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Monitoring Chemical-Induced Ripening of Castor ( Ricinus communis L.) by UAS-Based Remote Sensing

Author

Listed:
  • Chris Cavalaris

    (Department of Agricultural Crop Production and Rural Environment, School of Agricultural Sciences, University of Thessaly, Fytokou Str., 38446 Volos, Greece)

  • Francesco Latterini

    (Consiglio per la Ricerca in Agricoltura e l’analisi dell’Economia Agraria (CREA)–Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via della Pascolare 16, 00015 Rome, Italy)

  • Walter Stefanoni

    (Consiglio per la Ricerca in Agricoltura e l’analisi dell’Economia Agraria (CREA)–Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via della Pascolare 16, 00015 Rome, Italy)

  • Christos Karamoutis

    (Department of Agricultural Crop Production and Rural Environment, School of Agricultural Sciences, University of Thessaly, Fytokou Str., 38446 Volos, Greece)

  • Luigi Pari

    (Consiglio per la Ricerca in Agricoltura e l’analisi dell’Economia Agraria (CREA)–Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via della Pascolare 16, 00015 Rome, Italy)

  • Efthymia Alexopoulou

    (Centre for Renewable Energy Sources and Saving, 19th km Marathonos Avenue, Pikermi, 19009 Athens, Greece)

Abstract

Castor is a crop with an evergreen habit so artificially-induced ripening is an essential precondition for mechanical harvesting of new dwarf annual hybrids. Plants’ moisture imposes a determinant effect both on pre-harvest and post-harvest seed loss, so frequent monitoring of crop ripening is crucial for identifying the optimum moisture for harvest. Remote sensing information from Unmanned Aerial Systems (UASs) along with field measurements were utilized in the present study in order to evaluate three harvest aid chemicals, herbicides glyphosate (GLY) and diquat (DIQ) and the defoliant Spotlight ® (DEF) for terminating the castor crop and identifying opportunities for using remote sensing as a tool for monitoring crop ripening. The results showed that glyphosate required more than two weeks to dry out the crop while diquat and spotlight ® presented a rapid action within two to four days. Nineteen vegetation indexes (VIs) were derived from a multispectral and an RGB camera mounted on two UAS and were plotted against field measurements. NDVI presented a higher accuracy (R 2 = 0.67) for predicting the castor stems’ and leaves’ moisture content while OSAVI and SIPI2 were more powerful in predicting moisture of capsules (R 2 > 0.76). High efficiency was also obtained with VARI green , an index estimated from the common bands of a conventional RGB camera. The best performing VIs were further utilized in multiple linear regression models also incorporating the date of spraying as information. The VI models further improved the predicting power with an R 2 of up to 0.73 for stems and leaves and 0.81 for capsules.

Suggested Citation

  • Chris Cavalaris & Francesco Latterini & Walter Stefanoni & Christos Karamoutis & Luigi Pari & Efthymia Alexopoulou, 2022. "Monitoring Chemical-Induced Ripening of Castor ( Ricinus communis L.) by UAS-Based Remote Sensing," Agriculture, MDPI, vol. 12(2), pages 1-16, January.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:2:p:159-:d:731910
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    References listed on IDEAS

    as
    1. Luigi Pari & Alessandro Suardi & Walter Stefanoni & Francesco Latterini & Nadia Palmieri, 2020. "Environmental and Economic Assessment of Castor Oil Supply Chain: A Case Study," Sustainability, MDPI, vol. 12(16), pages 1-16, August.
    2. Vijaya Kumar, P. & Ramakrishna, Y. S. & Ramana Rao, B. V. & Khandgonda, I. R. & Victor, U. S. & Srivastava, N. N. & Rao, G. G. S. N., 1999. "Assessment of plant-extractable soil water in castor beans (Ricinus communis L.) using infrared thermometry," Agricultural Water Management, Elsevier, vol. 39(1), pages 69-83, February.
    3. Luigi Pari & Francesco Latterini & Walter Stefanoni, 2020. "Herbaceous Oil Crops, a Review on Mechanical Harvesting State of the Art," Agriculture, MDPI, vol. 10(8), pages 1-25, July.
    4. Munimathan Arunkumar & Vinayagam Mohanavel & Asif Afzal & Thanikodi Sathish & Manickam Ravichandran & Sher Afghan Khan & Nur Azam Abdullah & Muhammad Hanafi Bin Azami & Mohammad Asif, 2021. "A Study on Performance and Emission Characteristics of Diesel Engine Using Ricinus Communis (Castor Oil) Ethyl Esters," Energies, MDPI, vol. 14(14), pages 1-17, July.
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