Why farmers adopt best management practice in the United States: A meta-analysis of the adoption literature

Baumgart-Getz, Adam; Prokopy, Linda Stalker; Floress, Kristin

doi:10.1016/j.jenvman.2011.10.006

Cited by 627 publications

(518 citation statements)

References 40 publications

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“…High costs to adopt technology for individual farms and limited knowledge and skills can be significant adoption hurdles (12,13), especially in developing countries. Thus, the access to the latest technology may remain restricted to big and industrialized farms.…”

Section: Major Challengesmentioning

confidence: 99%

Smart farming is key to developing sustainable agriculture

Walter¹,

Finger²,

Huber³

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

561

259

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Agriculture has seen many revolutions, whether the domestication of animals and plants a few thousand years ago, the systematic use of crop rotations and other improvements in farming practice a few hundred years ago, or the "green revolution" with systematic breeding and the widespread use of man-made fertilizers and pesticides a few decades ago. We suggest that agriculture is undergoing a fourth revolution triggered by the exponentially increasing use of information and communication technology (ICT) in agriculture.Autonomous, robotic vehicles have been developed for farming purposes, such as mechanical weeding, application of fertilizer, or harvesting of fruits. The development of unmanned aerial vehicles with autonomous flight control (1), together with the development of lightweight and powerful hyperspectral snapshot cameras that can be used to calculate biomass development and fertilization status of crops (2, 3), opens the field for sophisticated farm management advice. Moreover, decision-tree models are available now that allow farmers to differentiate between plant diseases based on optical information (4). Virtual fence technologies (5) allow cattle herd management based on remote-sensing signals and sensors or actuators attached to the livestock.Taken together, these technical improvements constitute a technical revolution that will generate disruptive changes in agricultural practices. This trend holds for farming not only in developed countries but also in developing countries, where deployments in ICT (e.g., use of mobile phones, access to the Internet) are being adopted at a rapid pace and could become the game-changers in the future (e.g., in the form of seasonal drought forecasts, climate-smart agriculture).Such profound changes in practice come not only with opportunities but also big challenges. It is crucial to point them out at an early stage of this revolution to avoid "lock-ins": advocates and skeptics of technology need to engage in an open dialogue on the future development of farming in the digital era. Only if aspects of technology, diversity of crop and livestock systems, and networking and institutions (i.e. markets and policies), are considered jointly in the dialogue, should farming in the digital era be termed "smart farming." Ample OpportunitiesSmart farming reduces the ecological footprint of farming. Minimized or site-specific application of inputs, such as fertilizers and pesticides, in precision agriculture systems will mitigate leaching problems as well as the emission of greenhouse gases (6). With current ICT, it is possible to create a sensor network allowing for almost continuous monitoring of the farm. Similarly, theoretical and practical frameworks to connect the states of plants, animals, and soils with the needs for production inputs, such as water, fertilizer, and medications, are in reach with current ICT globally.Smart farming can make agriculture more profitable for the farmer. Decreasing resource inputs will save the farmer money and labor, and increased reliabi...

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Section: Major Challengesmentioning

confidence: 99%

Smart farming is key to developing sustainable agriculture

Walter¹,

Finger²,

Huber³

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

561

259

View full text Add to dashboard Cite

show abstract

“…Factors that have been found to be more or less consistently influential include education, age, income, farm size, and off-farm income (Soule et al 2000;Pannell et al 2006;Knowler and Bradshaw 2007;Prokopy et al 2008;Baumgart-Getz et al 2012). However, the sign and effect of each of these characteristics are not always consistent, which may have to do with variation in the types of practices analyzed and the confluence of other factors discussed above.…”

Section: Conceptual Framework For Agricultural Adaptationmentioning

confidence: 99%

“…Adaptation intentions under a Corn Belt climate change scenario 335 adaptation. Attitudes are multidimensional and have been found to be important predictors of behavioral intentions, including intentions related to conservation practice adoption (Prokopy et al 2008;Baumgart-Getz et al 2012;Reimer et al 2012b). Ajzen notes that attitudes should be measured directly in reference to a specific behavior and are defined as the ''degree to which a person has favorable or unfavorable evaluation or appraisal of the behavior in question' ' (1991, p. 10).…”

