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Monitoring Moringa oleifera Lam. in the Mediterranean Area Using Unmanned Aerial Vehicles (UAVs) and Leaf Powder Production for Food Fortification

Author

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  • Carlo Greco

    (Department of Agricultural, Food and Forestry Sciences, University of Palermo, Viale delle Scienze, Building 4, 90128 Palermo, Italy)

  • Raimondo Gaglio

    (Department of Agricultural, Food and Forestry Sciences, University of Palermo, Viale delle Scienze, Building 4, 90128 Palermo, Italy)

  • Luca Settanni

    (Department of Agricultural, Food and Forestry Sciences, University of Palermo, Viale delle Scienze, Building 4, 90128 Palermo, Italy)

  • Antonio Alfonzo

    (Department of Agricultural, Food and Forestry Sciences, University of Palermo, Viale delle Scienze, Building 4, 90128 Palermo, Italy)

  • Santo Orlando

    (Department of Agricultural, Food and Forestry Sciences, University of Palermo, Viale delle Scienze, Building 4, 90128 Palermo, Italy)

  • Salvatore Ciulla

    (Association of Producers SiciliaBio, Via Vittorio Emanuele 100, 92026 Favara, Italy)

  • Michele Massimo Mammano

    (CREA, Research Centre for Plant Protection and Certification, 90128 Palermo, Italy)

Abstract

The increasing global demand for resilient, sustainable agricultural systems has intensified the need for advanced monitoring strategies, particularly for climate-adaptive crops such as Moringa oleifera Lam. This study presents an integrated approach using Unmanned Aerial Vehicles (UAVs) equipped with multispectral and thermal cameras to monitor the vegetative performance and determine the optimal harvest period of four M. oleifera genotypes in a Mediterranean environment. High-resolution data were collected and processed to generate the NDVI, canopy temperature, and height maps, enabling the assessment of plant vigor, stress conditions, and spatial canopy structure. NDVI analysis revealed robust vegetative growth (0.7–0.9), with optimal harvest timing identified on 30 October 2024, when the mean NDVI exceeded 0.85. Thermal imaging effectively discriminated plant crowns from surrounding weeds by capturing cooler canopy zones due to active transpiration. A clear inverse correlation between NDVI and Land Surface Temperature (LST) was observed, reinforcing its relevance for stress diagnostics and environmental monitoring. The results underscore the value of UAV-based multi-sensor systems for precision agriculture, offering scalable tools for phenotyping, harvest optimization, and sustainable management of medicinal and aromatic crops in semiarid regions. Moreover, in this study, to produce M. oleifera leaf powder intended for use as a food ingredient, the leaves of four M. oleifera genotypes were dried, milled, and evaluated for their hygiene and safety characteristics. Plate count analyses confirmed the absence of pathogenic bacterial colonies in the M. oleifera leaf powders, highlighting their potential application as natural and functional additives in food production.

Suggested Citation

  • Carlo Greco & Raimondo Gaglio & Luca Settanni & Antonio Alfonzo & Santo Orlando & Salvatore Ciulla & Michele Massimo Mammano, 2025. "Monitoring Moringa oleifera Lam. in the Mediterranean Area Using Unmanned Aerial Vehicles (UAVs) and Leaf Powder Production for Food Fortification," Agriculture, MDPI, vol. 15(13), pages 1-18, June.
  • Handle: RePEc:gam:jagris:v:15:y:2025:i:13:p:1359-:d:1687176
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    References listed on IDEAS

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    3. Carlo Greco & Raimondo Gaglio & Luca Settanni & Lino Sciurba & Salvatore Ciulla & Santo Orlando & Michele Massimo Mammano, 2025. "Smart Farming Technologies for Sustainable Agriculture: A Case Study of a Mediterranean Aromatic Farm," Agriculture, MDPI, vol. 15(8), pages 1-17, April.
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