Abstract
This paper reports on the findings of a multi-site qualitative case study research project designed to document the utility and perceived usefulness of weather station and imagery data associated with the online resource GeoVisage among northeastern Ontario farmers. Interviews were conducted onsite at five participating farms (three dairy, one cash crop, and one public access fruit/vegetable) in 2014–2016, and these conversations were transcribed and returned to participants for member checking. Interview data was then entered into Atlas.ti software for the purpose of qualitative thematic analysis. Fifteen codes emerged from the data and findings center around three overarching themes: common uses of weather station data (e.g., air/soil temperature, rainfall); the use of GeoVisage Imagery data/tools (e.g., acreage calculations, remotely sensed imagery); and future recommendations for the online resource (e.g., communication, secure crop imagery, mobile access). Overall, weather station data and tools freely accessible through the GeoVisage site were viewed as representing a timely, positive, and important addition to contemporary agricultural decision-making in northeastern Ontario farming.
Highlights
IntroductionFarming has been characterized by compound and unpredictable factors.Aubert et al [1] discuss this complexity and the perennial uncertainty of crop farming as follows:A crop farmer needs to consider a variety of parameters such as crop yield, availability of water and nutrients, and a range of site- and soil-specific factors to optimize the plant treatment (e.g., application of fertilizer, pesticides, or irrigation)
Farming has been characterized by compound and unpredictable factors.Aubert et al [1] discuss this complexity and the perennial uncertainty of crop farming as follows:A crop farmer needs to consider a variety of parameters such as crop yield, availability of water and nutrients, and a range of site- and soil-specific factors to optimize the plant treatment
The qualitative research described in this paper provided the opportunity to directly interview a number of northeastern Ontario farmers to assess whether, and in what ways, they have adopted a freely available, locally developed decision support systems involving farm-based weather stations and the related, freely accessible online resource known as GeoVisage
Summary
Farming has been characterized by compound and unpredictable factors.Aubert et al [1] discuss this complexity and the perennial uncertainty of crop farming as follows:A crop farmer needs to consider a variety of parameters such as crop yield, availability of water and nutrients, and a range of site- and soil-specific factors to optimize the plant treatment (e.g., application of fertilizer, pesticides, or irrigation). Over the past 40 years, researchers have speculated that it was only a matter of time before agricultural decision support systems became an essential tool in the management of agricultural operations. Despite these systems being readily available and affordable [2,3,4,5,6,7,8], implementation at the farm-scale has not met expectations [9,10,11,12]. It was thought that computation could overcome the limitations of human ability to process information and to make rational decisions based on scientific evidence. McCown [13] argues that this information-processing view of human decision-making has been replaced by “more ‘ecological’
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