ArticleData in brief2023
Farm-level data on production systems, farmer- and farm characteristics of apple growers in Switzerland.
Article in Data in brief, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- Real-time identification and quantification of apple scab on fruit in preharvest and postharvest conditions using YOLO11: a deep learning approach.Plant methods · 2026Article
- Data covering soil management practices and farm characteristics on Swiss arable farms.Scientific data · 2025Article
- A typology of interdisciplinary collaborations: insights from agri-food transformation research.Sustainability science · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We here present survey data from apple growers across Switzerland. Data from 245 apple growers was collected, using an online survey in French and German in 2022. The sampled growers represent 24.4% from total land under apples. Apple production is one of the most economically relevant and pesticide intensive crops. Hence, the focus of the survey is on growers' pest management decisions and marketing strategies. Survey data contains details on growers' agronomic practices such as grown cultivars, pest management against fungi, insects, and weeds, as well as pesticide use for cosmetic purposes. Moreover, we collected information on pest management after harvest, i.e. storage loss strategies. Marketing characteristics include the sales channel chosen as well as labels used and contract arrangements with buyers. Moreover, detailed data about farm management strategies, behavioral factors, as well as other farm- and farmer characteristics was collected. Survey data is matched with a rich set of environmental data, i.e. precipitation, temperature, and apple scab infection risk.
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Registered trials
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