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Sociotechnological Sustainability in Pasture Management: Labor Input and Optimization Potential of Smart Tools to Measure Herbage Mass and Quality

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  • Leonie Hart

    (Competitiveness and System Evaluation, Agroscope, Tänikon 1, 8356 Ettenhausen, Switzerland
    Institute of Agricultural Sciences in the Tropics, University of Hohenheim, Fruwirthstrasse 31, 70599 Stuttgart, Germany)

  • Elisabeth Quendler

    (Institute of Agricultural Engineering, University of Natural Resources and Life Sciences, Peter-Jordan-Strasse 82, 1190 Vienna, Austria)

  • Christina Umstaetter

    (Competitiveness and System Evaluation, Agroscope, Tänikon 1, 8356 Ettenhausen, Switzerland
    Thuenen Institute of Agricultural Technology, Bundesallee 47, 38116 Braunschweig, Germany)

Abstract

Investing labor time in herbage measurements is important for precision pasture management. In this study, the labor input of three smart herbage measurement tools—multispectral imagery linked to an unmanned aerial vehicle (UAV), a semi-automated rising plate meter (RPM), and near-infrared reflectance spectroscopy (NIRS) of cut herbage samples—and of direct observation was modeled based on the REFA work element method. Three to five users were observed during work execution to identify best-practice workflows. Time measurements were conducted using video footage. The resulting standard times of work elements were used to model labor input for herbage measurements in different farm sizes (i.e., milking platforms of 6–100 ha) and subdivisions of a farm’s milking platform (i.e., 4–45 paddocks). Labor time requirement differed between the smart farming tools (0.7–5.9 h) depending on the farm size and milking platform scenario. The labor time requirement increased for all tools with an increase in farm size and was lowest for the RPM. For the UAV tool, it did not increase noticeably when the division of the milking platform changed. Nevertheless, the potential to save time was identified for the UAV and the NIRS. Therefore, the automation of certain steps in the workflows would contribute to sociotechnological sustainable pasture management.

Suggested Citation

  • Leonie Hart & Elisabeth Quendler & Christina Umstaetter, 2022. "Sociotechnological Sustainability in Pasture Management: Labor Input and Optimization Potential of Smart Tools to Measure Herbage Mass and Quality," Sustainability, MDPI, vol. 14(12), pages 1-23, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:12:p:7490-:d:842875
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    References listed on IDEAS

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    1. Anja Scheurich & Alexandra Penicka & Stefan Hörtenhuber & Thomas Lindenthal & Elisabeth Quendler & Werner Zollitsch, 2021. "Elements of Social Sustainability among Austrian Hay Milk Farmers: Between Satisfaction and Stress," Sustainability, MDPI, vol. 13(23), pages 1-20, November.
    2. Robert Finger & Scott M. Swinton & Nadja El Benni & Achim Walter, 2019. "Precision Farming at the Nexus of Agricultural Production and the Environment," Annual Review of Resource Economics, Annual Reviews, vol. 11(1), pages 313-335, October.
    3. Agnes van den Pol-van Dasselaar & Deirdre Hennessy & Johannes Isselstein, 2020. "Grazing of Dairy Cows in Europe—An In-Depth Analysis Based on the Perception of Grassland Experts," Sustainability, MDPI, vol. 12(3), pages 1-18, February.
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