In-field hyperspectral imaging: An overview on the ground-based applications in agriculture

  • Alessandro Benelli Department of Agricultural and Food Sciences, Alma Mater Studiorum, University of Bologna, Cesena (FC), Italy.
  • Chiara Cevoli | chiara.cevoli3@unibo.it Department of Agricultural and Food Sciences, Alma Mater Studiorum, University of Bologna, Cesena (FC); Interdepartmental Centre for Agri-Food Industrial Research, Alma Mater Studiorum, University of Bologna, Cesena (FC), Italy. https://orcid.org/0000-0003-4883-2589
  • Angelo Fabbri Department of Agricultural and Food Sciences, Alma Mater Studiorum, University of Bologna, Cesena (FC); Interdepartmental Centre for Agri-Food Industrial Research, Alma Mater Studiorum, University of Bologna, Cesena (FC), Italy. https://orcid.org/0000-0003-0097-6348

Abstract

The measurement of vegetation indexes that characterise the plants growth, assessing the fruit ripeness or detecting the presence of defects and diseases, is a key factor to gain high quality of fruit or vegetables. Such evaluation can be carried out using both destructive and non destructive techniques. Among non-destructive techniques, hyperspectral imaging (HSI), combining image analysis and visible/near-infrared spectroscopy, looks particularly useful. Many studies have been published concerning the use of hyperspectral cameras in the agronomic and food field, especially in controlled laboratory conditions. Conversely, few studies described the application of HSI technology directly in field, especially involving ground-based systems. Results suggest that this technique could be particularly useful, even if the role of environmental variables has to be considered (e.g., intensity and incidence of solar radiation, wind or the soil in the background). In this paper, recent in-field HSI applications based on ground systems are reviewed.

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Published
2020-09-29
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Section
Review Articles
Keywords:
Hyperspectral, fruits, vegetables, in-field application, prediction, classification.
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How to Cite
Benelli, A., Cevoli, C., & Fabbri, A. (2020). In-field hyperspectral imaging: An overview on the ground-based applications in agriculture. Journal of Agricultural Engineering, 51(3), 129-139. https://doi.org/10.4081/jae.2020.1030