Data Farming: Facilitating sustainable intensification through digital innovation

Lead Research Organisation: University of Nottingham
Department Name: School of Computer Science


Rapid growth in the global population puts agriculture under ever-increasing strain. Estimations suggest a 70-100% rise in food production is necessary by 2050. There is an evident need to develop and utilize new and inventive farming techniques. This task, however, is exacerbated by environmental externalities, leading to a steep rise in global temperatures and extremes of weather. The consequences of these issues are disproportionately concentrated in the developing world, where inequality and poverty are rampant. It is the intention of this study to critically appraise existing approaches and suggest pathways to agricultural prosperity through digital innovation.

Sustainable intensification (SI) of agriculture has emerged as a key strategy in climate adaptation, international development and food security. Defined as "a process or system where agricultural yields are increased without adverse environmental impact and without the conversion of additional non-agricultural land", SI provides a comprehensive solution. Technologies include the use of fertilizers, improved crop cultivars, soil and water conservation, intercropping, crop rotation and conservation agriculture. Providing smallholder farmers with greater access to SI technology is perceived as essential to increasing productivity, sustainability and resilience in the global South.

The economic study of adoption strives to understand the transferability and utilization of SI technologies. Several recent studies, however, have identified pervasive problems in the methodology and practice of technological change. Adoption as a concept captures a very limited picture of the decision processes and external factors that influence the uptake of SI. Studies draw from small datasets, with few explanatory variables, without a longitudinal perspective and rely upon a binary vision of success and failure. Due to these data biases, many of those who most require assistance are excluded or unrecognized. Studies do not appeal to the values of participants, obscuring a range of societal factors such as background, political beliefs, 'handed down' farming practices or the relationship of farmers to their wider community. There is an apparent disparity in understanding and awareness between researcher and respondent which requires further exploration.

Digital innovation refers to a broad spectrum of technologies which have in recent years proliferated throughout all aspects of society. Two of the most pervasive have been data analytics in shaping governance and policy, and ICT in mediating social lives and knowledge sharing. Both initiatives have shown great potential in advancing sustainable agriculture. In this case, they present an opportunity for researchers to better understand and model the needs and preferences of farmers and, following this, to develop and implement technologies that are more appealing.

Thus, the focus of this PhD is two-fold: to employ machine learning algorithms to distill a set of key adoption predictors and gain a superior understanding of technological change and the personal data required for its estimation; and to explore the potential of mobile phone-based service provision in developing countries as a key driver of SI technology awareness, understanding, uptake and peer support. It is intended that these measures may bridge the gap between users and researchers, enriching their mutual understanding with more accurate and accessible data.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S023305/1 30/09/2019 30/03/2028
2274246 Studentship EP/S023305/1 30/09/2019 29/09/2023 Eliot Jones
Description Two papers have been delivered since the beginning of this award.

The first, regarding the adoption of sustainable farming technologies for maize production in the Global South, systematically reviewed relevant literature between 2007 and 2018. Findings included that:
(1) Limited information access and technologies not suitable for the small landholdings were the major constraints of farmer adoption of technologies.
(2) The criticisms on the conventional adoption analysis concerning oversimplification and decontextualization of the decision-making process are reaffirmed.
(3) Empirical adoption research needs to incorporate the attributes of technologies and the socio-institutional context to develop better research strategies toward inclusive agrarian development.

The second, concerning farmers using online spaces to discuss Brexit, revealed:
(1) The internet forum can reshape traditional notions of the rural; displacing farmer identities from their deep connection with land and context.
(2) Instead, the forum celebrates an imagined 'British farmer identity', which feeds off of the negative tropes of rural people, and leads to a populist and violet political atmosphere.
(3) Brexit rhetoric acted as a catalyst for politics and emotional sentiment became the deciding factor of debate, above truth and reason.
Exploitation Route The first paper, by summarising the literature in this field to date, was able to set a research agenda for other scholars by emphasizing the need to incorporate the attributes of technologies and the socio-institutional context for inclusive agrarian development.

The second paper presents a novel methodology in a new area and a significant area for future study. The paper goes into detail about how to conduct a 'netnography'; doing research in online environments. Then, it shows that the online is not an unquestionably superior place for agricultural politics, and there is a continued demand for research into progressive spaces for farmers to voice their concerns.
Sectors Agriculture, Food and Drink