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Author Lessire, F.; Hornick, J.L.; Minet, J.; Dufrasne, I.
Title Rumination time, milk yield, milking frequency of grazing dairy cows milked by a mobile automatic system during mild heat stress Type Journal Article
Year 2015 Publication Advances in Animal Biosciences Abbreviated Journal Advances in Animal Biosciences
Volume 6 Issue 01 Pages (down) 12-14
Keywords dairy; heat stress; THI; behaviour; milk yield
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Language English Summary Language Original Title
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Series Volume Series Issue Edition
ISSN 2040-4700 ISBN Medium Article
Area Expedition Conference
Notes LiveM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4570
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Author Wang, X.; Biewald, A.; Dietrich, J.P.; Schmitz, C.; Lotze-Campen, H.; Humpenöder, F.; Bodirsky, B.L.; Popp, A.
Title Taking account of governance: Implications for land-use dynamics, food prices, and trade patterns Type Journal Article
Year 2016 Publication Ecological Economics Abbreviated Journal Ecol. Econ.
Volume 122 Issue Pages (down) 12-24
Keywords
Abstract Highlights • Governance impacts on land use dynamics are modeled at the global scale with an agro-economic dynamic optimization model. • Improved governance performance lowers deforestation, reduces cropland expansion and increases agricultural yield. • Good governance makes a decisive difference in investment for increasing yields in developing regions. • Weak governance increases food prices, particularly in Sub-Saharan Africa and Southeast Asia. • Improving governance performance has significant impacts on poverty reduction. Abstract Deforestation, mainly caused by unsustainable agricultural expansion, results in a loss of biodiversity and an increase in greenhouse gas emissions, as well as impinges on local livelihoods. Countries’ governance performance, particularly with respect to property rights security, exerts significant impacts on land-use patterns by affecting agricultural yield-related technological investment and cropland expansion. This study aims to incorporate governance factors into a recursive agro-economic dynamic model to simulate governance impacts on land-use patterns at the global scale. Due to the difficulties of including governance indicators directly into numerical models, we use lending interest rates as discount rates to reflect risk-accounting factors associated with different governance scenarios. In addition to a reference scenario, three scenarios with high, low and mixed divergent discount rates are formed to represent weak, strong and fragmented governance. We find that weak governance leads to slower yield growth, increased cropland expansion and associated deforestation, mainly in Latin America, Sub-Saharan Africa, South Asia and Southeast Asia. This is associated with increasing food prices, particularly in Sub-Saharan Africa and Southeast Asia. By contrast, strong governance performance provides a stable political and economic situation which may bring down deforestation rates, stimulate investment in agricultural technologies, and induce fairly strong decreases in food prices.
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ISSN 0921-8009 ISBN Medium
Area Expedition Conference
Notes TradeM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 5002
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Author Kässi, P.; Känkänen, H.; Niskanen, O.; Lehtonen, H.; Höglind, M.
Title Farm level approach to manage grass yield variation under climate change in Finland and north-western Russia Type Journal Article
Year 2015 Publication Biosystems Engineering Abbreviated Journal Biosystems Engineering
Volume 140 Issue Pages (down) 11-22
Keywords silage grass; risk management; dairy farms; buffer storage; agricultural economics; grassland modelling; dairy-cows; impact; security; timothy; harvest; future; growth; norway; europe; time
Abstract Cattle feeding in Northern Europe is based on grass silage, but grass growth is highly dependent on weather conditions. If ensuring sufficient silage availability in every situation is prioritised, the lowest expected yield level determines the cultivated area in farmers’ decision-making. One way to manage the variation in grass yield is to increase grass production and silage storage capacity so that they exceed the annual consumption at the farm. The cost of risk management in the current and the projected future climate was calculated taking into account grassland yield and yield variability for three study areas under current and mid-21st century climate conditions. The dataset on simulated future grass yields used as input for the risk management calculations were taken from a previously published simulation study. Strategies investigated included using up to 60% more silage grass area than needed in a year with average grass yields, and storing silage for up to 6 months more than consumed in a year (buffer storage). According to the results, utilising an excess silage grass area of 20% and a silage buffer storage capacity of 6 months were the most economic ways of managing drought risk in both the baseline climate and the projected climate of 2046-2065. It was found that the silage yield risk due to drought is likely to decrease in all studied locations, but the drought risk and costs implied still remain significant. (C) 2015 IAgrE. Published by Elsevier Ltd. All rights reserved.
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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1537-5110 ISBN Medium Article
Area Expedition Conference
Notes TradeM Approved no
Call Number MA @ admin @ Serial 4671
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Author Sharif, B.; Makowski, D.; Plauborg, F.; Olesen, J.E.
Title Comparison of regression techniques to predict response of oilseed rape yield to variation in climatic conditions in Denmark Type Journal Article
Year 2017 Publication European Journal of Agronomy Abbreviated Journal Europ. J. Agron.
Volume 82 Issue Pages (down) 11-20
Keywords Winter oilseed rape; Statistical models; Yield; Climate; Regression
Abstract Highlights • Regularization techniques for regression outperformed the classical regression techniques in predicting crop yields. • Different regression techniques with similar prediction accuracy showed different responses of major climatic variables to crop yield. • The regression models showed some responses of crop yield to climatic conditions that is mostly absent in process based crop models. Abstract Statistical regression models represent alternatives to process-based dynamic models for predicting the response of crop yields to variation in climatic conditions. Regression models can be used to quantify the effect of change in temperature and precipitation on yields. However, it is difficult to identify the most relevant input variables that should be included in regression models due to the high number of candidate variables and to their correlations. This paper compares several regression techniques for modeling response of winter oilseed rape yield to a high number of correlated input variables. Several statistical regression methods were fitted to a dataset including 689 observations of winter oilseed rape yield from replicated field experiments conducted in 239 sites in Denmark, covering nearly all regions of the country from 1992 to 2013. Regression methods were compared by cross-validation. The regression methods leading to the most accurate yield predictions were Lasso and Elastic Net, and the least accurate methods were ordinary least squares and stepwise regression. Partial least squares and ridge regression methods gave intermediate results. The estimated relative yield change for a +1°C temperature increase during flowering was estimated to range between 0 and +6 %, depending on choice of regression method. Precipitation was found to have an adverse effect on yield during autumn and winter. It was estimated that an increase in precipitation of +1 mm/day would result in a relative yield change ranging from 0 to −4 %. Soil type was also important for crop yields with lower yields on sandy soils compared to loamy soils. Later sowing was found to result in increased crop yield. The estimated effect of climate on yield was highly sensitive to the chosen regression method. Regression models showing similar performance led in some cases to different conclusions with respect to effect of temperature and precipitation. Hence, it is recommended to apply an ensemble of regression models, in order to account for the sensitivity of the data driven models for projecting crop yield under climate change.
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ISSN 1161-0301 ISBN Medium article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4966
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Author Sinabell, F.
Title Wirtschaftliche Herausforderungen für die Landwirtschaft Type Conference Article
Year 2016 Publication Abbreviated Journal
Volume 5 Issue Pages (down) 11-13
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Corporate Author Thesis
Publisher Place of Publication Irdning-Donnersbachtal Editor
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ISSN ISBN Medium
Area Expedition Conference Umweltökologisches Symposium. Landwirtschaft 2030 - Auswirkungen auf Boden, Wasser und Luft, 5. – 6. April 2016, Irdning-Donnersbachtal
Notes TradeM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 5013
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