Section: Conceptual Framework For Agricultural Adaptationmentioning

confidence: 99%

What would farmers do? Adaptation intentions under a Corn Belt climate change scenario

2016

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This paper examines farmer intentions to adapt to global climate change by analyzing responses to a climate change scenario presented in a survey given to largescale farmers (n = 4778) across the US Corn Belt in 2012. Adaptive strategies are evaluated in the context of decision making and farmers' intention to increase their use of three production practices promoted across the Corn Belt: no-till farming, cover crops, and tile drainage. This paper also provides a novel conceptual framework that bridges a typology of adaptation with concepts that help predict intentionality in behavior change models. This conceptual framework was developed to facilitate examination of adaptive decision making in the context of agriculture. This research effort examines key factors that influence farmers' intentions to increase their use of the practices evaluated given a climate change scenario. Twenty-two covariates are examined across three models developed for no-till farming, cover crops, and tile drainage. Findings highlight that farmers who believed they should adjust their practices to protect their farm from the negative impacts of increased weather variability were more likely to indicate that they would increase their use of each of the practices in response to climate change. Additionally, visiting with other farmers to observe their practices was positively associated with farmers' intentions to increase their use of the adaptive strategies examined. Farmers who were currently using no-till farming, cover crops, and tile drainage were also more likely to plan to increase their use of these practices in response to increased weather variability associated with climate change. However, farmers who reported high levels of confidence in their current practices were less likely to plan on changing their use of these practices in response to climatic changes.

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“…cooperation (Prokopy et al 2008;Baumgart-Getz et al 2012). For example, Conley and Udry (2010) find that farmers in Ghana innovate by mimicking the practices of their successful immediate contacts.…”

Section: Introductionmentioning

confidence: 99%

“…Globally, agricultural systems have been crucial to the development of modern civilization and they are now facing significant sustainability issues such as food security, natural resource management, and climate change. To address these issues, agricultural systems must catalyze the diffusion of innovations such us new farm management practices (Saltiel et al 1994;Baumgart-Getz et al 2012), cooperation to address common-pool resource problems such as groundwater management (Agrawal 2001;Dietz et al 2002;Henry and Dietz 2011), and boundary-spanning across different specialized components of food systems Hoffman et al 2015). Viticulture is a particularly useful example because it is a highly innovative and economically viable industry that is increasingly experimenting with sustainability programs, policies, and practices (Warner 2007a;Lubell et al 2011).…”

Section: Introductionmentioning

confidence: 99%

Innovation, cooperation, and the structure of three regional sustainable agriculture networks in California

Levy

Lubell

2017

Reg Environ Change

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Regional agroecological systems are examples of complex adaptive systems, where sustainability is promoted by social networks that facilitate information sharing, cooperation, and connectivity among specialized components of the system. Much of the existing literature on social capital fails to recognize how networks support multiple social processes. Our paper overcomes this problem by analyzing how the social networks of wine grape growers exhibit structural features related to multiple social processes: ties to central actors that build bridging social capital and facilitate the diffusion of innovations, ties that close triangles and build bonding social capital to solve cooperation dilemmas, and ties to individuals that span community boundaries to connect specialized components of the system. We use survey data to measure the communication networks of growers in three viticulture regions in California. A combination of descriptive statistics, conditional uniform random graph tests, and exponential random graph models provides empirical support for our hypotheses. The findings reflect regional differences in geography and institutional histories, which may influence the capacity to respond to regional environmental change.

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Why farmers adopt best management practice in the United States: A meta-analysis of the adoption literature

Cited by 627 publications

References 40 publications

Smart farming is key to developing sustainable agriculture

Smart farming is key to developing sustainable agriculture

What would farmers do? Adaptation intentions under a Corn Belt climate change scenario

Innovation, cooperation, and the structure of three regional sustainable agriculture networks in California

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