Abstract
This paper presents the state of application of Precision Agricultural enabling Technology (PAT) in Swiss farms as an example for small-scale, highly mechanised Central European agriculture. Furthermore, correlations between farm and farmers’ characteristics and technology adoption were evaluated. Being part of a comprehensive and representative study assessing the state of mechanisation and automation in Swiss agriculture, this paper focuses on the adoption of Driver Assistance Systems (DAS) and activities in which Electronic Measuring Systems (EMS) are used. The adoption rate of DAS was markedly higher compared to EMS in all agricultural enterprises. The adoption rate was highest for high-value enterprise vegetables and surprisingly low for the high-value enterprise grapes. The results of a binary logistic regression showed that farmers located in the mountain zone were less likely to adopt PAT compared to farmers in the valley. Small farm size correlated with low adoption rates and vice versa showing adoption happens country-specific in the upper farm size distribution. The results show the potential for novel technologies to be adopted by farmers of high-value products. Furthermore, technologies have been partially used to reduce physical workload but not yet to evaluate crop or management performance to support decisions. However, automatic collection and forwarding of data is a fundamental step towards Smart Farming realizing its full potential in the future.
Highlights
The application and connection of digital technologies in agricultural production has been the focus of research and received increasing attention in the last years
As this study focused on Precision Agricultural enabling Technology (PAT) adoption in plant production, the questionnaires containing the following two questions were evaluated: ‘Do you use any of the following Driver Assistance Systems (DAS)?’ and ‘In which of the following activities do you use Electronic Measuring Systems (EMS) (e.g. N-sensor, optical plant detection) on the machines?’
EMS were used less with higher non-adopter rates compared to adopters within all agricultural enterprises
Summary
The application and connection of digital technologies in agricultural production has been the focus of research and received increasing attention in the last years. Precision Agriculture (2020) 21:1327–1350 robots, sensor technology and automation as well as the use of information and communication technologies. It is associated by terms such as Precision Agriculture (PA), Precision Farming (PF), Smart Farming, Digital Farming or Agriculture 4.0 (Paustian and Theuvsen 2017; Pierpaoli et al 2013). A recently published definition of the International Society of Precision Agriculture states: “Precision Agriculture is a management strategy that gathers, processes and analyzes temporal, spatial and individual data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of agricultural production.” (ISPA 2019). The broadness of the definition considers PA at the management level and might make it difficult in some cases to define specific technologies inside or outside the PA category
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