Hyperspectral Reflectance as a Basis to Discriminate Olive Varieties—A Tool for Sustainable Crop Management

Luis Gomes, Tânia Nobre, Adélia Sousa, Fernando Rei and Nuno Guiomar
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Luis Gomes: MED-Mediterranean Institute for Agriculture, Environment and Development, Institute for Advanced Studies and Research, University of Évora, 7006-554 Évora, Portugal
Tânia Nobre: MED-Mediterranean Institute for Agriculture, Environment and Development, Institute for Advanced Studies and Research, University of Évora, 7006-554 Évora, Portugal
Adélia Sousa: MED-Mediterranean Institute for Agriculture, Environment and Development & Department of Rural Engineering, School of Science and Technology, University of Évora, 7006-554 Évora, Portugal
Fernando Rei: MED-Mediterranean Institute for Agriculture, Environment and Development & Departament of Phytotechnics, School of Science and Technology, University of Évora, 7006-554 Évora, Portugal
Nuno Guiomar: MED-Mediterranean Institute for Agriculture, Environment and Development, Institute for Advanced Studies and Research, University of Évora, 7006-554 Évora, Portugal

Sustainability, 2020, vol. 12, issue 7, 1-21

Abstract: Worldwide sustainable development is threatened by current agricultural land change trends, particularly by the increasing rural farmland abandonment and agricultural intensification phenomena. In Mediterranean countries, these processes are affecting especially traditional olive groves with enormous socio-economic costs to rural areas, endangering environmental sustainability and biodiversity. Traditional olive groves abandonment and intensification are clearly related to the reduction of olive oil production income, leading to reduced economic viability. Most promising strategies to boost traditional groves competitiveness—such as olive oil differentiation through adoption of protected denomination of origin labels and development of value-added olive products—rely on knowledge of the olive varieties and its specific properties that confer their uniqueness and authenticity. Given the lack of information about olive varieties on traditional groves, a feasible and inexpensive method of variety identification is required. We analyzed leaf spectral information of ten Portuguese olive varieties with a powerful data-mining approach in order to verify the ability of satellite’s hyperspectral sensors to provide an accurate olive variety identification. Our results show that these olive varieties are distinguishable by leaf reflectance information and suggest that even satellite open-source data could be used to map them. Additional advantages of olive varieties mapping were further discussed.

Keywords: traditional olive groves; olive cultivars; remote sensing; Sentinel 2; spectral reflectance; sustainable development; agricultural abandonment; agricultural intensification (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:12:y:2020:i:7:p:3059-:d:344014

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