Figure 6 - uploaded by Laura Schreiner
Content may be subject to copyright.
Schematic of agricultural system definition used for this research 

Schematic of agricultural system definition used for this research 

Source publication
Thesis
Full-text available
This paper explores Oregon’s land use planning policies and their outcomes for farmland and agriculture in the Willamette Valley. An agricultural systems planning framework is used to guide the investigation, which uses a combination of literature review and key informant interviews to extract lessons which may be relevant in the Greater Golden Hor...

Context in source publication

Context 1
... an agri-business group, consisting of farm businesses and farm families, infrastructure, input and support services, first-level processing, and wholesale and/or direct farmer-to-consumer marketing and delivery services. This definition is represented schematically in Figure 6. The agricultural land base is shown in green and underpins the agri-business group, shown in blue. ...

Citations

Preprint
Full-text available
Complex agricultural problems concern many countries, as the economic motives are increasingly higher, and at the same time the consequences from the irrational resources use and emissions are becoming more evident. In this work we study three of the most common agricultural problems and model them through optimization techniques, showing ways to assess conflicting objectives together as a system and provide overall optimum solutions. The studied problems refer to: i) a water-scarce area with overexploited surface and groundwater resources due to over-pumping for irrigation (Central Greece), ii) a water-abundant area with issues of water quality deterioration caused by agriculture (Southern Ontario, Canada), iii) and a case of intensified agriculture based on animal farming that causes issues of water, soil quality degradation, and increased greenhouse gases emissions (Central Ireland). Linear, non-linear, and Goal Programming optimization techniques have been developed and applied for each case to maximize farmers welfare, make a less intensive use of environmental resources, and control the emission of pollutants. The proposed approaches and their solutions are novel applications for each case-study, compared to the existing literature and practice. Furthermore, they provide useful insights for most countries facing similar problems, they are easily applicable, and developed and solved in publicly available tools such as Python.