Journal
AGRICULTURE-BASEL
Volume 13, Issue 1, Pages -Publisher
MDPI
DOI: 10.3390/agriculture13010163
Keywords
Internet of Things; wireless sensors; precision agriculture practices; barriers
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The production of row crops in the Midwestern (Indiana) region of the US is facing environmental and economic sustainability issues. The low adoption rate of IoT-based precision agriculture technologies and the barriers to their adoption, including cost effectiveness, power requirements, wireless communication range, data latency, data scalability, data storage, data processing, and data interoperability, are described in the literature. This study explores and understands decision-making variables related to these barriers through focus group interviews with subject matter experts in IoT-based precision agriculture practices.
The production of row crops in the Midwestern (Indiana) region of the US has been facing environmental and economic sustainability issues. There has been an increase in trend for the application of fertilizers (nitrogen & phosphorus), farm machinery fuel costs and decreasing labor productivity leading to non-optimized usage of farm inputs. Literature describes how sustainable practices such as profitability (return on investments), operational cost reduction, hazardous waste reduction, delivery performance and overall productivity might be adopted in the context of precision agriculture technologies (variable rate irrigation, variable rate fertilization, cloud-based analytics, and telematics for farm machinery navigation). The literature review describes low adoption of Internet of Things (IoT)-based precision agriculture technologies, such as variable rate fertilizer (39%), variable rate pesticide (8%), variable rate irrigation (4%), cloud-based data analytics (21%) and telematics (10%) amongst Midwestern row crop producers. Barriers to the adoption of IoT-based precision agriculture technologies cited in the literature include cost effectiveness, power requirements, wireless communication range, data latency, data scalability, data storage, data processing and data interoperability. Therefore, this study focused on exploring and understanding decision-making variables related to barriers through three focus group interview sessions conducted with eighteen (n = 18) subject matter experts (SME) in IoT- based precision agriculture practices. Dependency relationships described between cost, data latency, data scalability, power consumption, communication range, type of wireless communication and precision agriculture application is one of the main findings. The results might inform precision agriculture practitioners, producers and other stakeholders about variables related to technical and operational barriers for the adoption of IoT-based precision agriculture practices.
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