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Digital technologies are a promising means to tackle the increasing global challenges (e.g., climate change, water pollution, soil degradation) and revolutionising agricultural production. The current research used a two-stage Delphi study with 34 experts from various domains, including production, advisory and research, to identify the key drivers and barriers, the most promising technologies and possible measures to support technology adoption in Swiss outdoor vegetable production. Combining these experts' views, the method provides realistic scenarios for future development. In Round 1, open-ended questions were used to collect the experts' opinions. These were then transformed into closed-ended questions for Round 2, where controlled feedback was provided to the experts. Twenty-six experts participated in both rounds, resulting in an overall response rate that was comparably high (76%). It was found that economic factors were important drivers and barriers in technology adoption and, consequently, the experts recommended financial measures to support this adoption. The practical relevance of new technologies provided through communication and education holds further potential in terms of their promotion. These findings are valuable beyond the research field. Educators and policy makers can build on the results and optimally align their efforts to target technology adoption and contribute to more sustainable agriculture. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]