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Proximal Sensing in Grasslands and Pastures

Author

Listed:
  • Shayan Ghajar

    (School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, VA 24061, USA)

  • Benjamin Tracy

    (School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, VA 24061, USA)

Abstract

Reliable measures of biomass, species composition, nitrogen status, and nutritive value provide important indicators of the status of pastures and rangelands, allowing managers to make informed decisions. Traditional methods of sample collection necessitate significant investments in time and labor. Proximal sensing technologies have the potential to collect more data with a smaller investment in time and labor. However, methods and protocols for conducting pasture assessments with proximal sensors are still in development, equipment and software vary considerably, and the accuracy and utility of these assessments differ between methods and sites. This review summarizes the methods currently being developed to assess pastures and rangelands worldwide and discusses these emerging technologies in the context of diffusion of innovation theory.

Suggested Citation

  • Shayan Ghajar & Benjamin Tracy, 2021. "Proximal Sensing in Grasslands and Pastures," Agriculture, MDPI, vol. 11(8), pages 1-12, August.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:8:p:740-:d:608127
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    Citations

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    Cited by:

    1. João Serrano & Shakib Shahidian & Eliana Machado & Luís L. Paniagua & Emanuel Carreira & Francisco Moral & Alfredo Pereira & Mário de Carvalho, 2021. "Floristic Composition: Dynamic Biodiversity Indicator of Tree Canopy Effect on Dryland and Improved Mediterranean Pastures," Agriculture, MDPI, vol. 11(11), pages 1-25, November.

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