Athanasios Balafoutis

Performance and Emissions of Sunflower, Rapeseed, and Cottonseed Oils as Fuels in an Agricultural Tractor Engine

A comparative experimental investigation was conducted to evaluate the performance and exhaust emissions of an agricultural tractor engine when fueled with sunflower oil, rapeseed oil, and cottonseed oil and their blends with diesel fuel (20/80, 40/60 and 70/30 volumetrically). Tests were also carried out with diesel fuel to be used as a reference point. Engine power, torque, BSFC, thermal efficiency, NOx and CO2 were recorded for each tested fuel. All vegetable oils resulted in normal operation without problems during the short-term experiments. The 20/80 blends showed unstable results, in comparison to higher oil content fuels. Power, Torque and BSFC were higher as oil content was increased in the fuel. Rapeseed oil fuels showed increased power, torque and thermal efficiency with simultaneous lower BSFC in comparison to the other two vegetable oils. Cottonseed oil fuels gave better engine performance than sunflower oil fuels. In all oil types, NOx emissions were augmented when fuel oil percentage was increased. Cottonseed oil fuels led to higher NOx emission increase compared to rapeseed oil fuels. CO2 emissions showed a tendency to be increased as the oil content was evolved. The highest CO2 emissions were given by cottonseed oil fuels, followed by rapeseed and sunflower oil.

Research funding and academic output: evidence from the Agricultural University of Athens

This paper uses detailed data on funding information and research output from the Agricultural University of Athens to examine how each type of funding source is related to the quantity and quality of academic research output. Of special interest are private, Greek government and European Union sources of funding. We find that after controlling for unobserved heterogeneity from each research laboratory, all types of research funding are similarly related to both the count of publications and citations. Further, we find that research laboratories that have filed for at least one patent application produce more publications and citations to their work, indicating that laboratories that are close to industry are also engaged actively in research.

Sunflower Oil Fuel for Diesel Engines: An Experimental Investigation and Optimum Engine Setting Evaluation Using a Multi-Criteria Decision Making Approach

An experimental investigation on a diesel engine was conducted to evaluate the performance and exhaust emissions of sunflower oil and three blends with diesel fuel (20, 40, and 70% oil content volumetrically) in comparison to diesel fuel. Three injection timing and three injector protrusion settings were tested to study engine performance and exhaust emissions. The work was conducted in a direct injection agricultural tractor engine. Engine operation with sunflower oil-based fuels was unproblematic during the short-term experiments. Torque, brake-specific fuel consumption and NOx were enhanced as oil content was increased in the tested fuel. Early injection timing improved torque output, reduced BSFC, increased thermal efficiency, and NOx emissions. Deep injector protrusion increased torque release in low oil content fuels and shallow injector protrusion and increased torque in high oil content fuels. The experimental results were evaluated using two multi-criteria decision-making techniques (Analytical Hierarchy Process-AHP and Technique for Order Preference by Similarity to the Ideal Solution-TOPSIS) and the optimal fuel type-injection timing-injector protrusion configuration was selected. AHP and TOPSIS were run for three groups of criteria that were focusing on higher engine performance, lower environmental impact, and a balance between the first two, respectively. The results of the two techniques were compared. AHP and TOPSIS gave the same attribute ranking in all three groups of criteria, but did not give the same classification of Fuel/Injection Timing/Injector Protrusion configuration. The 70% oil content blend was selected from both techniques as optimal in the examined groups of criteria.

Smart Farming Technologies – Description, Taxonomy and Economic Impact

Precision Agriculture is a cyclic optimization process where data have to be collected from the field, analysed and evaluated and finally used for decision making for site-specific management of the field. Smart farming technologies (SFT ) cover all these aspects of precision agriculture and can be categorized in data acquisition, data analysis and evaluation and precision application technologies. Data acquisition technologies include GNSS technologies, mapping technologies, data acquisition of environmental properties and machines and their properties. Data analysis and evaluation technologies comprise the delineation of management zones, decision support systems and farm management information system s. Finally, precision application technologies embrace variable-rate application technologies, precision irrigation and weeding and machine guidance. In this chapter, the reader can find a technical description of the technologies included in each category accompanied by a taxonomy of all SFT in terms of farming system type, cropping system, availability, level of investment and farmers’ motives to adopt them. Finally, the economic impact that each SFT has compared to conventional agricultural practices is given.

Comparative Analysis of Energy Efficiency in Wheat Production in Different Climate Conditions en Europe

This paper presents results concerning energy efficiency of wheat production considered in the context of specific energy input variation in different climatic conditions of Europe as well as case studies on implementation of selected energy saving measures in practice. The source data collected from the six european union (EU) countries represent five agricultural regions of continental Europe and three climates: continental, temperate and Mediterranean. The life cycle assessment (LCA) methodology was applied to analyze the data excluding of pre-farm gate activities. The total primary energy consumption was decomposed into main energy input streams and it was regressed to yield. In order to compare energy efficiency of wheat production across the geographical areas, the data envelopment analysis (DEA) was applied. It was shown that the highest wheat yield (6.7 t/ha to 8.7 t/ha) at the lowest specific energy input (2.08 GJ/t to 2.56 GJ/t) is unique for temperate climate conditions. The yield in continental and Mediterranean climatic conditions is on average lower by 1.3 t/ha and 2.7 t/ha and energy efficiency lower by 14% and 38%, respectively. The case studies have shown that the energy saving activities in wheat production may be universal for the climatic zones or specific for a given geographical location. It was stated that trade-offs between energy, economic, and environmental effects, which are associated with implementation of a given energy saving measure or a set of measures to a great extent depend on the current energy efficiency status of the farm and opportunity for investment, which varies substantially across Europe