2018
DOI: 10.1016/j.agsy.2018.07.007
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Scaling up agricultural interventions: Case studies of climate-smart agriculture

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Cited by 131 publications
(84 citation statements)
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“…It is therefore often prudent to consider strengthening the non-public institutions in a region if they are able to assume a determining role in the long term and reduce the risks of failure (Teshome et al, 2016). Westermann et al (2015) and Aggarwal et al (2018) consider that multistakeholder platforms and policy-making networks are key to effective upscaling.…”
Section: Institutional Capacity Spacementioning
confidence: 99%
“…It is therefore often prudent to consider strengthening the non-public institutions in a region if they are able to assume a determining role in the long term and reduce the risks of failure (Teshome et al, 2016). Westermann et al (2015) and Aggarwal et al (2018) consider that multistakeholder platforms and policy-making networks are key to effective upscaling.…”
Section: Institutional Capacity Spacementioning
confidence: 99%
“…Instead, alternative approaches to achieving necessary transformation have been suggested. It has been argued that food production is a component of complex, adaptive socialecological systems (Walker et al, 2010;Reed et al, 2013;Foran et al, 2014), and therefore multiple technological and social interventions are required simultaneously at different scales to generate systemic change (Giller et al, 2009;Scherr et al, 2012;Food Agriculture Organisation of the United Nations, 2013;Steenwerth et al, 2014;Westermann et al, 2018). In parallel, there has been a shift from dependence on the pipeline model to an "actor innovation" model, which deliberately aims to change social and power dynamics, and institutions and governance that are shaped by these relationships (Biggs, 2007).…”
Section: Introductionmentioning
confidence: 99%
“…Aside from the sensing process, smart farming [5] and similar agricultural approaches deal with: (i) the data analysis process, including data mining and visualization; (ii) the decision-making process, involving decision-support systems, modeling and planning tools; and (iii) the action process, which includes online applications, monitoring robots and automation technologies. The aggregation and analysis of large volumes of data within short time periods grants producers the ability to act forthwith, contributing to the prediction and prevention of crop damage, the frequency of which never ceases to decrease, potentially as a consequence of climate change [6,7]. Thus, intelligent agriculture and other cross-disciplinary approaches in agricultural production, such as the one found in [8], is not merely a passing trend in innovation, but an auspicious endeavor for supplying satisfactory and adequate levels of food production of high quality [9,10], for an increasingly growing global population.…”
Section: Introductionmentioning
confidence: 99%