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Author Abdelrahman, H.M.; Olk, D.C.; Dinnes, D.; Ventrella, D.; Miano, T.; Cocozza, C. url  doi
openurl 
  Title Occurrence and abundance of carbohydrates and amino compounds in sequentially extracted labile soil organic matter fractions Type Journal Article
  Year 2016 Publication Journal of Soils and Sediments Abbreviated Journal Journal of Soils and Sediments  
  Volume 16 Issue 10 Pages 2375-2384  
  Keywords Light fraction; Mobile humic acid; Organic farming; Particulate organic matter; SOM sequential extraction  
  Abstract Purpose The study aimed to describe the carbohydrates and amino compounds content in soil, the light fraction (LF), the >53 μm particulate organic matter (POM), and the mobile humic acid (MHA) fraction and to find out whether the carbohydrates and amino compounds can be used to explain the origin of SOM fractions. Materials and methods Soil samples were collected from two agricultural fields managed under organic farming in southern Italy. The LF, the POM, and the MHA were sequentially extracted from each soil sample then characterized. Seven neutral sugars and 19 amino compounds (amino acids and amino sugars) were determined in each soil sample and its correspondent fractions. Results and discussion The MHA contained less carbohydrate than the LF or the POM but its carbohydrates, although dominated by arabinose, were relatively with larger microbial contribution as revealed by the mannose/xylose ratio. The amino compounds were generally less in the LF or the POM than in the MHA, while the fungal (aspartic and serine) and bacterial (alanine and glycine) amino acids were larger in the MHA than in the LF or the POM, underlining the microbial contribution to the MHA. Results from both sites indicated that total carbohydrates content decreased moving from the LF (younger fraction) to the MHA (older fraction), which seems to follow a decomposition continuum of organic matter in the soil-plant system. Conclusions The study showed that the MHA is a labile humified fraction of soil C due to its content of carbohydrates and concluded that the content of carbohydrates and amino compounds in the LF, the POM and the MHA can depict the nature of these fractions and their cycling pattern and response to land management.  
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  Series Volume Series Issue Edition  
  ISSN (up) 1439-0108 ISBN Medium  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4992  
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Author Leogrande, R.; Vitti, C.; Lopedota, O.; Ventrella, D.; Montemurro, F. url  doi
openurl 
  Title Effects of Irrigation Volume and Saline Water On Maize Yield and Soil in Southern Italy: Irrigation with saline water on maize Type Journal Article
  Year 2016 Publication Irrig. and Drain. Abbreviated Journal Irrig. and Drain.  
  Volume 65 Issue 3 Pages 243-253  
  Keywords  
  Abstract A field experiment was carried out in southern Italy to investigate the effects of irrigation and salinity on a maize crop and soil properties. The experiment was laid out comparing different irrigation rates (I1, I2, I3—re-establishing 50, 75 and 100% of the calculated maximum evapotranspiration) and water quality (FW, fresh water and SW, saline water). Grain yield was significantly greater by 60% in 2008 than in 2010. No significant difference was shown for grain yield between the irrigation treatments, whereas water productivity decreased significantly with increasing irrigation rates. Irrigation with saline water did not significantly reduce grain yield compared with fresh water, but it improved grain quality with higher protein content (9.1%) and lower grain moisture percentage (13.3%). Saline water determined a significant increase of saturated soil paste extract Na, ECe, SAR, some exchangeable cations and ESP compared with FW in both years. Furthermore, at the end of the experiment these parameters were lower than those at the end of the first maize crop. Lastly, in the saline treatment, at the end of the trial, the ECe and ESP values were below the critical threshold for soil salinization and/or sodification.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) 1531-0353 ISBN Medium  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4990  
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Author Paas, W.; Kanellopoulos, A.; van de Ven, G.; Reidsma, P. url  doi
openurl 
  Title Integrated impact assessment of climate and socio-economic change on dairy farms in a watershed in the Netherlands Type Journal Article
  Year 2016 Publication NJAS – Wageningen Journal of Life Sciences Abbreviated Journal NJAS – Wageningen Journal of Life Sciences  
  Volume Issue Pages  
  Keywords climate change; bio-economic model; explorations; land-use; 2050-scenario  
