|   | 
Details
   web
Records
Author Irz, X.; Kuosmanen, N.
Title Explaining growth in demand for dairy products in Finland: an econometric analysis Type Journal Article
Year 2013 Publication Food Economics Abbreviated Journal Food Economics
Volume 9 Issue sup5 Pages 47-56
Keywords Consumption; food; almost ideal demand system; decomposition; elasticities; milk; demand analysis; farm
Abstract The dairy sector represents the cornerstone of Finnish agriculture but faces new challenges linked to the decoupling of farm subsidies and abolition of milk production quotas. Because of its increasing exposure to market forces, the sector must anticipate future changes in demand and deliver precisely what Finnish consumers want. This paper contributes to that goal by analyzing retroactively the drivers of demand for dairy products over the period 1975–2010 using National Accounts Data. After presenting the evolution of consumption for dairy products, we estimate a complete system of demand for food and dairy products and use it to decompose demand growth into a substitution effect, income effect, and trend effect. The analysis points to the severity of the challenges that the sector is facing. Stagnant consumption is at least partially the result of continuous but adverse taste changes, and as Finnish consumers grow more prosperous, they allocate an increasingly smaller share of their food budget to the dairy group. The low own-price elasticity of demand for dairy products also limits the benefits to the sector of growth in milk production. Hence, business-as-usual will result in the dwindling importance of the dairy sector in the Finnish food chain. Innovation and product differentiation, perhaps emphasizing the attributes of livestock production processes, are clearly required to counter this evolution.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language (down) English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2164-828x ISBN Medium Article
Area Expedition Conference
Notes TradeM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 4491
Permanent link to this record
 

 
Author Schauberger, B.; Rolinski, S.; Müller, C.
Title A network-based approach for semi-quantitative knowledge mining and its application to yield variability Type Journal Article
Year 2016 Publication Environmental Research Letters Abbreviated Journal Environ. Res. Lett.
Volume 11 Issue 12 Pages 123001
Keywords yield variability; crop models; interaction network; plant process; wheat; maize; rice; Global Food Security; Climate-Change; Crop Production; Stress Tolerance; Wheat Yields; Heat-Stress; Temperature Variability; Environmental-Factors; United-States; Elevated CO2
Abstract Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. Asystematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields.
Address 2017-04-07
Corporate Author Thesis
Publisher Place of Publication Editor
Language (down) English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1748-9326 ISBN Medium Review
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4942
Permanent link to this record
 

 
Author Zimmermann, A.; Webber, H.; Zhao, G.; Ewert, F.; Kros, J.; Wolf, J.; Britz, W.; de Vries, W.
Title Climate change impacts on crop yields, land use and environment in response to crop sowing dates and thermal time requirements Type Journal Article
Year 2017 Publication Agricultural Systems Abbreviated Journal Agric. Syst.
Volume 157 Issue Pages 81-92
Keywords Integrated assessment; Crop management; Climate change; Europe; INTEGRATED ASSESSMENT; EUROPEAN AGRICULTURE; FOOD SECURITY; HEAT-STRESS; ADAPTATION; SYSTEMS; TEMPERATURE; SCENARIOS; WHEAT; PRODUCTIVITY; Vries W., 2011, ENVIRONMENTAL POLLUTION, V159, P3254
Abstract Impacts of climate change on European agricultural production, land use and the environment depend on its impact on crop yields. However, many impact studies assume that crop management remains unchanged in future scenarios, while farmers may adapt their sowing dates and cultivar thermal time requirements to minimize yield losses or realize yield gains. The main objective of this study was to investigate the sensitivity of climate change impacts on European crop yields, land use, production and environmental variables to adaptations in crops sowing dates and varieties’ thermal time requirements. A crop, economic and environmental model were coupled in an integrated assessment modelling approach for six important crops, for 27 countries of the European Union (EU27) to assess results of three SRES climate change scenarios to 2050. Crop yields under climate change were simulated considering three different management cases; (i) no change in crop management from baseline conditions (NoAd), (ii) adaptation of sowing date and thermal time requirements to give highest yields to 2050 (Opt) and (iii) a more conservative adaptation of sowing date and thermal time requirements (Act). Averaged across EU27, relative changes in water-limited crop yields due to climate change and increased CO2 varied between -6 and + 21% considering NoAd management, whereas impacts with Opt management varied between + 12 and + 53%, and those under Act management between 2 and + 27%. However, relative yield increases under climate change increased to + 17 and + 51% when technology progress was also considered. Importantly, the sensitivity to crop management assumptions of land use, production and environmental impacts were less pronounced than for crop yields due to the influence of corresponding market, farm resource and land allocation adjustments along the model chain acting via economic optimization of yields. We conclude that assumptions about crop sowing dates and thermal time requirements affect impact variables but to a different extent and generally decreasing for variables affected by economic drivers.
Address 2017-11-02
Corporate Author Thesis
Publisher Place of Publication Editor
Language (down) English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0308-521x ISBN Medium article
Area Expedition Conference
Notes CropM, TradeM, ft_macsur Approved no
Call Number MA @ admin @ Serial 5178
Permanent link to this record
 

