At the same time saturated soil paste sodium (Na) in SWC treatment recorded a decrease of 17.4% compared to SWF. |
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4991 |
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Bennetzen, E.H.; Smith, P.; Porter, J.R. |
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Title |
Agricultural production and greenhouse gas emissions from world regions—The major trends over 40 years |
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Journal Article |
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Year |
2016 |
Publication |
Global Environmental Change |
Abbreviated Journal |
Glob. Environ. Change |
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37 |
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43-55 |
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Keywords |
Agriculture; Greenhouse gas intensity; Climate change; Kaya-Porter; identity; Decoupling emissions; Kaya-identity; land-use change; carbon-dioxide emissions; sustainable intensification; livestock production; forest transitions; global agriculture; crop; production; food security; deforestation; mitigation |
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Since 1970, global agricultural production has more than doubled with agriculture and land-use change now responsible for similar to 1/4 of greenhouse gas emissions from human activities. Yet, while greenhouse gas (GHG) emissions per unit of agricultural product have been reduced at a global level, trends in world regions have been quantified less thoroughly. The KPI (Kaya-Porter Identity) is a novel framework for analysing trends in agricultural production and land-use change and related GHG emissions. We apply this to assess trends and differences in nine world regions over the period 1970-2007. We use a deconstructed analysis of emissions from the mix of multiple sources, and show how each is changing in terms of absolute emissions on a per area and per produced unit basis, and how the change of emissions from each source contributes to the change in total emissions over time. The doubling of global agricultural production has mainly been delivered by developing and transitional countries, and this has been mirrored by increased GHG emissions. The decoupling of emissions from production shows vast regional differences. Our estimates show that emissions per unit crop (as kg CO2-equivalents per Giga Joule crop product), in Oceania, have been reduced by 94% from 1093 to 69; in Central & South America by 57% from 849 to 362; in sub-Saharan Africa by 27% from 421 to 309, and in Europe by 56% from 86 to 38. Emissions per unit livestock (as kg CO2-eq. GJ(-1) livestock product) have reduced; in sub-Saharan Africa by 24% from 6001 to 4580; in Central & South America by 61% from 3742 to 1448; in Central & Eastern Asia by 82% from 3,205 to 591, and; in North America by 28% from 878 to 632. In general, intensive and industrialised systems show the lowest emissions per unit of agricultural production. (C) 2016 Elsevier Ltd. All rights reserved. |
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0959-3780 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4758 |
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Mínguez, M.I. |
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Agriculture in Spain and the climate change issue |
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Report |
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2016 |
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Watch Letter |
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Watch Lett. |
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37 |
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Climate change awareness is pushing research and innovation in agriculture. Studies are booming on phenology and heat stress physiology – in parallel with improvement of their simulation in crop models- water use, irrigation requirements and improvement – be it deficit, strategic or precision irrigation-, cereal grain quality, and pest and disease evolution; large international and European research projects are working on these and mapping new areas for cultivation or species/cultivar changes. |
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International Center for Advanced Mediterranean Agronomic Studies CIHEAM |
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MA @ admin @ |
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4881 |
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Murat, M.; Malinowska, I.; Hoffmann, H.; Baranowski, P. |
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Title |
Statistical modelling of agrometeorological time series by exponential smoothing |
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2016 |
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International Agrophysics |
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International Agrophysics |
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30 |
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1 |
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57-65 |
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exponential smoothing; meteorological time series; statistical forecasting; daily temperature records; weighted moving averages; climate-change; prediction; forecasts; state; weather |
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Meteorological time series are used in modelling agrophysical processes of the soil-plant-atmosphere system which determine plant growth and yield. Additionally, longterm meteorological series are used in climate change scenarios. Such studies often require forecasting or projection of meteorological variables, eg the projection of occurrence of the extreme events. The aim of the article was to determine the most suitable exponential smoothing models to generate forecast using data on air temperature, wind speed, and precipitation time series in Jokioinen (Finland), Dikopshof (Germany), Lleida (Spain), and Lublin (Poland). These series exhibit regular additive seasonality or non-seasonality without any trend, which is confirmed by their autocorrelation functions and partial autocorrelation functions. The most suitable models were indicated by the smallest mean absolute error and the smallest root mean squared error. |
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0236-8722 |
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CropM, ft_macsur |
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MA @ admin @ |
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4728 |
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Author |
Heinschink, K.; Lembacher, F.; Sinabell, F.; Trible, C. |
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Title |
Crop production costs in Austria: Comparison of simulated results and farm observations |
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Conference Article |
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Year |
2016 |
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Jahrbuch der ÖGA |
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26 |
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33-34 |
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26. Jahrestagung der Österreichischen Gesellschaft für Agrarökonomie, 2016-09-15 to 2016-09-16, Vienna, Austria |
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MA @ admin @ |
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5025 |
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