  Abstract Climate and socio-economic change will affect the land use and the economic viability of Dutch dairy farms. Explorations of future scenarios, which include different drivers and impacts, are needed to perform ex-ante policy assessment. This study uses a bio-economic farm model to assess impacts of climate and socio-economic change on dairy farms in a sandy area in the Netherlands. Farm data from the Farm Accountancy Data Network provided information on the current production levels and available farm resources. First, the farm plans of individual farms were optimized in the current situation to benchmark farms and assess the current scope for improvement. Secondly, simulations for two scenarios were included: a Global Economy with 2 °C global temperature rise (GE/W+) and a Regional Community with 1 °C global temperature rise (RC/G). The impacts of climate change, extreme events, juridical change (including abolishment of milk quota), technological change and price changes were evaluated in separate model runs within the predefined scenarios. We found that farms can increase profit both by intensification and land expansion; the latter especially for medium sized farms (less than 70 cows). Climate change including the effect of increased occurrence of extreme events may negatively affect farm gross margin in the GE/W+ scenario. Lower gross margins are compensated for by the effects of technology and price changes. In contrast with the GE/W+ scenario, climate change has positive impacts on farm profit in RC/G, but less favourable farm input-output price ratios have a negative effect. Technological change is needed to compensate for revenue losses due to higher input prices. In both GE/W+ and RC/G scenarios, dairy farms increase production and the use of artificial fertilizer. Medium sized farms have more options to increase profit than the large farms: they benefit more from the abolishment of the milk quota and better adapt to negative and positive impacts of climate change. While the exact impact of different drivers will always remain uncertain, this study showed that changes in prices, technology and markets have a relatively larger impact than climate change, even when extreme events are taken into account. By using whole farm plans as activities that can be selected, the model is grounded in observations, and it was shown that half of the farms are gross margin maximizers as assumed in the model. The model therefore indicates ‘what could happen if’, and gives insights in drivers and impacts of dairy farming in the region.  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) 1573-5214 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4712  
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Author Bannink, A.; van Lingen, H.J.; Ellis, J.L.; France, J.; Dijkstra, J. doi  openurl
  Title The contribution of mathematical modeling to understanding dynamic aspects of rumen metabolism Type Journal Article
  Year 2016 Publication Frontiers in Microbiology Abbreviated Journal Frontiers in Microbiology  
  Volume 7 Issue Pages 1820  
  Keywords lactating dairy-cows; milk urea concentration; fatty-acid production; ruminal fermentation; mechanistic model; holstein cows; beef-cattle; stoichiometric parameters; methane production; feeding frequency  
  Abstract All mechanistic rumen models cover the main drivers of variation in rumen function, which are feed intake, the differences between feedstuffs and feeds in their intrinsic rumen degradation characteristics, and fractional outflow rate of fluid and particulate matter. Dynamic modeling approaches are best suited to the prediction of more nuanced responses in rumen metabolism, and represent the dynamics of the interactions between substrates and micro-organisms and inter-microbial interactions. The concepts of dynamics are discussed for the case of rumen starch digestion as influenced by starch intake rate and frequency of feed intake, and for the case of fermentation of fiber in the large intestine. Adding representations of new functional classes of micro-organisms (i.e., with new characteristics from the perspective of whole rumen function) in rumen models only delivers new insights if complemented by the dynamics of their interactions with other functional classes. Rumen fermentation conditions have to be represented due to their profound impact on the dynamics of substrate degradation and microbial metabolism. Although the importance of rumen pH is generally acknowledged, more emphasis is needed on predicting its variation as well as variation in the processes that underlie rumen fluid dynamics. The rumen wall has an important role in adapting to rapid changes in the rumen environment, clearing of volatile fatty acids (VFA), and maintaining rumen pH within limits. Dynamics of rumen wall epithelia and their role in VFA absorption needs to be better represented in models that aim to predict rumen responses across nutritional or physiological states. For a detailed prediction of rumen N balance there is merit in a dynamic modeling approach compared to the static approaches adopted in current protein evaluation systems. Improvement is needed on previous attempts to predict rumen VFA profiles, and this should be pursued by introducing factors that relate more to microbial metabolism. For rumen model construction, data on rumen microbiomes are preferably coupled with knowledge consolidated in rumen models instead of relying on correlations with rather general aspects of treatment or animal. This helps to prevent the disregard of basic principles and underlying mechanisms of whole rumen function.  