 
Author Vilvert, E.; Lana, M.; Zander, P.; Sieber, S.
Title Multi-model approach for assessing the sunflower food value chain in Tanzania Type Journal Article
Year 2018 Publication Agricultural Systems Abbreviated Journal Agric. Syst.
Volume 159 Issue Pages 103-110
Keywords Sunflower; Food value chain; Modelling; Tanzania; Food security; Systems Simulation; Crop Model; Agricultural Systems; Farming Systems; Yield Response; Land-Use; Water; Aquacrop; Security; Stics
Abstract Sunflower is one of the major oilseeds produced in Tanzania, but due to insufficient domestic production more than half of the country’s demand is imported. The improvement of the sunflower food value chain (FVC) understanding is important to ensure an increase in the production, availability, and quality of edible oil. In order to analyse causes and propose solutions to increase the production of sunflower oil, a conceptual framework that proposes the combined use of different models to provide insights about the sunflower FVC was developed. This research focus on the identification of agricultural models that can provide a better understanding of the sunflower FVC in Tanzania, especially within the context of food security improvement. A FVC scheme was designed considering the main steps of sunflower production. Thereafter, relevant models were selected and placed along each step of the FVC. As result, the sunflower FVC model in Tanzania is organized in five steps, namely (1) natural resources; (2) crop production; (3) oil processing; (4) trade; and (5) consumption. Step 1 uses environmental indicators to analyse soil parameters on soil-water models (SWAT, LPJmL, APSIM or CroSyst), with outputs providing data for step 2 of the FVC. In the production step, data from step 1, together with other inputs, is used to run crop models (DSSAT, HERMES, MONICA, STICS, EPIC or AquaCrop) that analyse the impact on sunflower yields. Thereafter, outputs from crop models serve as input for bio-economic farm models (FSSIM or MODAM) to estimate production costs and farm income by optimizing resource allocation planning for step 2. In addition, outputs from crop models are used as inputs for macro-economic models (GTAP, MAGNET or MagPie) by adjusting supply functions and environmental impacts within steps 3, 4, and 5. These models simulate supply and demand, including the processing of products to determine prices and trade volumes at market equilibrium. In turn, these data is used by bio-economic farm models to assess sunflower returns for different farm types and agro-environmental conditions. Due to the large variety of models, it is possible to assess significant parts of the FVC, reducing the need to make assumptions, while improving the understanding of the FVC.
Address 2018-01-25
Corporate Author Thesis
Publisher Place of Publication Editor
Language (down) English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0308-521x ISBN Medium
Area Expedition Conference
Notes CropM, TradeM, ft_macsur Approved no
Call Number MA @ admin @ Serial 5187
Permanent link to this record
 

 
Author Weindl, I.; Popp, A.; Bodirsky, B.L.; Rolinski, S.; Lotze-Campen, H.; Biewald, A.; Humpenoeder, F.; Dietrich, J.P.; Stevanovic, M.
Title Livestock and human use of land: Productivity trends and dietary choices as drivers of future land and carbon dynamics Type Journal Article
Year 2017 Publication Global and Planetary Change Abbreviated Journal Global And Planetary Change
Volume 159 Issue Pages 1-10
Keywords Livestock productivity; Diets; Land use; Deforestation; Carbon emissions; Greenhouse gas mitigation; Greenhouse-Gas Emissions; Climate-Change Mitigation; Food-Demand; Crop; Productivity; Cover Change; Systems; Agriculture; Intensification; Environment; Deforestation
Abstract Land use change has been the primary driving force of human alteration of terrestrial ecosystems. With 80% of agricultural land dedicated to livestock production, the sector is an important lever to attenuate land requirements for food production and carbon emissions from land use change. In this study, we quantify impacts of changing human diets and livestock productivity on land dynamics and depletion of carbon stored in vegetation, litter and soils. Across all investigated productivity pathways, lower consumption of livestock products can substantially reduce deforestation (47-55%) and cumulative carbon losses (34-57%). On the supply side, already minor productivity growth in extensive livestock production systems leads to substantial CO2 emission abatement, but the emission saving potential of productivity gains in intensive systems is limited, also involving trade-offs with soil carbon stocks. If accounting for uncertainties related to future trade restrictions, crop yields and pasture productivity, the range of projected carbon savings from changing diets increases to 23-78%. Highest abatement of carbon emissions (63-78%) can be achieved if reduced consumption of animal-based products is combined with sustained investments into productivity increases in plant production. Our analysis emphasizes the importance to integrate demand- and supply-side oriented mitigation strategies and to combine efforts in the crop and livestock sector to enable synergies for climate protection.
Address 2018-01-25
Corporate Author Thesis
Publisher Place of Publication Editor
Language (down) English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0921-8181 ISBN Medium
Area Expedition Conference
Notes LiveM, TradeM, ft_macsur Approved no
Call Number MA @ admin @ Serial 5188
Permanent link to this record