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

Chris Cavalaris, Francesco Latterini, Walter Stefanoni, Christos Karamoutis, Luigi Pari and Efthymia Alexopoulou
Additional contact information
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

Agriculture, 2022, vol. 12, issue 2, 1-16

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.

Keywords: harvesting; harvest aids; seed moisture; seed losses; NDVI; drones; UAS (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
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