  Address 2017-01-06  
  Corporate Author Thesis  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) 1664-302x ISBN Medium  
  Area Expedition Conference  
  Notes LiveM, ft_MACSUR Approved no  
  Call Number MA @ admin @ Serial 4932  
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Author Kim, D.-G.; Thomas, A.D.; Pelster, D.; Rosenstock, T.S.; Sanz-Cobena, A. url  doi
openurl 
  Title Greenhouse gas emissions from natural ecosystems and agricultural lands in sub-Saharan Africa: synthesis of available data and suggestions for further research Type Journal Article
  Year 2016 Publication Biogeosciences Abbreviated Journal Biogeosciences  
  Volume 13 Issue 16 Pages 4789-4809  
  Keywords nitrous-oxide emissions; soil CO2 efflux; N2O emissions; carbon-dioxide; agroforestry residues; improved-fallow; disturbance gradient; fertilizer; nitrogen; sampling frequency; gaseous emissions  
  Abstract This paper summarizes currently available data on greenhouse gas (GHG) emissions from African natural ecosystems and agricultural lands. The available data are used to synthesize current understanding of the drivers of change in GHG emissions, outline the knowledge gaps, and suggest future directions and strategies for GHG emission research. GHG emission data were collected from 75 studies conducted in 22 countries (n = 244) in sub-Saharan Africa (SSA). Carbon dioxide (CO2) emissions were by far the largest contributor to GHG emissions and global warming potential (GWP) in SSA natural terrestrial systems. CO2 emissions ranged from 3.3 to 57.0 Mg CO2 ha(-1) yr(-1), methane (CH4) emissions ranged from -4.8 to 3.5 kg ha(-1) yr(-1) (-0.16 to 0.12 Mg CO2 equivalent (eq.) ha(-1) yr(-1)), and nitrous oxide (N2O) emissions ranged from -0.1 to 13.7 kg ha(-1) yr(-1) (-0.03 to 4.1 Mg CO2 eq. ha(-1) yr(-1)). Soil physical and chemical properties, rewetting, vegetation type, forest management, and land-use changes were all found to be important factors affecting soil GHG emissions from natural terrestrial systems. In aquatic systems, CO2 was the largest contributor to total GHG emissions, ranging from 5.7 to 232.0 Mg CO2 ha(-1) yr(-1), followed by -26.3 to 2741.9 kgCH(4) ha(-1) yr(-1) (-0.89 to 93.2 Mg CO2 eq. ha(-1) yr(-1)) and 0.2 to 3.5 kg N2O ha(-1) yr(-1) (0.06 to 1.0 Mg CO2 eq. ha(-1) yr(-1)). Rates of all GHG emissions from aquatic systems were affected by type, location, hydrological characteristics, and water quality. In croplands, soil GHG emissions were also dominated by CO2, ranging from 1.7 to 141.2 Mg CO2 ha(-1) yr(-1), with -1.3 to 66.7 kgCH(4) ha(-1) yr(-1) (-0.04 to 2.3 Mg CO2 eq. ha(-1) yr(-1)) and 0.05 to 112.0 kg N2O ha(-1) yr(-1) (0.015 to 33.4 Mg CO2 eq. ha(-1) yr(-1)). N2O emission factors (EFs) ranged from 0.01 to 4.1 %. Incorporation of crop residues or manure with inorganic fertilizers invariably resulted in significant changes in GHG emissions, but results were inconsistent as the magnitude and direction of changes were differed by gas. Soil GHG emissions from vegetable gardens ranged from 73.3 to 132.0 Mg CO2 ha(-1) yr(-1) and 53.4 to 177.6 kg N2O ha(-1) yr(-1) (15.9 to 52.9 Mg CO2 eq. ha(-1) yr(-1)) and N2O EFs ranged from 3 to 4 %. Soil CO2 and N2O emissions from agroforestry were 38.6 Mg CO2 ha(-1) yr(-1) and 0.2 to 26.7 kg N2O ha(-1) yr(-1) (0.06 to 8.0 Mg CO2 eq. ha(-1) yr(-1)), respectively. Improving fallow with nitrogen (N)-fixing trees led to increased CO2 and N2O emissions compared to conventional croplands. The type and quality of plant residue in the fallow is an important control on how CO2 and N2O emissions are affected. Throughout agricultural lands, N2O emissions slowly increased with N inputs below 150 kg N ha(-1) yr(-1) and increased exponentially with N application rates up to 300 kg N ha(-1) yr(-1). The lowest yield-scaled N2O emissions were reported with N application rates ranging between 100 and 150 kg N ha(-1). Overall, total CO2 eq. emissions from SSA natural ecosystems and agricultural lands were 56.9 +/- 12.7 x 10(9) Mg CO2 eq. yr(-1) with natural ecosystems and agricultural lands contributing 76.3 and 23.7 %, respectively. Additional GHG emission measurements are urgently required to reduce uncertainty on annual GHG emissions from the different land uses and identify major control factors and mitigation options for low-emission development. A common strategy for addressing this data gap may include identifying priorities for data acquisition, utilizing appropriate technologies, and involving international networks and collaboration.  
  Address 2016-10-18  
  Corporate Author Thesis  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) 1726-4170 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4687  
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